id	sid	tid	token	lemma	pos
ejpam-5934	1	1	european	european	PROPN
ejpam-5934	1	2	journal	journal	PROPN
ejpam-5934	1	3	of	of	ADP
ejpam-5934	1	4	pure	pure	ADJ
ejpam-5934	1	5	and	and	CCONJ
ejpam-5934	1	6	applied	applied	ADJ
ejpam-5934	1	7	mathematics	mathematic	NOUN
ejpam-5934	1	8	2025	2025	NUM
ejpam-5934	1	9	,	,	PUNCT
ejpam-5934	1	10	vol	vol	NOUN
ejpam-5934	1	11	.	.	PROPN
ejpam-5934	1	12	18	18	NUM
ejpam-5934	1	13	,	,	PUNCT
ejpam-5934	1	14	issue	issue	NOUN
ejpam-5934	1	15	2	2	NUM
ejpam-5934	1	16	,	,	PUNCT
ejpam-5934	1	17	article	article	NOUN
ejpam-5934	1	18	number	number	NOUN
ejpam-5934	1	19	5934	5934	NUM
ejpam-5934	1	20	issn	issn	PROPN
ejpam-5934	1	21	1307	1307	NUM
ejpam-5934	1	22	-	-	SYM
ejpam-5934	1	23	5543	5543	NUM
ejpam-5934	1	24	–	–	PUNCT
ejpam-5934	1	25	ejpam.com	ejpam.com	X
ejpam-5934	1	26	published	publish	VERB
ejpam-5934	1	27	by	by	ADP
ejpam-5934	1	28	new	new	PROPN
ejpam-5934	1	29	york	york	PROPN
ejpam-5934	1	30	business	business	PROPN
ejpam-5934	1	31	global	global	ADJ
ejpam-5934	1	32	enhancing	enhance	VERB
ejpam-5934	1	33	classification	classification	NOUN
ejpam-5934	1	34	performance	performance	NOUN
ejpam-5934	1	35	through	through	ADP
ejpam-5934	1	36	rough	rough	ADJ
ejpam-5934	1	37	set	set	NOUN
ejpam-5934	1	38	theory	theory	NOUN
ejpam-5934	1	39	feature	feature	NOUN
ejpam-5934	1	40	selection	selection	NOUN
ejpam-5934	1	41	:	:	PUNCT
ejpam-5934	1	42	a	a	DET
ejpam-5934	1	43	comparative	comparative	ADJ
ejpam-5934	1	44	study	study	NOUN
ejpam-5934	1	45	across	across	ADP
ejpam-5934	1	46	multiple	multiple	ADJ
ejpam-5934	1	47	datasets	dataset	NOUN
ejpam-5934	1	48	t.	t.	PROPN
ejpam-5934	1	49	ashika1	ashika1	PROPN
ejpam-5934	1	50	,	,	PUNCT
ejpam-5934	1	51	g.	g.	PROPN
ejpam-5934	1	52	hannah	hannah	PROPN
ejpam-5934	1	53	grace1,∗	grace1,∗	PROPN
ejpam-5934	1	54	1	1	NUM
ejpam-5934	1	55	department	department	NOUN
ejpam-5934	1	56	of	of	ADP
ejpam-5934	1	57	mathematics	mathematic	NOUN
ejpam-5934	1	58	,	,	PUNCT
ejpam-5934	1	59	school	school	NOUN
ejpam-5934	1	60	of	of	ADP
ejpam-5934	1	61	advanced	advanced	ADJ
ejpam-5934	1	62	sciences	science	NOUN
ejpam-5934	1	63	,	,	PUNCT
ejpam-5934	1	64	vellore	vellore	PROPN
ejpam-5934	1	65	institute	institute	PROPN
ejpam-5934	1	66	of	of	ADP
ejpam-5934	1	67	technology	technology	PROPN
ejpam-5934	1	68	chennai	chennai	PROPN
ejpam-5934	1	69	,	,	PUNCT
ejpam-5934	1	70	india	india	PROPN
ejpam-5934	1	71	abstract	abstract	NOUN
ejpam-5934	1	72	.	.	PUNCT
ejpam-5934	2	1	in	in	ADP
ejpam-5934	2	2	machine	machine	NOUN
ejpam-5934	2	3	learning	learning	NOUN
ejpam-5934	2	4	(	(	PUNCT
ejpam-5934	2	5	ml	ml	NOUN
ejpam-5934	2	6	)	)	PUNCT
ejpam-5934	2	7	,	,	PUNCT
ejpam-5934	2	8	handling	handle	VERB
ejpam-5934	2	9	high	high	ADJ
ejpam-5934	2	10	-	-	PUNCT
ejpam-5934	2	11	dimensional	dimensional	ADJ
ejpam-5934	2	12	data	datum	NOUN
ejpam-5934	2	13	with	with	ADP
ejpam-5934	2	14	redundant	redundant	ADJ
ejpam-5934	2	15	or	or	CCONJ
ejpam-5934	2	16	irrelevant	irrelevant	ADJ
ejpam-5934	2	17	features	feature	NOUN
ejpam-5934	2	18	presents	present	VERB
ejpam-5934	2	19	significant	significant	ADJ
ejpam-5934	2	20	challenges	challenge	NOUN
ejpam-5934	2	21	.	.	PUNCT
ejpam-5934	3	1	effective	effective	ADJ
ejpam-5934	3	2	feature	feature	NOUN
ejpam-5934	3	3	selection	selection	NOUN
ejpam-5934	3	4	is	be	AUX
ejpam-5934	3	5	essential	essential	ADJ
ejpam-5934	3	6	for	for	ADP
ejpam-5934	3	7	enhancing	enhance	VERB
ejpam-5934	3	8	model	model	NOUN
ejpam-5934	3	9	performance	performance	NOUN
ejpam-5934	3	10	,	,	PUNCT
ejpam-5934	3	11	reducing	reduce	VERB
ejpam-5934	3	12	computational	computational	ADJ
ejpam-5934	3	13	complexity	complexity	NOUN
ejpam-5934	3	14	,	,	PUNCT
ejpam-5934	3	15	and	and	CCONJ
ejpam-5934	3	16	improving	improve	VERB
ejpam-5934	3	17	interpretability	interpretability	NOUN
ejpam-5934	3	18	.	.	PUNCT
ejpam-5934	4	1	rough	rough	ADJ
ejpam-5934	4	2	set	set	NOUN
ejpam-5934	4	3	theory	theory	NOUN
ejpam-5934	4	4	(	(	PUNCT
ejpam-5934	4	5	rst	rst	PROPN
ejpam-5934	4	6	)	)	PUNCT
ejpam-5934	4	7	provides	provide	VERB
ejpam-5934	4	8	a	a	DET
ejpam-5934	4	9	powerful	powerful	ADJ
ejpam-5934	4	10	mathematical	mathematical	ADJ
ejpam-5934	4	11	framework	framework	NOUN
ejpam-5934	4	12	for	for	ADP
ejpam-5934	4	13	managing	manage	VERB
ejpam-5934	4	14	uncertainty	uncertainty	NOUN
ejpam-5934	4	15	,	,	PUNCT
ejpam-5934	4	16	making	make	VERB
ejpam-5934	4	17	it	it	PRON
ejpam-5934	4	18	a	a	DET
ejpam-5934	4	19	valuable	valuable	ADJ
ejpam-5934	4	20	tool	tool	NOUN
ejpam-5934	4	21	for	for	ADP
ejpam-5934	4	22	feature	feature	NOUN
ejpam-5934	4	23	selection	selection	NOUN
ejpam-5934	4	24	.	.	PUNCT
ejpam-5934	5	1	this	this	DET
ejpam-5934	5	2	study	study	NOUN
ejpam-5934	5	3	applies	apply	VERB
ejpam-5934	5	4	rst	rst	PROPN
ejpam-5934	5	5	-	-	PUNCT
ejpam-5934	5	6	based	base	VERB
ejpam-5934	5	7	feature	feature	NOUN
ejpam-5934	5	8	selection	selection	NOUN
ejpam-5934	5	9	to	to	ADP
ejpam-5934	5	10	five	five	NUM
ejpam-5934	5	11	diverse	diverse	ADJ
ejpam-5934	5	12	datasets	dataset	NOUN
ejpam-5934	5	13	,	,	PUNCT
ejpam-5934	5	14	aiming	aim	VERB
ejpam-5934	5	15	to	to	PART
ejpam-5934	5	16	eliminate	eliminate	VERB
ejpam-5934	5	17	insignificant	insignificant	ADJ
ejpam-5934	5	18	attributes	attribute	NOUN
ejpam-5934	5	19	.	.	PUNCT
ejpam-5934	6	1	the	the	DET
ejpam-5934	6	2	performance	performance	NOUN
ejpam-5934	6	3	of	of	ADP
ejpam-5934	6	4	various	various	ADJ
ejpam-5934	6	5	ml	ml	NOUN
ejpam-5934	6	6	models	model	NOUN
ejpam-5934	6	7	,	,	PUNCT
ejpam-5934	6	8	including	include	VERB
ejpam-5934	6	9	logistic	logistic	ADJ
ejpam-5934	6	10	regression	regression	NOUN
ejpam-5934	6	11	(	(	PUNCT
ejpam-5934	6	12	lr	lr	NOUN
ejpam-5934	6	13	)	)	PUNCT
ejpam-5934	6	14	,	,	PUNCT
ejpam-5934	6	15	k	k	X
ejpam-5934	6	16	-	-	PUNCT
ejpam-5934	6	17	nearest	near	ADJ
ejpam-5934	6	18	neighbor	neighbor	NOUN
ejpam-5934	6	19	(	(	PUNCT
ejpam-5934	6	20	knn	knn	PROPN
ejpam-5934	6	21	)	)	PUNCT
ejpam-5934	6	22	,	,	PUNCT
ejpam-5934	6	23	support	support	NOUN
ejpam-5934	6	24	vector	vector	NOUN
ejpam-5934	6	25	machine	machine	NOUN
ejpam-5934	6	26	(	(	PUNCT
ejpam-5934	6	27	svm	svm	PROPN
ejpam-5934	6	28	)	)	PUNCT
ejpam-5934	6	29	,	,	PUNCT
ejpam-5934	6	30	kernel	kernel	PROPN
ejpam-5934	6	31	svm	svm	PROPN
ejpam-5934	6	32	,	,	PUNCT
ejpam-5934	6	33	näıve	näıve	PRON
ejpam-5934	6	34	bayes	bayes	PROPN
ejpam-5934	6	35	(	(	PUNCT
ejpam-5934	6	36	nb	nb	NOUN
ejpam-5934	6	37	)	)	PUNCT
ejpam-5934	6	38	,	,	PUNCT
ejpam-5934	6	39	decision	decision	NOUN
ejpam-5934	6	40	tree	tree	NOUN
ejpam-5934	6	41	(	(	PUNCT
ejpam-5934	6	42	dt	dt	NOUN
ejpam-5934	6	43	)	)	PUNCT
ejpam-5934	6	44	and	and	CCONJ
ejpam-5934	6	45	random	random	ADJ
ejpam-5934	6	46	forest	forest	NOUN
ejpam-5934	6	47	(	(	PUNCT
ejpam-5934	6	48	rf	rf	NOUN
ejpam-5934	6	49	)	)	PUNCT
ejpam-5934	6	50	,	,	PUNCT
ejpam-5934	6	51	on	on	ADP
ejpam-5934	6	52	both	both	CCONJ
ejpam-5934	6	53	the	the	DET
ejpam-5934	6	54	original	original	ADJ
ejpam-5934	6	55	and	and	CCONJ
ejpam-5934	6	56	rst	rst	ADJ
ejpam-5934	6	57	selected	select	VERB
ejpam-5934	6	58	datasets	dataset	NOUN
ejpam-5934	6	59	was	be	AUX
ejpam-5934	6	60	evaluated	evaluate	VERB
ejpam-5934	6	61	.	.	PUNCT
ejpam-5934	7	1	standard	standard	ADJ
ejpam-5934	7	2	metrics	metric	NOUN
ejpam-5934	7	3	such	such	ADJ
ejpam-5934	7	4	as	as	ADP
ejpam-5934	7	5	accuracy	accuracy	NOUN
ejpam-5934	7	6	,	,	PUNCT
ejpam-5934	7	7	precision	precision	NOUN
ejpam-5934	7	8	,	,	PUNCT
ejpam-5934	7	9	recall	recall	NOUN
ejpam-5934	7	10	,	,	PUNCT
ejpam-5934	7	11	f1	f1	NOUN
ejpam-5934	7	12	score	score	NOUN
ejpam-5934	7	13	and	and	CCONJ
ejpam-5934	7	14	mean	mean	VERB
ejpam-5934	7	15	absolute	absolute	ADJ
ejpam-5934	7	16	error	error	NOUN
ejpam-5934	7	17	(	(	PUNCT
ejpam-5934	7	18	mae	mae	PROPN
ejpam-5934	7	19	)	)	PUNCT
ejpam-5934	7	20	are	be	AUX
ejpam-5934	7	21	used	use	VERB
ejpam-5934	7	22	for	for	ADP
ejpam-5934	7	23	evaluation	evaluation	NOUN
ejpam-5934	7	24	.	.	PUNCT
ejpam-5934	8	1	results	result	NOUN
ejpam-5934	8	2	demonstrate	demonstrate	VERB
ejpam-5934	8	3	that	that	SCONJ
ejpam-5934	8	4	rst	rst	PROPN
ejpam-5934	8	5	effectively	effectively	ADV
ejpam-5934	8	6	selects	select	VERB
ejpam-5934	8	7	relevant	relevant	ADJ
ejpam-5934	8	8	features	feature	NOUN
ejpam-5934	8	9	without	without	ADP
ejpam-5934	8	10	significant	significant	ADJ
ejpam-5934	8	11	information	information	NOUN
ejpam-5934	8	12	loss	loss	NOUN
ejpam-5934	8	13	.	.	PUNCT
ejpam-5934	9	1	models	model	NOUN
ejpam-5934	9	2	trained	train	VERB
ejpam-5934	9	3	on	on	ADP
ejpam-5934	9	4	rst	rst	NOUN
ejpam-5934	9	5	selected	select	VERB
ejpam-5934	9	6	datasets	dataset	NOUN
ejpam-5934	9	7	exhibit	exhibit	VERB
ejpam-5934	9	8	comparable	comparable	ADJ
ejpam-5934	9	9	or	or	CCONJ
ejpam-5934	9	10	improved	improved	ADJ
ejpam-5934	9	11	performance	performance	NOUN
ejpam-5934	9	12	.	.	PUNCT
ejpam-5934	10	1	these	these	DET
ejpam-5934	10	2	findings	finding	NOUN
ejpam-5934	10	3	highlight	highlight	VERB
ejpam-5934	10	4	the	the	DET
ejpam-5934	10	5	potential	potential	NOUN
ejpam-5934	10	6	of	of	ADP
ejpam-5934	10	7	rst	rst	NOUN
ejpam-5934	10	8	-	-	PUNCT
ejpam-5934	10	9	based	base	VERB
ejpam-5934	10	10	feature	feature	NOUN
ejpam-5934	10	11	selection	selection	NOUN
ejpam-5934	10	12	to	to	PART
ejpam-5934	10	13	enhance	enhance	VERB
ejpam-5934	10	14	ml	ml	NOUN
ejpam-5934	10	15	model	model	NOUN
ejpam-5934	10	16	performance	performance	NOUN
ejpam-5934	10	17	while	while	SCONJ
ejpam-5934	10	18	reducing	reduce	VERB
ejpam-5934	10	19	computational	computational	ADJ
ejpam-5934	10	20	complexity	complexity	NOUN
ejpam-5934	10	21	,	,	PUNCT
ejpam-5934	10	22	making	make	VERB
ejpam-5934	10	23	it	it	PRON
ejpam-5934	10	24	a	a	DET
ejpam-5934	10	25	valuable	valuable	ADJ
ejpam-5934	10	26	approach	approach	NOUN
ejpam-5934	10	27	for	for	ADP
ejpam-5934	10	28	various	various	ADJ
ejpam-5934	10	29	ml	ml	NOUN
ejpam-5934	10	30	applications	application	NOUN
ejpam-5934	10	31	.	.	PUNCT
ejpam-5934	11	1	2020	2020	NUM
ejpam-5934	11	2	mathematics	mathematic	NOUN
ejpam-5934	11	3	subject	subject	NOUN
ejpam-5934	11	4	classifications	classification	NOUN
ejpam-5934	11	5	:	:	PUNCT
ejpam-5934	11	6	68t30	68t30	NUM
ejpam-5934	11	7	,	,	PUNCT
ejpam-5934	11	8	68t37	68t37	NUM
ejpam-5934	11	9	,	,	PUNCT
ejpam-5934	11	10	68u35	68u35	NUM
ejpam-5934	11	11	key	key	ADJ
ejpam-5934	11	12	words	word	NOUN
ejpam-5934	11	13	and	and	CCONJ
ejpam-5934	11	14	phrases	phrase	NOUN
ejpam-5934	11	15	:	:	PUNCT
ejpam-5934	11	16	quickreduct	quickreduct	NOUN
ejpam-5934	11	17	,	,	PUNCT
ejpam-5934	11	18	machine	machine	NOUN
ejpam-5934	11	19	learning	learning	NOUN
ejpam-5934	11	20	,	,	PUNCT
ejpam-5934	11	21	rough	rough	ADJ
ejpam-5934	11	22	set	set	NOUN
ejpam-5934	11	23	theory	theory	NOUN
ejpam-5934	11	24	,	,	PUNCT
ejpam-5934	11	25	feature	feature	NOUN
ejpam-5934	11	26	selection	selection	NOUN
ejpam-5934	11	27	1	1	NUM
ejpam-5934	11	28	.	.	PUNCT
ejpam-5934	11	29	introduction	introduction	NOUN
ejpam-5934	11	30	a	a	DET
ejpam-5934	11	31	subfield	subfield	NOUN
ejpam-5934	11	32	of	of	ADP
ejpam-5934	11	33	computer	computer	NOUN
ejpam-5934	11	34	science	science	NOUN
ejpam-5934	11	35	and	and	CCONJ
ejpam-5934	11	36	artificial	artificial	ADJ
ejpam-5934	11	37	intelligence	intelligence	NOUN
ejpam-5934	11	38	(	(	PUNCT
ejpam-5934	11	39	ai	ai	AUX
ejpam-5934	11	40	)	)	PUNCT
ejpam-5934	11	41	called	call	VERB
ejpam-5934	11	42	”	"	PUNCT
ejpam-5934	11	43	machine	machine	NOUN
ejpam-5934	11	44	learning	learning	NOUN
ejpam-5934	11	45	”	"	PUNCT
ejpam-5934	11	46	focuses	focus	VERB
ejpam-5934	11	47	on	on	ADP
ejpam-5934	11	48	using	use	VERB
ejpam-5934	11	49	data	datum	NOUN
ejpam-5934	11	50	and	and	CCONJ
ejpam-5934	11	51	algorithms	algorithm	NOUN
ejpam-5934	11	52	to	to	PART
ejpam-5934	11	53	simulate	simulate	VERB
ejpam-5934	11	54	human	human	ADJ
ejpam-5934	11	55	learning	learning	NOUN
ejpam-5934	11	56	processes	process	NOUN
ejpam-5934	11	57	and	and	CCONJ
ejpam-5934	11	58	progressively	progressively	ADV
ejpam-5934	11	59	increase	increase	VERB
ejpam-5934	11	60	their	their	PRON
ejpam-5934	11	61	accuracy	accuracy	NOUN
ejpam-5934	11	62	.	.	PUNCT
ejpam-5934	12	1	ml	ml	NOUN
ejpam-5934	12	2	techniques	technique	NOUN
ejpam-5934	12	3	have	have	AUX
ejpam-5934	12	4	been	be	AUX
ejpam-5934	12	5	used	use	VERB
ejpam-5934	12	6	in	in	ADP
ejpam-5934	12	7	many	many	ADJ
ejpam-5934	12	8	domains	domain	NOUN
ejpam-5934	12	9	,	,	PUNCT
ejpam-5934	12	10	such	such	ADJ
ejpam-5934	12	11	as	as	ADP
ejpam-5934	12	12	email	email	NOUN
ejpam-5934	12	13	filtering	filtering	NOUN
ejpam-5934	12	14	,	,	PUNCT
ejpam-5934	12	15	computer	computer	NOUN
ejpam-5934	12	16	vision	vision	NOUN
ejpam-5934	12	17	,	,	PUNCT
ejpam-5934	12	18	speech	speech	NOUN
ejpam-5934	12	19	recognition	recognition	NOUN
ejpam-5934	12	20	,	,	PUNCT
ejpam-5934	12	21	agriculture	agriculture	NOUN
ejpam-5934	12	22	,	,	PUNCT
ejpam-5934	12	23	and	and	CCONJ
ejpam-5934	12	24	health	health	NOUN
ejpam-5934	12	25	,	,	PUNCT
ejpam-5934	12	26	where	where	SCONJ
ejpam-5934	12	27	developing	develop	VERB
ejpam-5934	12	28	algorithms	algorithm	NOUN
ejpam-5934	12	29	capable	capable	ADJ
ejpam-5934	12	30	of	of	ADP
ejpam-5934	12	31	carrying	carry	VERB
ejpam-5934	12	32	out	out	ADP
ejpam-5934	12	33	the	the	DET
ejpam-5934	12	34	necessary	necessary	ADJ
ejpam-5934	12	35	functions	function	NOUN
ejpam-5934	12	36	would	would	AUX
ejpam-5934	12	37	be	be	AUX
ejpam-5934	12	38	costly	costly	ADJ
ejpam-5934	12	39	.	.	PUNCT
ejpam-5934	13	1	although	although	SCONJ
ejpam-5934	13	2	ml	ml	PROPN
ejpam-5934	13	3	has	have	AUX
ejpam-5934	13	4	made	make	VERB
ejpam-5934	13	5	many	many	ADJ
ejpam-5934	13	6	revolutions	revolution	NOUN
ejpam-5934	13	7	in	in	ADP
ejpam-5934	13	8	different	different	ADJ
ejpam-5934	13	9	fields	field	NOUN
ejpam-5934	13	10	,	,	PUNCT
ejpam-5934	13	11	it	it	PRON
ejpam-5934	13	12	also	also	ADV
ejpam-5934	13	13	faces	face	VERB
ejpam-5934	13	14	many	many	ADJ
ejpam-5934	13	15	∗corresponding	∗corresponde	VERB
ejpam-5934	13	16	author	author	NOUN
ejpam-5934	13	17	.	.	PUNCT
ejpam-5934	14	1	doi	doi	NOUN
ejpam-5934	14	2	:	:	PUNCT
ejpam-5934	14	3	https://doi.org/10.29020/nybg.ejpam.v18i2.5934	https://doi.org/10.29020/nybg.ejpam.v18i2.5934	PUNCT
ejpam-5934	14	4	email	email	NOUN
ejpam-5934	14	5	addresses	address	NOUN
ejpam-5934	14	6	:	:	PUNCT
ejpam-5934	14	7	ashika.t2023@vitstudent.ac.in	ashika.t2023@vitstudent.ac.in	PROPN
ejpam-5934	14	8	(	(	PUNCT
ejpam-5934	14	9	t.	t.	NOUN
ejpam-5934	14	10	ashika	ashika	NOUN
ejpam-5934	14	11	)	)	PUNCT
ejpam-5934	14	12	,	,	PUNCT
ejpam-5934	14	13	hannahgrace.g@vit.ac.in	hannahgrace.g@vit.ac.in	PROPN
ejpam-5934	14	14	(	(	PUNCT
ejpam-5934	14	15	g.	g.	PROPN
ejpam-5934	14	16	h.	h.	PROPN
ejpam-5934	14	17	grace	grace	PROPN
ejpam-5934	14	18	)	)	PUNCT
ejpam-5934	14	19	https://www.ejpam.com	https://www.ejpam.com	X
ejpam-5934	15	1	1	1	NUM
ejpam-5934	15	2	copyright	copyright	NOUN
ejpam-5934	15	3	:	:	PUNCT
ejpam-5934	15	4	©	©	PROPN
ejpam-5934	15	5	2025	2025	NUM
ejpam-5934	15	6	the	the	DET
ejpam-5934	15	7	author(s	author(s	NOUN
ejpam-5934	15	8	)	)	PUNCT
ejpam-5934	15	9	.	.	PUNCT
ejpam-5934	16	1	(	(	PUNCT
ejpam-5934	16	2	cc	cc	NOUN
ejpam-5934	16	3	by	by	ADP
ejpam-5934	16	4	-	-	PUNCT
ejpam-5934	16	5	nc	nc	PROPN
ejpam-5934	16	6	4.0	4.0	NUM
ejpam-5934	16	7	)	)	PUNCT
ejpam-5934	16	8	t.	t.	ADJ
ejpam-5934	16	9	ashika	ashika	NOUN
ejpam-5934	16	10	,	,	PUNCT
ejpam-5934	16	11	g.	g.	PROPN
ejpam-5934	16	12	h.	h.	PROPN
ejpam-5934	16	13	grace	grace	PROPN
ejpam-5934	16	14	/	/	SYM
ejpam-5934	16	15	eur	eur	PROPN
ejpam-5934	16	16	.	.	PUNCT
ejpam-5934	17	1	j.	j.	PROPN
ejpam-5934	17	2	pure	pure	PROPN
ejpam-5934	17	3	appl	appl	PROPN
ejpam-5934	17	4	.	.	PROPN
ejpam-5934	17	5	math	math	PROPN
ejpam-5934	17	6	,	,	PUNCT
ejpam-5934	17	7	18	18	NUM
ejpam-5934	17	8	(	(	PUNCT
ejpam-5934	17	9	2	2	NUM
ejpam-5934	17	10	)	)	PUNCT
ejpam-5934	17	11	(	(	PUNCT
ejpam-5934	17	12	2025	2025	NUM
ejpam-5934	17	13	)	)	PUNCT
ejpam-5934	17	14	,	,	PUNCT
ejpam-5934	17	15	5934	5934	NUM
ejpam-5934	17	16	2	2	NUM
ejpam-5934	17	17	of	of	ADP
ejpam-5934	17	18	22	22	NUM
ejpam-5934	17	19	limitations	limitation	NOUN
ejpam-5934	17	20	such	such	ADJ
ejpam-5934	17	21	as	as	ADP
ejpam-5934	17	22	lack	lack	NOUN
ejpam-5934	17	23	of	of	ADP
ejpam-5934	17	24	data	datum	NOUN
ejpam-5934	17	25	,	,	PUNCT
ejpam-5934	17	26	challenges	challenge	NOUN
ejpam-5934	17	27	in	in	ADP
ejpam-5934	17	28	obtaining	obtain	VERB
ejpam-5934	17	29	the	the	DET
ejpam-5934	17	30	data	datum	NOUN
ejpam-5934	17	31	,	,	PUNCT
ejpam-5934	17	32	bias	bias	NOUN
ejpam-5934	17	33	in	in	ADP
ejpam-5934	17	34	the	the	DET
ejpam-5934	17	35	data	datum	NOUN
ejpam-5934	17	36	,	,	PUNCT
ejpam-5934	17	37	and	and	CCONJ
ejpam-5934	17	38	a	a	DET
ejpam-5934	17	39	vast	vast	ADJ
ejpam-5934	17	40	amount	amount	NOUN
ejpam-5934	17	41	of	of	ADP
ejpam-5934	17	42	irrelevant	irrelevant	ADJ
ejpam-5934	17	43	attributes	attribute	NOUN
ejpam-5934	17	44	in	in	ADP
ejpam-5934	17	45	the	the	DET
ejpam-5934	17	46	data	datum	NOUN
ejpam-5934	17	47	.	.	PUNCT
ejpam-5934	18	1	pawlak	pawlak	ADJ
ejpam-5934	18	2	[	[	X
ejpam-5934	18	3	1	1	NUM
ejpam-5934	18	4	]	]	PUNCT
ejpam-5934	18	5	introduced	introduce	VERB
ejpam-5934	18	6	rst	rst	PROPN
ejpam-5934	18	7	,	,	PUNCT
ejpam-5934	18	8	a	a	DET
ejpam-5934	18	9	technique	technique	NOUN
ejpam-5934	18	10	used	use	VERB
ejpam-5934	18	11	in	in	ADP
ejpam-5934	18	12	mathematics	mathematic	NOUN
ejpam-5934	18	13	that	that	PRON
ejpam-5934	18	14	can	can	AUX
ejpam-5934	18	15	be	be	AUX
ejpam-5934	18	16	applied	apply	VERB
ejpam-5934	18	17	to	to	ADP
ejpam-5934	18	18	problems	problem	NOUN
ejpam-5934	18	19	involving	involve	VERB
ejpam-5934	18	20	imprecision	imprecision	NOUN
ejpam-5934	18	21	and	and	CCONJ
ejpam-5934	18	22	vagueness	vagueness	NOUN
ejpam-5934	18	23	in	in	ADP
ejpam-5934	18	24	intelligent	intelligent	ADJ
ejpam-5934	18	25	data	datum	NOUN
ejpam-5934	18	26	mining	mining	NOUN
ejpam-5934	18	27	and	and	CCONJ
ejpam-5934	18	28	analysis	analysis	NOUN
ejpam-5934	18	29	for	for	ADP
ejpam-5934	18	30	handling	handle	VERB
ejpam-5934	18	31	huge	huge	ADJ
ejpam-5934	18	32	data	datum	NOUN
ejpam-5934	18	33	.	.	PUNCT
ejpam-5934	19	1	rst	rst	PROPN
ejpam-5934	19	2	provides	provide	VERB
ejpam-5934	19	3	several	several	ADJ
ejpam-5934	19	4	benefits	benefit	NOUN
ejpam-5934	19	5	,	,	PUNCT
ejpam-5934	19	6	such	such	ADJ
ejpam-5934	19	7	as	as	ADP
ejpam-5934	19	8	the	the	DET
ejpam-5934	19	9	ability	ability	NOUN
ejpam-5934	19	10	to	to	PART
ejpam-5934	19	11	operate	operate	VERB
ejpam-5934	19	12	without	without	ADP
ejpam-5934	19	13	needing	need	VERB
ejpam-5934	19	14	prior	prior	ADV
ejpam-5934	19	15	or	or	CCONJ
ejpam-5934	19	16	supplementary	supplementary	ADJ
ejpam-5934	19	17	information	information	NOUN
ejpam-5934	19	18	about	about	ADP
ejpam-5934	19	19	the	the	DET
ejpam-5934	19	20	data	datum	NOUN
ejpam-5934	19	21	.	.	PUNCT
ejpam-5934	20	1	it	it	PRON
ejpam-5934	20	2	delivers	deliver	VERB
ejpam-5934	20	3	meaningful	meaningful	ADJ
ejpam-5934	20	4	analysis	analysis	NOUN
ejpam-5934	20	5	even	even	ADV
ejpam-5934	20	6	when	when	SCONJ
ejpam-5934	20	7	data	datum	NOUN
ejpam-5934	20	8	is	be	AUX
ejpam-5934	20	9	incomplete	incomplete	ADJ
ejpam-5934	20	10	,	,	PUNCT
ejpam-5934	20	11	supports	support	VERB
ejpam-5934	20	12	the	the	DET
ejpam-5934	20	13	interpretation	interpretation	NOUN
ejpam-5934	20	14	of	of	ADP
ejpam-5934	20	15	both	both	CCONJ
ejpam-5934	20	16	quantitative	quantitative	ADJ
ejpam-5934	20	17	and	and	CCONJ
ejpam-5934	20	18	qualitative	qualitative	ADJ
ejpam-5934	20	19	data	datum	NOUN
ejpam-5934	20	20	,	,	PUNCT
ejpam-5934	20	21	and	and	CCONJ
ejpam-5934	20	22	can	can	AUX
ejpam-5934	20	23	model	model	VERB
ejpam-5934	20	24	highly	highly	ADV
ejpam-5934	20	25	nonlinear	nonlinear	ADJ
ejpam-5934	20	26	or	or	CCONJ
ejpam-5934	20	27	discontinuous	discontinuous	ADJ
ejpam-5934	20	28	relationships	relationship	NOUN
ejpam-5934	20	29	,	,	PUNCT
ejpam-5934	20	30	offering	offer	VERB
ejpam-5934	20	31	intricate	intricate	ADJ
ejpam-5934	20	32	characterizations	characterization	NOUN
ejpam-5934	20	33	of	of	ADP
ejpam-5934	20	34	the	the	DET
ejpam-5934	20	35	data	datum	NOUN
ejpam-5934	20	36	.	.	PUNCT
ejpam-5934	21	1	rst	rst	PROPN
ejpam-5934	21	2	excels	excel	NOUN
ejpam-5934	21	3	in	in	ADP
ejpam-5934	21	4	uncovering	uncover	VERB
ejpam-5934	21	5	hidden	hide	VERB
ejpam-5934	21	6	patterns	pattern	NOUN
ejpam-5934	21	7	and	and	CCONJ
ejpam-5934	21	8	representing	represent	VERB
ejpam-5934	21	9	them	they	PRON
ejpam-5934	21	10	as	as	ADP
ejpam-5934	21	11	decision	decision	NOUN
ejpam-5934	21	12	rules	rule	NOUN
ejpam-5934	21	13	,	,	PUNCT
ejpam-5934	21	14	all	all	PRON
ejpam-5934	21	15	of	of	ADP
ejpam-5934	21	16	which	which	PRON
ejpam-5934	21	17	are	be	AUX
ejpam-5934	21	18	grounded	ground	VERB
ejpam-5934	21	19	in	in	ADP
ejpam-5934	21	20	facts	fact	NOUN
ejpam-5934	21	21	supported	support	VERB
ejpam-5934	21	22	by	by	ADP
ejpam-5934	21	23	a	a	DET
ejpam-5934	21	24	set	set	NOUN
ejpam-5934	21	25	of	of	ADP
ejpam-5934	21	26	examples	example	NOUN
ejpam-5934	21	27	.	.	PUNCT
ejpam-5934	22	1	rst	rst	PROPN
ejpam-5934	22	2	is	be	AUX
ejpam-5934	22	3	a	a	DET
ejpam-5934	22	4	valuable	valuable	ADJ
ejpam-5934	22	5	tool	tool	NOUN
ejpam-5934	22	6	for	for	ADP
ejpam-5934	22	7	the	the	DET
ejpam-5934	22	8	ml	ml	X
ejpam-5934	22	9	community	community	NOUN
ejpam-5934	22	10	since	since	SCONJ
ejpam-5934	22	11	it	it	PRON
ejpam-5934	22	12	has	have	VERB
ejpam-5934	22	13	significant	significant	ADJ
ejpam-5934	22	14	potential	potential	NOUN
ejpam-5934	22	15	in	in	ADP
ejpam-5934	22	16	areas	area	NOUN
ejpam-5934	22	17	including	include	VERB
ejpam-5934	22	18	dynamic	dynamic	ADJ
ejpam-5934	22	19	learning	learning	NOUN
ejpam-5934	22	20	,	,	PUNCT
ejpam-5934	22	21	multi	multi	ADJ
ejpam-5934	22	22	-	-	ADJ
ejpam-5934	22	23	label	label	ADJ
ejpam-5934	22	24	classification	classification	NOUN
ejpam-5934	22	25	,	,	PUNCT
ejpam-5934	22	26	imbalanced	imbalanced	ADJ
ejpam-5934	22	27	classification	classification	NOUN
ejpam-5934	22	28	,	,	PUNCT
ejpam-5934	22	29	and	and	CCONJ
ejpam-5934	22	30	big	big	ADJ
ejpam-5934	22	31	data	datum	NOUN
ejpam-5934	22	32	research	research	NOUN
ejpam-5934	22	33	[	[	X
ejpam-5934	22	34	2	2	NUM
ejpam-5934	22	35	]	]	PUNCT
ejpam-5934	22	36	.	.	PUNCT
ejpam-5934	23	1	in	in	ADP
ejpam-5934	23	2	this	this	DET
ejpam-5934	23	3	paper	paper	NOUN
ejpam-5934	23	4	,	,	PUNCT
ejpam-5934	23	5	five	five	NUM
ejpam-5934	23	6	datasets	dataset	NOUN
ejpam-5934	23	7	were	be	AUX
ejpam-5934	23	8	sourced	source	VERB
ejpam-5934	23	9	from	from	ADP
ejpam-5934	23	10	kaggle	kaggle	PROPN
ejpam-5934	23	11	and	and	CCONJ
ejpam-5934	23	12	the	the	DET
ejpam-5934	23	13	uci	uci	PROPN
ejpam-5934	23	14	ml	ml	NOUN
ejpam-5934	23	15	repository	repository	NOUN
ejpam-5934	23	16	.	.	PUNCT
ejpam-5934	24	1	the	the	DET
ejpam-5934	24	2	study	study	NOUN
ejpam-5934	24	3	is	be	AUX
ejpam-5934	24	4	organized	organize	VERB
ejpam-5934	24	5	into	into	ADP
ejpam-5934	24	6	two	two	NUM
ejpam-5934	24	7	phases	phase	NOUN
ejpam-5934	24	8	.	.	PUNCT
ejpam-5934	25	1	in	in	ADP
ejpam-5934	25	2	the	the	DET
ejpam-5934	25	3	first	first	ADJ
ejpam-5934	25	4	phase	phase	NOUN
ejpam-5934	25	5	,	,	PUNCT
ejpam-5934	25	6	the	the	DET
ejpam-5934	25	7	data	datum	NOUN
ejpam-5934	25	8	was	be	AUX
ejpam-5934	25	9	pre	pre	ADJ
ejpam-5934	25	10	-	-	VERB
ejpam-5934	25	11	processed	process	VERB
ejpam-5934	25	12	,	,	PUNCT
ejpam-5934	25	13	followed	follow	VERB
ejpam-5934	25	14	by	by	ADP
ejpam-5934	25	15	the	the	DET
ejpam-5934	25	16	application	application	NOUN
ejpam-5934	25	17	of	of	ADP
ejpam-5934	25	18	various	various	ADJ
ejpam-5934	25	19	ml	ml	NOUN
ejpam-5934	25	20	algorithms	algorithm	NOUN
ejpam-5934	25	21	and	and	CCONJ
ejpam-5934	25	22	an	an	DET
ejpam-5934	25	23	evaluation	evaluation	NOUN
ejpam-5934	25	24	of	of	ADP
ejpam-5934	25	25	their	their	PRON
ejpam-5934	25	26	performance	performance	NOUN
ejpam-5934	25	27	.	.	PUNCT
ejpam-5934	26	1	the	the	DET
ejpam-5934	26	2	results	result	NOUN
ejpam-5934	26	3	of	of	ADP
ejpam-5934	26	4	these	these	DET
ejpam-5934	26	5	models	model	NOUN
ejpam-5934	26	6	were	be	AUX
ejpam-5934	26	7	analyzed	analyze	VERB
ejpam-5934	26	8	to	to	PART
ejpam-5934	26	9	assess	assess	VERB
ejpam-5934	26	10	their	their	PRON
ejpam-5934	26	11	classification	classification	NOUN
ejpam-5934	26	12	effectiveness	effectiveness	NOUN
ejpam-5934	26	13	.	.	PUNCT
ejpam-5934	27	1	in	in	ADP
ejpam-5934	27	2	the	the	DET
ejpam-5934	27	3	second	second	ADJ
ejpam-5934	27	4	phase	phase	NOUN
ejpam-5934	27	5	,	,	PUNCT
ejpam-5934	27	6	rst	rst	NOUN
ejpam-5934	27	7	feature	feature	NOUN
ejpam-5934	27	8	selection	selection	NOUN
ejpam-5934	27	9	was	be	AUX
ejpam-5934	27	10	applied	apply	VERB
ejpam-5934	27	11	,	,	PUNCT
ejpam-5934	27	12	involving	involve	VERB
ejpam-5934	27	13	similar	similar	ADJ
ejpam-5934	27	14	steps	step	NOUN
ejpam-5934	27	15	of	of	ADP
ejpam-5934	27	16	pre	pre	ADJ
ejpam-5934	27	17	-	-	ADJ
ejpam-5934	27	18	processing	processing	NOUN
ejpam-5934	27	19	and	and	CCONJ
ejpam-5934	27	20	the	the	DET
ejpam-5934	27	21	application	application	NOUN
ejpam-5934	27	22	of	of	ADP
ejpam-5934	27	23	ml	ml	NOUN
ejpam-5934	27	24	algorithms	algorithm	NOUN
ejpam-5934	27	25	.	.	PUNCT
ejpam-5934	28	1	after	after	ADP
ejpam-5934	28	2	evaluating	evaluate	VERB
ejpam-5934	28	3	the	the	DET
ejpam-5934	28	4	rst	rst	NOUN
ejpam-5934	28	5	based	base	VERB
ejpam-5934	28	6	models	model	NOUN
ejpam-5934	28	7	,	,	PUNCT
ejpam-5934	28	8	a	a	DET
ejpam-5934	28	9	comparison	comparison	NOUN
ejpam-5934	28	10	was	be	AUX
ejpam-5934	28	11	made	make	VERB
ejpam-5934	28	12	between	between	ADP
ejpam-5934	28	13	the	the	DET
ejpam-5934	28	14	results	result	NOUN
ejpam-5934	28	15	of	of	ADP
ejpam-5934	28	16	the	the	DET
ejpam-5934	28	17	original	original	ADJ
ejpam-5934	28	18	ml	ml	NOUN
ejpam-5934	28	19	models	model	NOUN
ejpam-5934	28	20	and	and	CCONJ
ejpam-5934	28	21	those	those	PRON
ejpam-5934	28	22	utilizing	utilize	VERB
ejpam-5934	28	23	rst	rst	PROPN
ejpam-5934	28	24	based	base	VERB
ejpam-5934	28	25	feature	feature	NOUN
ejpam-5934	28	26	selection	selection	NOUN
ejpam-5934	28	27	.	.	PUNCT
ejpam-5934	29	1	this	this	DET
ejpam-5934	29	2	comparative	comparative	ADJ
ejpam-5934	29	3	analysis	analysis	NOUN
ejpam-5934	29	4	highlights	highlight	VERB
ejpam-5934	29	5	the	the	DET
ejpam-5934	29	6	impact	impact	NOUN
ejpam-5934	29	7	of	of	ADP
ejpam-5934	29	8	rst	rst	PROPN
ejpam-5934	29	9	on	on	ADP
ejpam-5934	29	10	improving	improve	VERB
ejpam-5934	29	11	classification	classification	NOUN
ejpam-5934	29	12	performance	performance	NOUN
ejpam-5934	29	13	in	in	ADP
ejpam-5934	29	14	various	various	ADJ
ejpam-5934	29	15	models	model	NOUN
ejpam-5934	29	16	and	and	CCONJ
ejpam-5934	29	17	provides	provide	VERB
ejpam-5934	29	18	insight	insight	NOUN
ejpam-5934	29	19	into	into	ADP
ejpam-5934	29	20	its	its	PRON
ejpam-5934	29	21	potential	potential	NOUN
ejpam-5934	29	22	to	to	PART
ejpam-5934	29	23	improve	improve	VERB
ejpam-5934	29	24	model	model	NOUN
ejpam-5934	29	25	accuracy	accuracy	NOUN
ejpam-5934	29	26	and	and	CCONJ
ejpam-5934	29	27	robustness	robustness	NOUN
ejpam-5934	29	28	.	.	PUNCT
ejpam-5934	30	1	1.1	1.1	NUM
ejpam-5934	30	2	.	.	PUNCT
ejpam-5934	30	3	related	relate	VERB
ejpam-5934	30	4	work	work	NOUN
ejpam-5934	30	5	pawlak	pawlak	ADV
ejpam-5934	30	6	[	[	X
ejpam-5934	30	7	1	1	NUM
ejpam-5934	30	8	]	]	PUNCT
ejpam-5934	30	9	was	be	AUX
ejpam-5934	30	10	the	the	DET
ejpam-5934	30	11	one	one	NUM
ejpam-5934	30	12	who	who	PRON
ejpam-5934	30	13	first	first	ADV
ejpam-5934	30	14	proposed	propose	VERB
ejpam-5934	30	15	the	the	DET
ejpam-5934	30	16	theory	theory	NOUN
ejpam-5934	30	17	of	of	ADP
ejpam-5934	30	18	uncertainty	uncertainty	NOUN
ejpam-5934	30	19	and	and	CCONJ
ejpam-5934	30	20	rst	rst	NOUN
ejpam-5934	30	21	,	,	PUNCT
ejpam-5934	30	22	and	and	CCONJ
ejpam-5934	30	23	later	later	ADV
ejpam-5934	30	24	modified	modify	VERB
ejpam-5934	30	25	it	it	PRON
ejpam-5934	30	26	.	.	PUNCT
ejpam-5934	31	1	the	the	DET
ejpam-5934	31	2	cardiac	cardiac	ADV
ejpam-5934	31	3	-	-	PUNCT
ejpam-5934	31	4	related	relate	VERB
ejpam-5934	31	5	dataset	dataset	NOUN
ejpam-5934	31	6	was	be	AUX
ejpam-5934	31	7	classified	classify	VERB
ejpam-5934	31	8	and	and	CCONJ
ejpam-5934	31	9	forecasted	forecast	VERB
ejpam-5934	31	10	using	use	VERB
ejpam-5934	31	11	a	a	DET
ejpam-5934	31	12	variety	variety	NOUN
ejpam-5934	31	13	of	of	ADP
ejpam-5934	31	14	ml	ml	ADP
ejpam-5934	31	15	algorithms	algorithm	NOUN
ejpam-5934	31	16	,	,	PUNCT
ejpam-5934	31	17	such	such	ADJ
ejpam-5934	31	18	as	as	ADP
ejpam-5934	31	19	nb	nb	PROPN
ejpam-5934	31	20	,	,	PUNCT
ejpam-5934	31	21	svm	svm	PROPN
ejpam-5934	31	22	,	,	PUNCT
ejpam-5934	31	23	dt	dt	NOUN
ejpam-5934	31	24	j48	j48	PROPN
ejpam-5934	31	25	,	,	PUNCT
ejpam-5934	31	26	jrip	jrip	ADJ
ejpam-5934	31	27	,	,	PUNCT
ejpam-5934	31	28	adaboost	adaboost	ADV
ejpam-5934	31	29	,	,	PUNCT
ejpam-5934	31	30	knn	knn	PROPN
ejpam-5934	31	31	,	,	PUNCT
ejpam-5934	31	32	and	and	CCONJ
ejpam-5934	31	33	stochastic	stochastic	ADJ
ejpam-5934	31	34	gradient	gradient	NOUN
ejpam-5934	31	35	descents	descent	NOUN
ejpam-5934	31	36	(	(	PUNCT
ejpam-5934	31	37	sgd	sgd	NOUN
ejpam-5934	31	38	)	)	PUNCT
ejpam-5934	31	39	,	,	PUNCT
ejpam-5934	31	40	and	and	CCONJ
ejpam-5934	31	41	several	several	ADJ
ejpam-5934	31	42	others	other	NOUN
ejpam-5934	31	43	by	by	ADP
ejpam-5934	31	44	mohan	mohan	PROPN
ejpam-5934	31	45	et	et	PROPN
ejpam-5934	31	46	al	al	PROPN
ejpam-5934	31	47	.	.	PUNCT
ejpam-5934	32	1	[	[	X
ejpam-5934	32	2	3	3	NUM
ejpam-5934	32	3	]	]	PUNCT
ejpam-5934	32	4	.	.	PUNCT
ejpam-5934	33	1	using	use	VERB
ejpam-5934	33	2	rst	rst	PROPN
ejpam-5934	33	3	,	,	PUNCT
ejpam-5934	33	4	mishra	mishra	PROPN
ejpam-5934	33	5	et	et	PROPN
ejpam-5934	33	6	al	al	PROPN
ejpam-5934	33	7	.	.	PUNCT
ejpam-5934	34	1	[	[	X
ejpam-5934	34	2	4	4	X
ejpam-5934	34	3	]	]	PUNCT
ejpam-5934	34	4	offered	offer	VERB
ejpam-5934	34	5	a	a	DET
ejpam-5934	34	6	set	set	NOUN
ejpam-5934	34	7	of	of	ADP
ejpam-5934	34	8	guidelines	guideline	NOUN
ejpam-5934	34	9	for	for	ADP
ejpam-5934	34	10	solving	solve	VERB
ejpam-5934	34	11	social	social	ADJ
ejpam-5934	34	12	science	science	NOUN
ejpam-5934	34	13	challenges	challenge	NOUN
ejpam-5934	34	14	.	.	PUNCT
ejpam-5934	35	1	in	in	ADP
ejpam-5934	35	2	order	order	NOUN
ejpam-5934	35	3	to	to	PART
ejpam-5934	35	4	obtain	obtain	VERB
ejpam-5934	35	5	justice	justice	NOUN
ejpam-5934	35	6	,	,	PUNCT
ejpam-5934	35	7	employees	employee	NOUN
ejpam-5934	35	8	frequently	frequently	ADV
ejpam-5934	35	9	turn	turn	VERB
ejpam-5934	35	10	to	to	ADP
ejpam-5934	35	11	legal	legal	ADJ
ejpam-5934	35	12	authorities	authority	NOUN
ejpam-5934	35	13	,	,	PUNCT
ejpam-5934	35	14	which	which	PRON
ejpam-5934	35	15	is	be	AUX
ejpam-5934	35	16	harmful	harmful	ADJ
ejpam-5934	35	17	to	to	ADP
ejpam-5934	35	18	both	both	CCONJ
ejpam-5934	35	19	the	the	DET
ejpam-5934	35	20	employer	employer	NOUN
ejpam-5934	35	21	and	and	CCONJ
ejpam-5934	35	22	the	the	DET
ejpam-5934	35	23	employee	employee	NOUN
ejpam-5934	35	24	.	.	PUNCT
ejpam-5934	36	1	the	the	DET
ejpam-5934	36	2	paper	paper	NOUN
ejpam-5934	36	3	addresses	address	VERB
ejpam-5934	36	4	the	the	DET
ejpam-5934	36	5	need	need	NOUN
ejpam-5934	36	6	for	for	SCONJ
ejpam-5934	36	7	employers	employer	NOUN
ejpam-5934	36	8	in	in	ADP
ejpam-5934	36	9	various	various	ADJ
ejpam-5934	36	10	organizations	organization	NOUN
ejpam-5934	36	11	to	to	PART
ejpam-5934	36	12	provide	provide	VERB
ejpam-5934	36	13	proper	proper	ADJ
ejpam-5934	36	14	justice	justice	NOUN
ejpam-5934	36	15	.	.	PUNCT
ejpam-5934	37	1	the	the	DET
ejpam-5934	37	2	key	key	ADJ
ejpam-5934	37	3	characteristics	characteristic	NOUN
ejpam-5934	37	4	that	that	PRON
ejpam-5934	37	5	contribute	contribute	VERB
ejpam-5934	37	6	to	to	ADP
ejpam-5934	37	7	this	this	DET
ejpam-5934	37	8	kind	kind	NOUN
ejpam-5934	37	9	of	of	ADP
ejpam-5934	37	10	situation	situation	NOUN
ejpam-5934	37	11	in	in	ADP
ejpam-5934	37	12	various	various	ADJ
ejpam-5934	37	13	establishments	establishment	NOUN
ejpam-5934	37	14	were	be	AUX
ejpam-5934	37	15	identified	identify	VERB
ejpam-5934	37	16	using	use	VERB
ejpam-5934	37	17	rst	rst	PROPN
ejpam-5934	37	18	.	.	PUNCT
ejpam-5934	38	1	nayak	nayak	PROPN
ejpam-5934	38	2	et	et	PROPN
ejpam-5934	38	3	al	al	PROPN
ejpam-5934	38	4	.	.	PUNCT
ejpam-5934	39	1	[	[	X
ejpam-5934	39	2	5	5	NUM
ejpam-5934	39	3	]	]	PUNCT
ejpam-5934	39	4	created	create	VERB
ejpam-5934	39	5	a	a	DET
ejpam-5934	39	6	model	model	NOUN
ejpam-5934	39	7	using	use	VERB
ejpam-5934	39	8	rst	rst	PROPN
ejpam-5934	39	9	for	for	ADP
ejpam-5934	39	10	malaria	malaria	NOUN
ejpam-5934	39	11	symptom	symptom	NOUN
ejpam-5934	39	12	prediction	prediction	NOUN
ejpam-5934	39	13	.	.	PUNCT
ejpam-5934	40	1	in	in	ADP
ejpam-5934	40	2	order	order	NOUN
ejpam-5934	40	3	to	to	PART
ejpam-5934	40	4	identify	identify	VERB
ejpam-5934	40	5	the	the	DET
ejpam-5934	40	6	accurate	accurate	ADJ
ejpam-5934	40	7	symptoms	symptom	NOUN
ejpam-5934	40	8	of	of	ADP
ejpam-5934	40	9	malaria	malaria	NOUN
ejpam-5934	40	10	,	,	PUNCT
ejpam-5934	40	11	the	the	DET
ejpam-5934	40	12	study	study	NOUN
ejpam-5934	40	13	addresses	address	VERB
ejpam-5934	40	14	the	the	DET
ejpam-5934	40	15	application	application	NOUN
ejpam-5934	40	16	of	of	ADP
ejpam-5934	40	17	rst	rst	PROPN
ejpam-5934	40	18	to	to	PART
ejpam-5934	40	19	extract	extract	VERB
ejpam-5934	40	20	hidden	hidden	ADJ
ejpam-5934	40	21	information	information	NOUN
ejpam-5934	40	22	from	from	ADP
ejpam-5934	40	23	a	a	DET
ejpam-5934	40	24	set	set	NOUN
ejpam-5934	40	25	of	of	ADP
ejpam-5934	40	26	imprecise	imprecise	ADJ
ejpam-5934	40	27	data	datum	NOUN
ejpam-5934	40	28	.	.	PUNCT
ejpam-5934	41	1	research	research	NOUN
ejpam-5934	41	2	has	have	AUX
ejpam-5934	41	3	indicated	indicate	VERB
ejpam-5934	41	4	that	that	SCONJ
ejpam-5934	41	5	rst	rst	PROPN
ejpam-5934	41	6	is	be	AUX
ejpam-5934	41	7	marginally	marginally	ADV
ejpam-5934	41	8	superior	superior	ADJ
ejpam-5934	41	9	to	to	ADP
ejpam-5934	41	10	other	other	ADJ
ejpam-5934	41	11	soft	soft	ADJ
ejpam-5934	41	12	computing	computing	NOUN
ejpam-5934	41	13	techniques	technique	NOUN
ejpam-5934	41	14	and	and	CCONJ
ejpam-5934	41	15	is	be	AUX
ejpam-5934	41	16	a	a	DET
ejpam-5934	41	17	valuable	valuable	ADJ
ejpam-5934	41	18	tool	tool	NOUN
ejpam-5934	41	19	for	for	ADP
ejpam-5934	41	20	handling	handle	VERB
ejpam-5934	41	21	ambiguous	ambiguous	ADJ
ejpam-5934	41	22	data	datum	NOUN
ejpam-5934	41	23	.	.	PUNCT
ejpam-5934	42	1	subhalaxmi	subhalaxmi	VERB
ejpam-5934	42	2	das	das	PROPN
ejpam-5934	42	3	et	et	PROPN
ejpam-5934	42	4	al	al	PROPN
ejpam-5934	42	5	.	.	PUNCT
ejpam-5934	43	1	[	[	X
ejpam-5934	43	2	6	6	NUM
ejpam-5934	43	3	]	]	PUNCT
ejpam-5934	43	4	has	have	AUX
ejpam-5934	43	5	developed	develop	VERB
ejpam-5934	43	6	a	a	DET
ejpam-5934	43	7	technique	technique	NOUN
ejpam-5934	43	8	for	for	ADP
ejpam-5934	43	9	diagnosis	diagnosis	NOUN
ejpam-5934	43	10	of	of	ADP
ejpam-5934	43	11	cardiac	cardiac	ADJ
ejpam-5934	43	12	problem	problem	NOUN
ejpam-5934	43	13	using	use	VERB
ejpam-5934	43	14	rst	rst	PROPN
ejpam-5934	43	15	and	and	CCONJ
ejpam-5934	43	16	ml	ml	NOUN
ejpam-5934	43	17	.	.	PUNCT
ejpam-5934	44	1	the	the	DET
ejpam-5934	44	2	study	study	NOUN
ejpam-5934	44	3	proposes	propose	VERB
ejpam-5934	44	4	a	a	DET
ejpam-5934	44	5	model	model	NOUN
ejpam-5934	44	6	to	to	PART
ejpam-5934	44	7	diagnose	diagnose	VERB
ejpam-5934	44	8	cardiac	cardiac	ADJ
ejpam-5934	44	9	disorders	disorder	NOUN
ejpam-5934	44	10	by	by	ADP
ejpam-5934	44	11	utilizing	utilize	VERB
ejpam-5934	44	12	ml	ml	NOUN
ejpam-5934	44	13	techniques	technique	NOUN
ejpam-5934	44	14	in	in	ADP
ejpam-5934	44	15	conjunction	conjunction	NOUN
ejpam-5934	44	16	with	with	ADP
ejpam-5934	44	17	the	the	DET
ejpam-5934	44	18	stacking	stacking	NOUN
ejpam-5934	44	19	method	method	NOUN
ejpam-5934	44	20	.	.	PUNCT
ejpam-5934	45	1	the	the	DET
ejpam-5934	45	2	study	study	NOUN
ejpam-5934	45	3	uses	use	VERB
ejpam-5934	45	4	the	the	DET
ejpam-5934	45	5	cleveland	cleveland	PROPN
ejpam-5934	45	6	dataset	dataset	VERB
ejpam-5934	45	7	to	to	PART
ejpam-5934	45	8	diagnose	diagnose	VERB
ejpam-5934	45	9	cardiac	cardiac	ADJ
ejpam-5934	45	10	issues	issue	NOUN
ejpam-5934	45	11	.	.	PUNCT
ejpam-5934	46	1	rst	rst	PROPN
ejpam-5934	46	2	was	be	AUX
ejpam-5934	46	3	used	use	VERB
ejpam-5934	46	4	t.	t.	NOUN
ejpam-5934	46	5	ashika	ashika	NOUN
ejpam-5934	46	6	,	,	PUNCT
ejpam-5934	46	7	g.	g.	PROPN
ejpam-5934	46	8	h.	h.	PROPN
ejpam-5934	46	9	grace	grace	PROPN
ejpam-5934	46	10	/	/	SYM
ejpam-5934	46	11	eur	eur	PROPN
ejpam-5934	46	12	.	.	PUNCT
ejpam-5934	47	1	j.	j.	PROPN
ejpam-5934	47	2	pure	pure	PROPN
ejpam-5934	47	3	appl	appl	PROPN
ejpam-5934	47	4	.	.	PROPN
ejpam-5934	47	5	math	math	PROPN
ejpam-5934	47	6	,	,	PUNCT
ejpam-5934	47	7	18	18	NUM
ejpam-5934	47	8	(	(	PUNCT
ejpam-5934	47	9	2	2	NUM
ejpam-5934	47	10	)	)	PUNCT
ejpam-5934	47	11	(	(	PUNCT
ejpam-5934	47	12	2025	2025	NUM
ejpam-5934	47	13	)	)	PUNCT
ejpam-5934	47	14	,	,	PUNCT
ejpam-5934	47	15	5934	5934	NUM
ejpam-5934	47	16	3	3	NUM
ejpam-5934	47	17	of	of	ADP
ejpam-5934	47	18	22	22	NUM
ejpam-5934	47	19	to	to	PART
ejpam-5934	47	20	determine	determine	VERB
ejpam-5934	47	21	the	the	DET
ejpam-5934	47	22	most	most	ADV
ejpam-5934	47	23	significant	significant	ADJ
ejpam-5934	47	24	disease	disease	NOUN
ejpam-5934	47	25	among	among	ADP
ejpam-5934	47	26	all	all	DET
ejpam-5934	47	27	cardiac	cardiac	ADJ
ejpam-5934	47	28	-	-	PUNCT
ejpam-5934	47	29	related	relate	VERB
ejpam-5934	47	30	disease	disease	NOUN
ejpam-5934	47	31	.	.	PUNCT
ejpam-5934	48	1	the	the	DET
ejpam-5934	48	2	model	model	NOUN
ejpam-5934	48	3	’s	’s	PART
ejpam-5934	48	4	performance	performance	NOUN
ejpam-5934	48	5	was	be	AUX
ejpam-5934	48	6	assessed	assess	VERB
ejpam-5934	48	7	using	use	VERB
ejpam-5934	48	8	f1	f1	PROPN
ejpam-5934	48	9	score	score	NOUN
ejpam-5934	48	10	,	,	PUNCT
ejpam-5934	48	11	recall	recall	NOUN
ejpam-5934	48	12	,	,	PUNCT
ejpam-5934	48	13	accuracy	accuracy	NOUN
ejpam-5934	48	14	,	,	PUNCT
ejpam-5934	48	15	and	and	CCONJ
ejpam-5934	48	16	precision	precision	NOUN
ejpam-5934	48	17	.	.	PUNCT
ejpam-5934	49	1	additionally	additionally	ADV
ejpam-5934	49	2	,	,	PUNCT
ejpam-5934	49	3	error	error	NOUN
ejpam-5934	49	4	functions	function	NOUN
ejpam-5934	49	5	were	be	AUX
ejpam-5934	49	6	computed	compute	VERB
ejpam-5934	49	7	to	to	PART
ejpam-5934	49	8	evaluate	evaluate	VERB
ejpam-5934	49	9	the	the	DET
ejpam-5934	49	10	performance	performance	NOUN
ejpam-5934	49	11	of	of	ADP
ejpam-5934	49	12	the	the	DET
ejpam-5934	49	13	models	model	NOUN
ejpam-5934	49	14	.	.	PUNCT
ejpam-5934	50	1	rani	rani	PROPN
ejpam-5934	50	2	nuraeni	nuraeni	ADJ
ejpam-5934	50	3	and	and	CCONJ
ejpam-5934	50	4	sugiyarto	sugiyarto	PROPN
ejpam-5934	50	5	surono	surono	NOUN
ejpam-5934	50	6	[	[	X
ejpam-5934	50	7	7	7	NUM
ejpam-5934	50	8	]	]	PUNCT
ejpam-5934	50	9	has	have	AUX
ejpam-5934	50	10	proposed	propose	VERB
ejpam-5934	50	11	rst	rst	PROPN
ejpam-5934	50	12	for	for	ADP
ejpam-5934	50	13	dimension	dimension	NOUN
ejpam-5934	50	14	reduction	reduction	NOUN
ejpam-5934	50	15	on	on	ADP
ejpam-5934	50	16	ml	ml	ADP
ejpam-5934	50	17	algorithm	algorithm	NOUN
ejpam-5934	50	18	.	.	PUNCT
ejpam-5934	51	1	the	the	DET
ejpam-5934	51	2	use	use	NOUN
ejpam-5934	51	3	of	of	ADP
ejpam-5934	51	4	dimension	dimension	NOUN
ejpam-5934	51	5	reduction	reduction	NOUN
ejpam-5934	51	6	in	in	ADP
ejpam-5934	51	7	ml	ml	NOUN
ejpam-5934	51	8	to	to	PART
ejpam-5934	51	9	increase	increase	VERB
ejpam-5934	51	10	computational	computational	ADJ
ejpam-5934	51	11	efficiency	efficiency	NOUN
ejpam-5934	51	12	is	be	AUX
ejpam-5934	51	13	covered	cover	VERB
ejpam-5934	51	14	in	in	ADP
ejpam-5934	51	15	this	this	DET
ejpam-5934	51	16	paper	paper	NOUN
ejpam-5934	51	17	.	.	PUNCT
ejpam-5934	52	1	the	the	DET
ejpam-5934	52	2	authors	author	NOUN
ejpam-5934	52	3	convert	convert	VERB
ejpam-5934	52	4	high	high	ADJ
ejpam-5934	52	5	-	-	PUNCT
ejpam-5934	52	6	dimensional	dimensional	ADJ
ejpam-5934	52	7	data	datum	NOUN
ejpam-5934	52	8	into	into	ADP
ejpam-5934	52	9	much	much	ADV
ejpam-5934	52	10	lower	low	ADJ
ejpam-5934	52	11	dimensions	dimension	NOUN
ejpam-5934	52	12	without	without	ADP
ejpam-5934	52	13	appreciably	appreciably	ADV
ejpam-5934	52	14	losing	lose	VERB
ejpam-5934	52	15	the	the	DET
ejpam-5934	52	16	original	original	ADJ
ejpam-5934	52	17	characteristics	characteristic	NOUN
ejpam-5934	52	18	and	and	CCONJ
ejpam-5934	52	19	information	information	NOUN
ejpam-5934	52	20	of	of	ADP
ejpam-5934	52	21	the	the	DET
ejpam-5934	52	22	data	datum	NOUN
ejpam-5934	52	23	using	use	VERB
ejpam-5934	52	24	rst	rst	PROPN
ejpam-5934	52	25	.	.	PUNCT
ejpam-5934	53	1	the	the	DET
ejpam-5934	53	2	authors	author	NOUN
ejpam-5934	53	3	make	make	VERB
ejpam-5934	53	4	use	use	NOUN
ejpam-5934	53	5	of	of	ADP
ejpam-5934	53	6	five	five	NUM
ejpam-5934	53	7	uci	uci	PROPN
ejpam-5934	53	8	ml	ml	NOUN
ejpam-5934	53	9	datasets	dataset	NOUN
ejpam-5934	53	10	and	and	CCONJ
ejpam-5934	53	11	applied	apply	VERB
ejpam-5934	53	12	core	core	NOUN
ejpam-5934	53	13	and	and	CCONJ
ejpam-5934	53	14	reduct	reduct	NOUN
ejpam-5934	53	15	.	.	PUNCT
ejpam-5934	54	1	the	the	DET
ejpam-5934	54	2	performance	performance	NOUN
ejpam-5934	54	3	of	of	ADP
ejpam-5934	54	4	the	the	DET
ejpam-5934	54	5	reduced	reduce	VERB
ejpam-5934	54	6	dataset	dataset	NOUN
ejpam-5934	54	7	is	be	AUX
ejpam-5934	54	8	evaluated	evaluate	VERB
ejpam-5934	54	9	using	use	VERB
ejpam-5934	54	10	popular	popular	ADJ
ejpam-5934	54	11	ml	ml	NOUN
ejpam-5934	54	12	techniques	technique	NOUN
ejpam-5934	54	13	like	like	ADP
ejpam-5934	54	14	svm	svm	PROPN
ejpam-5934	54	15	,	,	PUNCT
ejpam-5934	54	16	lr	lr	NOUN
ejpam-5934	54	17	,	,	PUNCT
ejpam-5934	54	18	and	and	CCONJ
ejpam-5934	54	19	knn	knn	PROPN
ejpam-5934	54	20	.	.	PROPN
ejpam-5934	55	1	according	accord	VERB
ejpam-5934	55	2	to	to	ADP
ejpam-5934	55	3	the	the	DET
ejpam-5934	55	4	research	research	NOUN
ejpam-5934	55	5	,	,	PUNCT
ejpam-5934	55	6	core	core	NOUN
ejpam-5934	55	7	and	and	CCONJ
ejpam-5934	55	8	reduct	reduct	PROPN
ejpam-5934	55	9	can	can	AUX
ejpam-5934	55	10	reduce	reduce	VERB
ejpam-5934	55	11	computing	computing	NOUN
ejpam-5934	55	12	time	time	NOUN
ejpam-5934	55	13	by	by	ADP
ejpam-5934	55	14	up	up	ADP
ejpam-5934	55	15	to	to	PART
ejpam-5934	55	16	80	80	NUM
ejpam-5934	55	17	%	%	NOUN
ejpam-5934	55	18	without	without	ADP
ejpam-5934	55	19	compromising	compromise	VERB
ejpam-5934	55	20	the	the	DET
ejpam-5934	55	21	value	value	NOUN
ejpam-5934	55	22	of	of	ADP
ejpam-5934	55	23	each	each	DET
ejpam-5934	55	24	evaluation	evaluation	NOUN
ejpam-5934	55	25	model	model	NOUN
ejpam-5934	55	26	.	.	PUNCT
ejpam-5934	56	1	a	a	DET
ejpam-5934	56	2	prediction	prediction	NOUN
ejpam-5934	56	3	model	model	NOUN
ejpam-5934	56	4	for	for	ADP
ejpam-5934	56	5	building	build	VERB
ejpam-5934	56	6	energy	energy	NOUN
ejpam-5934	56	7	consumption	consumption	NOUN
ejpam-5934	56	8	based	base	VERB
ejpam-5934	56	9	on	on	ADP
ejpam-5934	56	10	rst	rst	PROPN
ejpam-5934	56	11	and	and	CCONJ
ejpam-5934	56	12	deep	deep	ADJ
ejpam-5934	56	13	neural	neural	ADJ
ejpam-5934	56	14	network	network	NOUN
ejpam-5934	56	15	(	(	PUNCT
ejpam-5934	56	16	dnn	dnn	PROPN
ejpam-5934	56	17	)	)	PUNCT
ejpam-5934	56	18	has	have	AUX
ejpam-5934	56	19	been	be	AUX
ejpam-5934	56	20	developed	develop	VERB
ejpam-5934	56	21	by	by	ADP
ejpam-5934	56	22	lei	lei	PROPN
ejpam-5934	56	23	lei	lei	X
ejpam-5934	56	24	et	et	PROPN
ejpam-5934	56	25	al	al	PROPN
ejpam-5934	56	26	.	.	PUNCT
ejpam-5934	57	1	[	[	X
ejpam-5934	57	2	8	8	NUM
ejpam-5934	57	3	]	]	PUNCT
ejpam-5934	57	4	.	.	PUNCT
ejpam-5934	58	1	rst	rst	PROPN
ejpam-5934	58	2	is	be	AUX
ejpam-5934	58	3	used	use	VERB
ejpam-5934	58	4	to	to	PART
ejpam-5934	58	5	minimize	minimize	VERB
ejpam-5934	58	6	unnecessary	unnecessary	ADJ
ejpam-5934	58	7	influencing	influence	VERB
ejpam-5934	58	8	factors	factor	NOUN
ejpam-5934	58	9	and	and	CCONJ
ejpam-5934	58	10	to	to	PART
ejpam-5934	58	11	identify	identify	VERB
ejpam-5934	58	12	the	the	DET
ejpam-5934	58	13	essential	essential	ADJ
ejpam-5934	58	14	components	component	NOUN
ejpam-5934	58	15	of	of	ADP
ejpam-5934	58	16	building	build	VERB
ejpam-5934	58	17	energy	energy	NOUN
ejpam-5934	58	18	consumption	consumption	NOUN
ejpam-5934	58	19	.	.	PUNCT
ejpam-5934	59	1	next	next	ADV
ejpam-5934	59	2	,	,	PUNCT
ejpam-5934	59	3	a	a	DET
ejpam-5934	59	4	dnn	dnn	PROPN
ejpam-5934	59	5	receives	receive	VERB
ejpam-5934	59	6	these	these	DET
ejpam-5934	59	7	essential	essential	ADJ
ejpam-5934	59	8	components	component	NOUN
ejpam-5934	59	9	.	.	PUNCT
ejpam-5934	60	1	the	the	DET
ejpam-5934	60	2	output	output	NOUN
ejpam-5934	60	3	of	of	ADP
ejpam-5934	60	4	the	the	DET
ejpam-5934	60	5	dnn	dnn	PROPN
ejpam-5934	60	6	is	be	AUX
ejpam-5934	60	7	the	the	DET
ejpam-5934	60	8	amount	amount	NOUN
ejpam-5934	60	9	of	of	ADP
ejpam-5934	60	10	energy	energy	NOUN
ejpam-5934	60	11	consumed	consume	VERB
ejpam-5934	60	12	by	by	ADP
ejpam-5934	60	13	buildings	building	NOUN
ejpam-5934	60	14	.	.	PUNCT
ejpam-5934	61	1	initially	initially	ADV
ejpam-5934	61	2	,	,	PUNCT
ejpam-5934	61	3	data	datum	NOUN
ejpam-5934	61	4	was	be	AUX
ejpam-5934	61	5	collected	collect	VERB
ejpam-5934	61	6	from	from	ADP
ejpam-5934	61	7	100	100	NUM
ejpam-5934	61	8	public	public	ADJ
ejpam-5934	61	9	buildings	building	NOUN
ejpam-5934	61	10	in	in	ADP
ejpam-5934	61	11	the	the	DET
ejpam-5934	61	12	civil	civil	ADJ
ejpam-5934	61	13	public	public	ADJ
ejpam-5934	61	14	buildings	building	NOUN
ejpam-5934	61	15	.	.	PUNCT
ejpam-5934	62	1	subsequently	subsequently	ADV
ejpam-5934	62	2	,	,	PUNCT
ejpam-5934	62	3	dnns	dnn	NOUN
ejpam-5934	62	4	were	be	AUX
ejpam-5934	62	5	trained	train	VERB
ejpam-5934	62	6	and	and	CCONJ
ejpam-5934	62	7	tested	test	VERB
ejpam-5934	62	8	using	use	VERB
ejpam-5934	62	9	data	datum	NOUN
ejpam-5934	62	10	gathered	gather	VERB
ejpam-5934	62	11	from	from	ADP
ejpam-5934	62	12	a	a	DET
ejpam-5934	62	13	university	university	NOUN
ejpam-5934	62	14	lab	lab	NOUN
ejpam-5934	62	15	in	in	ADP
ejpam-5934	62	16	dalian	dalian	PROPN
ejpam-5934	62	17	.	.	PUNCT
ejpam-5934	63	1	the	the	DET
ejpam-5934	63	2	study	study	NOUN
ejpam-5934	63	3	examined	examine	VERB
ejpam-5934	63	4	both	both	DET
ejpam-5934	63	5	shortand	shortand	NOUN
ejpam-5934	63	6	medium	medium	ADJ
ejpam-5934	63	7	-	-	PUNCT
ejpam-5934	63	8	term	term	NOUN
ejpam-5934	63	9	energy	energy	NOUN
ejpam-5934	63	10	consumption	consumption	NOUN
ejpam-5934	63	11	predictions	prediction	NOUN
ejpam-5934	63	12	for	for	ADP
ejpam-5934	63	13	buildings	building	NOUN
ejpam-5934	63	14	.	.	PUNCT
ejpam-5934	64	1	the	the	DET
ejpam-5934	64	2	outcomes	outcome	NOUN
ejpam-5934	64	3	of	of	ADP
ejpam-5934	64	4	the	the	DET
ejpam-5934	64	5	fuzzy	fuzzy	ADJ
ejpam-5934	64	6	,	,	PUNCT
ejpam-5934	64	7	elman	elman	NOUN
ejpam-5934	64	8	,	,	PUNCT
ejpam-5934	64	9	and	and	CCONJ
ejpam-5934	64	10	backpropagation	backpropagation	NOUN
ejpam-5934	64	11	neural	neural	ADJ
ejpam-5934	64	12	networks	network	NOUN
ejpam-5934	64	13	were	be	AUX
ejpam-5934	64	14	compared	compare	VERB
ejpam-5934	64	15	with	with	ADP
ejpam-5934	64	16	those	those	PRON
ejpam-5934	64	17	of	of	ADP
ejpam-5934	64	18	the	the	DET
ejpam-5934	64	19	dnn	dnn	PROPN
ejpam-5934	64	20	.	.	PROPN
ejpam-5934	65	1	compared	compare	VERB
ejpam-5934	65	2	to	to	ADP
ejpam-5934	65	3	previous	previous	ADJ
ejpam-5934	65	4	research	research	NOUN
ejpam-5934	65	5	works	work	NOUN
ejpam-5934	65	6	,	,	PUNCT
ejpam-5934	65	7	the	the	DET
ejpam-5934	65	8	combination	combination	NOUN
ejpam-5934	65	9	of	of	ADP
ejpam-5934	65	10	rst	rst	PROPN
ejpam-5934	65	11	and	and	CCONJ
ejpam-5934	65	12	dnn	dnn	PROPN
ejpam-5934	65	13	turned	turn	VERB
ejpam-5934	65	14	out	out	ADP
ejpam-5934	65	15	to	to	PART
ejpam-5934	65	16	be	be	AUX
ejpam-5934	65	17	the	the	DET
ejpam-5934	65	18	most	most	ADV
ejpam-5934	65	19	exact	exact	ADJ
ejpam-5934	65	20	.	.	PUNCT
ejpam-5934	66	1	lukshmi	lukshmi	PROPN
ejpam-5934	66	2	r.a	r.a	PROPN
ejpam-5934	66	3	et	et	NOUN
ejpam-5934	66	4	al	al	PROPN
ejpam-5934	66	5	.	.	PUNCT
ejpam-5934	67	1	[	[	X
ejpam-5934	67	2	9	9	NUM
ejpam-5934	67	3	]	]	PUNCT
ejpam-5934	67	4	analyzed	analyze	VERB
ejpam-5934	67	5	rst	rst	ADJ
ejpam-5934	67	6	approach	approach	NOUN
ejpam-5934	67	7	for	for	ADP
ejpam-5934	67	8	attribute	attribute	NOUN
ejpam-5934	67	9	reduction	reduction	NOUN
ejpam-5934	67	10	.	.	PUNCT
ejpam-5934	68	1	in	in	ADP
ejpam-5934	68	2	order	order	NOUN
ejpam-5934	68	3	to	to	PART
ejpam-5934	68	4	create	create	VERB
ejpam-5934	68	5	an	an	DET
ejpam-5934	68	6	efficient	efficient	ADJ
ejpam-5934	68	7	reduct	reduct	NOUN
ejpam-5934	68	8	set	set	VERB
ejpam-5934	68	9	and	and	CCONJ
ejpam-5934	68	10	formulate	formulate	VERB
ejpam-5934	68	11	the	the	DET
ejpam-5934	68	12	core	core	NOUN
ejpam-5934	68	13	of	of	ADP
ejpam-5934	68	14	the	the	DET
ejpam-5934	68	15	attribute	attribute	NOUN
ejpam-5934	68	16	set	set	VERB
ejpam-5934	68	17	,	,	PUNCT
ejpam-5934	68	18	the	the	DET
ejpam-5934	68	19	approach	approach	NOUN
ejpam-5934	68	20	focuses	focus	VERB
ejpam-5934	68	21	on	on	ADP
ejpam-5934	68	22	eliminating	eliminate	VERB
ejpam-5934	68	23	redundant	redundant	ADJ
ejpam-5934	68	24	attributes	attribute	NOUN
ejpam-5934	68	25	.	.	PUNCT
ejpam-5934	69	1	only	only	ADV
ejpam-5934	69	2	a	a	DET
ejpam-5934	69	3	subset	subset	NOUN
ejpam-5934	69	4	of	of	ADP
ejpam-5934	69	5	the	the	DET
ejpam-5934	69	6	features	feature	NOUN
ejpam-5934	69	7	that	that	PRON
ejpam-5934	69	8	maintain	maintain	VERB
ejpam-5934	69	9	the	the	DET
ejpam-5934	69	10	original	original	ADJ
ejpam-5934	69	11	feature	feature	NOUN
ejpam-5934	69	12	’s	’s	PART
ejpam-5934	69	13	accuracy	accuracy	NOUN
ejpam-5934	69	14	are	be	AUX
ejpam-5934	69	15	then	then	ADV
ejpam-5934	69	16	chosen	choose	VERB
ejpam-5934	69	17	for	for	ADP
ejpam-5934	69	18	further	further	ADJ
ejpam-5934	69	19	processing	processing	NOUN
ejpam-5934	69	20	using	use	VERB
ejpam-5934	69	21	ml	ml	NOUN
ejpam-5934	69	22	models	model	NOUN
ejpam-5934	69	23	.	.	PUNCT
ejpam-5934	70	1	vamsidhar	vamsidhar	PROPN
ejpam-5934	70	2	talasila	talasila	PROPN
ejpam-5934	70	3	et	et	PROPN
ejpam-5934	70	4	al	al	PROPN
ejpam-5934	70	5	.	.	PUNCT
ejpam-5934	71	1	[	[	X
ejpam-5934	71	2	10	10	NUM
ejpam-5934	71	3	]	]	PUNCT
ejpam-5934	71	4	predicted	predict	VERB
ejpam-5934	71	5	diseases	disease	NOUN
ejpam-5934	71	6	using	use	VERB
ejpam-5934	71	7	rst	rst	PROPN
ejpam-5934	71	8	with	with	ADP
ejpam-5934	71	9	recurrent	recurrent	ADJ
ejpam-5934	71	10	neural	neural	ADJ
ejpam-5934	71	11	network	network	NOUN
ejpam-5934	71	12	(	(	PUNCT
ejpam-5934	71	13	rnn	rnn	PROPN
ejpam-5934	71	14	)	)	PUNCT
ejpam-5934	71	15	in	in	ADP
ejpam-5934	71	16	big	big	ADJ
ejpam-5934	71	17	data	datum	NOUN
ejpam-5934	71	18	analytics	analytic	NOUN
ejpam-5934	71	19	where	where	SCONJ
ejpam-5934	71	20	rst	rst	NOUN
ejpam-5934	71	21	technique	technique	NOUN
ejpam-5934	71	22	was	be	AUX
ejpam-5934	71	23	used	use	VERB
ejpam-5934	71	24	to	to	PART
ejpam-5934	71	25	identify	identify	VERB
ejpam-5934	71	26	the	the	DET
ejpam-5934	71	27	most	most	ADV
ejpam-5934	71	28	pertinent	pertinent	ADJ
ejpam-5934	71	29	features	feature	NOUN
ejpam-5934	71	30	for	for	ADP
ejpam-5934	71	31	effective	effective	ADJ
ejpam-5934	71	32	disease	disease	NOUN
ejpam-5934	71	33	detection	detection	NOUN
ejpam-5934	71	34	and	and	CCONJ
ejpam-5934	71	35	medical	medical	ADJ
ejpam-5934	71	36	data	datum	NOUN
ejpam-5934	71	37	classification	classification	NOUN
ejpam-5934	71	38	.	.	PUNCT
ejpam-5934	72	1	the	the	DET
ejpam-5934	72	2	rnn	rnn	NOUN
ejpam-5934	72	3	method	method	NOUN
ejpam-5934	72	4	for	for	ADP
ejpam-5934	72	5	disease	disease	NOUN
ejpam-5934	72	6	prediction	prediction	NOUN
ejpam-5934	72	7	receives	receive	VERB
ejpam-5934	72	8	the	the	DET
ejpam-5934	72	9	chosen	choose	VERB
ejpam-5934	72	10	features	feature	NOUN
ejpam-5934	72	11	as	as	ADP
ejpam-5934	72	12	input	input	NOUN
ejpam-5934	72	13	.	.	PUNCT
ejpam-5934	73	1	the	the	DET
ejpam-5934	73	2	experiments	experiment	NOUN
ejpam-5934	73	3	for	for	ADP
ejpam-5934	73	4	the	the	DET
ejpam-5934	73	5	proposed	propose	VERB
ejpam-5934	73	6	method	method	NOUN
ejpam-5934	73	7	,	,	PUNCT
ejpam-5934	73	8	also	also	ADV
ejpam-5934	73	9	known	know	VERB
ejpam-5934	73	10	as	as	ADP
ejpam-5934	73	11	rst	rst	NOUN
ejpam-5934	73	12	-	-	PUNCT
ejpam-5934	73	13	rnn	rnn	PROPN
ejpam-5934	73	14	,	,	PUNCT
ejpam-5934	73	15	are	be	AUX
ejpam-5934	73	16	conducted	conduct	VERB
ejpam-5934	73	17	on	on	ADP
ejpam-5934	73	18	the	the	DET
ejpam-5934	73	19	uci	uci	PROPN
ejpam-5934	73	20	ml	ml	PROPN
ejpam-5934	73	21	repository	repository	NOUN
ejpam-5934	73	22	dataset	dataset	VERB
ejpam-5934	73	23	with	with	ADP
ejpam-5934	73	24	respect	respect	NOUN
ejpam-5934	73	25	to	to	ADP
ejpam-5934	73	26	accuracy	accuracy	NOUN
ejpam-5934	73	27	,	,	PUNCT
ejpam-5934	73	28	f	f	X
ejpam-5934	73	29	-	-	PUNCT
ejpam-5934	73	30	measure	measure	NOUN
ejpam-5934	73	31	,	,	PUNCT
ejpam-5934	73	32	sensitivity	sensitivity	NOUN
ejpam-5934	73	33	,	,	PUNCT
ejpam-5934	73	34	and	and	CCONJ
ejpam-5934	73	35	specificity	specificity	NOUN
ejpam-5934	73	36	.	.	PUNCT
ejpam-5934	74	1	the	the	DET
ejpam-5934	74	2	outcomes	outcome	NOUN
ejpam-5934	74	3	demonstrated	demonstrate	VERB
ejpam-5934	74	4	that	that	SCONJ
ejpam-5934	74	5	the	the	DET
ejpam-5934	74	6	rst	rst	PROPN
ejpam-5934	74	7	-	-	PUNCT
ejpam-5934	74	8	rnn	rnn	PROPN
ejpam-5934	74	9	approach	approach	NOUN
ejpam-5934	74	10	obtained	obtain	VERB
ejpam-5934	74	11	accuracy	accuracy	NOUN
ejpam-5934	74	12	of	of	ADP
ejpam-5934	74	13	98.57	98.57	NUM
ejpam-5934	74	14	%	%	NOUN
ejpam-5934	74	15	for	for	SCONJ
ejpam-5934	74	16	the	the	DET
ejpam-5934	74	17	heart	heart	NOUN
ejpam-5934	74	18	disease	disease	NOUN
ejpam-5934	74	19	dataset	dataset	VERB
ejpam-5934	74	20	.	.	PUNCT
ejpam-5934	75	1	touhid	touhid	VERB
ejpam-5934	75	2	mohammad	mohammad	PROPN
ejpam-5934	75	3	hossain	hossain	PROPN
ejpam-5934	75	4	et	et	PROPN
ejpam-5934	75	5	al	al	PROPN
ejpam-5934	75	6	.	.	PUNCT
ejpam-5934	76	1	[	[	X
ejpam-5934	76	2	11	11	NUM
ejpam-5934	76	3	]	]	PUNCT
ejpam-5934	76	4	had	have	AUX
ejpam-5934	76	5	discussed	discuss	VERB
ejpam-5934	76	6	a	a	DET
ejpam-5934	76	7	rst	rst	ADJ
ejpam-5934	76	8	approach	approach	NOUN
ejpam-5934	76	9	along	along	ADP
ejpam-5934	76	10	with	with	ADP
ejpam-5934	76	11	ml	ml	PROPN
ejpam-5934	76	12	in	in	ADP
ejpam-5934	76	13	electrofacies	electrofacie	NOUN
ejpam-5934	76	14	classification	classification	NOUN
ejpam-5934	76	15	and	and	CCONJ
ejpam-5934	76	16	subsurface	subsurface	NOUN
ejpam-5934	76	17	lithology	lithology	NOUN
ejpam-5934	76	18	interpretation	interpretation	NOUN
ejpam-5934	76	19	.	.	PUNCT
ejpam-5934	77	1	in	in	ADP
ejpam-5934	77	2	order	order	NOUN
ejpam-5934	77	3	to	to	PART
ejpam-5934	77	4	classify	classify	VERB
ejpam-5934	77	5	electrofacies	electrofacie	NOUN
ejpam-5934	77	6	,	,	PUNCT
ejpam-5934	77	7	the	the	DET
ejpam-5934	77	8	paper	paper	NOUN
ejpam-5934	77	9	suggests	suggest	VERB
ejpam-5934	77	10	a	a	DET
ejpam-5934	77	11	rst	rst	NOUN
ejpam-5934	77	12	-	-	PUNCT
ejpam-5934	77	13	based	base	VERB
ejpam-5934	77	14	white	white	PROPN
ejpam-5934	77	15	box	box	PROPN
ejpam-5934	77	16	classification	classification	NOUN
ejpam-5934	77	17	method	method	NOUN
ejpam-5934	77	18	that	that	PRON
ejpam-5934	77	19	generates	generate	VERB
ejpam-5934	77	20	decision	decision	NOUN
ejpam-5934	77	21	rules	rule	NOUN
ejpam-5934	77	22	.	.	PUNCT
ejpam-5934	78	1	additionally	additionally	ADV
ejpam-5934	78	2	,	,	PUNCT
ejpam-5934	78	3	the	the	DET
ejpam-5934	78	4	extra	extra	ADJ
ejpam-5934	78	5	tree	tree	NOUN
ejpam-5934	78	6	classifier	classifier	NOUN
ejpam-5934	78	7	(	(	PUNCT
ejpam-5934	78	8	etc	etc	X
ejpam-5934	78	9	)	)	PUNCT
ejpam-5934	78	10	was	be	AUX
ejpam-5934	78	11	used	use	VERB
ejpam-5934	78	12	to	to	PART
ejpam-5934	78	13	select	select	VERB
ejpam-5934	78	14	significant	significant	ADJ
ejpam-5934	78	15	well	well	INTJ
ejpam-5934	78	16	log	log	NOUN
ejpam-5934	78	17	features	feature	NOUN
ejpam-5934	78	18	,	,	PUNCT
ejpam-5934	78	19	from	from	ADP
ejpam-5934	78	20	which	which	PRON
ejpam-5934	78	21	they	they	PRON
ejpam-5934	78	22	created	create	VERB
ejpam-5934	78	23	five	five	NUM
ejpam-5934	78	24	distinct	distinct	ADJ
ejpam-5934	78	25	electrofacies	electrofacie	NOUN
ejpam-5934	78	26	.	.	PUNCT
ejpam-5934	79	1	yılmaz	yılmaz	PROPN
ejpam-5934	79	2	kayaa	kayaa	PROPN
ejpam-5934	79	3	and	and	CCONJ
ejpam-5934	79	4	murat	murat	PROPN
ejpam-5934	79	5	uyar	uyar	PROPN
ejpam-5934	80	1	[	[	X
ejpam-5934	80	2	12	12	NUM
ejpam-5934	80	3	]	]	PUNCT
ejpam-5934	80	4	proposed	propose	VERB
ejpam-5934	80	5	the	the	DET
ejpam-5934	80	6	use	use	NOUN
ejpam-5934	80	7	of	of	ADP
ejpam-5934	80	8	a	a	DET
ejpam-5934	80	9	hybrid	hybrid	ADJ
ejpam-5934	80	10	decision	decision	NOUN
ejpam-5934	80	11	support	support	NOUN
ejpam-5934	80	12	system	system	NOUN
ejpam-5934	80	13	to	to	PART
ejpam-5934	80	14	identify	identify	VERB
ejpam-5934	80	15	hepatitis	hepatitis	NOUN
ejpam-5934	80	16	.	.	PUNCT
ejpam-5934	81	1	rst	rst	PROPN
ejpam-5934	81	2	and	and	CCONJ
ejpam-5934	81	3	extreme	extreme	ADJ
ejpam-5934	81	4	learning	learning	NOUN
ejpam-5934	81	5	machine	machine	NOUN
ejpam-5934	81	6	(	(	PUNCT
ejpam-5934	81	7	elm	elm	NOUN
ejpam-5934	81	8	)	)	PUNCT
ejpam-5934	81	9	algorithms	algorithm	NOUN
ejpam-5934	81	10	form	form	VERB
ejpam-5934	81	11	the	the	DET
ejpam-5934	81	12	foundation	foundation	NOUN
ejpam-5934	81	13	of	of	ADP
ejpam-5934	81	14	the	the	DET
ejpam-5934	81	15	system	system	NOUN
ejpam-5934	81	16	.	.	PUNCT
ejpam-5934	82	1	the	the	DET
ejpam-5934	82	2	proposed	propose	VERB
ejpam-5934	82	3	model	model	NOUN
ejpam-5934	82	4	was	be	AUX
ejpam-5934	82	5	trained	train	VERB
ejpam-5934	82	6	using	use	VERB
ejpam-5934	82	7	the	the	DET
ejpam-5934	82	8	indian	indian	ADJ
ejpam-5934	82	9	liver	liver	NOUN
ejpam-5934	82	10	pat	pat	PROPN
ejpam-5934	82	11	.	.	PROPN
ejpam-5934	82	12	ashika	ashika	PROPN
ejpam-5934	82	13	,	,	PUNCT
ejpam-5934	82	14	g.	g.	PROPN
ejpam-5934	82	15	h.	h.	PROPN
ejpam-5934	82	16	grace	grace	PROPN
ejpam-5934	82	17	/	/	SYM
ejpam-5934	82	18	eur	eur	PROPN
ejpam-5934	82	19	.	.	PUNCT
ejpam-5934	83	1	j.	j.	PROPN
ejpam-5934	83	2	pure	pure	PROPN
ejpam-5934	83	3	appl	appl	PROPN
ejpam-5934	83	4	.	.	PROPN
ejpam-5934	83	5	math	math	PROPN
ejpam-5934	83	6	,	,	PUNCT
ejpam-5934	83	7	18	18	NUM
ejpam-5934	83	8	(	(	PUNCT
ejpam-5934	83	9	2	2	NUM
ejpam-5934	83	10	)	)	PUNCT
ejpam-5934	83	11	(	(	PUNCT
ejpam-5934	83	12	2025	2025	NUM
ejpam-5934	83	13	)	)	PUNCT
ejpam-5934	83	14	,	,	PUNCT
ejpam-5934	83	15	5934	5934	NUM
ejpam-5934	83	16	4	4	NUM
ejpam-5934	83	17	of	of	ADP
ejpam-5934	83	18	22	22	NUM
ejpam-5934	83	19	tient	tient	NOUN
ejpam-5934	83	20	dataset	dataset	NOUN
ejpam-5934	83	21	,	,	PUNCT
ejpam-5934	83	22	then	then	ADV
ejpam-5934	83	23	evaluated	evaluate	VERB
ejpam-5934	83	24	the	the	DET
ejpam-5934	83	25	effectiveness	effectiveness	NOUN
ejpam-5934	83	26	of	of	ADP
ejpam-5934	83	27	the	the	DET
ejpam-5934	83	28	suggested	suggest	VERB
ejpam-5934	83	29	classification	classification	NOUN
ejpam-5934	83	30	methods	method	NOUN
ejpam-5934	83	31	based	base	VERB
ejpam-5934	83	32	on	on	ADP
ejpam-5934	83	33	sensitivity	sensitivity	NOUN
ejpam-5934	83	34	and	and	CCONJ
ejpam-5934	83	35	specificity	specificity	NOUN
ejpam-5934	83	36	to	to	PART
ejpam-5934	83	37	determine	determine	VERB
ejpam-5934	83	38	the	the	DET
ejpam-5934	83	39	model	model	NOUN
ejpam-5934	83	40	’s	’s	PART
ejpam-5934	83	41	accuracy	accuracy	NOUN
ejpam-5934	83	42	.	.	PUNCT
ejpam-5934	84	1	a	a	DET
ejpam-5934	84	2	svm	svm	ADJ
ejpam-5934	84	3	classifier	classifier	NOUN
ejpam-5934	84	4	for	for	ADP
ejpam-5934	84	5	breast	breast	NOUN
ejpam-5934	84	6	cancer	cancer	NOUN
ejpam-5934	84	7	diagnosis	diagnosis	NOUN
ejpam-5934	84	8	using	use	VERB
ejpam-5934	84	9	rst	rst	NOUN
ejpam-5934	84	10	-	-	PUNCT
ejpam-5934	84	11	based	base	VERB
ejpam-5934	84	12	feature	feature	NOUN
ejpam-5934	84	13	selection	selection	NOUN
ejpam-5934	84	14	was	be	AUX
ejpam-5934	84	15	proposed	propose	VERB
ejpam-5934	84	16	by	by	ADP
ejpam-5934	84	17	hui	hui	PROPN
ejpam-5934	84	18	-	-	PUNCT
ejpam-5934	84	19	ling	ling	PROPN
ejpam-5934	84	20	chen	chen	PROPN
ejpam-5934	84	21	et	et	PROPN
ejpam-5934	84	22	al	al	PROPN
ejpam-5934	84	23	.	.	PUNCT
ejpam-5934	85	1	[	[	X
ejpam-5934	85	2	13	13	NUM
ejpam-5934	85	3	]	]	PUNCT
ejpam-5934	85	4	.	.	PUNCT
ejpam-5934	86	1	using	use	VERB
ejpam-5934	86	2	rst	rst	ADJ
ejpam-5934	86	3	reducts	reduct	NOUN
ejpam-5934	86	4	,	,	PUNCT
ejpam-5934	86	5	asma	asma	PROPN
ejpam-5934	86	6	trabelsi	trabelsi	PROPN
ejpam-5934	86	7	et	et	PROPN
ejpam-5934	86	8	al.[14	al.[14	PROPN
ejpam-5934	86	9	]	]	PUNCT
ejpam-5934	86	10	created	create	VERB
ejpam-5934	86	11	an	an	DET
ejpam-5934	86	12	ensemble	ensemble	ADJ
ejpam-5934	86	13	classifier	classifier	NOUN
ejpam-5934	86	14	to	to	PART
ejpam-5934	86	15	handle	handle	VERB
ejpam-5934	86	16	data	datum	NOUN
ejpam-5934	86	17	with	with	ADP
ejpam-5934	86	18	evidential	evidential	ADJ
ejpam-5934	86	19	attributes	attribute	NOUN
ejpam-5934	86	20	.	.	PUNCT
ejpam-5934	87	1	the	the	DET
ejpam-5934	87	2	objective	objective	NOUN
ejpam-5934	87	3	is	be	AUX
ejpam-5934	87	4	to	to	PART
ejpam-5934	87	5	use	use	VERB
ejpam-5934	87	6	rs	rs	PROPN
ejpam-5934	87	7	reduct	reduct	PROPN
ejpam-5934	87	8	to	to	PART
ejpam-5934	87	9	extract	extract	VERB
ejpam-5934	87	10	the	the	DET
ejpam-5934	87	11	best	good	ADJ
ejpam-5934	87	12	feature	feature	NOUN
ejpam-5934	87	13	subsets	subset	NOUN
ejpam-5934	87	14	for	for	ADP
ejpam-5934	87	15	the	the	DET
ejpam-5934	87	16	ensemble	ensemble	ADJ
ejpam-5934	87	17	classifier	classifier	NOUN
ejpam-5934	87	18	.	.	PUNCT
ejpam-5934	88	1	the	the	DET
ejpam-5934	88	2	diversity	diversity	NOUN
ejpam-5934	88	3	reduct	reduct	PROPN
ejpam-5934	88	4	method	method	PROPN
ejpam-5934	88	5	(	(	PUNCT
ejpam-5934	88	6	dr	dr	PROPN
ejpam-5934	88	7	)	)	PUNCT
ejpam-5934	88	8	,	,	PUNCT
ejpam-5934	88	9	the	the	DET
ejpam-5934	88	10	accuracy	accuracy	NOUN
ejpam-5934	88	11	-	-	PUNCT
ejpam-5934	88	12	diversity	diversity	NOUN
ejpam-5934	88	13	assessment	assessment	NOUN
ejpam-5934	88	14	function	function	NOUN
ejpam-5934	88	15	method	method	NOUN
ejpam-5934	88	16	(	(	PUNCT
ejpam-5934	88	17	ad	ad	NOUN
ejpam-5934	88	18	-	-	PUNCT
ejpam-5934	88	19	af	af	NOUN
ejpam-5934	88	20	)	)	PUNCT
ejpam-5934	88	21	,	,	PUNCT
ejpam-5934	88	22	and	and	CCONJ
ejpam-5934	88	23	the	the	DET
ejpam-5934	88	24	ensemble	ensemble	ADJ
ejpam-5934	88	25	accuracy	accuracy	NOUN
ejpam-5934	88	26	assessment	assessment	NOUN
ejpam-5934	88	27	function	function	NOUN
ejpam-5934	88	28	method	method	NOUN
ejpam-5934	88	29	(	(	PUNCT
ejpam-5934	88	30	ea	ea	NOUN
ejpam-5934	88	31	-	-	PUNCT
ejpam-5934	88	32	af	af	NOUN
ejpam-5934	88	33	)	)	PUNCT
ejpam-5934	88	34	are	be	AUX
ejpam-5934	88	35	the	the	DET
ejpam-5934	88	36	three	three	NUM
ejpam-5934	88	37	strategies	strategy	NOUN
ejpam-5934	88	38	that	that	PRON
ejpam-5934	88	39	have	have	AUX
ejpam-5934	88	40	been	be	AUX
ejpam-5934	88	41	suggested	suggest	VERB
ejpam-5934	88	42	to	to	PART
ejpam-5934	88	43	choose	choose	VERB
ejpam-5934	88	44	the	the	DET
ejpam-5934	88	45	best	good	ADJ
ejpam-5934	88	46	reducts	reduct	NOUN
ejpam-5934	88	47	.	.	PUNCT
ejpam-5934	89	1	the	the	DET
ejpam-5934	89	2	key	key	ADJ
ejpam-5934	89	3	differences	difference	NOUN
ejpam-5934	89	4	between	between	ADP
ejpam-5934	89	5	the	the	DET
ejpam-5934	89	6	previously	previously	ADV
ejpam-5934	89	7	mentioned	mention	VERB
ejpam-5934	89	8	methods	method	NOUN
ejpam-5934	89	9	have	have	AUX
ejpam-5934	89	10	been	be	AUX
ejpam-5934	89	11	compared	compare	VERB
ejpam-5934	89	12	using	use	VERB
ejpam-5934	89	13	a	a	DET
ejpam-5934	89	14	statistical	statistical	ADJ
ejpam-5934	89	15	test	test	NOUN
ejpam-5934	89	16	in	in	ADP
ejpam-5934	89	17	terms	term	NOUN
ejpam-5934	89	18	of	of	ADP
ejpam-5934	89	19	reduct	reduct	PROPN
ejpam-5934	89	20	diversity	diversity	PROPN
ejpam-5934	89	21	,	,	PUNCT
ejpam-5934	89	22	ensemble	ensemble	ADJ
ejpam-5934	89	23	size	size	NOUN
ejpam-5934	89	24	,	,	PUNCT
ejpam-5934	89	25	classification	classification	NOUN
ejpam-5934	89	26	performance	performance	NOUN
ejpam-5934	89	27	,	,	PUNCT
ejpam-5934	89	28	and	and	CCONJ
ejpam-5934	89	29	approach	approach	NOUN
ejpam-5934	89	30	performance	performance	NOUN
ejpam-5934	89	31	.	.	PUNCT
ejpam-5934	90	1	the	the	DET
ejpam-5934	90	2	outcomes	outcome	NOUN
ejpam-5934	90	3	show	show	VERB
ejpam-5934	90	4	that	that	SCONJ
ejpam-5934	90	5	the	the	DET
ejpam-5934	90	6	ea	ea	PROPN
ejpam-5934	90	7	-	-	PUNCT
ejpam-5934	90	8	af	af	PROPN
ejpam-5934	90	9	strategy	strategy	NOUN
ejpam-5934	90	10	generated	generate	VERB
ejpam-5934	90	11	the	the	DET
ejpam-5934	90	12	best	good	ADJ
ejpam-5934	90	13	effects	effect	NOUN
ejpam-5934	90	14	.	.	PUNCT
ejpam-5934	91	1	ping	ping	NOUN
ejpam-5934	91	2	-	-	PUNCT
ejpam-5934	91	3	feng	feng	PROPN
ejpam-5934	91	4	pai	pai	PROPN
ejpam-5934	91	5	et	et	PROPN
ejpam-5934	91	6	al	al	PROPN
ejpam-5934	91	7	.	.	PUNCT
ejpam-5934	92	1	[	[	X
ejpam-5934	92	2	15	15	NUM
ejpam-5934	92	3	]	]	PUNCT
ejpam-5934	92	4	analysed	analyse	VERB
ejpam-5934	92	5	foreign	foreign	ADJ
ejpam-5934	92	6	exchange	exchange	NOUN
ejpam-5934	92	7	rates	rate	NOUN
ejpam-5934	92	8	by	by	ADP
ejpam-5934	92	9	rst	rst	PROPN
ejpam-5934	92	10	and	and	CCONJ
ejpam-5934	92	11	directed	direct	VERB
ejpam-5934	92	12	acyclic	acyclic	ADJ
ejpam-5934	92	13	graph	graph	NOUN
ejpam-5934	92	14	svm	svm	PROPN
ejpam-5934	92	15	(	(	PUNCT
ejpam-5934	92	16	dagsvm	dagsvm	PROPN
ejpam-5934	92	17	)	)	PUNCT
ejpam-5934	92	18	.	.	PUNCT
ejpam-5934	93	1	a	a	DET
ejpam-5934	93	2	new	new	ADJ
ejpam-5934	93	3	approach	approach	NOUN
ejpam-5934	93	4	to	to	ADP
ejpam-5934	93	5	foreign	foreign	ADJ
ejpam-5934	93	6	exchange	exchange	NOUN
ejpam-5934	93	7	rate	rate	NOUN
ejpam-5934	93	8	analysis	analysis	NOUN
ejpam-5934	93	9	that	that	PRON
ejpam-5934	93	10	combines	combine	VERB
ejpam-5934	93	11	dagsvm	dagsvm	NOUN
ejpam-5934	93	12	and	and	CCONJ
ejpam-5934	93	13	rst	rst	PROPN
ejpam-5934	93	14	was	be	AUX
ejpam-5934	93	15	proposed	propose	VERB
ejpam-5934	93	16	.	.	PUNCT
ejpam-5934	94	1	they	they	PRON
ejpam-5934	94	2	examined	examine	VERB
ejpam-5934	94	3	the	the	DET
ejpam-5934	94	4	us	us	PROPN
ejpam-5934	94	5	dollar	dollar	NOUN
ejpam-5934	94	6	’s	’s	PART
ejpam-5934	94	7	exchange	exchange	NOUN
ejpam-5934	94	8	rates	rate	NOUN
ejpam-5934	94	9	versus	versus	ADP
ejpam-5934	94	10	the	the	DET
ejpam-5934	94	11	euro	euro	NOUN
ejpam-5934	94	12	and	and	CCONJ
ejpam-5934	94	13	the	the	DET
ejpam-5934	94	14	japanese	japanese	ADJ
ejpam-5934	94	15	yen	yen	NOUN
ejpam-5934	94	16	using	use	VERB
ejpam-5934	94	17	the	the	DET
ejpam-5934	94	18	suggested	suggest	VERB
ejpam-5934	94	19	methodology	methodology	NOUN
ejpam-5934	94	20	.	.	PUNCT
ejpam-5934	95	1	the	the	DET
ejpam-5934	95	2	outcome	outcome	NOUN
ejpam-5934	95	3	indicates	indicate	VERB
ejpam-5934	95	4	that	that	SCONJ
ejpam-5934	95	5	this	this	DET
ejpam-5934	95	6	method	method	NOUN
ejpam-5934	95	7	outperforms	outperform	VERB
ejpam-5934	95	8	alternative	alternative	ADJ
ejpam-5934	95	9	strategies	strategy	NOUN
ejpam-5934	95	10	like	like	ADP
ejpam-5934	95	11	back	back	NOUN
ejpam-5934	95	12	propagation	propagation	NOUN
ejpam-5934	95	13	neural	neural	ADJ
ejpam-5934	95	14	network	network	NOUN
ejpam-5934	95	15	(	(	PUNCT
ejpam-5934	95	16	bpnn	bpnn	NOUN
ejpam-5934	95	17	)	)	PUNCT
ejpam-5934	95	18	and	and	CCONJ
ejpam-5934	95	19	support	support	VERB
ejpam-5934	95	20	vector	vector	NOUN
ejpam-5934	95	21	regression	regression	NOUN
ejpam-5934	95	22	(	(	PUNCT
ejpam-5934	95	23	svr	svr	PROPN
ejpam-5934	95	24	)	)	PUNCT
ejpam-5934	95	25	.	.	PUNCT
ejpam-5934	96	1	for	for	ADP
ejpam-5934	96	2	real	real	ADV
ejpam-5934	96	3	-	-	PUNCT
ejpam-5934	96	4	valued	value	VERB
ejpam-5934	96	5	classification	classification	NOUN
ejpam-5934	96	6	problems	problem	NOUN
ejpam-5934	96	7	,	,	PUNCT
ejpam-5934	96	8	essam	essam	PROPN
ejpam-5934	96	9	debie	debie	PROPN
ejpam-5934	96	10	et	et	PROPN
ejpam-5934	96	11	al.[16	al.[16	PROPN
ejpam-5934	96	12	]	]	PUNCT
ejpam-5934	96	13	proposed	propose	VERB
ejpam-5934	96	14	an	an	DET
ejpam-5934	96	15	ensemble	ensemble	NOUN
ejpam-5934	96	16	of	of	ADP
ejpam-5934	96	17	learning	learn	VERB
ejpam-5934	96	18	classifier	classifier	NOUN
ejpam-5934	96	19	system	system	NOUN
ejpam-5934	96	20	based	base	VERB
ejpam-5934	96	21	on	on	ADP
ejpam-5934	96	22	reducts	reduct	NOUN
ejpam-5934	96	23	.	.	PUNCT
ejpam-5934	97	1	an	an	DET
ejpam-5934	97	2	ensemble	ensemble	ADJ
ejpam-5934	97	3	approach	approach	NOUN
ejpam-5934	97	4	for	for	ADP
ejpam-5934	97	5	rst	rst	NOUN
ejpam-5934	97	6	-	-	PUNCT
ejpam-5934	97	7	based	base	VERB
ejpam-5934	97	8	learning	learning	NOUN
ejpam-5934	97	9	classifier	classifier	NOUN
ejpam-5934	97	10	systems	system	NOUN
ejpam-5934	97	11	was	be	AUX
ejpam-5934	97	12	proposed	propose	VERB
ejpam-5934	97	13	to	to	PART
ejpam-5934	97	14	construct	construct	VERB
ejpam-5934	97	15	ensemble	ensemble	ADJ
ejpam-5934	97	16	learning	learning	NOUN
ejpam-5934	97	17	systems	system	NOUN
ejpam-5934	97	18	.	.	PUNCT
ejpam-5934	98	1	by	by	ADP
ejpam-5934	98	2	using	use	VERB
ejpam-5934	98	3	rst	rst	PROPN
ejpam-5934	98	4	attribute	attribute	NOUN
ejpam-5934	98	5	reduction	reduction	NOUN
ejpam-5934	98	6	,	,	PUNCT
ejpam-5934	98	7	the	the	DET
ejpam-5934	98	8	method	method	NOUN
ejpam-5934	98	9	creates	create	VERB
ejpam-5934	98	10	a	a	DET
ejpam-5934	98	11	set	set	NOUN
ejpam-5934	98	12	of	of	ADP
ejpam-5934	98	13	reducts	reduct	NOUN
ejpam-5934	98	14	.	.	PUNCT
ejpam-5934	99	1	a	a	DET
ejpam-5934	99	2	variety	variety	NOUN
ejpam-5934	99	3	of	of	ADP
ejpam-5934	99	4	these	these	DET
ejpam-5934	99	5	reducts	reduct	NOUN
ejpam-5934	99	6	is	be	AUX
ejpam-5934	99	7	then	then	ADV
ejpam-5934	99	8	chosen	choose	VERB
ejpam-5934	99	9	and	and	CCONJ
ejpam-5934	99	10	utilized	utilize	VERB
ejpam-5934	99	11	for	for	ADP
ejpam-5934	99	12	training	training	NOUN
ejpam-5934	99	13	of	of	ADP
ejpam-5934	99	14	ensemble	ensemble	ADJ
ejpam-5934	99	15	of	of	ADP
ejpam-5934	99	16	base	base	NOUN
ejpam-5934	99	17	classifiers	classifier	NOUN
ejpam-5934	99	18	.	.	PUNCT
ejpam-5934	100	1	according	accord	VERB
ejpam-5934	100	2	to	to	ADP
ejpam-5934	100	3	the	the	DET
ejpam-5934	100	4	analysis	analysis	NOUN
ejpam-5934	100	5	,	,	PUNCT
ejpam-5934	100	6	single	single	ADJ
ejpam-5934	100	7	learning	learning	NOUN
ejpam-5934	100	8	classifier	classifier	NOUN
ejpam-5934	100	9	system	system	NOUN
ejpam-5934	100	10	models	model	NOUN
ejpam-5934	100	11	are	be	AUX
ejpam-5934	100	12	outperformed	outperform	VERB
ejpam-5934	100	13	by	by	ADP
ejpam-5934	100	14	reduct	reduct	PROPN
ejpam-5934	100	15	-	-	PUNCT
ejpam-5934	100	16	based	base	VERB
ejpam-5934	100	17	ensemble	ensemble	ADJ
ejpam-5934	100	18	systems	system	NOUN
ejpam-5934	100	19	in	in	ADP
ejpam-5934	100	20	terms	term	NOUN
ejpam-5934	100	21	of	of	ADP
ejpam-5934	100	22	classification	classification	NOUN
ejpam-5934	100	23	accuracy	accuracy	NOUN
ejpam-5934	100	24	.	.	PUNCT
ejpam-5934	101	1	georg	georg	PROPN
ejpam-5934	101	2	peters	peters	PROPN
ejpam-5934	101	3	and	and	CCONJ
ejpam-5934	101	4	simon	simon	PROPN
ejpam-5934	101	5	poon	poon	NOUN
ejpam-5934	102	1	[	[	X
ejpam-5934	102	2	17	17	NUM
ejpam-5934	102	3	]	]	PUNCT
ejpam-5934	102	4	has	have	AUX
ejpam-5934	102	5	discussed	discuss	VERB
ejpam-5934	102	6	a	a	DET
ejpam-5934	102	7	dominance	dominance	NOUN
ejpam-5934	102	8	based	base	VERB
ejpam-5934	102	9	rs	rs	NOUN
ejpam-5934	102	10	approach	approach	NOUN
ejpam-5934	102	11	(	(	PUNCT
ejpam-5934	102	12	drsa	drsa	NOUN
ejpam-5934	102	13	)	)	PUNCT
ejpam-5934	102	14	by	by	ADP
ejpam-5934	102	15	analyzing	analyze	VERB
ejpam-5934	102	16	it	it	PRON
ejpam-5934	102	17	business	business	NOUN
ejpam-5934	102	18	values	value	NOUN
ejpam-5934	102	19	.	.	PUNCT
ejpam-5934	103	1	this	this	DET
ejpam-5934	103	2	paper	paper	NOUN
ejpam-5934	103	3	examine	examine	VERB
ejpam-5934	103	4	how	how	SCONJ
ejpam-5934	103	5	it	it	PRON
ejpam-5934	103	6	affects	affect	VERB
ejpam-5934	103	7	a	a	DET
ejpam-5934	103	8	partnership	partnership	NOUN
ejpam-5934	103	9	’s	’s	PART
ejpam-5934	103	10	business	business	NOUN
ejpam-5934	103	11	value	value	NOUN
ejpam-5934	103	12	.	.	PUNCT
ejpam-5934	104	1	a	a	DET
ejpam-5934	104	2	decision	decision	NOUN
ejpam-5934	104	3	table	table	NOUN
ejpam-5934	104	4	with	with	ADP
ejpam-5934	104	5	ordinal	ordinal	ADJ
ejpam-5934	104	6	data	datum	NOUN
ejpam-5934	104	7	can	can	AUX
ejpam-5934	104	8	be	be	AUX
ejpam-5934	104	9	used	use	VERB
ejpam-5934	104	10	to	to	PART
ejpam-5934	104	11	generate	generate	VERB
ejpam-5934	104	12	rules	rule	NOUN
ejpam-5934	104	13	using	use	VERB
ejpam-5934	104	14	drsa	drsa	NOUN
ejpam-5934	104	15	.	.	PUNCT
ejpam-5934	105	1	an	an	DET
ejpam-5934	105	2	investigation	investigation	NOUN
ejpam-5934	105	3	into	into	ADP
ejpam-5934	105	4	the	the	DET
ejpam-5934	105	5	it	it	NOUN
ejpam-5934	105	6	management	management	NOUN
ejpam-5934	105	7	practices	practice	NOUN
ejpam-5934	105	8	of	of	ADP
ejpam-5934	105	9	australian	australian	ADJ
ejpam-5934	105	10	businesses	business	NOUN
ejpam-5934	105	11	was	be	AUX
ejpam-5934	105	12	carried	carry	VERB
ejpam-5934	105	13	out	out	ADP
ejpam-5934	105	14	by	by	ADP
ejpam-5934	105	15	the	the	DET
ejpam-5934	105	16	department	department	PROPN
ejpam-5934	105	17	of	of	ADP
ejpam-5934	105	18	communications	communication	NOUN
ejpam-5934	105	19	,	,	PUNCT
ejpam-5934	105	20	information	information	NOUN
ejpam-5934	105	21	technology	technology	NOUN
ejpam-5934	105	22	,	,	PUNCT
ejpam-5934	105	23	and	and	CCONJ
ejpam-5934	105	24	the	the	DET
ejpam-5934	105	25	arts	art	NOUN
ejpam-5934	105	26	in	in	ADP
ejpam-5934	105	27	australia	australia	PROPN
ejpam-5934	105	28	,	,	PUNCT
ejpam-5934	105	29	from	from	ADP
ejpam-5934	105	30	which	which	PRON
ejpam-5934	105	31	the	the	DET
ejpam-5934	105	32	authors	author	NOUN
ejpam-5934	105	33	have	have	AUX
ejpam-5934	105	34	used	use	VERB
ejpam-5934	105	35	ordinal	ordinal	ADJ
ejpam-5934	105	36	data	datum	NOUN
ejpam-5934	105	37	.	.	PUNCT
ejpam-5934	106	1	the	the	DET
ejpam-5934	106	2	paper	paper	NOUN
ejpam-5934	106	3	offers	offer	VERB
ejpam-5934	106	4	a	a	DET
ejpam-5934	106	5	thorough	thorough	ADJ
ejpam-5934	106	6	analysis	analysis	NOUN
ejpam-5934	106	7	of	of	ADP
ejpam-5934	106	8	the	the	DET
ejpam-5934	106	9	underlying	underlying	ADJ
ejpam-5934	106	10	mechanisms	mechanism	NOUN
ejpam-5934	106	11	that	that	PRON
ejpam-5934	106	12	underpin	underpin	VERB
ejpam-5934	106	13	it	it	PRON
ejpam-5934	106	14	beneficial	beneficial	ADJ
ejpam-5934	106	15	effects	effect	NOUN
ejpam-5934	106	16	on	on	ADP
ejpam-5934	106	17	cooperatives	cooperative	NOUN
ejpam-5934	106	18	business	business	NOUN
ejpam-5934	106	19	values	value	NOUN
ejpam-5934	106	20	.	.	PUNCT
ejpam-5934	107	1	brightbox	brightbox	NOUN
ejpam-5934	107	2	is	be	AUX
ejpam-5934	107	3	a	a	DET
ejpam-5934	107	4	rst	rst	NOUN
ejpam-5934	107	5	-	-	PUNCT
ejpam-5934	107	6	based	base	VERB
ejpam-5934	107	7	technology	technology	NOUN
ejpam-5934	107	8	designed	design	VERB
ejpam-5934	107	9	by	by	ADP
ejpam-5934	107	10	andrzej	andrzej	PROPN
ejpam-5934	107	11	janusz	janusz	PROPN
ejpam-5934	107	12	et	et	PROPN
ejpam-5934	107	13	al	al	PROPN
ejpam-5934	107	14	.	.	PUNCT
ejpam-5934	108	1	[	[	X
ejpam-5934	108	2	18	18	NUM
ejpam-5934	108	3	]	]	PUNCT
ejpam-5934	108	4	for	for	ADP
ejpam-5934	108	5	identifying	identify	VERB
ejpam-5934	108	6	errors	error	NOUN
ejpam-5934	108	7	in	in	ADP
ejpam-5934	108	8	ml	ml	NOUN
ejpam-5934	108	9	models	model	NOUN
ejpam-5934	108	10	.	.	PUNCT
ejpam-5934	109	1	a	a	DET
ejpam-5934	109	2	new	new	ADJ
ejpam-5934	109	3	method	method	NOUN
ejpam-5934	109	4	for	for	ADP
ejpam-5934	109	5	looking	look	VERB
ejpam-5934	109	6	into	into	ADP
ejpam-5934	109	7	errors	error	NOUN
ejpam-5934	109	8	in	in	ADP
ejpam-5934	109	9	ml	ml	NOUN
ejpam-5934	109	10	model	model	NOUN
ejpam-5934	109	11	operations	operation	NOUN
ejpam-5934	109	12	is	be	AUX
ejpam-5934	109	13	called	call	VERB
ejpam-5934	109	14	brightbox	brightbox	NOUN
ejpam-5934	109	15	.	.	PUNCT
ejpam-5934	110	1	the	the	DET
ejpam-5934	110	2	method	method	NOUN
ejpam-5934	110	3	relies	rely	VERB
ejpam-5934	110	4	on	on	ADP
ejpam-5934	110	5	surrogate	surrogate	ADJ
ejpam-5934	110	6	rst	rst	PROPN
ejpam-5934	110	7	-	-	PUNCT
ejpam-5934	110	8	based	base	VERB
ejpam-5934	110	9	models	model	NOUN
ejpam-5934	110	10	that	that	PRON
ejpam-5934	110	11	are	be	AUX
ejpam-5934	110	12	inducted	induct	VERB
ejpam-5934	110	13	from	from	ADP
ejpam-5934	110	14	data	datum	NOUN
ejpam-5934	110	15	approximating	approximate	VERB
ejpam-5934	110	16	the	the	DET
ejpam-5934	110	17	decisions	decision	NOUN
ejpam-5934	110	18	made	make	VERB
ejpam-5934	110	19	by	by	ADP
ejpam-5934	110	20	the	the	DET
ejpam-5934	110	21	monitored	monitor	VERB
ejpam-5934	110	22	blackbox	blackbox	PROPN
ejpam-5934	110	23	models	model	NOUN
ejpam-5934	110	24	.	.	PUNCT
ejpam-5934	111	1	the	the	DET
ejpam-5934	111	2	neighborhoods	neighborhood	NOUN
ejpam-5934	111	3	of	of	ADP
ejpam-5934	111	4	instances	instance	NOUN
ejpam-5934	111	5	that	that	PRON
ejpam-5934	111	6	go	go	VERB
ejpam-5934	111	7	through	through	ADP
ejpam-5934	111	8	the	the	DET
ejpam-5934	111	9	diagnostic	diagnostic	ADJ
ejpam-5934	111	10	process	process	NOUN
ejpam-5934	111	11	are	be	AUX
ejpam-5934	111	12	computed	compute	VERB
ejpam-5934	111	13	using	use	VERB
ejpam-5934	111	14	these	these	DET
ejpam-5934	111	15	approximators	approximator	NOUN
ejpam-5934	111	16	which	which	PRON
ejpam-5934	111	17	consists	consist	VERB
ejpam-5934	111	18	of	of	ADP
ejpam-5934	111	19	historical	historical	ADJ
ejpam-5934	111	20	instances	instance	NOUN
ejpam-5934	111	21	that	that	PRON
ejpam-5934	111	22	were	be	AUX
ejpam-5934	111	23	handled	handle	VERB
ejpam-5934	111	24	similarly	similarly	ADV
ejpam-5934	111	25	by	by	ADP
ejpam-5934	111	26	rst	rst	PROPN
ejpam-5934	111	27	-	-	PUNCT
ejpam-5934	111	28	based	base	VERB
ejpam-5934	111	29	models	model	NOUN
ejpam-5934	111	30	.	.	PUNCT
ejpam-5934	112	1	the	the	DET
ejpam-5934	112	2	analysis	analysis	NOUN
ejpam-5934	112	3	of	of	ADP
ejpam-5934	112	4	mistakes	mistake	NOUN
ejpam-5934	112	5	reported	report	VERB
ejpam-5934	112	6	in	in	ADP
ejpam-5934	112	7	these	these	DET
ejpam-5934	112	8	neighborhoods	neighborhood	NOUN
ejpam-5934	112	9	serves	serve	VERB
ejpam-5934	112	10	as	as	ADP
ejpam-5934	112	11	the	the	DET
ejpam-5934	112	12	foundation	foundation	NOUN
ejpam-5934	112	13	for	for	ADP
ejpam-5934	112	14	the	the	DET
ejpam-5934	112	15	diagnostic	diagnostic	ADJ
ejpam-5934	112	16	procedure	procedure	NOUN
ejpam-5934	112	17	.	.	PUNCT
ejpam-5934	113	1	the	the	DET
ejpam-5934	113	2	study	study	NOUN
ejpam-5934	113	3	also	also	ADV
ejpam-5934	113	4	emphasizes	emphasize	VERB
ejpam-5934	113	5	how	how	SCONJ
ejpam-5934	113	6	brightbox	brightbox	ADJ
ejpam-5934	113	7	technology	technology	NOUN
ejpam-5934	113	8	can	can	AUX
ejpam-5934	113	9	be	be	AUX
ejpam-5934	113	10	applied	apply	VERB
ejpam-5934	113	11	to	to	ADP
ejpam-5934	113	12	model	model	NOUN
ejpam-5934	113	13	and	and	CCONJ
ejpam-5934	113	14	data	datum	NOUN
ejpam-5934	113	15	-	-	PUNCT
ejpam-5934	113	16	related	relate	VERB
ejpam-5934	113	17	problem	problem	NOUN
ejpam-5934	113	18	identification	identification	NOUN
ejpam-5934	113	19	and	and	CCONJ
ejpam-5934	113	20	analysis	analysis	NOUN
ejpam-5934	113	21	as	as	ADV
ejpam-5934	113	22	well	well	ADV
ejpam-5934	113	23	as	as	ADP
ejpam-5934	113	24	prediction	prediction	NOUN
ejpam-5934	113	25	model	model	NOUN
ejpam-5934	113	26	analysis	analysis	NOUN
ejpam-5934	113	27	.	.	PUNCT
ejpam-5934	114	1	experiments	experiment	NOUN
ejpam-5934	114	2	conducted	conduct	VERB
ejpam-5934	114	3	on	on	ADP
ejpam-5934	114	4	real	real	ADJ
ejpam-5934	114	5	-	-	PUNCT
ejpam-5934	114	6	world	world	NOUN
ejpam-5934	114	7	t.	t.	PROPN
ejpam-5934	114	8	ashika	ashika	NOUN
ejpam-5934	114	9	,	,	PUNCT
ejpam-5934	114	10	g.	g.	PROPN
ejpam-5934	114	11	h.	h.	PROPN
ejpam-5934	114	12	grace	grace	PROPN
ejpam-5934	114	13	/	/	SYM
ejpam-5934	114	14	eur	eur	PROPN
ejpam-5934	114	15	.	.	PUNCT
ejpam-5934	115	1	j.	j.	PROPN
ejpam-5934	115	2	pure	pure	PROPN
ejpam-5934	115	3	appl	appl	PROPN
ejpam-5934	115	4	.	.	PROPN
ejpam-5934	115	5	math	math	PROPN
ejpam-5934	115	6	,	,	PUNCT
ejpam-5934	115	7	18	18	NUM
ejpam-5934	115	8	(	(	PUNCT
ejpam-5934	115	9	2	2	NUM
ejpam-5934	115	10	)	)	PUNCT
ejpam-5934	115	11	(	(	PUNCT
ejpam-5934	115	12	2025	2025	NUM
ejpam-5934	115	13	)	)	PUNCT
ejpam-5934	115	14	,	,	PUNCT
ejpam-5934	115	15	5934	5934	NUM
ejpam-5934	115	16	5	5	NUM
ejpam-5934	115	17	of	of	ADP
ejpam-5934	115	18	22	22	NUM
ejpam-5934	115	19	datasets	dataset	NOUN
ejpam-5934	115	20	verify	verify	VERB
ejpam-5934	115	21	that	that	SCONJ
ejpam-5934	115	22	this	this	DET
ejpam-5934	115	23	type	type	NOUN
ejpam-5934	115	24	of	of	ADP
ejpam-5934	115	25	analysis	analysis	NOUN
ejpam-5934	115	26	may	may	AUX
ejpam-5934	115	27	provide	provide	VERB
ejpam-5934	115	28	us	we	PRON
ejpam-5934	115	29	efficient	efficient	ADJ
ejpam-5934	115	30	and	and	CCONJ
ejpam-5934	115	31	accurate	accurate	ADJ
ejpam-5934	115	32	insights	insight	NOUN
ejpam-5934	115	33	into	into	ADP
ejpam-5934	115	34	the	the	DET
ejpam-5934	115	35	reasons	reason	NOUN
ejpam-5934	115	36	of	of	ADP
ejpam-5934	115	37	ml	ml	NOUN
ejpam-5934	115	38	model	model	NOUN
ejpam-5934	115	39	’s	’s	PART
ejpam-5934	115	40	poor	poor	ADJ
ejpam-5934	115	41	performance	performance	NOUN
ejpam-5934	115	42	.	.	PUNCT
ejpam-5934	116	1	alessio	alessio	PROPN
ejpam-5934	116	2	ferone	ferone	NOUN
ejpam-5934	117	1	[	[	X
ejpam-5934	117	2	19	19	NUM
ejpam-5934	117	3	]	]	PUNCT
ejpam-5934	117	4	had	have	AUX
ejpam-5934	117	5	proposed	propose	VERB
ejpam-5934	117	6	feature	feature	NOUN
ejpam-5934	117	7	selection	selection	NOUN
ejpam-5934	117	8	determined	determine	VERB
ejpam-5934	117	9	by	by	ADP
ejpam-5934	117	10	the	the	DET
ejpam-5934	117	11	rst	rst	PROPN
ejpam-5934	117	12	composition	composition	NOUN
ejpam-5934	117	13	resulted	result	VERB
ejpam-5934	117	14	by	by	ADP
ejpam-5934	117	15	feature	feature	NOUN
ejpam-5934	117	16	granulation	granulation	NOUN
ejpam-5934	117	17	.	.	PUNCT
ejpam-5934	118	1	this	this	DET
ejpam-5934	118	2	research	research	NOUN
ejpam-5934	118	3	suggests	suggest	VERB
ejpam-5934	118	4	a	a	DET
ejpam-5934	118	5	rst	rst	NOUN
ejpam-5934	118	6	-	-	PUNCT
ejpam-5934	118	7	based	base	VERB
ejpam-5934	118	8	feature	feature	NOUN
ejpam-5934	118	9	selection	selection	NOUN
ejpam-5934	118	10	method	method	NOUN
ejpam-5934	118	11	that	that	PRON
ejpam-5934	118	12	consists	consist	VERB
ejpam-5934	118	13	of	of	ADP
ejpam-5934	118	14	two	two	NUM
ejpam-5934	118	15	stages	stage	NOUN
ejpam-5934	118	16	:	:	PUNCT
ejpam-5934	118	17	granulation	granulation	NOUN
ejpam-5934	118	18	and	and	CCONJ
ejpam-5934	118	19	roughinement	roughinement	NOUN
ejpam-5934	118	20	.	.	PUNCT
ejpam-5934	119	1	the	the	DET
ejpam-5934	119	2	suggested	suggest	VERB
ejpam-5934	119	3	method	method	NOUN
ejpam-5934	119	4	reduces	reduce	VERB
ejpam-5934	119	5	computation	computation	NOUN
ejpam-5934	119	6	costs	cost	NOUN
ejpam-5934	119	7	with	with	ADP
ejpam-5934	119	8	respect	respect	NOUN
ejpam-5934	119	9	to	to	ADP
ejpam-5934	119	10	the	the	DET
ejpam-5934	119	11	quickreduct	quickreduct	NOUN
ejpam-5934	119	12	(	(	PUNCT
ejpam-5934	119	13	qr	qr	NOUN
ejpam-5934	119	14	)	)	PUNCT
ejpam-5934	119	15	algorithm	algorithm	NOUN
ejpam-5934	119	16	.	.	PUNCT
ejpam-5934	120	1	in	in	ADP
ejpam-5934	120	2	recent	recent	ADJ
ejpam-5934	120	3	years	year	NOUN
ejpam-5934	120	4	,	,	PUNCT
ejpam-5934	120	5	several	several	ADJ
ejpam-5934	120	6	studies	study	NOUN
ejpam-5934	120	7	have	have	AUX
ejpam-5934	120	8	advanced	advance	VERB
ejpam-5934	120	9	the	the	DET
ejpam-5934	120	10	application	application	NOUN
ejpam-5934	120	11	of	of	ADP
ejpam-5934	120	12	rst	rst	PROPN
ejpam-5934	120	13	in	in	ADP
ejpam-5934	120	14	feature	feature	NOUN
ejpam-5934	120	15	selection	selection	NOUN
ejpam-5934	120	16	,	,	PUNCT
ejpam-5934	120	17	addressing	address	VERB
ejpam-5934	120	18	various	various	ADJ
ejpam-5934	120	19	challenges	challenge	NOUN
ejpam-5934	120	20	in	in	ADP
ejpam-5934	120	21	dynamic	dynamic	ADJ
ejpam-5934	120	22	and	and	CCONJ
ejpam-5934	120	23	high	high	ADJ
ejpam-5934	120	24	-	-	PUNCT
ejpam-5934	120	25	dimensional	dimensional	ADJ
ejpam-5934	120	26	datasets	dataset	NOUN
ejpam-5934	120	27	.	.	PUNCT
ejpam-5934	121	1	zhao	zhao	NOUN
ejpam-5934	121	2	et	et	NOUN
ejpam-5934	121	3	al.[20	al.[20	NOUN
ejpam-5934	121	4	]	]	PUNCT
ejpam-5934	121	5	proposed	propose	VERB
ejpam-5934	121	6	a	a	DET
ejpam-5934	121	7	triple	triple	ADJ
ejpam-5934	121	8	nested	nest	VERB
ejpam-5934	121	9	equivalence	equivalence	NOUN
ejpam-5934	121	10	class	class	NOUN
ejpam-5934	121	11	(	(	PUNCT
ejpam-5934	121	12	tnec	tnec	NOUN
ejpam-5934	121	13	)	)	PUNCT
ejpam-5934	121	14	approach	approach	NOUN
ejpam-5934	121	15	for	for	ADP
ejpam-5934	121	16	group	group	NOUN
ejpam-5934	121	17	incremental	incremental	ADJ
ejpam-5934	121	18	feature	feature	NOUN
ejpam-5934	121	19	selection	selection	NOUN
ejpam-5934	121	20	,	,	PUNCT
ejpam-5934	121	21	which	which	PRON
ejpam-5934	121	22	effectively	effectively	ADV
ejpam-5934	121	23	reduces	reduce	VERB
ejpam-5934	121	24	redundancy	redundancy	NOUN
ejpam-5934	121	25	and	and	CCONJ
ejpam-5934	121	26	enhances	enhance	VERB
ejpam-5934	121	27	efficiency	efficiency	NOUN
ejpam-5934	121	28	in	in	ADP
ejpam-5934	121	29	processing	process	VERB
ejpam-5934	121	30	ultra	ultra	ADJ
ejpam-5934	121	31	-	-	ADJ
ejpam-5934	121	32	high	high	ADJ
ejpam-5934	121	33	-	-	PUNCT
ejpam-5934	121	34	dimensional	dimensional	ADJ
ejpam-5934	121	35	datasets	dataset	NOUN
ejpam-5934	121	36	.	.	PUNCT
ejpam-5934	122	1	their	their	PRON
ejpam-5934	122	2	experimental	experimental	ADJ
ejpam-5934	122	3	results	result	NOUN
ejpam-5934	122	4	demonstrated	demonstrate	VERB
ejpam-5934	122	5	significant	significant	ADJ
ejpam-5934	122	6	improvements	improvement	NOUN
ejpam-5934	122	7	in	in	ADP
ejpam-5934	122	8	classification	classification	NOUN
ejpam-5934	122	9	efficiency	efficiency	NOUN
ejpam-5934	122	10	and	and	CCONJ
ejpam-5934	122	11	selection	selection	NOUN
ejpam-5934	122	12	accuracy	accuracy	NOUN
ejpam-5934	122	13	across	across	ADP
ejpam-5934	122	14	18	18	NUM
ejpam-5934	122	15	dynamic	dynamic	ADJ
ejpam-5934	122	16	datasets	dataset	NOUN
ejpam-5934	122	17	.	.	PUNCT
ejpam-5934	123	1	similarly	similarly	ADV
ejpam-5934	123	2	,	,	PUNCT
ejpam-5934	123	3	almania	almania	NOUN
ejpam-5934	123	4	et	et	PROPN
ejpam-5934	123	5	al	al	PROPN
ejpam-5934	123	6	.	.	PUNCT
ejpam-5934	124	1	[	[	X
ejpam-5934	124	2	21	21	NUM
ejpam-5934	124	3	]	]	PUNCT
ejpam-5934	124	4	introduced	introduce	VERB
ejpam-5934	124	5	a	a	DET
ejpam-5934	124	6	two	two	NUM
ejpam-5934	124	7	-	-	PUNCT
ejpam-5934	124	8	level	level	NOUN
ejpam-5934	124	9	feature	feature	NOUN
ejpam-5934	124	10	selection	selection	NOUN
ejpam-5934	124	11	approach	approach	NOUN
ejpam-5934	124	12	that	that	PRON
ejpam-5934	124	13	combines	combine	VERB
ejpam-5934	124	14	rst	rst	PROPN
ejpam-5934	124	15	with	with	ADP
ejpam-5934	124	16	binary	binary	ADJ
ejpam-5934	124	17	particle	particle	NOUN
ejpam-5934	124	18	swarm	swarm	NOUN
ejpam-5934	124	19	optimization	optimization	NOUN
ejpam-5934	124	20	(	(	PUNCT
ejpam-5934	124	21	bpso	bpso	NOUN
ejpam-5934	124	22	)	)	PUNCT
ejpam-5934	124	23	to	to	PART
ejpam-5934	124	24	enhance	enhance	VERB
ejpam-5934	124	25	accuracy	accuracy	NOUN
ejpam-5934	124	26	and	and	CCONJ
ejpam-5934	124	27	reduce	reduce	VERB
ejpam-5934	124	28	computational	computational	ADJ
ejpam-5934	124	29	overhead	overhead	NOUN
ejpam-5934	124	30	in	in	ADP
ejpam-5934	124	31	intrusion	intrusion	NOUN
ejpam-5934	124	32	detection	detection	NOUN
ejpam-5934	124	33	systems	system	NOUN
ejpam-5934	124	34	(	(	PUNCT
ejpam-5934	124	35	ids	id	NOUN
ejpam-5934	124	36	)	)	PUNCT
ejpam-5934	124	37	.	.	PUNCT
ejpam-5934	125	1	their	their	PRON
ejpam-5934	125	2	method	method	NOUN
ejpam-5934	125	3	achieved	achieve	VERB
ejpam-5934	125	4	a	a	DET
ejpam-5934	125	5	notable	notable	ADJ
ejpam-5934	125	6	improvement	improvement	NOUN
ejpam-5934	125	7	in	in	ADP
ejpam-5934	125	8	classification	classification	NOUN
ejpam-5934	125	9	accuracy	accuracy	NOUN
ejpam-5934	125	10	while	while	SCONJ
ejpam-5934	125	11	streamlining	streamline	VERB
ejpam-5934	125	12	the	the	DET
ejpam-5934	125	13	feature	feature	NOUN
ejpam-5934	125	14	set	set	NOUN
ejpam-5934	125	15	.	.	PUNCT
ejpam-5934	126	1	furthermore	furthermore	ADV
ejpam-5934	126	2	,	,	PUNCT
ejpam-5934	126	3	alsabilah	alsabilah	NOUN
ejpam-5934	126	4	and	and	CCONJ
ejpam-5934	126	5	rawat	rawat	PROPN
ejpam-5934	127	1	[	[	X
ejpam-5934	127	2	22	22	NUM
ejpam-5934	127	3	]	]	X
ejpam-5934	127	4	leveraged	leveraged	ADJ
ejpam-5934	127	5	rst	rst	NOUN
ejpam-5934	127	6	in	in	ADP
ejpam-5934	127	7	conjunction	conjunction	NOUN
ejpam-5934	127	8	with	with	ADP
ejpam-5934	127	9	xgboost	xgboost	PROPN
ejpam-5934	127	10	to	to	PART
ejpam-5934	127	11	develop	develop	VERB
ejpam-5934	127	12	a	a	DET
ejpam-5934	127	13	robust	robust	ADJ
ejpam-5934	127	14	network	network	NOUN
ejpam-5934	127	15	ids	id	NOUN
ejpam-5934	127	16	,	,	PUNCT
ejpam-5934	127	17	significantly	significantly	ADV
ejpam-5934	127	18	outperforming	outperform	VERB
ejpam-5934	127	19	existing	exist	VERB
ejpam-5934	127	20	methods	method	NOUN
ejpam-5934	127	21	in	in	ADP
ejpam-5934	127	22	terms	term	NOUN
ejpam-5934	127	23	of	of	ADP
ejpam-5934	127	24	accuracy	accuracy	NOUN
ejpam-5934	127	25	and	and	CCONJ
ejpam-5934	127	26	precision	precision	NOUN
ejpam-5934	127	27	.	.	PUNCT
ejpam-5934	128	1	turaga	turaga	NOUN
ejpam-5934	128	2	and	and	CCONJ
ejpam-5934	128	3	chebrolu	chebrolu	PRON
ejpam-5934	129	1	[	[	X
ejpam-5934	129	2	23	23	NUM
ejpam-5934	129	3	]	]	PUNCT
ejpam-5934	129	4	addressed	address	VERB
ejpam-5934	129	5	the	the	DET
ejpam-5934	129	6	inefficiencies	inefficiency	NOUN
ejpam-5934	129	7	of	of	ADP
ejpam-5934	129	8	traditional	traditional	ADJ
ejpam-5934	129	9	rst	rst	ADJ
ejpam-5934	129	10	algorithms	algorithm	NOUN
ejpam-5934	129	11	by	by	ADP
ejpam-5934	129	12	proposing	propose	VERB
ejpam-5934	129	13	a	a	DET
ejpam-5934	129	14	novel	novel	ADJ
ejpam-5934	129	15	attribute	attribute	NOUN
ejpam-5934	129	16	reduction	reduction	NOUN
ejpam-5934	129	17	algorithm	algorithm	NOUN
ejpam-5934	129	18	designed	design	VERB
ejpam-5934	129	19	for	for	ADP
ejpam-5934	129	20	execution	execution	NOUN
ejpam-5934	129	21	on	on	ADP
ejpam-5934	129	22	graphics	graphic	NOUN
ejpam-5934	129	23	processing	processing	NOUN
ejpam-5934	129	24	units	unit	NOUN
ejpam-5934	129	25	(	(	PUNCT
ejpam-5934	129	26	gpus	gpus	PROPN
ejpam-5934	129	27	)	)	PUNCT
ejpam-5934	129	28	,	,	PUNCT
ejpam-5934	129	29	achieving	achieve	VERB
ejpam-5934	129	30	high	high	ADJ
ejpam-5934	129	31	classification	classification	NOUN
ejpam-5934	129	32	accuracies	accuracy	NOUN
ejpam-5934	129	33	in	in	ADP
ejpam-5934	129	34	reduced	reduced	ADJ
ejpam-5934	129	35	execution	execution	NOUN
ejpam-5934	129	36	times	time	NOUN
ejpam-5934	129	37	.	.	PUNCT
ejpam-5934	130	1	these	these	DET
ejpam-5934	130	2	studies	study	NOUN
ejpam-5934	130	3	collectively	collectively	ADV
ejpam-5934	130	4	highlight	highlight	VERB
ejpam-5934	130	5	the	the	DET
ejpam-5934	130	6	evolving	evolve	VERB
ejpam-5934	130	7	landscape	landscape	NOUN
ejpam-5934	130	8	of	of	ADP
ejpam-5934	130	9	rst	rst	PROPN
ejpam-5934	130	10	applications	application	NOUN
ejpam-5934	130	11	and	and	CCONJ
ejpam-5934	130	12	underscore	underscore	VERB
ejpam-5934	130	13	the	the	DET
ejpam-5934	130	14	importance	importance	NOUN
ejpam-5934	130	15	of	of	ADP
ejpam-5934	130	16	integrating	integrate	VERB
ejpam-5934	130	17	rst	rst	PROPN
ejpam-5934	130	18	with	with	ADP
ejpam-5934	130	19	modern	modern	ADJ
ejpam-5934	130	20	computational	computational	ADJ
ejpam-5934	130	21	techniques	technique	NOUN
ejpam-5934	130	22	to	to	PART
ejpam-5934	130	23	enhance	enhance	VERB
ejpam-5934	130	24	feature	feature	NOUN
ejpam-5934	130	25	selection	selection	NOUN
ejpam-5934	130	26	processes	process	NOUN
ejpam-5934	130	27	.	.	PUNCT
ejpam-5934	131	1	the	the	DET
ejpam-5934	131	2	summary	summary	NOUN
ejpam-5934	131	3	of	of	ADP
ejpam-5934	131	4	the	the	DET
ejpam-5934	131	5	related	relate	VERB
ejpam-5934	131	6	work	work	NOUN
ejpam-5934	131	7	is	be	AUX
ejpam-5934	131	8	provided	provide	VERB
ejpam-5934	131	9	in	in	ADP
ejpam-5934	131	10	table	table	NOUN
ejpam-5934	131	11	1	1	NUM
ejpam-5934	131	12	.	.	PUNCT
ejpam-5934	131	13	t.	t.	ADJ
ejpam-5934	131	14	ashika	ashika	PROPN
ejpam-5934	131	15	,	,	PUNCT
ejpam-5934	131	16	g.	g.	PROPN
ejpam-5934	131	17	h.	h.	PROPN
ejpam-5934	131	18	grace	grace	PROPN
ejpam-5934	131	19	/	/	SYM
ejpam-5934	131	20	eur	eur	PROPN
ejpam-5934	131	21	.	.	PUNCT
ejpam-5934	132	1	j.	j.	PROPN
ejpam-5934	132	2	pure	pure	PROPN
ejpam-5934	132	3	appl	appl	PROPN
ejpam-5934	132	4	.	.	PROPN
ejpam-5934	132	5	math	math	PROPN
ejpam-5934	132	6	,	,	PUNCT
ejpam-5934	132	7	18	18	NUM
ejpam-5934	132	8	(	(	PUNCT
ejpam-5934	132	9	2	2	NUM
ejpam-5934	132	10	)	)	PUNCT
ejpam-5934	132	11	(	(	PUNCT
ejpam-5934	132	12	2025	2025	NUM
ejpam-5934	132	13	)	)	PUNCT
ejpam-5934	132	14	,	,	PUNCT
ejpam-5934	132	15	5934	5934	NUM
ejpam-5934	132	16	6	6	NUM
ejpam-5934	132	17	of	of	ADP
ejpam-5934	132	18	22	22	NUM
ejpam-5934	132	19	table	table	NOUN
ejpam-5934	132	20	1	1	NUM
ejpam-5934	132	21	:	:	PUNCT
ejpam-5934	132	22	comparison	comparison	NOUN
ejpam-5934	132	23	of	of	ADP
ejpam-5934	132	24	rst	rst	NOUN
ejpam-5934	132	25	-	-	PUNCT
ejpam-5934	132	26	based	base	VERB
ejpam-5934	132	27	and	and	CCONJ
ejpam-5934	132	28	non	non	ADJ
ejpam-5934	132	29	-	-	ADJ
ejpam-5934	132	30	rst	rst	ADJ
ejpam-5934	132	31	feature	feature	NOUN
ejpam-5934	132	32	selection	selection	NOUN
ejpam-5934	132	33	methods	method	NOUN
ejpam-5934	132	34	from	from	ADP
ejpam-5934	132	35	recent	recent	ADJ
ejpam-5934	132	36	literature	literature	NOUN
ejpam-5934	132	37	method	method	NOUN
ejpam-5934	132	38	references	reference	NOUN
ejpam-5934	132	39	approach	approach	NOUN
ejpam-5934	132	40	advantages	advantage	NOUN
ejpam-5934	132	41	limitations	limitation	VERB
ejpam-5934	132	42	rst	rst	PROPN
ejpam-5934	133	1	[	[	X
ejpam-5934	133	2	1	1	NUM
ejpam-5934	133	3	,	,	PUNCT
ejpam-5934	133	4	5	5	NUM
ejpam-5934	133	5	,	,	PUNCT
ejpam-5934	133	6	6	6	NUM
ejpam-5934	133	7	]	]	PUNCT
ejpam-5934	133	8	rule	rule	NOUN
ejpam-5934	133	9	-	-	PUNCT
ejpam-5934	133	10	based	base	VERB
ejpam-5934	133	11	reduction	reduction	NOUN
ejpam-5934	133	12	using	use	VERB
ejpam-5934	133	13	core	core	NOUN
ejpam-5934	133	14	and	and	CCONJ
ejpam-5934	133	15	reducts	reduct	NOUN
ejpam-5934	133	16	handles	handle	VERB
ejpam-5934	133	17	uncertainty	uncertainty	NOUN
ejpam-5934	133	18	,	,	PUNCT
ejpam-5934	133	19	generates	generate	VERB
ejpam-5934	133	20	humanunderstandable	humanunderstandable	ADJ
ejpam-5934	133	21	rules	rule	NOUN
ejpam-5934	133	22	,	,	PUNCT
ejpam-5934	133	23	supports	support	VERB
ejpam-5934	133	24	imprecise	imprecise	ADJ
ejpam-5934	133	25	data	datum	NOUN
ejpam-5934	133	26	needs	need	VERB
ejpam-5934	133	27	discretization	discretization	NOUN
ejpam-5934	133	28	,	,	PUNCT
ejpam-5934	133	29	can	can	AUX
ejpam-5934	133	30	be	be	AUX
ejpam-5934	133	31	computationally	computationally	ADV
ejpam-5934	133	32	intensive	intensive	ADJ
ejpam-5934	133	33	for	for	ADP
ejpam-5934	133	34	large	large	ADJ
ejpam-5934	133	35	feature	feature	NOUN
ejpam-5934	133	36	sets	set	VERB
ejpam-5934	133	37	rst	rst	PROPN
ejpam-5934	133	38	vs	vs	ADP
ejpam-5934	133	39	core	core	NOUN
ejpam-5934	133	40	+	+	CCONJ
ejpam-5934	133	41	reduct	reduct	NOUN
ejpam-5934	134	1	[	[	X
ejpam-5934	134	2	7	7	NUM
ejpam-5934	134	3	]	]	PUNCT
ejpam-5934	134	4	compared	compare	VERB
ejpam-5934	134	5	performance	performance	NOUN
ejpam-5934	134	6	with	with	ADP
ejpam-5934	134	7	and	and	CCONJ
ejpam-5934	134	8	without	without	ADP
ejpam-5934	134	9	rst	rst	NOUN
ejpam-5934	134	10	-	-	PUNCT
ejpam-5934	134	11	based	base	VERB
ejpam-5934	134	12	dimensionality	dimensionality	NOUN
ejpam-5934	134	13	reduction	reduction	NOUN
ejpam-5934	134	14	reduced	reduce	VERB
ejpam-5934	134	15	computation	computation	NOUN
ejpam-5934	134	16	time	time	NOUN
ejpam-5934	134	17	by	by	ADP
ejpam-5934	134	18	up	up	ADP
ejpam-5934	134	19	to	to	PART
ejpam-5934	134	20	80	80	NUM
ejpam-5934	134	21	%	%	NOUN
ejpam-5934	134	22	with	with	ADP
ejpam-5934	134	23	minimal	minimal	ADJ
ejpam-5934	134	24	accuracy	accuracy	NOUN
ejpam-5934	134	25	loss	loss	NOUN
ejpam-5934	134	26	focused	focus	VERB
ejpam-5934	134	27	on	on	ADP
ejpam-5934	134	28	only	only	ADV
ejpam-5934	134	29	a	a	DET
ejpam-5934	134	30	few	few	ADJ
ejpam-5934	134	31	ml	ml	NOUN
ejpam-5934	134	32	models	model	NOUN
ejpam-5934	134	33	(	(	PUNCT
ejpam-5934	134	34	svm	svm	PROPN
ejpam-5934	134	35	,	,	PUNCT
ejpam-5934	134	36	lr	lr	PROPN
ejpam-5934	134	37	,	,	PUNCT
ejpam-5934	134	38	knn	knn	PROPN
ejpam-5934	134	39	)	)	PUNCT
ejpam-5934	134	40	rst	rst	PROPN
ejpam-5934	135	1	+	+	CCONJ
ejpam-5934	135	2	dnn	dnn	PROPN
ejpam-5934	136	1	[	[	X
ejpam-5934	136	2	8	8	NUM
ejpam-5934	136	3	]	]	X
ejpam-5934	136	4	rst	rst	PROPN
ejpam-5934	136	5	for	for	ADP
ejpam-5934	136	6	dimension	dimension	NOUN
ejpam-5934	136	7	reduction	reduction	NOUN
ejpam-5934	136	8	before	before	ADP
ejpam-5934	136	9	deep	deep	ADJ
ejpam-5934	136	10	learning	learning	NOUN
ejpam-5934	136	11	(	(	PUNCT
ejpam-5934	136	12	dl	dl	NOUN
ejpam-5934	136	13	)	)	PUNCT
ejpam-5934	136	14	enhanced	enhance	VERB
ejpam-5934	136	15	prediction	prediction	NOUN
ejpam-5934	136	16	accuracy	accuracy	NOUN
ejpam-5934	136	17	by	by	ADP
ejpam-5934	136	18	removing	remove	VERB
ejpam-5934	136	19	noisy	noisy	ADJ
ejpam-5934	136	20	/	/	SYM
ejpam-5934	136	21	irrelevant	irrelevant	ADJ
ejpam-5934	136	22	features	feature	NOUN
ejpam-5934	136	23	before	before	SCONJ
ejpam-5934	136	24	dnn	dnn	PROPN
ejpam-5934	136	25	requires	require	VERB
ejpam-5934	136	26	tuning	tune	VERB
ejpam-5934	136	27	both	both	DET
ejpam-5934	136	28	rst	rst	PROPN
ejpam-5934	136	29	reduct	reduct	PROPN
ejpam-5934	136	30	and	and	CCONJ
ejpam-5934	136	31	dl	dl	PROPN
ejpam-5934	136	32	model	model	PROPN
ejpam-5934	136	33	rst	rst	PROPN
ejpam-5934	136	34	+	+	CCONJ
ejpam-5934	136	35	rnn	rnn	VERB
ejpam-5934	136	36	[	[	PUNCT
ejpam-5934	136	37	10	10	NUM
ejpam-5934	136	38	]	]	PUNCT
ejpam-5934	136	39	feature	feature	NOUN
ejpam-5934	136	40	selection	selection	NOUN
ejpam-5934	136	41	via	via	ADP
ejpam-5934	136	42	rst	rst	PROPN
ejpam-5934	136	43	,	,	PUNCT
ejpam-5934	136	44	then	then	ADV
ejpam-5934	136	45	fed	feed	VERB
ejpam-5934	136	46	to	to	PART
ejpam-5934	136	47	rnn	rnn	VERB
ejpam-5934	136	48	achieved	achieve	VERB
ejpam-5934	136	49	98.57	98.57	NUM
ejpam-5934	136	50	%	%	NOUN
ejpam-5934	136	51	accuracy	accuracy	NOUN
ejpam-5934	136	52	on	on	ADP
ejpam-5934	136	53	heart	heart	NOUN
ejpam-5934	136	54	disease	disease	NOUN
ejpam-5934	136	55	dataset	dataset	VERB
ejpam-5934	136	56	limited	limit	VERB
ejpam-5934	136	57	to	to	ADP
ejpam-5934	136	58	specific	specific	ADJ
ejpam-5934	136	59	dataset	dataset	NOUN
ejpam-5934	136	60	;	;	PUNCT
ejpam-5934	136	61	needs	need	VERB
ejpam-5934	136	62	sequential	sequential	ADJ
ejpam-5934	136	63	data	datum	NOUN
ejpam-5934	136	64	handling	handle	VERB
ejpam-5934	136	65	rst	rst	PROPN
ejpam-5934	136	66	+	+	CCONJ
ejpam-5934	136	67	etc	etc	X
ejpam-5934	137	1	[	[	X
ejpam-5934	137	2	11	11	NUM
ejpam-5934	137	3	]	]	X
ejpam-5934	137	4	rst	rst	PROPN
ejpam-5934	137	5	to	to	PART
ejpam-5934	137	6	identify	identify	VERB
ejpam-5934	137	7	features	feature	NOUN
ejpam-5934	137	8	for	for	ADP
ejpam-5934	137	9	lithology	lithology	NOUN
ejpam-5934	137	10	;	;	PUNCT
ejpam-5934	137	11	etc	etc	X
ejpam-5934	137	12	to	to	PART
ejpam-5934	137	13	classify	classify	VERB
ejpam-5934	137	14	white	white	ADJ
ejpam-5934	137	15	-	-	PUNCT
ejpam-5934	137	16	box	box	NOUN
ejpam-5934	137	17	interpretability	interpretability	NOUN
ejpam-5934	137	18	with	with	ADP
ejpam-5934	137	19	competitive	competitive	ADJ
ejpam-5934	137	20	classification	classification	NOUN
ejpam-5934	137	21	performance	performance	NOUN
ejpam-5934	137	22	focused	focus	VERB
ejpam-5934	137	23	on	on	ADP
ejpam-5934	137	24	geophysical	geophysical	ADJ
ejpam-5934	137	25	/	/	SYM
ejpam-5934	137	26	electrofacies	electrofacie	NOUN
ejpam-5934	137	27	domain	domain	VERB
ejpam-5934	137	28	non	non	ADJ
ejpam-5934	137	29	-	-	ADJ
ejpam-5934	137	30	rst	rst	ADJ
ejpam-5934	137	31	feature	feature	NOUN
ejpam-5934	137	32	selection	selection	NOUN
ejpam-5934	137	33	[	[	X
ejpam-5934	137	34	3	3	NUM
ejpam-5934	137	35	,	,	PUNCT
ejpam-5934	137	36	12	12	NUM
ejpam-5934	137	37	]	]	PUNCT
ejpam-5934	137	38	used	use	VERB
ejpam-5934	137	39	traditional	traditional	ADJ
ejpam-5934	137	40	ml	ml	NOUN
ejpam-5934	137	41	or	or	CCONJ
ejpam-5934	137	42	hybrid	hybrid	NOUN
ejpam-5934	137	43	models	model	NOUN
ejpam-5934	137	44	(	(	PUNCT
ejpam-5934	137	45	e.g.	e.g.	ADV
ejpam-5934	137	46	,	,	PUNCT
ejpam-5934	137	47	elm	elm	PROPN
ejpam-5934	137	48	,	,	PUNCT
ejpam-5934	137	49	svm	svm	PROPN
ejpam-5934	137	50	)	)	PUNCT
ejpam-5934	137	51	without	without	ADP
ejpam-5934	137	52	rst	rst	PROPN
ejpam-5934	137	53	simpler	simple	ADJ
ejpam-5934	137	54	implementation	implementation	NOUN
ejpam-5934	137	55	,	,	PUNCT
ejpam-5934	137	56	fast	fast	ADJ
ejpam-5934	137	57	training	training	NOUN
ejpam-5934	137	58	on	on	ADP
ejpam-5934	137	59	structured	structured	ADJ
ejpam-5934	137	60	datasets	dataset	NOUN
ejpam-5934	137	61	may	may	AUX
ejpam-5934	137	62	not	not	PART
ejpam-5934	137	63	handle	handle	VERB
ejpam-5934	137	64	ambiguity	ambiguity	NOUN
ejpam-5934	137	65	/	/	SYM
ejpam-5934	137	66	uncertainty	uncertainty	NOUN
ejpam-5934	137	67	well	well	ADV
ejpam-5934	137	68	;	;	PUNCT
ejpam-5934	137	69	lacks	lack	VERB
ejpam-5934	137	70	interpretability	interpretability	NOUN
ejpam-5934	137	71	of	of	ADP
ejpam-5934	137	72	rst	rst	PROPN
ejpam-5934	137	73	rules	rule	NOUN
ejpam-5934	137	74	rst	rst	PROPN
ejpam-5934	137	75	ensemble	ensemble	ADJ
ejpam-5934	137	76	feature	feature	NOUN
ejpam-5934	137	77	selection	selection	NOUN
ejpam-5934	138	1	[	[	X
ejpam-5934	138	2	14	14	NUM
ejpam-5934	138	3	]	]	X
ejpam-5934	138	4	dr	dr	PROPN
ejpam-5934	138	5	,	,	PUNCT
ejpam-5934	138	6	ad	ad	NOUN
ejpam-5934	138	7	-	-	PUNCT
ejpam-5934	138	8	af	af	PROPN
ejpam-5934	138	9	,	,	PUNCT
ejpam-5934	138	10	ea	ea	PUNCT
ejpam-5934	138	11	-	-	PUNCT
ejpam-5934	138	12	af	af	VERB
ejpam-5934	138	13	for	for	ADP
ejpam-5934	138	14	best	good	ADJ
ejpam-5934	138	15	reducts	reduct	NOUN
ejpam-5934	138	16	in	in	ADP
ejpam-5934	138	17	ensemble	ensemble	ADJ
ejpam-5934	138	18	classifiers	classifier	NOUN
ejpam-5934	138	19	ea	ea	VERB
ejpam-5934	138	20	-	-	PUNCT
ejpam-5934	138	21	af	af	PROPN
ejpam-5934	138	22	achieved	achieve	VERB
ejpam-5934	138	23	highest	high	ADJ
ejpam-5934	138	24	classification	classification	NOUN
ejpam-5934	138	25	performance	performance	NOUN
ejpam-5934	138	26	using	use	VERB
ejpam-5934	138	27	feature	feature	NOUN
ejpam-5934	138	28	diversity	diversity	NOUN
ejpam-5934	138	29	metrics	metric	NOUN
ejpam-5934	138	30	needs	need	VERB
ejpam-5934	138	31	statistical	statistical	ADJ
ejpam-5934	138	32	evaluation	evaluation	NOUN
ejpam-5934	138	33	and	and	CCONJ
ejpam-5934	138	34	multiple	multiple	ADJ
ejpam-5934	138	35	reduct	reduct	PROPN
ejpam-5934	138	36	generation	generation	PROPN
ejpam-5934	138	37	rst	rst	PROPN
ejpam-5934	139	1	+	+	CCONJ
ejpam-5934	139	2	drsa	drsa	NOUN
ejpam-5934	139	3	[	[	X
ejpam-5934	139	4	17	17	NUM
ejpam-5934	139	5	]	]	PUNCT
ejpam-5934	139	6	dominance	dominance	NOUN
ejpam-5934	139	7	relations	relation	NOUN
ejpam-5934	139	8	used	use	VERB
ejpam-5934	139	9	in	in	ADP
ejpam-5934	139	10	ordinal	ordinal	ADJ
ejpam-5934	139	11	decision	decision	NOUN
ejpam-5934	139	12	tables	table	NOUN
ejpam-5934	139	13	suitable	suitable	ADJ
ejpam-5934	139	14	for	for	ADP
ejpam-5934	139	15	subjective	subjective	ADJ
ejpam-5934	139	16	/	/	SYM
ejpam-5934	139	17	ordinal	ordinal	ADJ
ejpam-5934	139	18	data	datum	NOUN
ejpam-5934	139	19	(	(	PUNCT
ejpam-5934	139	20	e.g.	e.g.	ADV
ejpam-5934	139	21	,	,	PUNCT
ejpam-5934	139	22	it	it	PRON
ejpam-5934	139	23	business	business	NOUN
ejpam-5934	139	24	values	value	NOUN
ejpam-5934	139	25	)	)	PUNCT
ejpam-5934	139	26	more	more	ADV
ejpam-5934	139	27	complex	complex	ADJ
ejpam-5934	139	28	than	than	ADP
ejpam-5934	139	29	standard	standard	PROPN
ejpam-5934	139	30	rst	rst	PROPN
ejpam-5934	139	31	;	;	PUNCT
ejpam-5934	139	32	limited	limited	ADJ
ejpam-5934	139	33	applicability	applicability	NOUN
ejpam-5934	139	34	rst	rst	PROPN
ejpam-5934	139	35	+	+	CCONJ
ejpam-5934	139	36	tnec	tnec	NOUN
ejpam-5934	139	37	[	[	X
ejpam-5934	139	38	20	20	NUM
ejpam-5934	139	39	]	]	PUNCT
ejpam-5934	139	40	group	group	NOUN
ejpam-5934	139	41	incremental	incremental	ADJ
ejpam-5934	139	42	feature	feature	NOUN
ejpam-5934	139	43	selection	selection	NOUN
ejpam-5934	139	44	for	for	ADP
ejpam-5934	139	45	high	high	ADJ
ejpam-5934	139	46	-	-	PUNCT
ejpam-5934	139	47	dimensional	dimensional	ADJ
ejpam-5934	139	48	dynamic	dynamic	ADJ
ejpam-5934	139	49	data	datum	NOUN
ejpam-5934	139	50	reduces	reduce	VERB
ejpam-5934	139	51	redundancy	redundancy	NOUN
ejpam-5934	139	52	,	,	PUNCT
ejpam-5934	139	53	improves	improve	VERB
ejpam-5934	139	54	classification	classification	NOUN
ejpam-5934	139	55	accuracy	accuracy	NOUN
ejpam-5934	139	56	on	on	ADP
ejpam-5934	139	57	large	large	ADJ
ejpam-5934	139	58	-	-	PUNCT
ejpam-5934	139	59	scale	scale	NOUN
ejpam-5934	139	60	datasets	dataset	NOUN
ejpam-5934	139	61	focused	focus	VERB
ejpam-5934	139	62	on	on	ADP
ejpam-5934	139	63	dynamic	dynamic	ADJ
ejpam-5934	139	64	datasets	dataset	NOUN
ejpam-5934	139	65	,	,	PUNCT
ejpam-5934	139	66	complex	complex	ADJ
ejpam-5934	139	67	implementation	implementation	NOUN
ejpam-5934	139	68	rst	rst	PROPN
ejpam-5934	140	1	+	+	CCONJ
ejpam-5934	140	2	bpso	bpso	NOUN
ejpam-5934	140	3	[	[	X
ejpam-5934	140	4	21	21	NUM
ejpam-5934	140	5	]	]	SYM
ejpam-5934	140	6	two	two	NUM
ejpam-5934	140	7	-	-	PUNCT
ejpam-5934	140	8	level	level	NOUN
ejpam-5934	140	9	hybrid	hybrid	ADJ
ejpam-5934	140	10	feature	feature	NOUN
ejpam-5934	140	11	selection	selection	NOUN
ejpam-5934	140	12	for	for	ADP
ejpam-5934	140	13	ids	id	NOUN
ejpam-5934	140	14	high	high	ADJ
ejpam-5934	140	15	accuracy	accuracy	NOUN
ejpam-5934	140	16	and	and	CCONJ
ejpam-5934	140	17	reduced	reduce	VERB
ejpam-5934	140	18	overhead	overhead	ADV
ejpam-5934	140	19	;	;	PUNCT
ejpam-5934	140	20	robust	robust	ADJ
ejpam-5934	140	21	for	for	ADP
ejpam-5934	140	22	cybersecurity	cybersecurity	NOUN
ejpam-5934	140	23	tailored	tailor	VERB
ejpam-5934	140	24	to	to	ADP
ejpam-5934	140	25	ids	id	NOUN
ejpam-5934	140	26	;	;	PUNCT
ejpam-5934	140	27	parameter	parameter	NOUN
ejpam-5934	140	28	tuning	tune	VERB
ejpam-5934	140	29	required	require	VERB
ejpam-5934	140	30	t.	t.	NOUN
ejpam-5934	140	31	ashika	ashika	NOUN
ejpam-5934	140	32	,	,	PUNCT
ejpam-5934	140	33	g.	g.	PROPN
ejpam-5934	140	34	h.	h.	PROPN
ejpam-5934	140	35	grace	grace	PROPN
ejpam-5934	140	36	/	/	SYM
ejpam-5934	140	37	eur	eur	PROPN
ejpam-5934	140	38	.	.	PUNCT
ejpam-5934	141	1	j.	j.	PROPN
ejpam-5934	141	2	pure	pure	PROPN
ejpam-5934	141	3	appl	appl	PROPN
ejpam-5934	141	4	.	.	PROPN
ejpam-5934	141	5	math	math	PROPN
ejpam-5934	141	6	,	,	PUNCT
ejpam-5934	141	7	18	18	NUM
ejpam-5934	141	8	(	(	PUNCT
ejpam-5934	141	9	2	2	NUM
ejpam-5934	141	10	)	)	PUNCT
ejpam-5934	141	11	(	(	PUNCT
ejpam-5934	141	12	2025	2025	NUM
ejpam-5934	141	13	)	)	PUNCT
ejpam-5934	141	14	,	,	PUNCT
ejpam-5934	141	15	5934	5934	NUM
ejpam-5934	141	16	7	7	NUM
ejpam-5934	141	17	of	of	ADP
ejpam-5934	141	18	22	22	NUM
ejpam-5934	141	19	1.2	1.2	NUM
ejpam-5934	141	20	.	.	PUNCT
ejpam-5934	142	1	motivation	motivation	NOUN
ejpam-5934	142	2	and	and	CCONJ
ejpam-5934	142	3	novelty	novelty	NOUN
ejpam-5934	142	4	ml	ml	VERB
ejpam-5934	142	5	has	have	AUX
ejpam-5934	142	6	revolutionized	revolutionize	VERB
ejpam-5934	142	7	various	various	ADJ
ejpam-5934	142	8	fields	field	NOUN
ejpam-5934	142	9	by	by	ADP
ejpam-5934	142	10	enabling	enable	VERB
ejpam-5934	142	11	systems	system	NOUN
ejpam-5934	142	12	to	to	PART
ejpam-5934	142	13	learn	learn	VERB
ejpam-5934	142	14	from	from	ADP
ejpam-5934	142	15	data	datum	NOUN
ejpam-5934	142	16	and	and	CCONJ
ejpam-5934	142	17	make	make	VERB
ejpam-5934	142	18	informed	informed	ADJ
ejpam-5934	142	19	decisions	decision	NOUN
ejpam-5934	142	20	.	.	PUNCT
ejpam-5934	143	1	however	however	ADV
ejpam-5934	143	2	,	,	PUNCT
ejpam-5934	143	3	the	the	DET
ejpam-5934	143	4	presence	presence	NOUN
ejpam-5934	143	5	of	of	ADP
ejpam-5934	143	6	irrelevant	irrelevant	ADJ
ejpam-5934	143	7	or	or	CCONJ
ejpam-5934	143	8	redundant	redundant	ADJ
ejpam-5934	143	9	features	feature	NOUN
ejpam-5934	143	10	in	in	ADP
ejpam-5934	143	11	datasets	dataset	NOUN
ejpam-5934	143	12	can	can	AUX
ejpam-5934	143	13	hinder	hinder	VERB
ejpam-5934	143	14	model	model	NOUN
ejpam-5934	143	15	performance	performance	NOUN
ejpam-5934	143	16	,	,	PUNCT
ejpam-5934	143	17	leading	lead	VERB
ejpam-5934	143	18	to	to	ADP
ejpam-5934	143	19	overfitting	overfitte	VERB
ejpam-5934	143	20	,	,	PUNCT
ejpam-5934	143	21	increased	increase	VERB
ejpam-5934	143	22	computational	computational	ADJ
ejpam-5934	143	23	costs	cost	NOUN
ejpam-5934	143	24	,	,	PUNCT
ejpam-5934	143	25	and	and	CCONJ
ejpam-5934	143	26	reduced	reduce	VERB
ejpam-5934	143	27	interpretability	interpretability	NOUN
ejpam-5934	143	28	.	.	PUNCT
ejpam-5934	144	1	traditional	traditional	ADJ
ejpam-5934	144	2	feature	feature	NOUN
ejpam-5934	144	3	selection	selection	NOUN
ejpam-5934	144	4	methods	method	NOUN
ejpam-5934	144	5	often	often	ADV
ejpam-5934	144	6	rely	rely	VERB
ejpam-5934	144	7	on	on	ADP
ejpam-5934	144	8	statistical	statistical	ADJ
ejpam-5934	144	9	measures	measure	NOUN
ejpam-5934	144	10	or	or	CCONJ
ejpam-5934	144	11	domain	domain	NOUN
ejpam-5934	144	12	knowledge	knowledge	NOUN
ejpam-5934	144	13	,	,	PUNCT
ejpam-5934	144	14	which	which	PRON
ejpam-5934	144	15	may	may	AUX
ejpam-5934	144	16	not	not	PART
ejpam-5934	144	17	always	always	ADV
ejpam-5934	144	18	be	be	AUX
ejpam-5934	144	19	available	available	ADJ
ejpam-5934	144	20	or	or	CCONJ
ejpam-5934	144	21	sufficient	sufficient	ADJ
ejpam-5934	144	22	.	.	PUNCT
ejpam-5934	145	1	this	this	DET
ejpam-5934	145	2	study	study	NOUN
ejpam-5934	145	3	is	be	AUX
ejpam-5934	145	4	motivated	motivate	VERB
ejpam-5934	145	5	by	by	ADP
ejpam-5934	145	6	the	the	DET
ejpam-5934	145	7	need	need	NOUN
ejpam-5934	145	8	for	for	ADP
ejpam-5934	145	9	an	an	DET
ejpam-5934	145	10	effective	effective	ADJ
ejpam-5934	145	11	,	,	PUNCT
ejpam-5934	145	12	data	data	NOUN
ejpam-5934	145	13	-	-	PUNCT
ejpam-5934	145	14	driven	drive	VERB
ejpam-5934	145	15	approach	approach	NOUN
ejpam-5934	145	16	to	to	ADP
ejpam-5934	145	17	feature	feature	NOUN
ejpam-5934	145	18	selection	selection	NOUN
ejpam-5934	145	19	that	that	PRON
ejpam-5934	145	20	can	can	AUX
ejpam-5934	145	21	handle	handle	VERB
ejpam-5934	145	22	uncertainty	uncertainty	NOUN
ejpam-5934	145	23	and	and	CCONJ
ejpam-5934	145	24	imprecision	imprecision	NOUN
ejpam-5934	145	25	inherent	inherent	ADJ
ejpam-5934	145	26	in	in	ADP
ejpam-5934	145	27	real	real	ADJ
ejpam-5934	145	28	-	-	PUNCT
ejpam-5934	145	29	world	world	NOUN
ejpam-5934	145	30	datasets	dataset	NOUN
ejpam-5934	145	31	.	.	PUNCT
ejpam-5934	146	1	this	this	DET
ejpam-5934	146	2	research	research	NOUN
ejpam-5934	146	3	introduces	introduce	VERB
ejpam-5934	146	4	a	a	DET
ejpam-5934	146	5	novel	novel	ADJ
ejpam-5934	146	6	application	application	NOUN
ejpam-5934	146	7	of	of	ADP
ejpam-5934	146	8	rst	rst	PROPN
ejpam-5934	146	9	for	for	ADP
ejpam-5934	146	10	feature	feature	NOUN
ejpam-5934	146	11	selection	selection	NOUN
ejpam-5934	146	12	in	in	ADP
ejpam-5934	146	13	ml	ml	ADP
ejpam-5934	146	14	workflows	workflow	NOUN
ejpam-5934	146	15	.	.	PUNCT
ejpam-5934	147	1	the	the	DET
ejpam-5934	147	2	novelty	novelty	NOUN
ejpam-5934	147	3	lies	lie	VERB
ejpam-5934	147	4	in	in	ADP
ejpam-5934	147	5	integrating	integrate	VERB
ejpam-5934	147	6	rst	rst	PROPN
ejpam-5934	147	7	-	-	PUNCT
ejpam-5934	147	8	based	base	VERB
ejpam-5934	147	9	feature	feature	NOUN
ejpam-5934	147	10	selection	selection	NOUN
ejpam-5934	147	11	with	with	ADP
ejpam-5934	147	12	ml	ml	NOUN
ejpam-5934	147	13	models	model	NOUN
ejpam-5934	147	14	across	across	ADP
ejpam-5934	147	15	diverse	diverse	ADJ
ejpam-5934	147	16	domains	domain	NOUN
ejpam-5934	147	17	,	,	PUNCT
ejpam-5934	147	18	providing	provide	VERB
ejpam-5934	147	19	a	a	DET
ejpam-5934	147	20	comprehensive	comprehensive	ADJ
ejpam-5934	147	21	evaluation	evaluation	NOUN
ejpam-5934	147	22	of	of	ADP
ejpam-5934	147	23	its	its	PRON
ejpam-5934	147	24	impact	impact	NOUN
ejpam-5934	147	25	on	on	ADP
ejpam-5934	147	26	model	model	NOUN
ejpam-5934	147	27	performance	performance	NOUN
ejpam-5934	147	28	.	.	PUNCT
ejpam-5934	148	1	1.3	1.3	NUM
ejpam-5934	148	2	.	.	PUNCT
ejpam-5934	148	3	contribution	contribution	VERB
ejpam-5934	148	4	the	the	DET
ejpam-5934	148	5	contribution	contribution	NOUN
ejpam-5934	148	6	of	of	ADP
ejpam-5934	148	7	this	this	DET
ejpam-5934	148	8	study	study	NOUN
ejpam-5934	148	9	is	be	AUX
ejpam-5934	148	10	provided	provide	VERB
ejpam-5934	148	11	below	below	ADP
ejpam-5934	148	12	(	(	PUNCT
ejpam-5934	148	13	i	i	NOUN
ejpam-5934	148	14	)	)	PUNCT
ejpam-5934	148	15	application	application	NOUN
ejpam-5934	148	16	of	of	ADP
ejpam-5934	148	17	rst	rst	NOUN
ejpam-5934	148	18	-	-	PUNCT
ejpam-5934	148	19	based	base	VERB
ejpam-5934	148	20	feature	feature	NOUN
ejpam-5934	148	21	selection	selection	NOUN
ejpam-5934	148	22	to	to	ADP
ejpam-5934	148	23	five	five	NUM
ejpam-5934	148	24	diverse	diverse	ADJ
ejpam-5934	148	25	datasets	dataset	NOUN
ejpam-5934	148	26	,	,	PUNCT
ejpam-5934	148	27	encompassing	encompass	VERB
ejpam-5934	148	28	domains	domain	NOUN
ejpam-5934	148	29	such	such	ADJ
ejpam-5934	148	30	as	as	ADP
ejpam-5934	148	31	seed	seed	NOUN
ejpam-5934	148	32	,	,	PUNCT
ejpam-5934	148	33	heart	heart	NOUN
ejpam-5934	148	34	attack	attack	NOUN
ejpam-5934	148	35	,	,	PUNCT
ejpam-5934	148	36	obesity	obesity	NOUN
ejpam-5934	148	37	,	,	PUNCT
ejpam-5934	148	38	online	online	ADJ
ejpam-5934	148	39	delivery	delivery	NOUN
ejpam-5934	148	40	,	,	PUNCT
ejpam-5934	148	41	and	and	CCONJ
ejpam-5934	148	42	breast	breast	NOUN
ejpam-5934	148	43	cancer	cancer	NOUN
ejpam-5934	148	44	.	.	PUNCT
ejpam-5934	149	1	this	this	DET
ejpam-5934	149	2	extensive	extensive	ADJ
ejpam-5934	149	3	evaluation	evaluation	NOUN
ejpam-5934	149	4	provides	provide	VERB
ejpam-5934	149	5	insights	insight	NOUN
ejpam-5934	149	6	into	into	ADP
ejpam-5934	149	7	the	the	DET
ejpam-5934	149	8	applicability	applicability	NOUN
ejpam-5934	149	9	and	and	CCONJ
ejpam-5934	149	10	effectiveness	effectiveness	NOUN
ejpam-5934	149	11	of	of	ADP
ejpam-5934	149	12	rst	rst	PROPN
ejpam-5934	149	13	across	across	ADP
ejpam-5934	149	14	various	various	ADJ
ejpam-5934	149	15	contexts	contexts	NOUN
ejpam-5934	149	16	.	.	PUNCT
ejpam-5934	150	1	(	(	PUNCT
ejpam-5934	150	2	ii	ii	NOUN
ejpam-5934	150	3	)	)	PUNCT
ejpam-5934	150	4	comparative	comparative	ADJ
ejpam-5934	150	5	analysis	analysis	NOUN
ejpam-5934	150	6	of	of	ADP
ejpam-5934	150	7	ml	ml	NOUN
ejpam-5934	150	8	models	model	NOUN
ejpam-5934	150	9	trained	train	VERB
ejpam-5934	150	10	on	on	ADP
ejpam-5934	150	11	datasets	dataset	NOUN
ejpam-5934	150	12	with	with	ADP
ejpam-5934	150	13	and	and	CCONJ
ejpam-5934	150	14	without	without	ADP
ejpam-5934	150	15	rstbased	rstbase	VERB
ejpam-5934	150	16	feature	feature	NOUN
ejpam-5934	150	17	selection	selection	NOUN
ejpam-5934	150	18	is	be	AUX
ejpam-5934	150	19	conducted	conduct	VERB
ejpam-5934	150	20	.	.	PUNCT
ejpam-5934	151	1	the	the	DET
ejpam-5934	151	2	results	result	NOUN
ejpam-5934	151	3	indicate	indicate	VERB
ejpam-5934	151	4	that	that	SCONJ
ejpam-5934	151	5	rst	rst	PROPN
ejpam-5934	151	6	either	either	CCONJ
ejpam-5934	151	7	enhances	enhance	NOUN
ejpam-5934	151	8	or	or	CCONJ
ejpam-5934	151	9	maintains	maintain	VERB
ejpam-5934	151	10	model	model	NOUN
ejpam-5934	151	11	performance	performance	NOUN
ejpam-5934	151	12	,	,	PUNCT
ejpam-5934	151	13	highlighting	highlight	VERB
ejpam-5934	151	14	its	its	PRON
ejpam-5934	151	15	potential	potential	NOUN
ejpam-5934	151	16	as	as	ADP
ejpam-5934	151	17	a	a	DET
ejpam-5934	151	18	valuable	valuable	ADJ
ejpam-5934	151	19	tool	tool	NOUN
ejpam-5934	151	20	in	in	ADP
ejpam-5934	151	21	ml	ml	ADP
ejpam-5934	151	22	workflows	workflow	NOUN
ejpam-5934	151	23	.	.	PUNCT
ejpam-5934	152	1	(	(	PUNCT
ejpam-5934	152	2	iii	iii	X
ejpam-5934	152	3	)	)	PUNCT
ejpam-5934	152	4	the	the	DET
ejpam-5934	152	5	findings	finding	NOUN
ejpam-5934	152	6	suggest	suggest	VERB
ejpam-5934	152	7	that	that	SCONJ
ejpam-5934	152	8	integrating	integrate	VERB
ejpam-5934	152	9	rst	rst	PROPN
ejpam-5934	152	10	into	into	ADP
ejpam-5934	152	11	feature	feature	NOUN
ejpam-5934	152	12	selection	selection	NOUN
ejpam-5934	152	13	processes	process	NOUN
ejpam-5934	152	14	can	can	AUX
ejpam-5934	152	15	lead	lead	VERB
ejpam-5934	152	16	to	to	ADP
ejpam-5934	152	17	more	more	ADV
ejpam-5934	152	18	efficient	efficient	ADJ
ejpam-5934	152	19	and	and	CCONJ
ejpam-5934	152	20	accurate	accurate	ADJ
ejpam-5934	152	21	ml	ml	NOUN
ejpam-5934	152	22	models	model	NOUN
ejpam-5934	152	23	,	,	PUNCT
ejpam-5934	152	24	with	with	ADP
ejpam-5934	152	25	potential	potential	ADJ
ejpam-5934	152	26	applications	application	NOUN
ejpam-5934	152	27	in	in	ADP
ejpam-5934	152	28	various	various	ADJ
ejpam-5934	152	29	fields	field	NOUN
ejpam-5934	152	30	.	.	PUNCT
ejpam-5934	153	1	by	by	ADP
ejpam-5934	153	2	addressing	address	VERB
ejpam-5934	153	3	the	the	DET
ejpam-5934	153	4	limitations	limitation	NOUN
ejpam-5934	153	5	of	of	ADP
ejpam-5934	153	6	traditional	traditional	ADJ
ejpam-5934	153	7	feature	feature	NOUN
ejpam-5934	153	8	selection	selection	NOUN
ejpam-5934	153	9	methods	method	NOUN
ejpam-5934	153	10	and	and	CCONJ
ejpam-5934	153	11	demonstrating	demonstrate	VERB
ejpam-5934	153	12	the	the	DET
ejpam-5934	153	13	efficacy	efficacy	NOUN
ejpam-5934	153	14	of	of	ADP
ejpam-5934	153	15	rst	rst	PROPN
ejpam-5934	153	16	,	,	PUNCT
ejpam-5934	153	17	this	this	DET
ejpam-5934	153	18	work	work	NOUN
ejpam-5934	153	19	contributes	contribute	VERB
ejpam-5934	153	20	to	to	ADP
ejpam-5934	153	21	the	the	DET
ejpam-5934	153	22	advancement	advancement	NOUN
ejpam-5934	153	23	of	of	ADP
ejpam-5934	153	24	ml	ml	NOUN
ejpam-5934	153	25	techniques	technique	NOUN
ejpam-5934	153	26	and	and	CCONJ
ejpam-5934	153	27	their	their	PRON
ejpam-5934	153	28	practical	practical	ADJ
ejpam-5934	153	29	applications	application	NOUN
ejpam-5934	153	30	.	.	PUNCT
ejpam-5934	154	1	the	the	DET
ejpam-5934	154	2	structure	structure	NOUN
ejpam-5934	154	3	of	of	ADP
ejpam-5934	154	4	the	the	DET
ejpam-5934	154	5	paper	paper	NOUN
ejpam-5934	154	6	is	be	AUX
ejpam-5934	154	7	as	as	SCONJ
ejpam-5934	154	8	follows	follow	VERB
ejpam-5934	154	9	:	:	PUNCT
ejpam-5934	154	10	section	section	NOUN
ejpam-5934	154	11	2	2	NUM
ejpam-5934	154	12	presents	present	VERB
ejpam-5934	154	13	the	the	DET
ejpam-5934	154	14	materials	material	NOUN
ejpam-5934	154	15	and	and	CCONJ
ejpam-5934	154	16	methods	method	NOUN
ejpam-5934	154	17	.	.	PUNCT
ejpam-5934	155	1	the	the	DET
ejpam-5934	155	2	research	research	NOUN
ejpam-5934	155	3	findings	finding	NOUN
ejpam-5934	155	4	of	of	ADP
ejpam-5934	155	5	the	the	DET
ejpam-5934	155	6	suggested	suggest	VERB
ejpam-5934	155	7	model	model	NOUN
ejpam-5934	155	8	are	be	AUX
ejpam-5934	155	9	covered	cover	VERB
ejpam-5934	155	10	in	in	ADP
ejpam-5934	155	11	section	section	NOUN
ejpam-5934	155	12	3	3	NUM
ejpam-5934	155	13	.	.	PUNCT
ejpam-5934	155	14	section	section	NOUN
ejpam-5934	155	15	4	4	NUM
ejpam-5934	155	16	discusses	discuss	VERB
ejpam-5934	155	17	the	the	DET
ejpam-5934	155	18	paper	paper	NOUN
ejpam-5934	155	19	and	and	CCONJ
ejpam-5934	155	20	section	section	NOUN
ejpam-5934	155	21	5	5	NUM
ejpam-5934	155	22	concludes	conclude	VERB
ejpam-5934	155	23	the	the	DET
ejpam-5934	155	24	suggested	suggested	ADJ
ejpam-5934	155	25	work	work	NOUN
ejpam-5934	155	26	.	.	PUNCT
ejpam-5934	156	1	2	2	X
ejpam-5934	156	2	.	.	X
ejpam-5934	156	3	materials	material	NOUN
ejpam-5934	156	4	and	and	CCONJ
ejpam-5934	156	5	methods	method	NOUN
ejpam-5934	156	6	this	this	DET
ejpam-5934	156	7	section	section	NOUN
ejpam-5934	156	8	outlines	outline	VERB
ejpam-5934	156	9	the	the	DET
ejpam-5934	156	10	materials	material	NOUN
ejpam-5934	156	11	and	and	CCONJ
ejpam-5934	156	12	methods	method	NOUN
ejpam-5934	156	13	utilized	utilize	VERB
ejpam-5934	156	14	in	in	ADP
ejpam-5934	156	15	this	this	DET
ejpam-5934	156	16	study	study	NOUN
ejpam-5934	156	17	,	,	PUNCT
ejpam-5934	156	18	including	include	VERB
ejpam-5934	156	19	the	the	DET
ejpam-5934	156	20	proposed	propose	VERB
ejpam-5934	156	21	methodology	methodology	NOUN
ejpam-5934	156	22	,	,	PUNCT
ejpam-5934	156	23	description	description	NOUN
ejpam-5934	156	24	of	of	ADP
ejpam-5934	156	25	the	the	DET
ejpam-5934	156	26	datasets	dataset	NOUN
ejpam-5934	156	27	,	,	PUNCT
ejpam-5934	156	28	the	the	DET
ejpam-5934	156	29	data	datum	NOUN
ejpam-5934	156	30	preprocessing	preprocesse	VERB
ejpam-5934	156	31	steps	step	NOUN
ejpam-5934	156	32	,	,	PUNCT
ejpam-5934	156	33	the	the	DET
ejpam-5934	156	34	application	application	NOUN
ejpam-5934	156	35	of	of	ADP
ejpam-5934	156	36	rst	rst	PROPN
ejpam-5934	156	37	for	for	ADP
ejpam-5934	156	38	feature	feature	NOUN
ejpam-5934	156	39	selection	selection	NOUN
ejpam-5934	156	40	,	,	PUNCT
ejpam-5934	156	41	the	the	DET
ejpam-5934	156	42	ml	ml	NOUN
ejpam-5934	156	43	models	model	NOUN
ejpam-5934	156	44	employed	employ	VERB
ejpam-5934	156	45	,	,	PUNCT
ejpam-5934	156	46	and	and	CCONJ
ejpam-5934	156	47	the	the	DET
ejpam-5934	156	48	evaluation	evaluation	NOUN
ejpam-5934	156	49	metrics	metric	NOUN
ejpam-5934	156	50	used	use	VERB
ejpam-5934	156	51	to	to	PART
ejpam-5934	156	52	assess	assess	VERB
ejpam-5934	156	53	model	model	NOUN
ejpam-5934	156	54	performance	performance	NOUN
ejpam-5934	156	55	.	.	PUNCT
ejpam-5934	157	1	t.	t.	ADJ
ejpam-5934	157	2	ashika	ashika	PROPN
ejpam-5934	157	3	,	,	PUNCT
ejpam-5934	157	4	g.	g.	PROPN
ejpam-5934	157	5	h.	h.	PROPN
ejpam-5934	157	6	grace	grace	PROPN
ejpam-5934	157	7	/	/	SYM
ejpam-5934	157	8	eur	eur	PROPN
ejpam-5934	157	9	.	.	PUNCT
ejpam-5934	158	1	j.	j.	PROPN
ejpam-5934	158	2	pure	pure	PROPN
ejpam-5934	158	3	appl	appl	PROPN
ejpam-5934	158	4	.	.	PROPN
ejpam-5934	158	5	math	math	PROPN
ejpam-5934	158	6	,	,	PUNCT
ejpam-5934	158	7	18	18	NUM
ejpam-5934	158	8	(	(	PUNCT
ejpam-5934	158	9	2	2	NUM
ejpam-5934	158	10	)	)	PUNCT
ejpam-5934	158	11	(	(	PUNCT
ejpam-5934	158	12	2025	2025	NUM
ejpam-5934	158	13	)	)	PUNCT
ejpam-5934	158	14	,	,	PUNCT
ejpam-5934	158	15	5934	5934	NUM
ejpam-5934	158	16	8	8	NUM
ejpam-5934	158	17	of	of	ADP
ejpam-5934	158	18	22	22	NUM
ejpam-5934	158	19	2.1	2.1	NUM
ejpam-5934	158	20	.	.	PUNCT
ejpam-5934	159	1	proposed	propose	VERB
ejpam-5934	159	2	work	work	NOUN
ejpam-5934	159	3	the	the	DET
ejpam-5934	159	4	paper	paper	NOUN
ejpam-5934	159	5	proposes	propose	VERB
ejpam-5934	159	6	two	two	NUM
ejpam-5934	159	7	process	process	NOUN
ejpam-5934	159	8	which	which	PRON
ejpam-5934	159	9	includes	include	VERB
ejpam-5934	159	10	classification	classification	NOUN
ejpam-5934	159	11	without	without	ADP
ejpam-5934	159	12	rst	rst	NOUN
ejpam-5934	159	13	and	and	CCONJ
ejpam-5934	159	14	classification	classification	NOUN
ejpam-5934	159	15	with	with	ADP
ejpam-5934	159	16	rst	rst	PROPN
ejpam-5934	159	17	.	.	PUNCT
ejpam-5934	160	1	five	five	NUM
ejpam-5934	160	2	different	different	ADJ
ejpam-5934	160	3	datasets	dataset	NOUN
ejpam-5934	160	4	with	with	ADP
ejpam-5934	160	5	varying	vary	VERB
ejpam-5934	160	6	number	number	NOUN
ejpam-5934	160	7	of	of	ADP
ejpam-5934	160	8	attributes	attribute	NOUN
ejpam-5934	160	9	and	and	CCONJ
ejpam-5934	160	10	variables	variable	NOUN
ejpam-5934	160	11	are	be	AUX
ejpam-5934	160	12	chosen	choose	VERB
ejpam-5934	160	13	.	.	PUNCT
ejpam-5934	161	1	firstly	firstly	ADV
ejpam-5934	161	2	,	,	PUNCT
ejpam-5934	161	3	these	these	DET
ejpam-5934	161	4	datasets	dataset	NOUN
ejpam-5934	161	5	were	be	AUX
ejpam-5934	161	6	preprocessed	preprocesse	VERB
ejpam-5934	161	7	and	and	CCONJ
ejpam-5934	161	8	evaluated	evaluate	VERB
ejpam-5934	161	9	using	use	VERB
ejpam-5934	161	10	various	various	ADJ
ejpam-5934	161	11	ml	ml	NOUN
ejpam-5934	161	12	classifiers	classifier	NOUN
ejpam-5934	161	13	like	like	ADP
ejpam-5934	161	14	lr	lr	PROPN
ejpam-5934	161	15	,	,	PUNCT
ejpam-5934	161	16	knn	knn	PROPN
ejpam-5934	161	17	,	,	PUNCT
ejpam-5934	161	18	svm	svm	PROPN
ejpam-5934	161	19	,	,	PUNCT
ejpam-5934	161	20	kernel	kernel	PROPN
ejpam-5934	161	21	svm	svm	PROPN
ejpam-5934	161	22	,	,	PUNCT
ejpam-5934	161	23	nb	nb	INTJ
ejpam-5934	161	24	,	,	PUNCT
ejpam-5934	161	25	dt	dt	PUNCT
ejpam-5934	161	26	and	and	CCONJ
ejpam-5934	161	27	rf	rf	PROPN
ejpam-5934	161	28	.	.	PUNCT
ejpam-5934	162	1	the	the	DET
ejpam-5934	162	2	model	model	NOUN
ejpam-5934	162	3	’s	’s	PART
ejpam-5934	162	4	performance	performance	NOUN
ejpam-5934	162	5	is	be	AUX
ejpam-5934	162	6	then	then	ADV
ejpam-5934	162	7	assessed	assess	VERB
ejpam-5934	162	8	using	use	VERB
ejpam-5934	162	9	evaluation	evaluation	NOUN
ejpam-5934	162	10	metrics	metric	NOUN
ejpam-5934	162	11	,	,	PUNCT
ejpam-5934	162	12	which	which	PRON
ejpam-5934	162	13	include	include	VERB
ejpam-5934	162	14	mae	mae	PROPN
ejpam-5934	162	15	,	,	PUNCT
ejpam-5934	162	16	accuracy	accuracy	NOUN
ejpam-5934	162	17	,	,	PUNCT
ejpam-5934	162	18	precision	precision	NOUN
ejpam-5934	162	19	,	,	PUNCT
ejpam-5934	162	20	recall	recall	NOUN
ejpam-5934	162	21	,	,	PUNCT
ejpam-5934	162	22	f1	f1	NOUN
ejpam-5934	162	23	score	score	NOUN
ejpam-5934	162	24	,	,	PUNCT
ejpam-5934	162	25	and	and	CCONJ
ejpam-5934	162	26	confusion	confusion	NOUN
ejpam-5934	162	27	matrix	matrix	NOUN
ejpam-5934	162	28	.	.	PUNCT
ejpam-5934	163	1	secondly	secondly	ADV
ejpam-5934	163	2	,	,	PUNCT
ejpam-5934	163	3	the	the	DET
ejpam-5934	163	4	insignificant	insignificant	ADJ
ejpam-5934	163	5	features	feature	NOUN
ejpam-5934	163	6	of	of	ADP
ejpam-5934	163	7	these	these	DET
ejpam-5934	163	8	five	five	NUM
ejpam-5934	163	9	datasets	dataset	NOUN
ejpam-5934	163	10	are	be	AUX
ejpam-5934	163	11	reduced	reduce	VERB
ejpam-5934	163	12	using	use	VERB
ejpam-5934	163	13	rst	rst	PROPN
ejpam-5934	163	14	reduct	reduct	PROPN
ejpam-5934	163	15	and	and	CCONJ
ejpam-5934	163	16	core	core	NOUN
ejpam-5934	163	17	.	.	PUNCT
ejpam-5934	164	1	these	these	DET
ejpam-5934	164	2	reduced	reduce	VERB
ejpam-5934	164	3	dataset	dataset	NOUN
ejpam-5934	164	4	are	be	AUX
ejpam-5934	164	5	evaluated	evaluate	VERB
ejpam-5934	164	6	using	use	VERB
ejpam-5934	164	7	the	the	DET
ejpam-5934	164	8	ml	ml	NOUN
ejpam-5934	164	9	techniques	technique	NOUN
ejpam-5934	164	10	like	like	ADP
ejpam-5934	164	11	lr	lr	PROPN
ejpam-5934	164	12	,	,	PUNCT
ejpam-5934	164	13	knn	knn	PROPN
ejpam-5934	164	14	,	,	PUNCT
ejpam-5934	164	15	svm	svm	PROPN
ejpam-5934	164	16	,	,	PUNCT
ejpam-5934	164	17	kernel	kernel	PROPN
ejpam-5934	164	18	svm	svm	PROPN
ejpam-5934	164	19	,	,	PUNCT
ejpam-5934	164	20	nb	nb	INTJ
ejpam-5934	164	21	,	,	PUNCT
ejpam-5934	164	22	dt	dt	PUNCT
ejpam-5934	165	1	and	and	CCONJ
ejpam-5934	165	2	rf	rf	PROPN
ejpam-5934	165	3	and	and	CCONJ
ejpam-5934	165	4	the	the	DET
ejpam-5934	165	5	performance	performance	NOUN
ejpam-5934	165	6	of	of	ADP
ejpam-5934	165	7	these	these	DET
ejpam-5934	165	8	models	model	NOUN
ejpam-5934	165	9	is	be	AUX
ejpam-5934	165	10	evaluated	evaluate	VERB
ejpam-5934	165	11	and	and	CCONJ
ejpam-5934	165	12	compared	compare	VERB
ejpam-5934	165	13	with	with	ADP
ejpam-5934	165	14	the	the	DET
ejpam-5934	165	15	original	original	ADJ
ejpam-5934	165	16	dataset	dataset	NOUN
ejpam-5934	165	17	to	to	PART
ejpam-5934	165	18	analyse	analyse	VERB
ejpam-5934	165	19	whether	whether	SCONJ
ejpam-5934	165	20	the	the	DET
ejpam-5934	165	21	rst	rst	PROPN
ejpam-5934	165	22	selected	select	VERB
ejpam-5934	165	23	features	feature	NOUN
ejpam-5934	165	24	improve	improve	VERB
ejpam-5934	165	25	performance	performance	NOUN
ejpam-5934	165	26	compared	compare	VERB
ejpam-5934	165	27	to	to	ADP
ejpam-5934	165	28	the	the	DET
ejpam-5934	165	29	original	original	ADJ
ejpam-5934	165	30	dataset	dataset	NOUN
ejpam-5934	165	31	.	.	PUNCT
ejpam-5934	166	1	suitable	suitable	ADJ
ejpam-5934	166	2	ml	ml	ADP
ejpam-5934	166	3	algorithms	algorithm	NOUN
ejpam-5934	166	4	for	for	ADP
ejpam-5934	166	5	each	each	DET
ejpam-5934	166	6	dataset	dataset	NOUN
ejpam-5934	166	7	were	be	AUX
ejpam-5934	166	8	also	also	ADV
ejpam-5934	166	9	identified	identify	VERB
ejpam-5934	166	10	based	base	VERB
ejpam-5934	166	11	on	on	ADP
ejpam-5934	166	12	the	the	DET
ejpam-5934	166	13	comparative	comparative	ADJ
ejpam-5934	166	14	analysis	analysis	NOUN
ejpam-5934	166	15	.	.	PUNCT
ejpam-5934	167	1	the	the	DET
ejpam-5934	167	2	architecture	architecture	NOUN
ejpam-5934	167	3	of	of	ADP
ejpam-5934	167	4	the	the	DET
ejpam-5934	167	5	suggested	suggest	VERB
ejpam-5934	167	6	work	work	NOUN
ejpam-5934	167	7	is	be	AUX
ejpam-5934	167	8	shown	show	VERB
ejpam-5934	167	9	in	in	ADP
ejpam-5934	167	10	figure	figure	NOUN
ejpam-5934	167	11	1	1	NUM
ejpam-5934	167	12	.	.	PUNCT
ejpam-5934	167	13	figure	figure	NOUN
ejpam-5934	167	14	1	1	NUM
ejpam-5934	167	15	:	:	PUNCT
ejpam-5934	167	16	overall	overall	ADJ
ejpam-5934	167	17	architecture	architecture	NOUN
ejpam-5934	167	18	of	of	ADP
ejpam-5934	167	19	the	the	DET
ejpam-5934	167	20	suggested	suggest	VERB
ejpam-5934	167	21	work	work	NOUN
ejpam-5934	167	22	2.2	2.2	NUM
ejpam-5934	167	23	.	.	PUNCT
ejpam-5934	168	1	dataset	dataset	ADJ
ejpam-5934	168	2	description	description	NOUN
ejpam-5934	168	3	the	the	DET
ejpam-5934	168	4	study	study	NOUN
ejpam-5934	168	5	utilized	utilize	VERB
ejpam-5934	168	6	five	five	NUM
ejpam-5934	168	7	datasets	dataset	NOUN
ejpam-5934	168	8	sourced	source	VERB
ejpam-5934	168	9	from	from	ADP
ejpam-5934	168	10	kaggle	kaggle	PROPN
ejpam-5934	168	11	and	and	CCONJ
ejpam-5934	168	12	the	the	DET
ejpam-5934	168	13	uci	uci	PROPN
ejpam-5934	168	14	ml	ml	NOUN
ejpam-5934	168	15	repository	repository	PROPN
ejpam-5934	168	16	,	,	PUNCT
ejpam-5934	168	17	a	a	DET
ejpam-5934	168	18	widely	widely	ADV
ejpam-5934	168	19	recognized	recognize	VERB
ejpam-5934	168	20	platform	platform	NOUN
ejpam-5934	168	21	for	for	ADP
ejpam-5934	168	22	its	its	PRON
ejpam-5934	168	23	diverse	diverse	ADJ
ejpam-5934	168	24	and	and	CCONJ
ejpam-5934	168	25	comprehensive	comprehensive	ADJ
ejpam-5934	168	26	data	datum	NOUN
ejpam-5934	168	27	.	.	PUNCT
ejpam-5934	169	1	this	this	DET
ejpam-5934	169	2	selection	selection	NOUN
ejpam-5934	169	3	provides	provide	VERB
ejpam-5934	169	4	a	a	DET
ejpam-5934	169	5	robust	robust	ADJ
ejpam-5934	169	6	foundation	foundation	NOUN
ejpam-5934	169	7	for	for	ADP
ejpam-5934	169	8	evaluating	evaluate	VERB
ejpam-5934	169	9	the	the	DET
ejpam-5934	169	10	effectiveness	effectiveness	NOUN
ejpam-5934	169	11	of	of	ADP
ejpam-5934	169	12	classification	classification	NOUN
ejpam-5934	169	13	models	model	NOUN
ejpam-5934	169	14	both	both	CCONJ
ejpam-5934	169	15	with	with	ADP
ejpam-5934	169	16	and	and	CCONJ
ejpam-5934	169	17	without	without	ADP
ejpam-5934	169	18	rst	rst	PROPN
ejpam-5934	169	19	based	base	VERB
ejpam-5934	169	20	feature	feature	NOUN
ejpam-5934	169	21	selection	selection	NOUN
ejpam-5934	169	22	.	.	PUNCT
ejpam-5934	170	1	the	the	DET
ejpam-5934	170	2	selected	select	VERB
ejpam-5934	170	3	datasets	dataset	NOUN
ejpam-5934	170	4	include	include	VERB
ejpam-5934	170	5	seeds	seed	NOUN
ejpam-5934	170	6	[	[	X
ejpam-5934	170	7	24	24	NUM
ejpam-5934	170	8	]	]	PUNCT
ejpam-5934	170	9	,	,	PUNCT
ejpam-5934	170	10	online	online	ADJ
ejpam-5934	170	11	food	food	NOUN
ejpam-5934	170	12	delivery	delivery	NOUN
ejpam-5934	171	1	[	[	X
ejpam-5934	171	2	25	25	NUM
ejpam-5934	171	3	]	]	PUNCT
ejpam-5934	171	4	,	,	PUNCT
ejpam-5934	171	5	heart	heart	NOUN
ejpam-5934	171	6	attack	attack	NOUN
ejpam-5934	171	7	[	[	X
ejpam-5934	171	8	26	26	NUM
ejpam-5934	171	9	]	]	PUNCT
ejpam-5934	171	10	,	,	PUNCT
ejpam-5934	171	11	obesity	obesity	NOUN
ejpam-5934	171	12	[	[	X
ejpam-5934	171	13	27	27	NUM
ejpam-5934	171	14	]	]	PUNCT
ejpam-5934	171	15	and	and	CCONJ
ejpam-5934	171	16	breast	breast	NOUN
ejpam-5934	171	17	cancer	cancer	NOUN
ejpam-5934	171	18	[	[	X
ejpam-5934	171	19	28	28	NUM
ejpam-5934	171	20	]	]	PUNCT
ejpam-5934	171	21	.	.	PUNCT
ejpam-5934	172	1	the	the	DET
ejpam-5934	172	2	seeds	seed	NOUN
ejpam-5934	172	3	dataset	dataset	NOUN
ejpam-5934	172	4	features	feature	VERB
ejpam-5934	172	5	7	7	NUM
ejpam-5934	172	6	conditional	conditional	ADJ
ejpam-5934	172	7	attributes	attribute	NOUN
ejpam-5934	172	8	and	and	CCONJ
ejpam-5934	172	9	1	1	NUM
ejpam-5934	172	10	decision	decision	NOUN
ejpam-5934	172	11	attribute	attribute	NOUN
ejpam-5934	172	12	to	to	ADP
ejpam-5934	172	13	clast	clast	NOUN
ejpam-5934	172	14	.	.	PUNCT
ejpam-5934	173	1	ashika	ashika	PROPN
ejpam-5934	173	2	,	,	PUNCT
ejpam-5934	173	3	g.	g.	PROPN
ejpam-5934	173	4	h.	h.	PROPN
ejpam-5934	173	5	grace	grace	PROPN
ejpam-5934	173	6	/	/	SYM
ejpam-5934	173	7	eur	eur	PROPN
ejpam-5934	173	8	.	.	PUNCT
ejpam-5934	174	1	j.	j.	PROPN
ejpam-5934	174	2	pure	pure	PROPN
ejpam-5934	174	3	appl	appl	PROPN
ejpam-5934	174	4	.	.	PROPN
ejpam-5934	174	5	math	math	PROPN
ejpam-5934	174	6	,	,	PUNCT
ejpam-5934	174	7	18	18	NUM
ejpam-5934	174	8	(	(	PUNCT
ejpam-5934	174	9	2	2	NUM
ejpam-5934	174	10	)	)	PUNCT
ejpam-5934	174	11	(	(	PUNCT
ejpam-5934	174	12	2025	2025	NUM
ejpam-5934	174	13	)	)	PUNCT
ejpam-5934	174	14	,	,	PUNCT
ejpam-5934	174	15	5934	5934	NUM
ejpam-5934	174	16	9	9	NUM
ejpam-5934	174	17	of	of	ADP
ejpam-5934	174	18	22	22	NUM
ejpam-5934	174	19	sify	sify	NOUN
ejpam-5934	174	20	wheat	wheat	NOUN
ejpam-5934	174	21	types	type	NOUN
ejpam-5934	174	22	.	.	PUNCT
ejpam-5934	175	1	the	the	DET
ejpam-5934	175	2	online	online	ADJ
ejpam-5934	175	3	food	food	NOUN
ejpam-5934	175	4	delivery	delivery	NOUN
ejpam-5934	175	5	dataset	dataset	NOUN
ejpam-5934	175	6	,	,	PUNCT
ejpam-5934	175	7	focusing	focus	VERB
ejpam-5934	175	8	on	on	ADP
ejpam-5934	175	9	the	the	DET
ejpam-5934	175	10	bangalore	bangalore	NOUN
ejpam-5934	175	11	region	region	NOUN
ejpam-5934	175	12	,	,	PUNCT
ejpam-5934	175	13	includes	include	VERB
ejpam-5934	175	14	54	54	NUM
ejpam-5934	175	15	conditional	conditional	ADJ
ejpam-5934	175	16	attributes	attribute	NOUN
ejpam-5934	175	17	and	and	CCONJ
ejpam-5934	175	18	1	1	NUM
ejpam-5934	175	19	decision	decision	NOUN
ejpam-5934	175	20	attribute	attribute	NOUN
ejpam-5934	175	21	,	,	PUNCT
ejpam-5934	175	22	examining	examine	VERB
ejpam-5934	175	23	the	the	DET
ejpam-5934	175	24	growth	growth	NOUN
ejpam-5934	175	25	in	in	ADP
ejpam-5934	175	26	demand	demand	NOUN
ejpam-5934	175	27	for	for	ADP
ejpam-5934	175	28	food	food	NOUN
ejpam-5934	175	29	delivery	delivery	NOUN
ejpam-5934	175	30	.	.	PUNCT
ejpam-5934	176	1	the	the	DET
ejpam-5934	176	2	heart	heart	NOUN
ejpam-5934	176	3	attack	attack	NOUN
ejpam-5934	176	4	dataset	dataset	NOUN
ejpam-5934	176	5	,	,	PUNCT
ejpam-5934	176	6	with	with	ADP
ejpam-5934	176	7	54	54	NUM
ejpam-5934	176	8	conditional	conditional	ADJ
ejpam-5934	176	9	attributes	attribute	NOUN
ejpam-5934	176	10	and	and	CCONJ
ejpam-5934	176	11	1	1	NUM
ejpam-5934	176	12	decision	decision	NOUN
ejpam-5934	176	13	attribute	attribute	NOUN
ejpam-5934	176	14	,	,	PUNCT
ejpam-5934	176	15	identifies	identify	VERB
ejpam-5934	176	16	predictors	predictor	NOUN
ejpam-5934	176	17	of	of	ADP
ejpam-5934	176	18	heart	heart	NOUN
ejpam-5934	176	19	disease	disease	NOUN
ejpam-5934	176	20	and	and	CCONJ
ejpam-5934	176	21	classifies	classify	VERB
ejpam-5934	176	22	outcomes	outcome	NOUN
ejpam-5934	176	23	as	as	ADP
ejpam-5934	176	24	positive	positive	ADJ
ejpam-5934	176	25	(	(	PUNCT
ejpam-5934	176	26	disease	disease	NOUN
ejpam-5934	176	27	present	present	ADJ
ejpam-5934	176	28	)	)	PUNCT
ejpam-5934	176	29	or	or	CCONJ
ejpam-5934	176	30	negative	negative	ADJ
ejpam-5934	176	31	(	(	PUNCT
ejpam-5934	176	32	absent	absent	ADJ
ejpam-5934	176	33	)	)	PUNCT
ejpam-5934	176	34	.	.	PUNCT
ejpam-5934	177	1	the	the	DET
ejpam-5934	177	2	obesity	obesity	NOUN
ejpam-5934	177	3	dataset	dataset	NOUN
ejpam-5934	177	4	contains	contain	VERB
ejpam-5934	177	5	6	6	NUM
ejpam-5934	177	6	conditional	conditional	ADJ
ejpam-5934	177	7	attributes	attribute	NOUN
ejpam-5934	177	8	and	and	CCONJ
ejpam-5934	177	9	1	1	NUM
ejpam-5934	177	10	decision	decision	NOUN
ejpam-5934	177	11	attribute	attribute	NOUN
ejpam-5934	177	12	,	,	PUNCT
ejpam-5934	177	13	categorizing	categorize	VERB
ejpam-5934	177	14	individuals	individual	NOUN
ejpam-5934	177	15	into	into	ADP
ejpam-5934	177	16	weight	weight	NOUN
ejpam-5934	177	17	classifications	classification	NOUN
ejpam-5934	177	18	such	such	ADJ
ejpam-5934	177	19	as	as	ADP
ejpam-5934	177	20	overweight	overweight	ADJ
ejpam-5934	177	21	,	,	PUNCT
ejpam-5934	177	22	underweight	underweight	NOUN
ejpam-5934	177	23	,	,	PUNCT
ejpam-5934	177	24	normal	normal	ADJ
ejpam-5934	177	25	,	,	PUNCT
ejpam-5934	177	26	or	or	CCONJ
ejpam-5934	177	27	obese	obese	ADJ
ejpam-5934	177	28	.	.	PUNCT
ejpam-5934	178	1	for	for	ADP
ejpam-5934	178	2	breast	breast	NOUN
ejpam-5934	178	3	cancer	cancer	NOUN
ejpam-5934	178	4	,	,	PUNCT
ejpam-5934	178	5	the	the	DET
ejpam-5934	178	6	wisconsin	wisconsin	NOUN
ejpam-5934	178	7	dataset	dataset	NOUN
ejpam-5934	178	8	includes	include	VERB
ejpam-5934	178	9	8	8	NUM
ejpam-5934	178	10	conditional	conditional	ADJ
ejpam-5934	178	11	attributes	attribute	NOUN
ejpam-5934	178	12	and	and	CCONJ
ejpam-5934	178	13	1	1	NUM
ejpam-5934	178	14	decision	decision	NOUN
ejpam-5934	178	15	attribute	attribute	NOUN
ejpam-5934	178	16	to	to	PART
ejpam-5934	178	17	classify	classify	VERB
ejpam-5934	178	18	tumors	tumor	NOUN
ejpam-5934	178	19	as	as	ADP
ejpam-5934	178	20	benign	benign	ADJ
ejpam-5934	178	21	or	or	CCONJ
ejpam-5934	178	22	malignant	malignant	ADJ
ejpam-5934	178	23	.	.	PUNCT
ejpam-5934	179	1	together	together	ADV
ejpam-5934	179	2	,	,	PUNCT
ejpam-5934	179	3	these	these	DET
ejpam-5934	179	4	datasets	dataset	NOUN
ejpam-5934	179	5	provide	provide	VERB
ejpam-5934	179	6	a	a	DET
ejpam-5934	179	7	diverse	diverse	ADJ
ejpam-5934	179	8	and	and	CCONJ
ejpam-5934	179	9	structured	structured	ADJ
ejpam-5934	179	10	basis	basis	NOUN
ejpam-5934	179	11	for	for	ADP
ejpam-5934	179	12	classification	classification	NOUN
ejpam-5934	179	13	and	and	CCONJ
ejpam-5934	179	14	prediction	prediction	NOUN
ejpam-5934	179	15	in	in	ADP
ejpam-5934	179	16	the	the	DET
ejpam-5934	179	17	study	study	NOUN
ejpam-5934	179	18	.	.	PUNCT
ejpam-5934	180	1	table	table	NOUN
ejpam-5934	180	2	2	2	NUM
ejpam-5934	180	3	presents	present	VERB
ejpam-5934	180	4	a	a	DET
ejpam-5934	180	5	list	list	NOUN
ejpam-5934	180	6	of	of	ADP
ejpam-5934	180	7	datasets	dataset	NOUN
ejpam-5934	180	8	,	,	PUNCT
ejpam-5934	180	9	detailing	detail	VERB
ejpam-5934	180	10	the	the	DET
ejpam-5934	180	11	number	number	NOUN
ejpam-5934	180	12	of	of	ADP
ejpam-5934	180	13	attributes	attribute	NOUN
ejpam-5934	180	14	and	and	CCONJ
ejpam-5934	180	15	instances	instance	NOUN
ejpam-5934	180	16	for	for	ADP
ejpam-5934	180	17	each	each	DET
ejpam-5934	180	18	dataset	dataset	NOUN
ejpam-5934	180	19	.	.	PUNCT
ejpam-5934	181	1	table	table	NOUN
ejpam-5934	181	2	2	2	NUM
ejpam-5934	181	3	:	:	PUNCT
ejpam-5934	181	4	list	list	NOUN
ejpam-5934	181	5	of	of	ADP
ejpam-5934	181	6	dataset	dataset	NOUN
ejpam-5934	181	7	along	along	ADP
ejpam-5934	181	8	with	with	ADP
ejpam-5934	181	9	the	the	DET
ejpam-5934	181	10	number	number	NOUN
ejpam-5934	181	11	of	of	ADP
ejpam-5934	181	12	features	feature	NOUN
ejpam-5934	181	13	and	and	CCONJ
ejpam-5934	181	14	instances	instance	NOUN
ejpam-5934	181	15	s.	s.	PROPN
ejpam-5934	181	16	no	no	DET
ejpam-5934	181	17	datasets	dataset	NOUN
ejpam-5934	181	18	number	number	NOUN
ejpam-5934	181	19	conditional	conditional	ADJ
ejpam-5934	181	20	decision	decision	NOUN
ejpam-5934	181	21	number	number	NOUN
ejpam-5934	181	22	of	of	ADP
ejpam-5934	181	23	features	feature	NOUN
ejpam-5934	181	24	attribute	attribute	NOUN
ejpam-5934	181	25	attribute	attribute	NOUN
ejpam-5934	181	26	of	of	ADP
ejpam-5934	181	27	instances	instance	NOUN
ejpam-5934	181	28	1	1	NUM
ejpam-5934	181	29	seeds	seed	NOUN
ejpam-5934	181	30	8	8	NUM
ejpam-5934	181	31	7	7	NUM
ejpam-5934	181	32	1	1	NUM
ejpam-5934	181	33	211	211	NUM
ejpam-5934	181	34	2	2	NUM
ejpam-5934	181	35	online	online	ADJ
ejpam-5934	181	36	food	food	NOUN
ejpam-5934	181	37	delivery	delivery	NOUN
ejpam-5934	181	38	55	55	NUM
ejpam-5934	181	39	54	54	NUM
ejpam-5934	181	40	1	1	NUM
ejpam-5934	181	41	387	387	NUM
ejpam-5934	181	42	3	3	NUM
ejpam-5934	181	43	heart	heart	NOUN
ejpam-5934	181	44	attack	attack	NOUN
ejpam-5934	181	45	9	9	NUM
ejpam-5934	181	46	8	8	NUM
ejpam-5934	181	47	1	1	NUM
ejpam-5934	181	48	1319	1319	NUM
ejpam-5934	181	49	4	4	NUM
ejpam-5934	181	50	obesity	obesity	NOUN
ejpam-5934	181	51	7	7	NUM
ejpam-5934	181	52	6	6	NUM
ejpam-5934	181	53	1	1	NUM
ejpam-5934	181	54	108	108	NUM
ejpam-5934	181	55	5	5	NUM
ejpam-5934	181	56	breast	breast	NOUN
ejpam-5934	181	57	cancer	cancer	NOUN
ejpam-5934	181	58	9	9	NUM
ejpam-5934	181	59	8	8	NUM
ejpam-5934	181	60	1	1	NUM
ejpam-5934	181	61	699	699	NUM
ejpam-5934	181	62	2.3	2.3	NUM
ejpam-5934	181	63	.	.	PUNCT
ejpam-5934	182	1	data	datum	NOUN
ejpam-5934	182	2	preprocessing	preprocesse	VERB
ejpam-5934	182	3	the	the	DET
ejpam-5934	182	4	dataset	dataset	NOUN
ejpam-5934	182	5	might	might	AUX
ejpam-5934	182	6	include	include	VERB
ejpam-5934	182	7	insufficient	insufficient	ADJ
ejpam-5934	182	8	data	datum	NOUN
ejpam-5934	182	9	,	,	PUNCT
ejpam-5934	182	10	missing	miss	VERB
ejpam-5934	182	11	data	datum	NOUN
ejpam-5934	182	12	or	or	CCONJ
ejpam-5934	182	13	categorical	categorical	ADJ
ejpam-5934	182	14	data	datum	NOUN
ejpam-5934	182	15	.	.	PUNCT
ejpam-5934	183	1	in	in	ADP
ejpam-5934	183	2	order	order	NOUN
ejpam-5934	183	3	to	to	PART
ejpam-5934	183	4	convert	convert	VERB
ejpam-5934	183	5	this	this	DET
ejpam-5934	183	6	raw	raw	ADJ
ejpam-5934	183	7	dataset	dataset	NOUN
ejpam-5934	183	8	into	into	ADP
ejpam-5934	183	9	a	a	DET
ejpam-5934	183	10	clean	clean	ADJ
ejpam-5934	183	11	dataset	dataset	NOUN
ejpam-5934	183	12	,	,	PUNCT
ejpam-5934	183	13	data	datum	NOUN
ejpam-5934	183	14	preprocessing	preprocessing	NOUN
ejpam-5934	183	15	is	be	AUX
ejpam-5934	183	16	performed	perform	VERB
ejpam-5934	183	17	.	.	PUNCT
ejpam-5934	184	1	data	datum	NOUN
ejpam-5934	184	2	preprocessing	preprocesse	VERB
ejpam-5934	184	3	techniques	technique	NOUN
ejpam-5934	184	4	include	include	VERB
ejpam-5934	184	5	:	:	PUNCT
ejpam-5934	184	6	handling	handle	VERB
ejpam-5934	184	7	missing	missing	ADJ
ejpam-5934	184	8	data	datum	NOUN
ejpam-5934	184	9	,	,	PUNCT
ejpam-5934	184	10	splitting	split	VERB
ejpam-5934	184	11	the	the	DET
ejpam-5934	184	12	dataset	dataset	NOUN
ejpam-5934	184	13	,	,	PUNCT
ejpam-5934	184	14	feature	feature	NOUN
ejpam-5934	184	15	scaling	scaling	NOUN
ejpam-5934	184	16	,	,	PUNCT
ejpam-5934	184	17	and	and	CCONJ
ejpam-5934	184	18	encoding	encode	VERB
ejpam-5934	184	19	categorical	categorical	ADJ
ejpam-5934	184	20	data	datum	NOUN
ejpam-5934	184	21	.	.	PUNCT
ejpam-5934	185	1	missing	miss	VERB
ejpam-5934	185	2	values	value	NOUN
ejpam-5934	185	3	were	be	AUX
ejpam-5934	185	4	imputed	impute	VERB
ejpam-5934	185	5	by	by	ADP
ejpam-5934	185	6	replacing	replace	VERB
ejpam-5934	185	7	them	they	PRON
ejpam-5934	185	8	with	with	ADP
ejpam-5934	185	9	the	the	DET
ejpam-5934	185	10	column	column	NOUN
ejpam-5934	185	11	average	average	NOUN
ejpam-5934	185	12	to	to	PART
ejpam-5934	185	13	mitigate	mitigate	VERB
ejpam-5934	185	14	potential	potential	ADJ
ejpam-5934	185	15	errors	error	NOUN
ejpam-5934	185	16	.	.	PUNCT
ejpam-5934	186	1	categorical	categorical	ADJ
ejpam-5934	186	2	features	feature	NOUN
ejpam-5934	186	3	were	be	AUX
ejpam-5934	186	4	converted	convert	VERB
ejpam-5934	186	5	into	into	ADP
ejpam-5934	186	6	numerical	numerical	ADJ
ejpam-5934	186	7	format	format	NOUN
ejpam-5934	186	8	using	use	VERB
ejpam-5934	186	9	one	one	NUM
ejpam-5934	186	10	-	-	PUNCT
ejpam-5934	186	11	hot	hot	ADJ
ejpam-5934	186	12	encoding	encoding	NOUN
ejpam-5934	186	13	to	to	PART
ejpam-5934	186	14	create	create	VERB
ejpam-5934	186	15	binary	binary	ADJ
ejpam-5934	186	16	vectors	vector	NOUN
ejpam-5934	186	17	for	for	ADP
ejpam-5934	186	18	each	each	DET
ejpam-5934	186	19	category	category	NOUN
ejpam-5934	186	20	.	.	PUNCT
ejpam-5934	187	1	in	in	ADP
ejpam-5934	187	2	addition	addition	NOUN
ejpam-5934	187	3	,	,	PUNCT
ejpam-5934	187	4	standardization	standardization	NOUN
ejpam-5934	187	5	was	be	AUX
ejpam-5934	187	6	applied	apply	VERB
ejpam-5934	187	7	to	to	PART
ejpam-5934	187	8	scale	scale	VERB
ejpam-5934	187	9	all	all	DET
ejpam-5934	187	10	features	feature	NOUN
ejpam-5934	187	11	uniformly	uniformly	ADV
ejpam-5934	187	12	,	,	PUNCT
ejpam-5934	187	13	typically	typically	ADV
ejpam-5934	187	14	adjusting	adjust	VERB
ejpam-5934	187	15	values	value	NOUN
ejpam-5934	187	16	to	to	ADP
ejpam-5934	187	17	a	a	DET
ejpam-5934	187	18	range	range	NOUN
ejpam-5934	187	19	between	between	ADP
ejpam-5934	187	20	-3	-3	PUNCT
ejpam-5934	187	21	and	and	CCONJ
ejpam-5934	187	22	+3	+3	PROPN
ejpam-5934	187	23	.	.	PUNCT
ejpam-5934	188	1	finally	finally	ADV
ejpam-5934	188	2	,	,	PUNCT
ejpam-5934	188	3	each	each	DET
ejpam-5934	188	4	dataset	dataset	NOUN
ejpam-5934	188	5	was	be	AUX
ejpam-5934	188	6	divided	divide	VERB
ejpam-5934	188	7	into	into	ADP
ejpam-5934	188	8	training	training	NOUN
ejpam-5934	188	9	and	and	CCONJ
ejpam-5934	188	10	testing	testing	NOUN
ejpam-5934	188	11	sets	set	NOUN
ejpam-5934	188	12	using	use	VERB
ejpam-5934	188	13	an	an	DET
ejpam-5934	188	14	80:20	80:20	NUM
ejpam-5934	188	15	split	split	NOUN
ejpam-5934	188	16	,	,	PUNCT
ejpam-5934	188	17	ensuring	ensure	VERB
ejpam-5934	188	18	a	a	DET
ejpam-5934	188	19	consistent	consistent	ADJ
ejpam-5934	188	20	evaluation	evaluation	NOUN
ejpam-5934	188	21	framework	framework	NOUN
ejpam-5934	188	22	across	across	ADP
ejpam-5934	188	23	the	the	DET
ejpam-5934	188	24	diverse	diverse	ADJ
ejpam-5934	188	25	datasets	dataset	NOUN
ejpam-5934	188	26	.	.	PUNCT
ejpam-5934	189	1	2.4	2.4	NUM
ejpam-5934	189	2	.	.	PUNCT
ejpam-5934	190	1	rough	rough	ADJ
ejpam-5934	190	2	set	set	PROPN
ejpam-5934	190	3	theory	theory	NOUN
ejpam-5934	190	4	a	a	DET
ejpam-5934	190	5	mathematical	mathematical	ADJ
ejpam-5934	190	6	tool	tool	NOUN
ejpam-5934	190	7	called	call	VERB
ejpam-5934	190	8	rst	rst	PROPN
ejpam-5934	190	9	is	be	AUX
ejpam-5934	190	10	used	use	VERB
ejpam-5934	190	11	to	to	PART
ejpam-5934	190	12	deal	deal	VERB
ejpam-5934	190	13	with	with	ADP
ejpam-5934	190	14	uncertain	uncertain	ADJ
ejpam-5934	190	15	and	and	CCONJ
ejpam-5934	190	16	inconsistent	inconsistent	ADJ
ejpam-5934	190	17	data	datum	NOUN
ejpam-5934	190	18	.	.	PUNCT
ejpam-5934	191	1	it	it	PRON
ejpam-5934	191	2	was	be	AUX
ejpam-5934	191	3	first	first	ADV
ejpam-5934	191	4	proposed	propose	VERB
ejpam-5934	191	5	by	by	ADP
ejpam-5934	191	6	pawlak	pawlak	ADJ
ejpam-5934	191	7	[	[	X
ejpam-5934	191	8	1	1	NUM
ejpam-5934	191	9	]	]	PUNCT
ejpam-5934	191	10	at	at	ADP
ejpam-5934	191	11	the	the	DET
ejpam-5934	191	12	beginning	beginning	NOUN
ejpam-5934	191	13	of	of	ADP
ejpam-5934	191	14	the	the	DET
ejpam-5934	191	15	1980	1980	NUM
ejpam-5934	191	16	’s	’s	NOUN
ejpam-5934	191	17	.	.	PUNCT
ejpam-5934	192	1	rst	rst	PROPN
ejpam-5934	192	2	expresses	express	VERB
ejpam-5934	192	3	uncertainty	uncertainty	NOUN
ejpam-5934	192	4	and	and	CCONJ
ejpam-5934	192	5	imprecision	imprecision	NOUN
ejpam-5934	192	6	through	through	ADP
ejpam-5934	192	7	a	a	DET
ejpam-5934	192	8	set	set	NOUN
ejpam-5934	192	9	’s	’s	PART
ejpam-5934	192	10	boundary	boundary	ADJ
ejpam-5934	192	11	region	region	NOUN
ejpam-5934	192	12	rather	rather	ADV
ejpam-5934	192	13	than	than	ADP
ejpam-5934	192	14	through	through	ADP
ejpam-5934	192	15	partial	partial	ADJ
ejpam-5934	192	16	membership	membership	NOUN
ejpam-5934	192	17	function	function	NOUN
ejpam-5934	192	18	as	as	SCONJ
ejpam-5934	192	19	fuzzy	fuzzy	ADJ
ejpam-5934	192	20	set	set	NOUN
ejpam-5934	192	21	theory	theory	NOUN
ejpam-5934	192	22	does	do	VERB
ejpam-5934	192	23	.	.	PUNCT
ejpam-5934	193	1	rst	rst	PROPN
ejpam-5934	193	2	consists	consist	VERB
ejpam-5934	193	3	of	of	ADP
ejpam-5934	193	4	lower	low	ADJ
ejpam-5934	193	5	and	and	CCONJ
ejpam-5934	193	6	upper	upper	ADJ
ejpam-5934	193	7	approximations	approximation	NOUN
ejpam-5934	193	8	,	,	PUNCT
ejpam-5934	193	9	a	a	DET
ejpam-5934	193	10	boundary	boundary	ADJ
ejpam-5934	193	11	region	region	NOUN
ejpam-5934	193	12	,	,	PUNCT
ejpam-5934	193	13	and	and	CCONJ
ejpam-5934	193	14	the	the	DET
ejpam-5934	193	15	concepts	concept	NOUN
ejpam-5934	193	16	of	of	ADP
ejpam-5934	193	17	indiscernibility	indiscernibility	NOUN
ejpam-5934	193	18	,	,	PUNCT
ejpam-5934	193	19	which	which	PRON
ejpam-5934	193	20	lead	lead	VERB
ejpam-5934	193	21	to	to	ADP
ejpam-5934	193	22	the	the	DET
ejpam-5934	193	23	identification	identification	NOUN
ejpam-5934	193	24	of	of	ADP
ejpam-5934	193	25	reducts	reduct	NOUN
ejpam-5934	193	26	and	and	CCONJ
ejpam-5934	193	27	cores	core	NOUN
ejpam-5934	193	28	.	.	PUNCT
ejpam-5934	194	1	rst	rst	PROPN
ejpam-5934	194	2	allows	allow	VERB
ejpam-5934	194	3	for	for	SCONJ
ejpam-5934	194	4	a	a	DET
ejpam-5934	194	5	crisp	crisp	ADJ
ejpam-5934	194	6	set	set	NOUN
ejpam-5934	194	7	to	to	PART
ejpam-5934	194	8	be	be	AUX
ejpam-5934	194	9	formally	formally	ADV
ejpam-5934	194	10	approximated	approximate	VERB
ejpam-5934	194	11	using	use	VERB
ejpam-5934	194	12	the	the	DET
ejpam-5934	194	13	lower	low	ADJ
ejpam-5934	194	14	and	and	CCONJ
ejpam-5934	194	15	upper	upper	ADJ
ejpam-5934	194	16	approximations	approximation	NOUN
ejpam-5934	194	17	of	of	ADP
ejpam-5934	194	18	the	the	DET
ejpam-5934	194	19	original	original	ADJ
ejpam-5934	194	20	set	set	NOUN
ejpam-5934	194	21	.	.	PUNCT
ejpam-5934	195	1	to	to	PART
ejpam-5934	195	2	enable	enable	VERB
ejpam-5934	195	3	effective	effective	ADJ
ejpam-5934	195	4	classification	classification	NOUN
ejpam-5934	195	5	,	,	PUNCT
ejpam-5934	195	6	the	the	DET
ejpam-5934	195	7	most	most	ADV
ejpam-5934	195	8	pertinent	pertinent	ADJ
ejpam-5934	195	9	features	feature	NOUN
ejpam-5934	195	10	are	be	AUX
ejpam-5934	195	11	selected	select	VERB
ejpam-5934	195	12	using	use	VERB
ejpam-5934	195	13	the	the	DET
ejpam-5934	195	14	rst	rst	ADJ
ejpam-5934	195	15	technique	technique	NOUN
ejpam-5934	195	16	.	.	PUNCT
ejpam-5934	196	1	let	let	VERB
ejpam-5934	196	2	t.	t.	PROPN
ejpam-5934	196	3	ashika	ashika	PROPN
ejpam-5934	196	4	,	,	PUNCT
ejpam-5934	196	5	g.	g.	PROPN
ejpam-5934	196	6	h.	h.	PROPN
ejpam-5934	196	7	grace	grace	PROPN
ejpam-5934	196	8	/	/	SYM
ejpam-5934	196	9	eur	eur	PROPN
ejpam-5934	196	10	.	.	PUNCT
ejpam-5934	197	1	j.	j.	PROPN
ejpam-5934	197	2	pure	pure	PROPN
ejpam-5934	197	3	appl	appl	PROPN
ejpam-5934	197	4	.	.	PROPN
ejpam-5934	197	5	math	math	PROPN
ejpam-5934	197	6	,	,	PUNCT
ejpam-5934	197	7	18	18	NUM
ejpam-5934	197	8	(	(	PUNCT
ejpam-5934	197	9	2	2	NUM
ejpam-5934	197	10	)	)	PUNCT
ejpam-5934	197	11	(	(	PUNCT
ejpam-5934	197	12	2025	2025	NUM
ejpam-5934	197	13	)	)	PUNCT
ejpam-5934	197	14	,	,	PUNCT
ejpam-5934	197	15	5934	5934	NUM
ejpam-5934	197	16	10	10	NUM
ejpam-5934	197	17	of	of	ADP
ejpam-5934	197	18	22	22	NUM
ejpam-5934	198	1	i	i	NOUN
ejpam-5934	198	2	=	=	PUNCT
ejpam-5934	198	3	(	(	PUNCT
ejpam-5934	198	4	u	u	NOUN
ejpam-5934	198	5	,	,	PUNCT
ejpam-5934	198	6	a	a	PRON
ejpam-5934	198	7	)	)	PUNCT
ejpam-5934	198	8	represent	represent	VERB
ejpam-5934	198	9	an	an	DET
ejpam-5934	198	10	information	information	NOUN
ejpam-5934	198	11	system	system	NOUN
ejpam-5934	198	12	,	,	PUNCT
ejpam-5934	198	13	where	where	SCONJ
ejpam-5934	198	14	u	u	PRON
ejpam-5934	198	15	denotes	denote	VERB
ejpam-5934	198	16	a	a	DET
ejpam-5934	198	17	nonempty	nonempty	ADV
ejpam-5934	198	18	set	set	NOUN
ejpam-5934	198	19	of	of	ADP
ejpam-5934	198	20	finite	finite	ADJ
ejpam-5934	198	21	objects	object	NOUN
ejpam-5934	198	22	that	that	PRON
ejpam-5934	198	23	is	be	AUX
ejpam-5934	198	24	the	the	DET
ejpam-5934	198	25	universe	universe	NOUN
ejpam-5934	198	26	of	of	ADP
ejpam-5934	198	27	discourse	discourse	NOUN
ejpam-5934	198	28	.	.	PUNCT
ejpam-5934	199	1	a	a	PRON
ejpam-5934	199	2	is	be	AUX
ejpam-5934	199	3	non	non	ADJ
ejpam-5934	199	4	-	-	ADJ
ejpam-5934	199	5	empty	empty	ADJ
ejpam-5934	199	6	.	.	PUNCT
ejpam-5934	200	1	an	an	DET
ejpam-5934	200	2	associated	associated	ADJ
ejpam-5934	200	3	set	set	NOUN
ejpam-5934	200	4	of	of	ADP
ejpam-5934	200	5	values	value	NOUN
ejpam-5934	200	6	(	(	PUNCT
ejpam-5934	200	7	va	va	NOUN
ejpam-5934	200	8	)	)	PUNCT
ejpam-5934	200	9	exists	exist	VERB
ejpam-5934	200	10	for	for	ADP
ejpam-5934	200	11	each	each	DET
ejpam-5934	200	12	attribute	attribute	NOUN
ejpam-5934	200	13	a	a	DET
ejpam-5934	200	14	∈	∈	NOUN
ejpam-5934	200	15	a.	a.	NOUN
ejpam-5934	200	16	for	for	ADP
ejpam-5934	200	17	a	a	DET
ejpam-5934	200	18	subset	subset	NOUN
ejpam-5934	200	19	,	,	PUNCT
ejpam-5934	200	20	x	x	X
ejpam-5934	200	21	⊆	⊆	NUM
ejpam-5934	200	22	u	u	NOUN
ejpam-5934	200	23	,	,	PUNCT
ejpam-5934	200	24	x	x	PRON
ejpam-5934	200	25	can	can	AUX
ejpam-5934	200	26	be	be	AUX
ejpam-5934	200	27	approximated	approximate	VERB
ejpam-5934	200	28	using	use	VERB
ejpam-5934	200	29	only	only	ADJ
ejpam-5934	200	30	information	information	NOUN
ejpam-5934	200	31	contained	contain	VERB
ejpam-5934	200	32	within	within	ADP
ejpam-5934	200	33	p	p	NOUN
ejpam-5934	200	34	by	by	ADP
ejpam-5934	200	35	constructing	construct	VERB
ejpam-5934	200	36	the	the	DET
ejpam-5934	200	37	p	p	NOUN
ejpam-5934	200	38	-lower	-lower	NOUN
ejpam-5934	200	39	approximation	approximation	NOUN
ejpam-5934	200	40	given	give	VERB
ejpam-5934	200	41	as	as	ADP
ejpam-5934	200	42	p∗x	p∗x	NUM
ejpam-5934	200	43	,	,	PUNCT
ejpam-5934	200	44	is	be	AUX
ejpam-5934	200	45	the	the	DET
ejpam-5934	200	46	set	set	NOUN
ejpam-5934	200	47	of	of	ADP
ejpam-5934	200	48	all	all	DET
ejpam-5934	200	49	elements	element	NOUN
ejpam-5934	200	50	of	of	ADP
ejpam-5934	200	51	u	u	NOUN
ejpam-5934	200	52	,	,	PUNCT
ejpam-5934	200	53	which	which	PRON
ejpam-5934	200	54	can	can	AUX
ejpam-5934	200	55	be	be	AUX
ejpam-5934	200	56	certainly	certainly	ADV
ejpam-5934	200	57	classified	classify	VERB
ejpam-5934	200	58	as	as	ADP
ejpam-5934	200	59	elements	element	NOUN
ejpam-5934	200	60	of	of	ADP
ejpam-5934	200	61	x	x	PUNCT
ejpam-5934	200	62	based	base	VERB
ejpam-5934	200	63	on	on	ADP
ejpam-5934	200	64	the	the	DET
ejpam-5934	200	65	attribute	attribute	NOUN
ejpam-5934	200	66	set	set	VERB
ejpam-5934	200	67	p	p	PROPN
ejpam-5934	200	68	.	.	PUNCT
ejpam-5934	201	1	the	the	DET
ejpam-5934	201	2	p	p	PROPN
ejpam-5934	201	3	upper	upper	ADJ
ejpam-5934	201	4	approximation	approximation	NOUN
ejpam-5934	201	5	of	of	ADP
ejpam-5934	201	6	x	x	PRON
ejpam-5934	201	7	,	,	PUNCT
ejpam-5934	201	8	denoted	denote	VERB
ejpam-5934	201	9	as	as	ADP
ejpam-5934	201	10	p	p	ADJ
ejpam-5934	201	11	∗x	∗x	NOUN
ejpam-5934	201	12	,	,	PUNCT
ejpam-5934	201	13	which	which	PRON
ejpam-5934	201	14	can	can	AUX
ejpam-5934	201	15	be	be	AUX
ejpam-5934	201	16	possibly	possibly	ADV
ejpam-5934	201	17	classified	classify	VERB
ejpam-5934	201	18	as	as	ADP
ejpam-5934	201	19	elements	element	NOUN
ejpam-5934	201	20	of	of	ADP
ejpam-5934	201	21	x	x	PUNCT
ejpam-5934	201	22	based	base	VERB
ejpam-5934	201	23	on	on	ADP
ejpam-5934	201	24	the	the	DET
ejpam-5934	201	25	attribute	attribute	NOUN
ejpam-5934	201	26	set	set	VERB
ejpam-5934	201	27	p	p	PROPN
ejpam-5934	201	28	.	.	PUNCT
ejpam-5934	202	1	the	the	DET
ejpam-5934	202	2	lower	low	ADJ
ejpam-5934	202	3	and	and	CCONJ
ejpam-5934	202	4	upper	upper	ADJ
ejpam-5934	202	5	approximation	approximation	NOUN
ejpam-5934	202	6	can	can	AUX
ejpam-5934	202	7	be	be	AUX
ejpam-5934	202	8	defined	define	VERB
ejpam-5934	202	9	as	as	ADP
ejpam-5934	202	10	shown	show	VERB
ejpam-5934	202	11	in	in	ADP
ejpam-5934	202	12	equations	equation	NOUN
ejpam-5934	202	13	(	(	PUNCT
ejpam-5934	202	14	1	1	NUM
ejpam-5934	202	15	)	)	PUNCT
ejpam-5934	202	16	and	and	CCONJ
ejpam-5934	202	17	(	(	PUNCT
ejpam-5934	202	18	2	2	NUM
ejpam-5934	202	19	)	)	PUNCT
ejpam-5934	202	20	,	,	PUNCT
ejpam-5934	202	21	p∗(x	p∗(x	PROPN
ejpam-5934	202	22	)	)	PUNCT
ejpam-5934	202	23	=	=	PRON
ejpam-5934	202	24	{	{	PUNCT
ejpam-5934	202	25	x	x	PUNCT
ejpam-5934	202	26	∈	∈	PROPN
ejpam-5934	202	27	u	u	NOUN
ejpam-5934	202	28	:	:	PUNCT
ejpam-5934	202	29	p	p	X
ejpam-5934	202	30	(	(	PUNCT
ejpam-5934	202	31	x	x	NOUN
ejpam-5934	202	32	)	)	PUNCT
ejpam-5934	202	33	⊆	⊆	NUM
ejpam-5934	202	34	x	x	SYM
ejpam-5934	202	35	}	}	PUNCT
ejpam-5934	202	36	(	(	PUNCT
ejpam-5934	202	37	1	1	X
ejpam-5934	202	38	)	)	PUNCT
ejpam-5934	202	39	p	p	NOUN
ejpam-5934	202	40	∗(x	∗(x	PROPN
ejpam-5934	202	41	)	)	PUNCT
ejpam-5934	202	42	=	=	PRON
ejpam-5934	202	43	{	{	PUNCT
ejpam-5934	202	44	x	x	PUNCT
ejpam-5934	202	45	∈	∈	PROPN
ejpam-5934	202	46	u	u	NOUN
ejpam-5934	202	47	:	:	PUNCT
ejpam-5934	202	48	p	p	X
ejpam-5934	202	49	(	(	PUNCT
ejpam-5934	202	50	x	x	NOUN
ejpam-5934	202	51	)	)	PUNCT
ejpam-5934	202	52	∩x	∩x	X
ejpam-5934	203	1	̸=	̸=	NOUN
ejpam-5934	203	2	∅	∅	NOUN
ejpam-5934	203	3	}	}	PUNCT
ejpam-5934	203	4	(	(	PUNCT
ejpam-5934	203	5	2	2	X
ejpam-5934	203	6	)	)	PUNCT
ejpam-5934	203	7	the	the	DET
ejpam-5934	203	8	difference	difference	NOUN
ejpam-5934	203	9	of	of	ADP
ejpam-5934	203	10	the	the	DET
ejpam-5934	203	11	upper	upper	ADJ
ejpam-5934	203	12	p	p	X
ejpam-5934	203	13	∗x	∗x	PROPN
ejpam-5934	203	14	and	and	CCONJ
ejpam-5934	203	15	the	the	DET
ejpam-5934	203	16	lower	low	ADJ
ejpam-5934	203	17	approximation	approximation	NOUN
ejpam-5934	203	18	p∗x	p∗x	NUM
ejpam-5934	203	19	yields	yield	VERB
ejpam-5934	203	20	the	the	DET
ejpam-5934	203	21	boundary	boundary	ADJ
ejpam-5934	203	22	region	region	NOUN
ejpam-5934	203	23	pn(x	pn(x	PUNCT
ejpam-5934	203	24	)	)	PUNCT
ejpam-5934	203	25	as	as	SCONJ
ejpam-5934	203	26	shown	show	VERB
ejpam-5934	203	27	in	in	ADP
ejpam-5934	203	28	equation	equation	NOUN
ejpam-5934	203	29	(	(	PUNCT
ejpam-5934	203	30	3	3	NUM
ejpam-5934	203	31	)	)	PUNCT
ejpam-5934	203	32	.	.	PUNCT
ejpam-5934	204	1	pn(x	pn(x	PUNCT
ejpam-5934	204	2	)	)	PUNCT
ejpam-5934	205	1	=	=	PUNCT
ejpam-5934	205	2	p	p	DET
ejpam-5934	205	3	∗(x)−	∗(x)−	PROPN
ejpam-5934	205	4	p∗(x	p∗(x	PROPN
ejpam-5934	205	5	)	)	PUNCT
ejpam-5934	205	6	(	(	PUNCT
ejpam-5934	205	7	3	3	X
ejpam-5934	205	8	)	)	PUNCT
ejpam-5934	205	9	the	the	DET
ejpam-5934	205	10	accuracy	accuracy	NOUN
ejpam-5934	205	11	of	of	ADP
ejpam-5934	205	12	approximation	approximation	NOUN
ejpam-5934	205	13	αp	αp	NOUN
ejpam-5934	205	14	(	(	PUNCT
ejpam-5934	205	15	x	x	X
ejpam-5934	205	16	)	)	PUNCT
ejpam-5934	205	17	is	be	AUX
ejpam-5934	205	18	shown	show	VERB
ejpam-5934	205	19	in	in	ADP
ejpam-5934	205	20	equation	equation	NOUN
ejpam-5934	205	21	(	(	PUNCT
ejpam-5934	205	22	4	4	NUM
ejpam-5934	205	23	)	)	PUNCT
ejpam-5934	205	24	where	where	SCONJ
ejpam-5934	205	25	the	the	DET
ejpam-5934	205	26	resultant	resultant	NOUN
ejpam-5934	205	27	values	value	VERB
ejpam-5934	205	28	lies	lie	VERB
ejpam-5934	205	29	in	in	ADP
ejpam-5934	205	30	the	the	DET
ejpam-5934	205	31	range	range	NOUN
ejpam-5934	205	32	of	of	ADP
ejpam-5934	205	33	0	0	NUM
ejpam-5934	205	34	≤	≤	NUM
ejpam-5934	205	35	αp	αp	NOUN
ejpam-5934	205	36	(	(	PUNCT
ejpam-5934	205	37	x	x	NOUN
ejpam-5934	205	38	)	)	PUNCT
ejpam-5934	205	39	≤	≤	NUM
ejpam-5934	205	40	1	1	NUM
ejpam-5934	205	41	.	.	PUNCT
ejpam-5934	206	1	αp	αp	INTJ
ejpam-5934	206	2	(	(	PUNCT
ejpam-5934	206	3	x	x	X
ejpam-5934	206	4	)	)	PUNCT
ejpam-5934	206	5	=	=	SYM
ejpam-5934	206	6	|(p∗x)|	|(p∗x)|	PROPN
ejpam-5934	206	7	|(p	|(p	PROPN
ejpam-5934	207	1	∗(x))|	∗(x))|	PROPN
ejpam-5934	207	2	(	(	PUNCT
ejpam-5934	207	3	4	4	NUM
ejpam-5934	207	4	)	)	PUNCT
ejpam-5934	207	5	dependency	dependency	NOUN
ejpam-5934	207	6	between	between	ADP
ejpam-5934	207	7	the	the	DET
ejpam-5934	207	8	decision	decision	NOUN
ejpam-5934	207	9	attribute	attribute	NOUN
ejpam-5934	207	10	d	d	NOUN
ejpam-5934	207	11	and	and	CCONJ
ejpam-5934	207	12	the	the	DET
ejpam-5934	207	13	condition	condition	NOUN
ejpam-5934	207	14	attribute	attribute	NOUN
ejpam-5934	207	15	c	c	NOUN
ejpam-5934	207	16	,	,	PUNCT
ejpam-5934	207	17	where	where	SCONJ
ejpam-5934	207	18	d	d	NOUN
ejpam-5934	207	19	depends	depend	VERB
ejpam-5934	207	20	on	on	ADP
ejpam-5934	207	21	c	c	PROPN
ejpam-5934	207	22	in	in	ADP
ejpam-5934	207	23	a	a	DET
ejpam-5934	207	24	degree	degree	NOUN
ejpam-5934	207	25	k(0	k(0	PROPN
ejpam-5934	207	26	≤	≤	NUM
ejpam-5934	208	1	k	k	PROPN
ejpam-5934	208	2	≤	≤	NUM
ejpam-5934	208	3	1	1	NUM
ejpam-5934	208	4	)	)	PUNCT
ejpam-5934	208	5	,	,	PUNCT
ejpam-5934	208	6	denoted	denote	VERB
ejpam-5934	208	7	c	c	PROPN
ejpam-5934	208	8	⇒k	⇒k	PROPN
ejpam-5934	208	9	d	d	PROPN
ejpam-5934	208	10	,	,	PUNCT
ejpam-5934	208	11	if	if	SCONJ
ejpam-5934	208	12	k	k	PROPN
ejpam-5934	208	13	=	=	SYM
ejpam-5934	208	14	γ(c	γ(c	PROPN
ejpam-5934	208	15	,	,	PUNCT
ejpam-5934	208	16	d	d	X
ejpam-5934	208	17	)	)	PUNCT
ejpam-5934	208	18	are	be	AUX
ejpam-5934	208	19	represented	represent	VERB
ejpam-5934	208	20	as	as	ADP
ejpam-5934	208	21	given	give	VERB
ejpam-5934	208	22	in	in	ADP
ejpam-5934	208	23	equation	equation	NOUN
ejpam-5934	208	24	(	(	PUNCT
ejpam-5934	208	25	5	5	NUM
ejpam-5934	208	26	)	)	PUNCT
ejpam-5934	208	27	and	and	CCONJ
ejpam-5934	208	28	(	(	PUNCT
ejpam-5934	208	29	6	6	NUM
ejpam-5934	208	30	)	)	PUNCT
ejpam-5934	208	31	.	.	PUNCT
ejpam-5934	209	1	γ(c	γ(c	PROPN
ejpam-5934	209	2	,	,	PUNCT
ejpam-5934	209	3	d	d	NOUN
ejpam-5934	209	4	)	)	PUNCT
ejpam-5934	209	5	=	=	SYM
ejpam-5934	209	6	|(posc(d))|	|(posc(d))|	PROPN
ejpam-5934	209	7	|u	|u	ADJ
ejpam-5934	209	8	|	|	NOUN
ejpam-5934	209	9	(	(	PUNCT
ejpam-5934	209	10	5	5	NUM
ejpam-5934	209	11	)	)	PUNCT
ejpam-5934	209	12	posc(d	posc(d	NOUN
ejpam-5934	209	13	)	)	PUNCT
ejpam-5934	209	14	=	=	SYM
ejpam-5934	209	15	∪p∗(x	∪p∗(x	NOUN
ejpam-5934	209	16	)	)	PUNCT
ejpam-5934	209	17	(	(	PUNCT
ejpam-5934	209	18	6	6	NUM
ejpam-5934	209	19	)	)	PUNCT
ejpam-5934	209	20	where	where	SCONJ
ejpam-5934	209	21	,	,	PUNCT
ejpam-5934	209	22	the	the	DET
ejpam-5934	209	23	set	set	NOUN
ejpam-5934	209	24	of	of	ADP
ejpam-5934	209	25	all	all	DET
ejpam-5934	209	26	elements	element	NOUN
ejpam-5934	209	27	of	of	ADP
ejpam-5934	209	28	u	u	PRON
ejpam-5934	209	29	that	that	PRON
ejpam-5934	209	30	can	can	AUX
ejpam-5934	209	31	be	be	AUX
ejpam-5934	209	32	specifically	specifically	ADV
ejpam-5934	209	33	assigned	assign	VERB
ejpam-5934	209	34	to	to	ADP
ejpam-5934	209	35	blocks	block	NOUN
ejpam-5934	209	36	of	of	ADP
ejpam-5934	209	37	the	the	DET
ejpam-5934	209	38	partition	partition	NOUN
ejpam-5934	209	39	u	u	NOUN
ejpam-5934	209	40	/	/	SYM
ejpam-5934	209	41	d	d	NOUN
ejpam-5934	209	42	by	by	ADP
ejpam-5934	209	43	means	mean	NOUN
ejpam-5934	209	44	of	of	ADP
ejpam-5934	209	45	c	c	PROPN
ejpam-5934	209	46	is	be	AUX
ejpam-5934	209	47	known	know	VERB
ejpam-5934	209	48	as	as	ADP
ejpam-5934	209	49	posc(d	posc(d	NOUN
ejpam-5934	209	50	)	)	PUNCT
ejpam-5934	209	51	also	also	ADV
ejpam-5934	209	52	known	know	VERB
ejpam-5934	209	53	as	as	ADP
ejpam-5934	209	54	the	the	DET
ejpam-5934	209	55	positive	positive	ADJ
ejpam-5934	209	56	region	region	NOUN
ejpam-5934	209	57	of	of	ADP
ejpam-5934	209	58	the	the	DET
ejpam-5934	209	59	partition	partition	NOUN
ejpam-5934	209	60	u	u	X
ejpam-5934	209	61	d	d	NOUN
ejpam-5934	209	62	with	with	ADP
ejpam-5934	209	63	respect	respect	NOUN
ejpam-5934	209	64	to	to	ADP
ejpam-5934	209	65	c.	c.	NOUN
ejpam-5934	209	66	definition	definition	NOUN
ejpam-5934	209	67	of	of	ADP
ejpam-5934	209	68	the	the	DET
ejpam-5934	209	69	indiscernibility	indiscernibility	NOUN
ejpam-5934	209	70	relation	relation	PROPN
ejpam-5934	209	71	ind(p	ind(p	PROPN
ejpam-5934	209	72	)	)	PUNCT
ejpam-5934	209	73	is	be	AUX
ejpam-5934	209	74	shown	show	VERB
ejpam-5934	209	75	in	in	ADP
ejpam-5934	209	76	equation	equation	NOUN
ejpam-5934	209	77	(	(	PUNCT
ejpam-5934	209	78	7	7	NUM
ejpam-5934	209	79	)	)	PUNCT
ejpam-5934	209	80	.	.	PUNCT
ejpam-5934	210	1	ind(p	ind(p	NOUN
ejpam-5934	210	2	)	)	PUNCT
ejpam-5934	211	1	=	=	PRON
ejpam-5934	211	2	{	{	PUNCT
ejpam-5934	211	3	(	(	PUNCT
ejpam-5934	211	4	x	x	NOUN
ejpam-5934	211	5	,	,	PUNCT
ejpam-5934	211	6	y	y	NOUN
ejpam-5934	211	7	)	)	PUNCT
ejpam-5934	211	8	∈	∈	PROPN
ejpam-5934	211	9	u2|∀a	u2|∀a	PROPN
ejpam-5934	211	10	∈	∈	PROPN
ejpam-5934	211	11	p	p	NOUN
ejpam-5934	211	12	,	,	PUNCT
ejpam-5934	211	13	a(x	a(x	PROPN
ejpam-5934	211	14	)	)	PUNCT
ejpam-5934	211	15	=	=	SYM
ejpam-5934	211	16	a(y	a(y	PROPN
ejpam-5934	211	17	)	)	PUNCT
ejpam-5934	211	18	}	}	PUNCT
ejpam-5934	211	19	(	(	PUNCT
ejpam-5934	211	20	7	7	X
ejpam-5934	211	21	)	)	PUNCT
ejpam-5934	211	22	the	the	DET
ejpam-5934	211	23	minimum	minimum	NOUN
ejpam-5934	211	24	subset	subset	NOUN
ejpam-5934	211	25	of	of	ADP
ejpam-5934	211	26	attributes	attribute	NOUN
ejpam-5934	211	27	known	know	VERB
ejpam-5934	211	28	as	as	ADP
ejpam-5934	211	29	a	a	DET
ejpam-5934	211	30	reduct	reduct	NOUN
ejpam-5934	211	31	that	that	PRON
ejpam-5934	211	32	permits	permit	VERB
ejpam-5934	211	33	the	the	DET
ejpam-5934	211	34	same	same	ADJ
ejpam-5934	211	35	classification	classification	NOUN
ejpam-5934	211	36	of	of	ADP
ejpam-5934	211	37	universe	universe	NOUN
ejpam-5934	211	38	’s	’s	PART
ejpam-5934	211	39	elements	element	NOUN
ejpam-5934	211	40	as	as	SCONJ
ejpam-5934	211	41	the	the	DET
ejpam-5934	211	42	entire	entire	ADJ
ejpam-5934	211	43	set	set	NOUN
ejpam-5934	211	44	of	of	ADP
ejpam-5934	211	45	attributes	attribute	NOUN
ejpam-5934	211	46	is	be	AUX
ejpam-5934	211	47	known	know	VERB
ejpam-5934	211	48	as	as	ADP
ejpam-5934	211	49	a	a	DET
ejpam-5934	211	50	reduct	reduct	NOUN
ejpam-5934	211	51	where	where	SCONJ
ejpam-5934	211	52	if	if	SCONJ
ejpam-5934	211	53	i(p	i(p	NOUN
ejpam-5934	211	54	)	)	PUNCT
ejpam-5934	211	55	=	=	SYM
ejpam-5934	211	56	i(p	i(p	NOUN
ejpam-5934	211	57	−{a	−{a	NOUN
ejpam-5934	211	58	}	}	PUNCT
ejpam-5934	211	59	)	)	PUNCT
ejpam-5934	211	60	,	,	PUNCT
ejpam-5934	211	61	then	then	ADV
ejpam-5934	211	62	’	'	PUNCT
ejpam-5934	211	63	a	a	PRON
ejpam-5934	211	64	’	'	PUNCT
ejpam-5934	211	65	is	be	AUX
ejpam-5934	211	66	dispensable	dispensable	ADJ
ejpam-5934	211	67	in	in	ADP
ejpam-5934	211	68	p	p	NOUN
ejpam-5934	211	69	;	;	PUNCT
ejpam-5934	211	70	otherwise	otherwise	ADV
ejpam-5934	211	71	,	,	PUNCT
ejpam-5934	211	72	’	'	PUNCT
ejpam-5934	211	73	a	a	PRON
ejpam-5934	211	74	’	'	PUNCT
ejpam-5934	211	75	is	be	AUX
ejpam-5934	211	76	indispensable	indispensable	ADJ
ejpam-5934	211	77	in	in	ADP
ejpam-5934	211	78	p	p	PROPN
ejpam-5934	211	79	.	.	PUNCT
ejpam-5934	212	1	set	set	VERB
ejpam-5934	212	2	p	p	NOUN
ejpam-5934	212	3	is	be	AUX
ejpam-5934	212	4	independent	independent	ADJ
ejpam-5934	212	5	if	if	SCONJ
ejpam-5934	212	6	all	all	DET
ejpam-5934	212	7	its	its	PRON
ejpam-5934	212	8	attributes	attribute	NOUN
ejpam-5934	212	9	are	be	AUX
ejpam-5934	212	10	indispensable	indispensable	ADJ
ejpam-5934	212	11	.	.	PUNCT
ejpam-5934	213	1	subset	subset	VERB
ejpam-5934	214	1	p	p	X
ejpam-5934	214	2	′	′	NOUN
ejpam-5934	214	3	of	of	ADP
ejpam-5934	214	4	p	p	NOUN
ejpam-5934	214	5	is	be	AUX
ejpam-5934	214	6	a	a	DET
ejpam-5934	214	7	reduct	reduct	NOUN
ejpam-5934	214	8	of	of	ADP
ejpam-5934	214	9	p	p	PRON
ejpam-5934	214	10	if	if	SCONJ
ejpam-5934	214	11	p	p	ADJ
ejpam-5934	214	12	′	′	NOUN
ejpam-5934	214	13	is	be	AUX
ejpam-5934	214	14	independent	independent	ADJ
ejpam-5934	214	15	and	and	CCONJ
ejpam-5934	214	16	i(p	i(p	NOUN
ejpam-5934	214	17	′	′	NUM
ejpam-5934	214	18	)	)	PUNCT
ejpam-5934	215	1	=	=	SYM
ejpam-5934	215	2	i(p	i(p	NOUN
ejpam-5934	215	3	)	)	PUNCT
ejpam-5934	215	4	.	.	PUNCT
ejpam-5934	216	1	assume	assume	VERB
ejpam-5934	216	2	p	p	NOUN
ejpam-5934	216	3	is	be	AUX
ejpam-5934	216	4	a	a	DET
ejpam-5934	216	5	subset	subset	NOUN
ejpam-5934	216	6	of	of	ADP
ejpam-5934	216	7	a.	a.	NOUN
ejpam-5934	216	8	the	the	DET
ejpam-5934	216	9	combination	combination	NOUN
ejpam-5934	216	10	of	of	ADP
ejpam-5934	216	11	all	all	DET
ejpam-5934	216	12	the	the	DET
ejpam-5934	216	13	vital	vital	ADJ
ejpam-5934	216	14	attributes	attribute	NOUN
ejpam-5934	216	15	that	that	PRON
ejpam-5934	216	16	make	make	VERB
ejpam-5934	216	17	up	up	ADP
ejpam-5934	216	18	p	p	NOUN
ejpam-5934	216	19	is	be	AUX
ejpam-5934	216	20	its	its	PRON
ejpam-5934	216	21	core	core	NOUN
ejpam-5934	216	22	.	.	PUNCT
ejpam-5934	217	1	core	core	NOUN
ejpam-5934	217	2	is	be	AUX
ejpam-5934	217	3	the	the	DET
ejpam-5934	217	4	intersection	intersection	NOUN
ejpam-5934	217	5	of	of	ADP
ejpam-5934	217	6	all	all	DET
ejpam-5934	217	7	reducts	reduct	NOUN
ejpam-5934	217	8	as	as	SCONJ
ejpam-5934	217	9	shown	show	VERB
ejpam-5934	217	10	in	in	ADP
ejpam-5934	217	11	equation	equation	NOUN
ejpam-5934	217	12	(	(	PUNCT
ejpam-5934	217	13	8)	8)	NUM
ejpam-5934	217	14	.	.	PUNCT
ejpam-5934	217	15	core(p	core(p	NOUN
ejpam-5934	217	16	)	)	PUNCT
ejpam-5934	218	1	=	=	PUNCT
ejpam-5934	218	2	∩red(p	∩red(p	PRON
ejpam-5934	218	3	)	)	PUNCT
ejpam-5934	218	4	(	(	PUNCT
ejpam-5934	218	5	8)	8)	NUM
ejpam-5934	218	6	red(p	red(p	NOUN
ejpam-5934	218	7	)	)	PUNCT
ejpam-5934	218	8	denotes	denote	VERB
ejpam-5934	218	9	the	the	DET
ejpam-5934	218	10	set	set	NOUN
ejpam-5934	218	11	of	of	ADP
ejpam-5934	218	12	all	all	DET
ejpam-5934	218	13	reduct	reduct	NOUN
ejpam-5934	218	14	of	of	ADP
ejpam-5934	218	15	p	p	PROPN
ejpam-5934	218	16	.	.	PUNCT
ejpam-5934	219	1	numerous	numerous	ADJ
ejpam-5934	219	2	applications	application	NOUN
ejpam-5934	219	3	of	of	ADP
ejpam-5934	219	4	rst	rst	PROPN
ejpam-5934	219	5	have	have	AUX
ejpam-5934	219	6	shown	show	VERB
ejpam-5934	219	7	it	it	PRON
ejpam-5934	219	8	to	to	PART
ejpam-5934	219	9	be	be	AUX
ejpam-5934	219	10	effective	effective	ADJ
ejpam-5934	219	11	,	,	PUNCT
ejpam-5934	219	12	including	include	VERB
ejpam-5934	219	13	data	data	NOUN
ejpam-5934	219	14	reduction	reduction	NOUN
ejpam-5934	219	15	,	,	PUNCT
ejpam-5934	219	16	identifying	identify	VERB
ejpam-5934	219	17	hidden	hidden	ADJ
ejpam-5934	219	18	trends	trend	NOUN
ejpam-5934	219	19	in	in	ADP
ejpam-5934	219	20	data	datum	NOUN
ejpam-5934	219	21	,	,	PUNCT
ejpam-5934	219	22	assessing	assess	VERB
ejpam-5934	219	23	the	the	DET
ejpam-5934	219	24	significance	significance	NOUN
ejpam-5934	219	25	of	of	ADP
ejpam-5934	219	26	data	datum	NOUN
ejpam-5934	219	27	,	,	PUNCT
ejpam-5934	219	28	and	and	CCONJ
ejpam-5934	219	29	creating	create	VERB
ejpam-5934	219	30	sets	set	NOUN
ejpam-5934	219	31	of	of	ADP
ejpam-5934	219	32	decision	decision	NOUN
ejpam-5934	219	33	rules	rule	NOUN
ejpam-5934	219	34	based	base	VERB
ejpam-5934	219	35	on	on	ADP
ejpam-5934	219	36	data	datum	NOUN
ejpam-5934	219	37	.	.	PUNCT
ejpam-5934	220	1	t.	t.	PROPN
ejpam-5934	220	2	ashika	ashika	PROPN
ejpam-5934	220	3	,	,	PUNCT
ejpam-5934	220	4	g.	g.	PROPN
ejpam-5934	220	5	h.	h.	PROPN
ejpam-5934	220	6	grace	grace	PROPN
ejpam-5934	220	7	/	/	SYM
ejpam-5934	220	8	eur	eur	PROPN
ejpam-5934	220	9	.	.	PUNCT
ejpam-5934	221	1	j.	j.	PROPN
ejpam-5934	221	2	pure	pure	PROPN
ejpam-5934	221	3	appl	appl	PROPN
ejpam-5934	221	4	.	.	PROPN
ejpam-5934	221	5	math	math	PROPN
ejpam-5934	221	6	,	,	PUNCT
ejpam-5934	221	7	18	18	NUM
ejpam-5934	221	8	(	(	PUNCT
ejpam-5934	221	9	2	2	NUM
ejpam-5934	221	10	)	)	PUNCT
ejpam-5934	221	11	(	(	PUNCT
ejpam-5934	221	12	2025	2025	NUM
ejpam-5934	221	13	)	)	PUNCT
ejpam-5934	221	14	,	,	PUNCT
ejpam-5934	221	15	5934	5934	NUM
ejpam-5934	221	16	11	11	NUM
ejpam-5934	221	17	of	of	ADP
ejpam-5934	221	18	22	22	NUM
ejpam-5934	221	19	2.4.1	2.4.1	NUM
ejpam-5934	221	20	.	.	PUNCT
ejpam-5934	222	1	rst	rst	PROPN
ejpam-5934	222	2	qr	qr	PROPN
ejpam-5934	222	3	algorithm	algorithm	PROPN
ejpam-5934	222	4	qr	qr	PROPN
ejpam-5934	222	5	algorithm	algorithm	PROPN
ejpam-5934	223	1	[	[	X
ejpam-5934	223	2	29	29	NUM
ejpam-5934	223	3	]	]	PUNCT
ejpam-5934	223	4	constructs	construct	VERB
ejpam-5934	223	5	a	a	DET
ejpam-5934	223	6	reduct	reduct	NOUN
ejpam-5934	223	7	by	by	ADP
ejpam-5934	223	8	sequentially	sequentially	ADV
ejpam-5934	223	9	adding	add	VERB
ejpam-5934	223	10	those	those	DET
ejpam-5934	223	11	attributes	attribute	NOUN
ejpam-5934	223	12	that	that	PRON
ejpam-5934	223	13	most	most	ADV
ejpam-5934	223	14	significantly	significantly	ADV
ejpam-5934	223	15	enhance	enhance	VERB
ejpam-5934	223	16	the	the	DET
ejpam-5934	223	17	dependency	dependency	NOUN
ejpam-5934	223	18	degree	degree	NOUN
ejpam-5934	223	19	,	,	PUNCT
ejpam-5934	223	20	halting	halt	VERB
ejpam-5934	223	21	the	the	DET
ejpam-5934	223	22	process	process	NOUN
ejpam-5934	223	23	when	when	SCONJ
ejpam-5934	223	24	no	no	DET
ejpam-5934	223	25	further	further	ADJ
ejpam-5934	223	26	improvement	improvement	NOUN
ejpam-5934	223	27	is	be	AUX
ejpam-5934	223	28	observed	observe	VERB
ejpam-5934	223	29	.	.	PUNCT
ejpam-5934	224	1	because	because	SCONJ
ejpam-5934	224	2	it	it	PRON
ejpam-5934	224	3	is	be	AUX
ejpam-5934	224	4	computationally	computationally	ADV
ejpam-5934	224	5	impractical	impractical	ADJ
ejpam-5934	224	6	to	to	PART
ejpam-5934	224	7	evaluate	evaluate	VERB
ejpam-5934	224	8	all	all	DET
ejpam-5934	224	9	possible	possible	ADJ
ejpam-5934	224	10	feature	feature	NOUN
ejpam-5934	224	11	combinations	combination	NOUN
ejpam-5934	224	12	,	,	PUNCT
ejpam-5934	224	13	qr	qr	PROPN
ejpam-5934	224	14	adopts	adopt	VERB
ejpam-5934	224	15	a	a	DET
ejpam-5934	224	16	greedy	greedy	ADJ
ejpam-5934	224	17	strategy	strategy	NOUN
ejpam-5934	224	18	by	by	ADP
ejpam-5934	224	19	selecting	select	VERB
ejpam-5934	224	20	one	one	NUM
ejpam-5934	224	21	attribute	attribute	NOUN
ejpam-5934	224	22	at	at	ADP
ejpam-5934	224	23	a	a	DET
ejpam-5934	224	24	time	time	NOUN
ejpam-5934	224	25	for	for	ADP
ejpam-5934	224	26	inclusion	inclusion	NOUN
ejpam-5934	224	27	.	.	PUNCT
ejpam-5934	225	1	algorithm	algorithm	PROPN
ejpam-5934	225	2	1	1	NUM
ejpam-5934	225	3	provides	provide	VERB
ejpam-5934	225	4	the	the	DET
ejpam-5934	225	5	implementation	implementation	NOUN
ejpam-5934	225	6	of	of	ADP
ejpam-5934	225	7	the	the	DET
ejpam-5934	225	8	qr	qr	PROPN
ejpam-5934	225	9	approach	approach	NOUN
ejpam-5934	225	10	.	.	PUNCT
ejpam-5934	226	1	algorithm	algorithm	NOUN
ejpam-5934	226	2	1	1	NUM
ejpam-5934	226	3	:	:	PUNCT
ejpam-5934	226	4	qr	qr	NOUN
ejpam-5934	226	5	algorithm	algorithm	NOUN
ejpam-5934	226	6	input	input	NOUN
ejpam-5934	226	7	:	:	PUNCT
ejpam-5934	226	8	c	c	NOUN
ejpam-5934	226	9	:	:	PUNCT
ejpam-5934	227	1	set	set	VERB
ejpam-5934	227	2	of	of	ADP
ejpam-5934	227	3	all	all	DET
ejpam-5934	227	4	conditional	conditional	ADJ
ejpam-5934	227	5	attributes	attribute	NOUN
ejpam-5934	227	6	d	d	NOUN
ejpam-5934	227	7	:	:	PUNCT
ejpam-5934	228	1	set	set	VERB
ejpam-5934	228	2	of	of	ADP
ejpam-5934	228	3	decision	decision	NOUN
ejpam-5934	228	4	attribute	attribute	NOUN
ejpam-5934	228	5	output	output	NOUN
ejpam-5934	228	6	:	:	PUNCT
ejpam-5934	228	7	a	a	DET
ejpam-5934	228	8	:	:	PUNCT
ejpam-5934	228	9	minimal	minimal	ADJ
ejpam-5934	228	10	subset	subset	NOUN
ejpam-5934	228	11	of	of	ADP
ejpam-5934	228	12	c	c	PROPN
ejpam-5934	228	13	that	that	PRON
ejpam-5934	228	14	retains	retain	VERB
ejpam-5934	228	15	the	the	DET
ejpam-5934	228	16	same	same	ADJ
ejpam-5934	228	17	classification	classification	NOUN
ejpam-5934	228	18	power	power	NOUN
ejpam-5934	228	19	as	as	ADP
ejpam-5934	228	20	the	the	DET
ejpam-5934	228	21	full	full	ADJ
ejpam-5934	228	22	set	set	NOUN
ejpam-5934	228	23	of	of	ADP
ejpam-5934	228	24	attributes	attribute	NOUN
ejpam-5934	229	1	c	c	PROPN
ejpam-5934	229	2	w.	w.	PROPN
ejpam-5934	229	3	r.	r.	PROPN
ejpam-5934	229	4	t.	t.	PROPN
ejpam-5934	230	1	d	d	PROPN
ejpam-5934	230	2	step	step	NOUN
ejpam-5934	230	3	1	1	NUM
ejpam-5934	230	4	:	:	PUNCT
ejpam-5934	230	5	start	start	VERB
ejpam-5934	230	6	with	with	ADP
ejpam-5934	230	7	empty	empty	ADJ
ejpam-5934	230	8	set	set	NOUN
ejpam-5934	230	9	a	a	DET
ejpam-5934	230	10	a←	a←	NOUN
ejpam-5934	230	11	∅	∅	NOUN
ejpam-5934	230	12	step	step	NOUN
ejpam-5934	230	13	2	2	NUM
ejpam-5934	230	14	:	:	PUNCT
ejpam-5934	230	15	iterate	iterate	NOUN
ejpam-5934	230	16	until	until	ADP
ejpam-5934	230	17	the	the	DET
ejpam-5934	230	18	discernibility	discernibility	NOUN
ejpam-5934	230	19	measure	measure	NOUN
ejpam-5934	230	20	of	of	ADP
ejpam-5934	230	21	a	a	DET
ejpam-5934	230	22	equals	equal	VERB
ejpam-5934	230	23	to	to	ADP
ejpam-5934	230	24	c	c	NOUN
ejpam-5934	230	25	step	step	NOUN
ejpam-5934	230	26	3	3	NUM
ejpam-5934	230	27	:	:	PUNCT
ejpam-5934	230	28	repeat	repeat	VERB
ejpam-5934	230	29	until	until	ADP
ejpam-5934	230	30	γa(d	γa(d	NUM
ejpam-5934	230	31	)	)	PUNCT
ejpam-5934	230	32	=	=	SYM
ejpam-5934	231	1	γc(d	γc(d	NUM
ejpam-5934	231	2	)	)	PUNCT
ejpam-5934	231	3	step	step	NOUN
ejpam-5934	231	4	3.1	3.1	NUM
ejpam-5934	231	5	:	:	PUNCT
ejpam-5934	231	6	assign	assign	NOUN
ejpam-5934	231	7	t	t	PROPN
ejpam-5934	231	8	=	=	PUNCT
ejpam-5934	231	9	a	a	DET
ejpam-5934	231	10	step	step	NOUN
ejpam-5934	231	11	3.2	3.2	NUM
ejpam-5934	231	12	:	:	PUNCT
ejpam-5934	231	13	for	for	ADP
ejpam-5934	231	14	each	each	DET
ejpam-5934	231	15	x	x	SYM
ejpam-5934	231	16	∈	∈	PROPN
ejpam-5934	231	17	c	c	NOUN
ejpam-5934	231	18	−a	−a	NOUN
ejpam-5934	231	19	:	:	PUNCT
ejpam-5934	231	20	compute	compute	NOUN
ejpam-5934	231	21	,	,	PUNCT
ejpam-5934	231	22	γr(a∪{x})(d	γr(a∪{x})(d	PROPN
ejpam-5934	231	23	)	)	PUNCT
ejpam-5934	231	24	step	step	NOUN
ejpam-5934	231	25	3.3	3.3	NUM
ejpam-5934	231	26	:	:	PUNCT
ejpam-5934	231	27	if	if	SCONJ
ejpam-5934	231	28	γr(a∪{x})(d	γr(a∪{x})(d	NUM
ejpam-5934	231	29	)	)	PUNCT
ejpam-5934	231	30	>	>	X
ejpam-5934	231	31	γt	γt	PROPN
ejpam-5934	231	32	(	(	PUNCT
ejpam-5934	231	33	d	d	NOUN
ejpam-5934	231	34	)	)	PUNCT
ejpam-5934	231	35	,	,	PUNCT
ejpam-5934	231	36	update	update	NOUN
ejpam-5934	231	37	,	,	PUNCT
ejpam-5934	231	38	t	t	PROPN
ejpam-5934	231	39	←	←	PROPN
ejpam-5934	231	40	a	a	DET
ejpam-5934	231	41	∪	∪	X
ejpam-5934	231	42	{	{	PUNCT
ejpam-5934	231	43	x	x	NOUN
ejpam-5934	231	44	}	}	PUNCT
ejpam-5934	231	45	step	step	NOUN
ejpam-5934	231	46	3.4	3.4	NUM
ejpam-5934	231	47	:	:	PUNCT
ejpam-5934	231	48	set	set	VERB
ejpam-5934	231	49	a←	a←	PROPN
ejpam-5934	231	50	t	t	PROPN
ejpam-5934	231	51	step	step	NOUN
ejpam-5934	231	52	4	4	NUM
ejpam-5934	231	53	:	:	PUNCT
ejpam-5934	231	54	return	return	VERB
ejpam-5934	231	55	a	a	DET
ejpam-5934	231	56	where	where	SCONJ
ejpam-5934	231	57	,	,	PUNCT
ejpam-5934	231	58	γa(d)→	γa(d)→	NOUN
ejpam-5934	231	59	discernibility	discernibility	NOUN
ejpam-5934	231	60	of	of	ADP
ejpam-5934	231	61	a	a	DET
ejpam-5934	231	62	w.	w.	PROPN
ejpam-5934	231	63	r.	r.	PROPN
ejpam-5934	231	64	t.	t.	PROPN
ejpam-5934	232	1	d	d	PROPN
ejpam-5934	232	2	γc(d)→	γc(d)→	PROPN
ejpam-5934	232	3	discernibility	discernibility	NOUN
ejpam-5934	232	4	of	of	ADP
ejpam-5934	232	5	c	c	PROPN
ejpam-5934	232	6	w.	w.	PROPN
ejpam-5934	232	7	r.	r.	PROPN
ejpam-5934	232	8	t.	t.	PROPN
ejpam-5934	233	1	d	d	PROPN
ejpam-5934	233	2	a→	a→	PUNCT
ejpam-5934	233	3	set	set	VERB
ejpam-5934	233	4	of	of	ADP
ejpam-5934	233	5	selected	select	VERB
ejpam-5934	233	6	attributes	attribute	NOUN
ejpam-5934	233	7	t	t	PROPN
ejpam-5934	233	8	→	→	SYM
ejpam-5934	233	9	temporary	temporary	ADJ
ejpam-5934	233	10	set	set	NOUN
ejpam-5934	233	11	to	to	PART
ejpam-5934	233	12	evaluate	evaluate	VERB
ejpam-5934	233	13	attribute	attribute	NOUN
ejpam-5934	233	14	addition	addition	NOUN
ejpam-5934	233	15	2.5	2.5	NUM
ejpam-5934	233	16	.	.	PUNCT
ejpam-5934	234	1	models	model	NOUN
ejpam-5934	234	2	of	of	ADP
ejpam-5934	234	3	ml	ml	NOUN
ejpam-5934	234	4	for	for	ADP
ejpam-5934	234	5	the	the	DET
ejpam-5934	234	6	study	study	NOUN
ejpam-5934	234	7	,	,	PUNCT
ejpam-5934	234	8	several	several	ADJ
ejpam-5934	234	9	well	well	ADV
ejpam-5934	234	10	-	-	PUNCT
ejpam-5934	234	11	established	establish	VERB
ejpam-5934	234	12	ml	ml	NOUN
ejpam-5934	234	13	classifiers	classifier	NOUN
ejpam-5934	234	14	are	be	AUX
ejpam-5934	234	15	employed	employ	VERB
ejpam-5934	234	16	to	to	PART
ejpam-5934	234	17	evaluate	evaluate	VERB
ejpam-5934	234	18	the	the	DET
ejpam-5934	234	19	diverse	diverse	ADJ
ejpam-5934	234	20	datasets	dataset	NOUN
ejpam-5934	234	21	.	.	PUNCT
ejpam-5934	235	1	lr	lr	X
ejpam-5934	236	1	[	[	NOUN
ejpam-5934	236	2	30	30	NUM
ejpam-5934	236	3	]	]	PUNCT
ejpam-5934	236	4	was	be	AUX
ejpam-5934	236	5	chosen	choose	VERB
ejpam-5934	236	6	for	for	ADP
ejpam-5934	236	7	its	its	PRON
ejpam-5934	236	8	simplicity	simplicity	NOUN
ejpam-5934	236	9	in	in	ADP
ejpam-5934	236	10	modeling	model	VERB
ejpam-5934	236	11	binary	binary	ADJ
ejpam-5934	236	12	outcomes	outcome	NOUN
ejpam-5934	236	13	using	use	VERB
ejpam-5934	236	14	a	a	DET
ejpam-5934	236	15	logistic	logistic	ADJ
ejpam-5934	236	16	function	function	NOUN
ejpam-5934	236	17	,	,	PUNCT
ejpam-5934	236	18	while	while	SCONJ
ejpam-5934	236	19	knn	knn	PROPN
ejpam-5934	236	20	[	[	X
ejpam-5934	236	21	31	31	NUM
ejpam-5934	236	22	]	]	PUNCT
ejpam-5934	236	23	offers	offer	VERB
ejpam-5934	236	24	a	a	DET
ejpam-5934	236	25	non	non	ADJ
ejpam-5934	236	26	-	-	ADJ
ejpam-5934	236	27	parametric	parametric	ADJ
ejpam-5934	236	28	approach	approach	NOUN
ejpam-5934	236	29	based	base	VERB
ejpam-5934	236	30	on	on	ADP
ejpam-5934	236	31	euclidean	euclidean	ADJ
ejpam-5934	236	32	distance	distance	NOUN
ejpam-5934	236	33	to	to	PART
ejpam-5934	236	34	classify	classify	VERB
ejpam-5934	236	35	data	datum	NOUN
ejpam-5934	236	36	points	point	NOUN
ejpam-5934	236	37	.	.	PUNCT
ejpam-5934	237	1	svm	svm	PROPN
ejpam-5934	237	2	[	[	X
ejpam-5934	237	3	32	32	NUM
ejpam-5934	237	4	]	]	PUNCT
ejpam-5934	237	5	was	be	AUX
ejpam-5934	237	6	included	include	VERB
ejpam-5934	237	7	for	for	ADP
ejpam-5934	237	8	its	its	PRON
ejpam-5934	237	9	robust	robust	ADJ
ejpam-5934	237	10	ability	ability	NOUN
ejpam-5934	237	11	to	to	PART
ejpam-5934	237	12	find	find	VERB
ejpam-5934	237	13	optimal	optimal	ADJ
ejpam-5934	237	14	decision	decision	NOUN
ejpam-5934	237	15	boundaries	boundary	NOUN
ejpam-5934	237	16	,	,	PUNCT
ejpam-5934	237	17	and	and	CCONJ
ejpam-5934	237	18	its	its	PRON
ejpam-5934	237	19	extension	extension	NOUN
ejpam-5934	237	20	,	,	PUNCT
ejpam-5934	237	21	kernel	kernel	PROPN
ejpam-5934	237	22	svm	svm	PROPN
ejpam-5934	238	1	[	[	X
ejpam-5934	238	2	33	33	NUM
ejpam-5934	238	3	]	]	PUNCT
ejpam-5934	238	4	,	,	PUNCT
ejpam-5934	238	5	enables	enable	VERB
ejpam-5934	238	6	non	non	ADJ
ejpam-5934	238	7	-	-	ADJ
ejpam-5934	238	8	linear	linear	ADJ
ejpam-5934	238	9	classification	classification	NOUN
ejpam-5934	238	10	by	by	ADP
ejpam-5934	238	11	mapping	map	VERB
ejpam-5934	238	12	inputs	input	NOUN
ejpam-5934	238	13	into	into	ADP
ejpam-5934	238	14	high	high	ADJ
ejpam-5934	238	15	-	-	PUNCT
ejpam-5934	238	16	dimensional	dimensional	ADJ
ejpam-5934	238	17	feature	feature	NOUN
ejpam-5934	238	18	spaces	space	NOUN
ejpam-5934	238	19	.	.	PUNCT
ejpam-5934	239	1	additionally	additionally	ADV
ejpam-5934	239	2	,	,	PUNCT
ejpam-5934	239	3	nb	nb	PROPN
ejpam-5934	240	1	[	[	X
ejpam-5934	240	2	31	31	NUM
ejpam-5934	240	3	]	]	PUNCT
ejpam-5934	240	4	was	be	AUX
ejpam-5934	240	5	utilized	utilize	VERB
ejpam-5934	240	6	for	for	ADP
ejpam-5934	240	7	its	its	PRON
ejpam-5934	240	8	probabilistic	probabilistic	ADJ
ejpam-5934	240	9	framework	framework	NOUN
ejpam-5934	240	10	based	base	VERB
ejpam-5934	240	11	on	on	ADP
ejpam-5934	240	12	bayes	bayes	PROPN
ejpam-5934	240	13	’	'	PUNCT
ejpam-5934	240	14	theorem	theorem	NOUN
ejpam-5934	240	15	and	and	CCONJ
ejpam-5934	240	16	the	the	DET
ejpam-5934	240	17	assumption	assumption	NOUN
ejpam-5934	240	18	of	of	ADP
ejpam-5934	240	19	predictor	predictor	NOUN
ejpam-5934	240	20	independence	independence	NOUN
ejpam-5934	240	21	,	,	PUNCT
ejpam-5934	240	22	and	and	CCONJ
ejpam-5934	240	23	dt	dt	X
ejpam-5934	241	1	[	[	X
ejpam-5934	241	2	31	31	NUM
ejpam-5934	241	3	]	]	PUNCT
ejpam-5934	241	4	was	be	AUX
ejpam-5934	241	5	selected	select	VERB
ejpam-5934	241	6	for	for	ADP
ejpam-5934	241	7	its	its	PRON
ejpam-5934	241	8	clear	clear	ADJ
ejpam-5934	241	9	,	,	PUNCT
ejpam-5934	241	10	interpretable	interpretable	ADJ
ejpam-5934	241	11	structure	structure	NOUN
ejpam-5934	241	12	driven	drive	VERB
ejpam-5934	241	13	by	by	ADP
ejpam-5934	241	14	entropy	entropy	NOUN
ejpam-5934	241	15	measures	measure	NOUN
ejpam-5934	241	16	.	.	PUNCT
ejpam-5934	242	1	to	to	PART
ejpam-5934	242	2	further	far	ADV
ejpam-5934	242	3	enhance	enhance	VERB
ejpam-5934	242	4	prediction	prediction	NOUN
ejpam-5934	242	5	accuracy	accuracy	NOUN
ejpam-5934	242	6	and	and	CCONJ
ejpam-5934	242	7	address	address	NOUN
ejpam-5934	242	8	complex	complex	ADJ
ejpam-5934	242	9	patterns	pattern	NOUN
ejpam-5934	242	10	,	,	PUNCT
ejpam-5934	242	11	ensemble	ensemble	ADJ
ejpam-5934	242	12	methods	method	NOUN
ejpam-5934	242	13	such	such	ADJ
ejpam-5934	242	14	as	as	ADP
ejpam-5934	242	15	rf[34	rf[34	PROPN
ejpam-5934	242	16	]	]	PUNCT
ejpam-5934	242	17	.	.	PUNCT
ejpam-5934	243	1	these	these	DET
ejpam-5934	243	2	classifiers	classifier	NOUN
ejpam-5934	243	3	were	be	AUX
ejpam-5934	243	4	chosen	choose	VERB
ejpam-5934	243	5	for	for	ADP
ejpam-5934	243	6	their	their	PRON
ejpam-5934	243	7	complementary	complementary	ADJ
ejpam-5934	243	8	strengths	strength	NOUN
ejpam-5934	243	9	and	and	CCONJ
ejpam-5934	243	10	proven	prove	VERB
ejpam-5934	243	11	effectiveness	effectiveness	NOUN
ejpam-5934	243	12	in	in	ADP
ejpam-5934	243	13	tackling	tackle	VERB
ejpam-5934	243	14	varied	varied	ADJ
ejpam-5934	243	15	classification	classification	NOUN
ejpam-5934	243	16	challenges	challenge	NOUN
ejpam-5934	243	17	.	.	PUNCT
ejpam-5934	244	1	2.6	2.6	NUM
ejpam-5934	244	2	.	.	PUNCT
ejpam-5934	244	3	evaluation	evaluation	NOUN
ejpam-5934	244	4	metrics	metric	NOUN
ejpam-5934	244	5	evaluation	evaluation	NOUN
ejpam-5934	244	6	metrics	metric	NOUN
ejpam-5934	244	7	like	like	ADP
ejpam-5934	244	8	accuracy	accuracy	NOUN
ejpam-5934	244	9	,	,	PUNCT
ejpam-5934	244	10	precision	precision	NOUN
ejpam-5934	244	11	,	,	PUNCT
ejpam-5934	244	12	recall	recall	NOUN
ejpam-5934	244	13	,	,	PUNCT
ejpam-5934	244	14	f1	f1	NOUN
ejpam-5934	244	15	-	-	PUNCT
ejpam-5934	244	16	score	score	NOUN
ejpam-5934	244	17	,	,	PUNCT
ejpam-5934	244	18	and	and	CCONJ
ejpam-5934	244	19	mae	mae	PROPN
ejpam-5934	244	20	rate	rate	NOUN
ejpam-5934	244	21	are	be	AUX
ejpam-5934	244	22	used	use	VERB
ejpam-5934	244	23	to	to	PART
ejpam-5934	244	24	assess	assess	VERB
ejpam-5934	244	25	the	the	DET
ejpam-5934	244	26	effectiveness	effectiveness	NOUN
ejpam-5934	244	27	of	of	ADP
ejpam-5934	244	28	the	the	DET
ejpam-5934	244	29	suggested	suggest	VERB
ejpam-5934	244	30	approach	approach	NOUN
ejpam-5934	244	31	.	.	PUNCT
ejpam-5934	245	1	the	the	DET
ejpam-5934	245	2	percentage	percentage	NOUN
ejpam-5934	245	3	of	of	ADP
ejpam-5934	245	4	all	all	DET
ejpam-5934	245	5	subjects	subject	NOUN
ejpam-5934	245	6	t.	t.	NOUN
ejpam-5934	245	7	ashika	ashika	NOUN
ejpam-5934	245	8	,	,	PUNCT
ejpam-5934	245	9	g.	g.	PROPN
ejpam-5934	245	10	h.	h.	PROPN
ejpam-5934	245	11	grace	grace	PROPN
ejpam-5934	245	12	/	/	SYM
ejpam-5934	245	13	eur	eur	PROPN
ejpam-5934	245	14	.	.	PUNCT
ejpam-5934	246	1	j.	j.	PROPN
ejpam-5934	246	2	pure	pure	PROPN
ejpam-5934	246	3	appl	appl	PROPN
ejpam-5934	246	4	.	.	PROPN
ejpam-5934	246	5	math	math	PROPN
ejpam-5934	246	6	,	,	PUNCT
ejpam-5934	246	7	18	18	NUM
ejpam-5934	246	8	(	(	PUNCT
ejpam-5934	246	9	2	2	NUM
ejpam-5934	246	10	)	)	PUNCT
ejpam-5934	246	11	(	(	PUNCT
ejpam-5934	246	12	2025	2025	NUM
ejpam-5934	246	13	)	)	PUNCT
ejpam-5934	246	14	,	,	PUNCT
ejpam-5934	246	15	5934	5934	NUM
ejpam-5934	246	16	12	12	NUM
ejpam-5934	246	17	of	of	ADP
ejpam-5934	246	18	22	22	NUM
ejpam-5934	246	19	correctly	correctly	ADV
ejpam-5934	246	20	classified	classified	ADJ
ejpam-5934	246	21	is	be	AUX
ejpam-5934	246	22	known	know	VERB
ejpam-5934	246	23	as	as	ADP
ejpam-5934	246	24	accuracy	accuracy	NOUN
ejpam-5934	246	25	.	.	PUNCT
ejpam-5934	247	1	the	the	DET
ejpam-5934	247	2	percentage	percentage	NOUN
ejpam-5934	247	3	of	of	ADP
ejpam-5934	247	4	subjects	subject	NOUN
ejpam-5934	247	5	correctly	correctly	ADV
ejpam-5934	247	6	classified	classify	VERB
ejpam-5934	247	7	as	as	ADP
ejpam-5934	247	8	positive	positive	ADJ
ejpam-5934	247	9	out	out	ADP
ejpam-5934	247	10	of	of	ADP
ejpam-5934	247	11	all	all	DET
ejpam-5934	247	12	positive	positive	ADJ
ejpam-5934	247	13	subjects	subject	NOUN
ejpam-5934	247	14	is	be	AUX
ejpam-5934	247	15	known	know	VERB
ejpam-5934	247	16	as	as	ADP
ejpam-5934	247	17	precision	precision	NOUN
ejpam-5934	247	18	.	.	PUNCT
ejpam-5934	248	1	the	the	DET
ejpam-5934	248	2	recall	recall	NOUN
ejpam-5934	248	3	evaluates	evaluate	VERB
ejpam-5934	248	4	the	the	DET
ejpam-5934	248	5	model	model	NOUN
ejpam-5934	248	6	’s	’s	PART
ejpam-5934	248	7	ability	ability	NOUN
ejpam-5934	248	8	to	to	PART
ejpam-5934	248	9	recognize	recognize	VERB
ejpam-5934	248	10	positive	positive	ADJ
ejpam-5934	248	11	samples	sample	NOUN
ejpam-5934	248	12	.	.	PUNCT
ejpam-5934	249	1	a	a	DET
ejpam-5934	249	2	harmonic	harmonic	ADJ
ejpam-5934	249	3	mean	mean	NOUN
ejpam-5934	249	4	of	of	ADP
ejpam-5934	249	5	recall	recall	NOUN
ejpam-5934	249	6	and	and	CCONJ
ejpam-5934	249	7	precision	precision	NOUN
ejpam-5934	249	8	is	be	AUX
ejpam-5934	249	9	the	the	DET
ejpam-5934	249	10	f1	f1	NOUN
ejpam-5934	249	11	-	-	PUNCT
ejpam-5934	249	12	score	score	NOUN
ejpam-5934	249	13	.	.	PUNCT
ejpam-5934	250	1	a	a	DET
ejpam-5934	250	2	measure	measure	NOUN
ejpam-5934	250	3	of	of	ADP
ejpam-5934	250	4	errors	error	NOUN
ejpam-5934	250	5	between	between	ADP
ejpam-5934	250	6	paired	pair	VERB
ejpam-5934	250	7	observations	observation	NOUN
ejpam-5934	250	8	expressing	express	VERB
ejpam-5934	250	9	the	the	DET
ejpam-5934	250	10	same	same	ADJ
ejpam-5934	250	11	phenomenon	phenomenon	NOUN
ejpam-5934	250	12	is	be	AUX
ejpam-5934	250	13	called	call	VERB
ejpam-5934	250	14	mae	mae	PROPN
ejpam-5934	250	15	.	.	PUNCT
ejpam-5934	251	1	the	the	DET
ejpam-5934	251	2	formula	formula	NOUN
ejpam-5934	251	3	of	of	ADP
ejpam-5934	251	4	the	the	DET
ejpam-5934	251	5	evaluation	evaluation	NOUN
ejpam-5934	251	6	metrics	metric	NOUN
ejpam-5934	251	7	and	and	CCONJ
ejpam-5934	251	8	error	error	NOUN
ejpam-5934	251	9	rate	rate	NOUN
ejpam-5934	251	10	is	be	AUX
ejpam-5934	251	11	shown	show	VERB
ejpam-5934	251	12	in	in	ADP
ejpam-5934	251	13	table	table	NOUN
ejpam-5934	251	14	3	3	NUM
ejpam-5934	251	15	.	.	PUNCT
ejpam-5934	251	16	table	table	NOUN
ejpam-5934	251	17	3	3	NUM
ejpam-5934	251	18	:	:	PUNCT
ejpam-5934	251	19	formulae	formulae	NOUN
ejpam-5934	251	20	of	of	ADP
ejpam-5934	251	21	evaluation	evaluation	NOUN
ejpam-5934	251	22	metrics	metric	NOUN
ejpam-5934	251	23	and	and	CCONJ
ejpam-5934	251	24	error	error	NOUN
ejpam-5934	251	25	function	function	NOUN
ejpam-5934	251	26	s.	s.	PROPN
ejpam-5934	252	1	no	no	PRON
ejpam-5934	252	2	.	.	PUNCT
ejpam-5934	253	1	evaluation	evaluation	NOUN
ejpam-5934	253	2	metrics	metric	NOUN
ejpam-5934	253	3	formulae	formulae	VERB
ejpam-5934	253	4	1	1	NUM
ejpam-5934	253	5	accuracy	accuracy	NOUN
ejpam-5934	253	6	(	(	PUNCT
ejpam-5934	253	7	tp	tp	NOUN
ejpam-5934	253	8	+	+	CCONJ
ejpam-5934	253	9	tn	tn	PROPN
ejpam-5934	253	10	)	)	PUNCT
ejpam-5934	253	11	(	(	PUNCT
ejpam-5934	253	12	tp	tp	ADP
ejpam-5934	253	13	+	+	CCONJ
ejpam-5934	253	14	tn	tn	NOUN
ejpam-5934	254	1	+	+	CCONJ
ejpam-5934	254	2	fp	fp	PROPN
ejpam-5934	254	3	+	+	NUM
ejpam-5934	254	4	fn	fn	NOUN
ejpam-5934	254	5	)	)	PUNCT
ejpam-5934	254	6	2	2	NUM
ejpam-5934	254	7	precision	precision	NOUN
ejpam-5934	254	8	(	(	PUNCT
ejpam-5934	254	9	tp	tp	NOUN
ejpam-5934	254	10	)	)	PUNCT
ejpam-5934	254	11	(	(	PUNCT
ejpam-5934	254	12	tp	tp	ADP
ejpam-5934	254	13	+	+	X
ejpam-5934	254	14	fp	fp	X
ejpam-5934	254	15	)	)	PUNCT
ejpam-5934	254	16	3	3	NUM
ejpam-5934	254	17	recall	recall	NOUN
ejpam-5934	254	18	(	(	PUNCT
ejpam-5934	254	19	tp	tp	NOUN
ejpam-5934	254	20	)	)	PUNCT
ejpam-5934	254	21	(	(	PUNCT
ejpam-5934	254	22	tp	tp	X
ejpam-5934	254	23	+	+	CCONJ
ejpam-5934	254	24	fn	fn	X
ejpam-5934	254	25	)	)	PUNCT
ejpam-5934	254	26	4	4	NUM
ejpam-5934	254	27	f1	f1	NOUN
ejpam-5934	254	28	score	score	NOUN
ejpam-5934	254	29	2×recall	2×recall	NUM
ejpam-5934	254	30	×	×	NOUN
ejpam-5934	254	31	precision	precision	NOUN
ejpam-5934	254	32	recall	recall	NOUN
ejpam-5934	254	33	+	+	CCONJ
ejpam-5934	254	34	precision	precision	NOUN
ejpam-5934	254	35	5	5	NUM
ejpam-5934	254	36	mae	mae	PROPN
ejpam-5934	254	37	1	1	PROPN
ejpam-5934	254	38	n	n	PROPN
ejpam-5934	254	39	∑n	∑n	PROPN
ejpam-5934	254	40	i=1	i=1	PROPN
ejpam-5934	254	41	|yi	|yi	NUM
ejpam-5934	254	42	−	−	PROPN
ejpam-5934	254	43	xi|	xi|	NOUN
ejpam-5934	254	44	3	3	NUM
ejpam-5934	254	45	.	.	PUNCT
ejpam-5934	255	1	experimental	experimental	ADJ
ejpam-5934	255	2	results	result	NOUN
ejpam-5934	255	3	the	the	DET
ejpam-5934	255	4	study	study	NOUN
ejpam-5934	255	5	results	result	NOUN
ejpam-5934	255	6	include	include	VERB
ejpam-5934	255	7	the	the	DET
ejpam-5934	255	8	following	follow	VERB
ejpam-5934	255	9	steps	step	NOUN
ejpam-5934	255	10	:	:	PUNCT
ejpam-5934	255	11	feature	feature	NOUN
ejpam-5934	255	12	selection	selection	NOUN
ejpam-5934	255	13	using	use	VERB
ejpam-5934	255	14	rst	rst	PROPN
ejpam-5934	255	15	with	with	ADP
ejpam-5934	255	16	the	the	DET
ejpam-5934	255	17	qr	qr	PROPN
ejpam-5934	255	18	algorithm	algorithm	NOUN
ejpam-5934	255	19	,	,	PUNCT
ejpam-5934	255	20	classification	classification	NOUN
ejpam-5934	255	21	with	with	ADP
ejpam-5934	255	22	ml	ml	ADP
ejpam-5934	255	23	algorithms	algorithm	NOUN
ejpam-5934	255	24	using	use	VERB
ejpam-5934	255	25	the	the	DET
ejpam-5934	255	26	original	original	ADJ
ejpam-5934	255	27	features	feature	NOUN
ejpam-5934	255	28	,	,	PUNCT
ejpam-5934	255	29	classification	classification	NOUN
ejpam-5934	255	30	using	use	VERB
ejpam-5934	255	31	features	feature	NOUN
ejpam-5934	255	32	selected	select	VERB
ejpam-5934	255	33	by	by	ADP
ejpam-5934	255	34	rst	rst	PROPN
ejpam-5934	255	35	,	,	PUNCT
ejpam-5934	255	36	and	and	CCONJ
ejpam-5934	255	37	a	a	DET
ejpam-5934	255	38	comparison	comparison	NOUN
ejpam-5934	255	39	of	of	ADP
ejpam-5934	255	40	the	the	DET
ejpam-5934	255	41	results	result	NOUN
ejpam-5934	255	42	before	before	ADP
ejpam-5934	255	43	and	and	CCONJ
ejpam-5934	255	44	after	after	ADP
ejpam-5934	255	45	feature	feature	NOUN
ejpam-5934	255	46	selection	selection	NOUN
ejpam-5934	255	47	.	.	PUNCT
ejpam-5934	256	1	3.1	3.1	NUM
ejpam-5934	256	2	.	.	PUNCT
ejpam-5934	256	3	experimental	experimental	ADJ
ejpam-5934	256	4	setup	setup	NOUN
ejpam-5934	256	5	the	the	DET
ejpam-5934	256	6	experiments	experiment	NOUN
ejpam-5934	256	7	were	be	AUX
ejpam-5934	256	8	conducted	conduct	VERB
ejpam-5934	256	9	using	use	VERB
ejpam-5934	256	10	r	r	NOUN
ejpam-5934	256	11	programming	programming	NOUN
ejpam-5934	256	12	,	,	PUNCT
ejpam-5934	256	13	specifically	specifically	ADV
ejpam-5934	256	14	utilizing	utilize	VERB
ejpam-5934	256	15	the	the	DET
ejpam-5934	256	16	roughsets	roughset	NOUN
ejpam-5934	256	17	package	package	NOUN
ejpam-5934	256	18	for	for	ADP
ejpam-5934	256	19	feature	feature	NOUN
ejpam-5934	256	20	selection	selection	NOUN
ejpam-5934	256	21	.	.	PUNCT
ejpam-5934	257	1	model	model	NOUN
ejpam-5934	257	2	training	training	NOUN
ejpam-5934	257	3	was	be	AUX
ejpam-5934	257	4	performed	perform	VERB
ejpam-5934	257	5	in	in	ADP
ejpam-5934	257	6	google	google	PROPN
ejpam-5934	257	7	colab	colab	PROPN
ejpam-5934	257	8	,	,	PUNCT
ejpam-5934	257	9	a	a	DET
ejpam-5934	257	10	cloud	cloud	NOUN
ejpam-5934	257	11	-	-	PUNCT
ejpam-5934	257	12	based	base	VERB
ejpam-5934	257	13	jupyter	jupyter	ADJ
ejpam-5934	257	14	notebook	notebook	NOUN
ejpam-5934	257	15	environment	environment	NOUN
ejpam-5934	257	16	,	,	PUNCT
ejpam-5934	257	17	utilizing	utilize	VERB
ejpam-5934	257	18	pytorch	pytorch	NOUN
ejpam-5934	257	19	for	for	ADP
ejpam-5934	257	20	ml	ml	NOUN
ejpam-5934	257	21	implementation	implementation	NOUN
ejpam-5934	257	22	.	.	PUNCT
ejpam-5934	258	1	the	the	DET
ejpam-5934	258	2	system	system	NOUN
ejpam-5934	258	3	used	use	VERB
ejpam-5934	258	4	for	for	ADP
ejpam-5934	258	5	training	training	NOUN
ejpam-5934	258	6	was	be	AUX
ejpam-5934	258	7	equipped	equip	VERB
ejpam-5934	258	8	with	with	ADP
ejpam-5934	258	9	a	a	DET
ejpam-5934	258	10	12th	12th	ADJ
ejpam-5934	258	11	gen	gen	PROPN
ejpam-5934	258	12	intel	intel	PROPN
ejpam-5934	258	13	core	core	NOUN
ejpam-5934	258	14	i3	i3	NOUN
ejpam-5934	258	15	-	-	PUNCT
ejpam-5934	258	16	1215u	1215u	NUM
ejpam-5934	258	17	processor	processor	NOUN
ejpam-5934	258	18	(	(	PUNCT
ejpam-5934	258	19	1.20	1.20	NUM
ejpam-5934	258	20	ghz	ghz	NOUN
ejpam-5934	258	21	)	)	PUNCT
ejpam-5934	258	22	and	and	CCONJ
ejpam-5934	258	23	8	8	NUM
ejpam-5934	258	24	gb	gb	NOUN
ejpam-5934	258	25	ram	ram	NOUN
ejpam-5934	258	26	,	,	PUNCT
ejpam-5934	258	27	ensuring	ensure	VERB
ejpam-5934	258	28	efficient	efficient	ADJ
ejpam-5934	258	29	data	datum	NOUN
ejpam-5934	258	30	processing	processing	NOUN
ejpam-5934	258	31	and	and	CCONJ
ejpam-5934	258	32	optimal	optimal	ADJ
ejpam-5934	258	33	performance	performance	NOUN
ejpam-5934	258	34	across	across	ADP
ejpam-5934	258	35	the	the	DET
ejpam-5934	258	36	five	five	NUM
ejpam-5934	258	37	different	different	ADJ
ejpam-5934	258	38	datasets	dataset	NOUN
ejpam-5934	258	39	.	.	PUNCT
ejpam-5934	259	1	3.2	3.2	NUM
ejpam-5934	259	2	.	.	PUNCT
ejpam-5934	260	1	feature	feature	NOUN
ejpam-5934	260	2	selection	selection	NOUN
ejpam-5934	260	3	in	in	ADP
ejpam-5934	260	4	this	this	DET
ejpam-5934	260	5	study	study	NOUN
ejpam-5934	260	6	,	,	PUNCT
ejpam-5934	260	7	the	the	DET
ejpam-5934	260	8	qr	qr	ADJ
ejpam-5934	260	9	algorithm	algorithm	NOUN
ejpam-5934	260	10	of	of	ADP
ejpam-5934	260	11	rst	rst	PROPN
ejpam-5934	260	12	is	be	AUX
ejpam-5934	260	13	utilized	utilize	VERB
ejpam-5934	260	14	to	to	PART
ejpam-5934	260	15	determine	determine	VERB
ejpam-5934	260	16	the	the	DET
ejpam-5934	260	17	reducts	reduct	NOUN
ejpam-5934	260	18	,	,	PUNCT
ejpam-5934	260	19	enabling	enable	VERB
ejpam-5934	260	20	the	the	DET
ejpam-5934	260	21	selection	selection	NOUN
ejpam-5934	260	22	of	of	ADP
ejpam-5934	260	23	the	the	DET
ejpam-5934	260	24	most	most	ADV
ejpam-5934	260	25	relevant	relevant	ADJ
ejpam-5934	260	26	features	feature	NOUN
ejpam-5934	260	27	while	while	SCONJ
ejpam-5934	260	28	discarding	discard	VERB
ejpam-5934	260	29	irrelevant	irrelevant	ADJ
ejpam-5934	260	30	ones	one	NOUN
ejpam-5934	260	31	.	.	PUNCT
ejpam-5934	261	1	the	the	DET
ejpam-5934	261	2	seeds	seed	NOUN
ejpam-5934	261	3	dataset	dataset	VERB
ejpam-5934	261	4	was	be	AUX
ejpam-5934	261	5	reduced	reduce	VERB
ejpam-5934	261	6	from	from	ADP
ejpam-5934	261	7	7	7	NUM
ejpam-5934	261	8	attributes	attribute	NOUN
ejpam-5934	261	9	to	to	ADP
ejpam-5934	261	10	2	2	NUM
ejpam-5934	261	11	attributes	attribute	NOUN
ejpam-5934	261	12	.	.	PUNCT
ejpam-5934	262	1	the	the	DET
ejpam-5934	262	2	online	online	ADJ
ejpam-5934	262	3	food	food	NOUN
ejpam-5934	262	4	delivery	delivery	NOUN
ejpam-5934	262	5	dataset	dataset	NOUN
ejpam-5934	262	6	was	be	AUX
ejpam-5934	262	7	reduced	reduce	VERB
ejpam-5934	262	8	from	from	ADP
ejpam-5934	262	9	54	54	NUM
ejpam-5934	262	10	attributes	attribute	NOUN
ejpam-5934	262	11	to	to	ADP
ejpam-5934	262	12	4	4	NUM
ejpam-5934	262	13	attributes	attribute	NOUN
ejpam-5934	262	14	.	.	PUNCT
ejpam-5934	263	1	the	the	DET
ejpam-5934	263	2	heart	heart	NOUN
ejpam-5934	263	3	attack	attack	NOUN
ejpam-5934	263	4	dataset	dataset	NOUN
ejpam-5934	263	5	was	be	AUX
ejpam-5934	263	6	reduced	reduce	VERB
ejpam-5934	263	7	from	from	ADP
ejpam-5934	263	8	8	8	NUM
ejpam-5934	263	9	attributes	attribute	NOUN
ejpam-5934	263	10	to	to	ADP
ejpam-5934	263	11	2	2	NUM
ejpam-5934	263	12	attributes	attribute	NOUN
ejpam-5934	263	13	.	.	PUNCT
ejpam-5934	264	1	the	the	DET
ejpam-5934	264	2	obesity	obesity	NOUN
ejpam-5934	264	3	dataset	dataset	NOUN
ejpam-5934	264	4	was	be	AUX
ejpam-5934	264	5	reduced	reduce	VERB
ejpam-5934	264	6	from	from	ADP
ejpam-5934	264	7	6	6	NUM
ejpam-5934	264	8	attributes	attribute	NOUN
ejpam-5934	264	9	to	to	ADP
ejpam-5934	264	10	5	5	NUM
ejpam-5934	264	11	attributes	attribute	NOUN
ejpam-5934	264	12	.	.	PUNCT
ejpam-5934	265	1	the	the	DET
ejpam-5934	265	2	breast	breast	NOUN
ejpam-5934	265	3	cancer	cancer	NOUN
ejpam-5934	265	4	dataset	dataset	NOUN
ejpam-5934	265	5	was	be	AUX
ejpam-5934	265	6	reduced	reduce	VERB
ejpam-5934	265	7	from	from	ADP
ejpam-5934	265	8	8	8	NUM
ejpam-5934	265	9	attributes	attribute	NOUN
ejpam-5934	265	10	to	to	ADP
ejpam-5934	265	11	4	4	NUM
ejpam-5934	265	12	attributes	attribute	NOUN
ejpam-5934	265	13	.	.	PUNCT
ejpam-5934	266	1	the	the	DET
ejpam-5934	266	2	dataset	dataset	NOUN
ejpam-5934	266	3	before	before	ADP
ejpam-5934	266	4	reduction	reduction	NOUN
ejpam-5934	266	5	and	and	CCONJ
ejpam-5934	266	6	after	after	ADP
ejpam-5934	266	7	reduction	reduction	NOUN
ejpam-5934	266	8	is	be	AUX
ejpam-5934	266	9	shown	show	VERB
ejpam-5934	266	10	in	in	ADP
ejpam-5934	266	11	table	table	NOUN
ejpam-5934	266	12	4	4	NUM
ejpam-5934	266	13	.	.	PUNCT
ejpam-5934	267	1	t.	t.	ADJ
ejpam-5934	267	2	ashika	ashika	PROPN
ejpam-5934	267	3	,	,	PUNCT
ejpam-5934	267	4	g.	g.	PROPN
ejpam-5934	267	5	h.	h.	PROPN
ejpam-5934	267	6	grace	grace	PROPN
ejpam-5934	267	7	/	/	SYM
ejpam-5934	267	8	eur	eur	PROPN
ejpam-5934	267	9	.	.	PUNCT
ejpam-5934	268	1	j.	j.	PROPN
ejpam-5934	268	2	pure	pure	PROPN
ejpam-5934	268	3	appl	appl	PROPN
ejpam-5934	268	4	.	.	PROPN
ejpam-5934	268	5	math	math	PROPN
ejpam-5934	268	6	,	,	PUNCT
ejpam-5934	268	7	18	18	NUM
ejpam-5934	268	8	(	(	PUNCT
ejpam-5934	268	9	2	2	NUM
ejpam-5934	268	10	)	)	PUNCT
ejpam-5934	268	11	(	(	PUNCT
ejpam-5934	268	12	2025	2025	NUM
ejpam-5934	268	13	)	)	PUNCT
ejpam-5934	268	14	,	,	PUNCT
ejpam-5934	268	15	5934	5934	NUM
ejpam-5934	268	16	13	13	NUM
ejpam-5934	268	17	of	of	ADP
ejpam-5934	268	18	22	22	NUM
ejpam-5934	268	19	table	table	NOUN
ejpam-5934	268	20	4	4	NUM
ejpam-5934	268	21	:	:	PUNCT
ejpam-5934	268	22	list	list	NOUN
ejpam-5934	268	23	of	of	ADP
ejpam-5934	268	24	dataset	dataset	NOUN
ejpam-5934	268	25	along	along	ADP
ejpam-5934	268	26	with	with	ADP
ejpam-5934	268	27	attribute	attribute	NOUN
ejpam-5934	268	28	list	list	NOUN
ejpam-5934	268	29	before	before	ADP
ejpam-5934	268	30	and	and	CCONJ
ejpam-5934	268	31	after	after	ADP
ejpam-5934	268	32	reduction	reduction	NOUN
ejpam-5934	268	33	s.	s.	PROPN
ejpam-5934	269	1	no	no	DET
ejpam-5934	269	2	datasets	dataset	NOUN
ejpam-5934	269	3	no	no	INTJ
ejpam-5934	269	4	.	.	PUNCT
ejpam-5934	269	5	of	of	ADP
ejpam-5934	269	6	attributes	attribute	NOUN
ejpam-5934	269	7	before	before	ADP
ejpam-5934	269	8	no	no	INTJ
ejpam-5934	269	9	.	.	PUNCT
ejpam-5934	269	10	of	of	ADP
ejpam-5934	269	11	attributes	attribute	NOUN
ejpam-5934	269	12	after	after	ADP
ejpam-5934	269	13	reduction	reduction	NOUN
ejpam-5934	269	14	reduction	reduction	NOUN
ejpam-5934	269	15	1	1	NUM
ejpam-5934	269	16	seeds	seed	NOUN
ejpam-5934	269	17	7	7	NUM
ejpam-5934	269	18	2	2	NUM
ejpam-5934	269	19	2	2	NUM
ejpam-5934	269	20	online	online	ADJ
ejpam-5934	269	21	food	food	NOUN
ejpam-5934	269	22	delivery	delivery	NOUN
ejpam-5934	269	23	54	54	NUM
ejpam-5934	269	24	4	4	NUM
ejpam-5934	269	25	3	3	NUM
ejpam-5934	269	26	heart	heart	NOUN
ejpam-5934	269	27	attack	attack	NOUN
ejpam-5934	269	28	8	8	NUM
ejpam-5934	269	29	2	2	NUM
ejpam-5934	269	30	4	4	NUM
ejpam-5934	269	31	obesity	obesity	NOUN
ejpam-5934	269	32	6	6	NUM
ejpam-5934	269	33	5	5	NUM
ejpam-5934	269	34	5	5	NUM
ejpam-5934	269	35	breast	breast	NOUN
ejpam-5934	269	36	cancer	cancer	NOUN
ejpam-5934	269	37	8	8	NUM
ejpam-5934	269	38	4	4	NUM
ejpam-5934	269	39	3.3	3.3	NUM
ejpam-5934	269	40	.	.	PUNCT
ejpam-5934	270	1	classification	classification	NOUN
ejpam-5934	270	2	with	with	ADP
ejpam-5934	270	3	ml	ml	ADP
ejpam-5934	270	4	algorithms	algorithm	NOUN
ejpam-5934	270	5	using	use	VERB
ejpam-5934	270	6	original	original	ADJ
ejpam-5934	270	7	features	feature	NOUN
ejpam-5934	270	8	the	the	DET
ejpam-5934	270	9	original	original	ADJ
ejpam-5934	270	10	dataset	dataset	NOUN
ejpam-5934	270	11	is	be	AUX
ejpam-5934	270	12	pre	pre	ADJ
ejpam-5934	270	13	-	-	VERB
ejpam-5934	270	14	processed	processed	ADJ
ejpam-5934	270	15	and	and	CCONJ
ejpam-5934	270	16	then	then	ADV
ejpam-5934	270	17	evaluated	evaluate	VERB
ejpam-5934	270	18	using	use	VERB
ejpam-5934	270	19	various	various	ADJ
ejpam-5934	270	20	ml	ml	NOUN
ejpam-5934	270	21	classifiers	classifier	NOUN
ejpam-5934	270	22	like	like	ADP
ejpam-5934	270	23	lr	lr	PROPN
ejpam-5934	270	24	,	,	PUNCT
ejpam-5934	270	25	knn	knn	PROPN
ejpam-5934	270	26	,	,	PUNCT
ejpam-5934	270	27	svm	svm	PROPN
ejpam-5934	270	28	,	,	PUNCT
ejpam-5934	270	29	kernel	kernel	PROPN
ejpam-5934	270	30	svm	svm	PROPN
ejpam-5934	270	31	,	,	PUNCT
ejpam-5934	270	32	nb	nb	INTJ
ejpam-5934	270	33	,	,	PUNCT
ejpam-5934	270	34	dt	dt	X
ejpam-5934	270	35	,	,	PUNCT
ejpam-5934	270	36	and	and	CCONJ
ejpam-5934	270	37	rf	rf	NOUN
ejpam-5934	270	38	.	.	PUNCT
ejpam-5934	271	1	the	the	DET
ejpam-5934	271	2	model	model	NOUN
ejpam-5934	271	3	’s	’s	PART
ejpam-5934	271	4	performance	performance	NOUN
ejpam-5934	271	5	is	be	AUX
ejpam-5934	271	6	assessed	assess	VERB
ejpam-5934	271	7	using	use	VERB
ejpam-5934	271	8	evaluation	evaluation	NOUN
ejpam-5934	271	9	metrics	metric	NOUN
ejpam-5934	271	10	.	.	PUNCT
ejpam-5934	272	1	figure	figure	NOUN
ejpam-5934	272	2	2	2	NUM
ejpam-5934	272	3	shows	show	VERB
ejpam-5934	272	4	that	that	SCONJ
ejpam-5934	272	5	certain	certain	ADJ
ejpam-5934	272	6	algorithms	algorithm	NOUN
ejpam-5934	272	7	perform	perform	VERB
ejpam-5934	272	8	best	well	ADV
ejpam-5934	272	9	across	across	ADP
ejpam-5934	272	10	different	different	ADJ
ejpam-5934	272	11	datasets	dataset	NOUN
ejpam-5934	272	12	:	:	PUNCT
ejpam-5934	272	13	svm	svm	PROPN
ejpam-5934	272	14	works	work	VERB
ejpam-5934	272	15	well	well	ADV
ejpam-5934	272	16	for	for	ADP
ejpam-5934	272	17	seeds	seed	NOUN
ejpam-5934	272	18	,	,	PUNCT
ejpam-5934	272	19	while	while	SCONJ
ejpam-5934	272	20	dt	dt	PROPN
ejpam-5934	272	21	and	and	CCONJ
ejpam-5934	272	22	rf	rf	PRON
ejpam-5934	272	23	are	be	AUX
ejpam-5934	272	24	effective	effective	ADJ
ejpam-5934	272	25	for	for	ADP
ejpam-5934	272	26	heart	heart	NOUN
ejpam-5934	272	27	attack	attack	NOUN
ejpam-5934	272	28	and	and	CCONJ
ejpam-5934	272	29	obesity	obesity	NOUN
ejpam-5934	272	30	.	.	PUNCT
ejpam-5934	273	1	in	in	ADP
ejpam-5934	273	2	online	online	ADJ
ejpam-5934	273	3	food	food	NOUN
ejpam-5934	273	4	delivery	delivery	NOUN
ejpam-5934	273	5	,	,	PUNCT
ejpam-5934	273	6	lr	lr	NOUN
ejpam-5934	273	7	,	,	PUNCT
ejpam-5934	273	8	svm	svm	PROPN
ejpam-5934	273	9	,	,	PUNCT
ejpam-5934	273	10	kernel	kernel	PROPN
ejpam-5934	273	11	svm	svm	PROPN
ejpam-5934	273	12	,	,	PUNCT
ejpam-5934	273	13	nb	nb	INTJ
ejpam-5934	273	14	,	,	PUNCT
ejpam-5934	273	15	and	and	CCONJ
ejpam-5934	273	16	rf	rf	NOUN
ejpam-5934	273	17	shows	show	VERB
ejpam-5934	273	18	similar	similar	ADJ
ejpam-5934	273	19	performance	performance	NOUN
ejpam-5934	273	20	,	,	PUNCT
ejpam-5934	273	21	and	and	CCONJ
ejpam-5934	273	22	nb	nb	PROPN
ejpam-5934	273	23	yields	yield	VERB
ejpam-5934	273	24	the	the	DET
ejpam-5934	273	25	best	good	ADJ
ejpam-5934	273	26	results	result	NOUN
ejpam-5934	273	27	in	in	ADP
ejpam-5934	273	28	breast	breast	NOUN
ejpam-5934	273	29	cancer	cancer	NOUN
ejpam-5934	273	30	.	.	PUNCT
ejpam-5934	274	1	figure	figure	NOUN
ejpam-5934	274	2	2	2	NUM
ejpam-5934	274	3	:	:	PUNCT
ejpam-5934	274	4	ml	ml	ADP
ejpam-5934	274	5	algorithm	algorithm	NOUN
ejpam-5934	274	6	performance	performance	NOUN
ejpam-5934	274	7	with	with	ADP
ejpam-5934	274	8	original	original	ADJ
ejpam-5934	274	9	features	feature	NOUN
ejpam-5934	274	10	across	across	ADP
ejpam-5934	274	11	datasets	dataset	NOUN
ejpam-5934	274	12	t.	t.	NOUN
ejpam-5934	274	13	ashika	ashika	NOUN
ejpam-5934	274	14	,	,	PUNCT
ejpam-5934	274	15	g.	g.	PROPN
ejpam-5934	274	16	h.	h.	PROPN
ejpam-5934	274	17	grace	grace	PROPN
ejpam-5934	274	18	/	/	SYM
ejpam-5934	274	19	eur	eur	PROPN
ejpam-5934	274	20	.	.	PUNCT
ejpam-5934	275	1	j.	j.	PROPN
ejpam-5934	275	2	pure	pure	PROPN
ejpam-5934	275	3	appl	appl	PROPN
ejpam-5934	275	4	.	.	PROPN
ejpam-5934	275	5	math	math	PROPN
ejpam-5934	275	6	,	,	PUNCT
ejpam-5934	275	7	18	18	NUM
ejpam-5934	275	8	(	(	PUNCT
ejpam-5934	275	9	2	2	NUM
ejpam-5934	275	10	)	)	PUNCT
ejpam-5934	275	11	(	(	PUNCT
ejpam-5934	275	12	2025	2025	NUM
ejpam-5934	275	13	)	)	PUNCT
ejpam-5934	275	14	,	,	PUNCT
ejpam-5934	275	15	5934	5934	NUM
ejpam-5934	275	16	14	14	NUM
ejpam-5934	275	17	of	of	ADP
ejpam-5934	275	18	22	22	NUM
ejpam-5934	275	19	3.4	3.4	NUM
ejpam-5934	275	20	.	.	PUNCT
ejpam-5934	276	1	classification	classification	NOUN
ejpam-5934	276	2	with	with	ADP
ejpam-5934	276	3	ml	ml	ADP
ejpam-5934	276	4	algorithms	algorithm	NOUN
ejpam-5934	276	5	using	use	VERB
ejpam-5934	276	6	features	feature	NOUN
ejpam-5934	276	7	selected	select	VERB
ejpam-5934	276	8	by	by	ADP
ejpam-5934	276	9	rst	rst	NOUN
ejpam-5934	276	10	this	this	DET
ejpam-5934	276	11	section	section	NOUN
ejpam-5934	276	12	discusses	discuss	VERB
ejpam-5934	276	13	the	the	DET
ejpam-5934	276	14	performance	performance	NOUN
ejpam-5934	276	15	evaluation	evaluation	NOUN
ejpam-5934	276	16	after	after	ADP
ejpam-5934	276	17	applying	apply	VERB
ejpam-5934	276	18	rst	rst	NOUN
ejpam-5934	276	19	feature	feature	NOUN
ejpam-5934	276	20	selection	selection	NOUN
ejpam-5934	276	21	,	,	PUNCT
ejpam-5934	276	22	focusing	focus	VERB
ejpam-5934	276	23	on	on	ADP
ejpam-5934	276	24	the	the	DET
ejpam-5934	276	25	performance	performance	NOUN
ejpam-5934	276	26	of	of	ADP
ejpam-5934	276	27	selected	select	VERB
ejpam-5934	276	28	features	feature	NOUN
ejpam-5934	276	29	.	.	PUNCT
ejpam-5934	277	1	from	from	ADP
ejpam-5934	277	2	figure	figure	NOUN
ejpam-5934	277	3	3	3	NUM
ejpam-5934	277	4	,	,	PUNCT
ejpam-5934	277	5	it	it	PRON
ejpam-5934	277	6	is	be	AUX
ejpam-5934	277	7	evident	evident	ADJ
ejpam-5934	277	8	that	that	SCONJ
ejpam-5934	277	9	after	after	ADP
ejpam-5934	277	10	applying	apply	VERB
ejpam-5934	277	11	rst	rst	VERB
ejpam-5934	277	12	-	-	PUNCT
ejpam-5934	277	13	selected	select	VERB
ejpam-5934	277	14	features	feature	NOUN
ejpam-5934	277	15	,	,	PUNCT
ejpam-5934	277	16	lr	lr	NOUN
ejpam-5934	277	17	,	,	PUNCT
ejpam-5934	277	18	svm	svm	ADJ
ejpam-5934	277	19	,	,	PUNCT
ejpam-5934	277	20	and	and	CCONJ
ejpam-5934	277	21	kernel	kernel	PROPN
ejpam-5934	277	22	svm	svm	PROPN
ejpam-5934	277	23	perform	perform	VERB
ejpam-5934	277	24	well	well	ADV
ejpam-5934	277	25	for	for	SCONJ
ejpam-5934	277	26	the	the	DET
ejpam-5934	277	27	seeds	seed	NOUN
ejpam-5934	277	28	dataset	dataset	VERB
ejpam-5934	277	29	;	;	PUNCT
ejpam-5934	277	30	rf	rf	PRON
ejpam-5934	277	31	achieves	achieve	VERB
ejpam-5934	277	32	the	the	DET
ejpam-5934	277	33	best	good	ADJ
ejpam-5934	277	34	performance	performance	NOUN
ejpam-5934	277	35	for	for	ADP
ejpam-5934	277	36	heart	heart	NOUN
ejpam-5934	277	37	attack	attack	NOUN
ejpam-5934	277	38	;	;	PUNCT
ejpam-5934	277	39	dt	dt	PROPN
ejpam-5934	277	40	is	be	AUX
ejpam-5934	277	41	most	most	ADV
ejpam-5934	277	42	effective	effective	ADJ
ejpam-5934	277	43	for	for	ADP
ejpam-5934	277	44	obesity	obesity	NOUN
ejpam-5934	277	45	;	;	PUNCT
ejpam-5934	277	46	knn	knn	PROPN
ejpam-5934	277	47	,	,	PUNCT
ejpam-5934	277	48	kernel	kernel	PROPN
ejpam-5934	277	49	svm	svm	PROPN
ejpam-5934	277	50	,	,	PUNCT
ejpam-5934	277	51	and	and	CCONJ
ejpam-5934	277	52	dt	dt	VERB
ejpam-5934	277	53	perform	perform	VERB
ejpam-5934	277	54	well	well	ADV
ejpam-5934	277	55	for	for	ADP
ejpam-5934	277	56	online	online	ADJ
ejpam-5934	277	57	food	food	NOUN
ejpam-5934	277	58	delivery	delivery	NOUN
ejpam-5934	277	59	;	;	PUNCT
ejpam-5934	277	60	and	and	CCONJ
ejpam-5934	277	61	knn	knn	PROPN
ejpam-5934	277	62	yields	yield	VERB
ejpam-5934	277	63	the	the	DET
ejpam-5934	277	64	best	good	ADJ
ejpam-5934	277	65	results	result	NOUN
ejpam-5934	277	66	for	for	ADP
ejpam-5934	277	67	breast	breast	NOUN
ejpam-5934	277	68	cancer	cancer	NOUN
ejpam-5934	277	69	.	.	PUNCT
ejpam-5934	278	1	figure	figure	VERB
ejpam-5934	278	2	3	3	NUM
ejpam-5934	278	3	:	:	PUNCT
ejpam-5934	278	4	ml	ml	ADP
ejpam-5934	278	5	algorithm	algorithm	NOUN
ejpam-5934	278	6	performance	performance	NOUN
ejpam-5934	278	7	with	with	ADP
ejpam-5934	278	8	rst	rst	VERB
ejpam-5934	278	9	-	-	PUNCT
ejpam-5934	278	10	selected	select	VERB
ejpam-5934	278	11	features	feature	NOUN
ejpam-5934	278	12	across	across	ADP
ejpam-5934	278	13	different	different	ADJ
ejpam-5934	278	14	datasets	dataset	NOUN
ejpam-5934	278	15	3.5	3.5	NUM
ejpam-5934	278	16	.	.	PUNCT
ejpam-5934	279	1	comparison	comparison	NOUN
ejpam-5934	279	2	of	of	ADP
ejpam-5934	279	3	results	result	NOUN
ejpam-5934	279	4	before	before	ADP
ejpam-5934	279	5	and	and	CCONJ
ejpam-5934	279	6	after	after	ADP
ejpam-5934	279	7	feature	feature	NOUN
ejpam-5934	279	8	selection	selection	NOUN
ejpam-5934	279	9	using	use	VERB
ejpam-5934	279	10	rst	rst	NOUN
ejpam-5934	279	11	this	this	DET
ejpam-5934	279	12	section	section	NOUN
ejpam-5934	279	13	discusses	discuss	VERB
ejpam-5934	279	14	the	the	DET
ejpam-5934	279	15	performance	performance	NOUN
ejpam-5934	279	16	changes	change	NOUN
ejpam-5934	279	17	after	after	ADP
ejpam-5934	279	18	applying	apply	VERB
ejpam-5934	279	19	rst	rst	NOUN
ejpam-5934	279	20	feature	feature	NOUN
ejpam-5934	279	21	selection	selection	NOUN
ejpam-5934	279	22	.	.	PUNCT
ejpam-5934	280	1	by	by	ADP
ejpam-5934	280	2	comparing	compare	VERB
ejpam-5934	280	3	the	the	DET
ejpam-5934	280	4	results	result	NOUN
ejpam-5934	280	5	before	before	ADP
ejpam-5934	280	6	and	and	CCONJ
ejpam-5934	280	7	after	after	ADP
ejpam-5934	280	8	feature	feature	NOUN
ejpam-5934	280	9	selection	selection	NOUN
ejpam-5934	280	10	,	,	PUNCT
ejpam-5934	280	11	the	the	DET
ejpam-5934	280	12	study	study	NOUN
ejpam-5934	280	13	evaluate	evaluate	VERB
ejpam-5934	280	14	how	how	SCONJ
ejpam-5934	280	15	rst	rst	PROPN
ejpam-5934	280	16	affects	affect	VERB
ejpam-5934	280	17	classification	classification	NOUN
ejpam-5934	280	18	accuracy	accuracy	NOUN
ejpam-5934	280	19	,	,	PUNCT
ejpam-5934	280	20	precision	precision	NOUN
ejpam-5934	280	21	,	,	PUNCT
ejpam-5934	280	22	recall	recall	NOUN
ejpam-5934	280	23	,	,	PUNCT
ejpam-5934	280	24	and	and	CCONJ
ejpam-5934	280	25	other	other	ADJ
ejpam-5934	280	26	metrics	metric	NOUN
ejpam-5934	280	27	across	across	ADP
ejpam-5934	280	28	various	various	ADJ
ejpam-5934	280	29	ml	ml	NOUN
ejpam-5934	280	30	algorithms	algorithm	NOUN
ejpam-5934	280	31	.	.	PUNCT
ejpam-5934	281	1	this	this	DET
ejpam-5934	281	2	analysis	analysis	NOUN
ejpam-5934	281	3	showcases	showcase	VERB
ejpam-5934	281	4	how	how	SCONJ
ejpam-5934	281	5	reducing	reduce	VERB
ejpam-5934	281	6	the	the	DET
ejpam-5934	281	7	feature	feature	NOUN
ejpam-5934	281	8	set	set	VERB
ejpam-5934	281	9	to	to	ADP
ejpam-5934	281	10	the	the	DET
ejpam-5934	281	11	most	most	ADV
ejpam-5934	281	12	relevant	relevant	ADJ
ejpam-5934	281	13	attributes	attribute	NOUN
ejpam-5934	281	14	can	can	AUX
ejpam-5934	281	15	improve	improve	VERB
ejpam-5934	281	16	model	model	NOUN
ejpam-5934	281	17	performance	performance	NOUN
ejpam-5934	281	18	and	and	CCONJ
ejpam-5934	281	19	efficiency	efficiency	NOUN
ejpam-5934	281	20	.	.	PUNCT
ejpam-5934	282	1	t.	t.	ADJ
ejpam-5934	282	2	ashika	ashika	PROPN
ejpam-5934	282	3	,	,	PUNCT
ejpam-5934	282	4	g.	g.	PROPN
ejpam-5934	282	5	h.	h.	PROPN
ejpam-5934	282	6	grace	grace	PROPN
ejpam-5934	282	7	/	/	SYM
ejpam-5934	282	8	eur	eur	PROPN
ejpam-5934	282	9	.	.	PUNCT
ejpam-5934	283	1	j.	j.	PROPN
ejpam-5934	283	2	pure	pure	PROPN
ejpam-5934	283	3	appl	appl	PROPN
ejpam-5934	283	4	.	.	PROPN
ejpam-5934	283	5	math	math	PROPN
ejpam-5934	283	6	,	,	PUNCT
ejpam-5934	283	7	18	18	NUM
ejpam-5934	283	8	(	(	PUNCT
ejpam-5934	283	9	2	2	NUM
ejpam-5934	283	10	)	)	PUNCT
ejpam-5934	283	11	(	(	PUNCT
ejpam-5934	283	12	2025	2025	NUM
ejpam-5934	283	13	)	)	PUNCT
ejpam-5934	283	14	,	,	PUNCT
ejpam-5934	283	15	5934	5934	NUM
ejpam-5934	283	16	15	15	NUM
ejpam-5934	283	17	of	of	ADP
ejpam-5934	283	18	22	22	NUM
ejpam-5934	283	19	3.5.1	3.5.1	NUM
ejpam-5934	283	20	.	.	PUNCT
ejpam-5934	284	1	seeds	seed	NOUN
ejpam-5934	284	2	dataset	dataset	VERB
ejpam-5934	284	3	table	table	NOUN
ejpam-5934	284	4	5	5	NUM
ejpam-5934	284	5	,	,	PUNCT
ejpam-5934	284	6	shows	show	VERB
ejpam-5934	284	7	that	that	SCONJ
ejpam-5934	284	8	applying	apply	VERB
ejpam-5934	284	9	rst	rst	PROPN
ejpam-5934	284	10	for	for	ADP
ejpam-5934	284	11	feature	feature	NOUN
ejpam-5934	284	12	selection	selection	NOUN
ejpam-5934	284	13	for	for	ADP
ejpam-5934	284	14	the	the	DET
ejpam-5934	284	15	seeds	seed	NOUN
ejpam-5934	284	16	dataset	dataset	VERB
ejpam-5934	284	17	results	result	NOUN
ejpam-5934	284	18	enhances	enhance	VERB
ejpam-5934	284	19	model	model	NOUN
ejpam-5934	284	20	performance	performance	NOUN
ejpam-5934	284	21	across	across	ADP
ejpam-5934	284	22	metrics	metric	NOUN
ejpam-5934	284	23	,	,	PUNCT
ejpam-5934	284	24	with	with	SCONJ
ejpam-5934	284	25	substantial	substantial	ADJ
ejpam-5934	284	26	gains	gain	NOUN
ejpam-5934	284	27	observed	observe	VERB
ejpam-5934	284	28	in	in	ADP
ejpam-5934	284	29	models	model	NOUN
ejpam-5934	284	30	such	such	ADJ
ejpam-5934	284	31	as	as	ADP
ejpam-5934	284	32	lr	lr	PROPN
ejpam-5934	284	33	,	,	PUNCT
ejpam-5934	284	34	svm	svm	ADJ
ejpam-5934	284	35	,	,	PUNCT
ejpam-5934	284	36	and	and	CCONJ
ejpam-5934	284	37	kernel	kernel	PROPN
ejpam-5934	284	38	svm	svm	PROPN
ejpam-5934	284	39	,	,	PUNCT
ejpam-5934	284	40	where	where	SCONJ
ejpam-5934	284	41	accuracy	accuracy	NOUN
ejpam-5934	284	42	,	,	PUNCT
ejpam-5934	284	43	precision	precision	NOUN
ejpam-5934	284	44	,	,	PUNCT
ejpam-5934	284	45	recall	recall	NOUN
ejpam-5934	284	46	,	,	PUNCT
ejpam-5934	284	47	and	and	CCONJ
ejpam-5934	284	48	f1	f1	NOUN
ejpam-5934	284	49	scores	score	NOUN
ejpam-5934	284	50	all	all	PRON
ejpam-5934	284	51	increase	increase	VERB
ejpam-5934	284	52	significantly	significantly	ADV
ejpam-5934	284	53	.	.	PUNCT
ejpam-5934	285	1	while	while	SCONJ
ejpam-5934	285	2	rf	rf	NOUN
ejpam-5934	285	3	shows	show	VERB
ejpam-5934	285	4	only	only	ADV
ejpam-5934	285	5	a	a	DET
ejpam-5934	285	6	slight	slight	ADJ
ejpam-5934	285	7	improvement	improvement	NOUN
ejpam-5934	285	8	,	,	PUNCT
ejpam-5934	285	9	most	most	ADJ
ejpam-5934	285	10	other	other	ADJ
ejpam-5934	285	11	models	model	NOUN
ejpam-5934	285	12	benefit	benefit	VERB
ejpam-5934	285	13	notably	notably	ADV
ejpam-5934	285	14	from	from	ADP
ejpam-5934	285	15	the	the	DET
ejpam-5934	285	16	refined	refined	ADJ
ejpam-5934	285	17	feature	feature	NOUN
ejpam-5934	285	18	set	set	NOUN
ejpam-5934	285	19	,	,	PUNCT
ejpam-5934	285	20	confirming	confirm	VERB
ejpam-5934	285	21	the	the	DET
ejpam-5934	285	22	effectiveness	effectiveness	NOUN
ejpam-5934	285	23	of	of	ADP
ejpam-5934	285	24	rst	rst	PROPN
ejpam-5934	285	25	in	in	ADP
ejpam-5934	285	26	boosting	boost	VERB
ejpam-5934	285	27	classification	classification	NOUN
ejpam-5934	285	28	metrics	metric	NOUN
ejpam-5934	285	29	.	.	PUNCT
ejpam-5934	286	1	table	table	NOUN
ejpam-5934	286	2	5	5	NUM
ejpam-5934	286	3	:	:	PUNCT
ejpam-5934	286	4	different	different	ADJ
ejpam-5934	286	5	ml	ml	NOUN
ejpam-5934	286	6	algorithms	algorithm	NOUN
ejpam-5934	286	7	on	on	ADP
ejpam-5934	286	8	seeds	seed	NOUN
ejpam-5934	286	9	dataset	dataset	VERB
ejpam-5934	286	10	ml	ml	NOUN
ejpam-5934	286	11	model	model	NOUN
ejpam-5934	286	12	accuracy	accuracy	PROPN
ejpam-5934	286	13	precision	precision	NOUN
ejpam-5934	286	14	recall	recall	NOUN
ejpam-5934	286	15	f1	f1	PROPN
ejpam-5934	286	16	score	score	NOUN
ejpam-5934	286	17	mae	mae	PROPN
ejpam-5934	286	18	before	before	ADP
ejpam-5934	286	19	rst	rst	PROPN
ejpam-5934	286	20	after	after	ADP
ejpam-5934	286	21	rst	rst	PROPN
ejpam-5934	286	22	before	before	ADP
ejpam-5934	286	23	rst	rst	PROPN
ejpam-5934	286	24	after	after	ADP
ejpam-5934	286	25	rst	rst	PROPN
ejpam-5934	286	26	before	before	ADP
ejpam-5934	286	27	rst	rst	PROPN
ejpam-5934	286	28	after	after	ADP
ejpam-5934	286	29	rst	rst	PROPN
ejpam-5934	286	30	before	before	ADP
ejpam-5934	286	31	rst	rst	PROPN
ejpam-5934	286	32	after	after	ADP
ejpam-5934	286	33	rst	rst	PROPN
ejpam-5934	286	34	before	before	ADP
ejpam-5934	286	35	rst	rst	PROPN
ejpam-5934	286	36	after	after	ADP
ejpam-5934	286	37	rst	rst	PROPN
ejpam-5934	286	38	lr	lr	VERB
ejpam-5934	286	39	0.9245	0.9245	NUM
ejpam-5934	287	1	0.9623	0.9623	NUM
ejpam-5934	287	2	0.9265	0.9265	NUM
ejpam-5934	287	3	0.9649	0.9649	NUM
ejpam-5934	287	4	0.9328	0.9328	NUM
ejpam-5934	287	5	0.968	0.968	NUM
ejpam-5934	287	6	0.9266	0.9266	NUM
ejpam-5934	287	7	0.9648	0.9648	NUM
ejpam-5934	287	8	0.0943	0.0943	NUM
ejpam-5934	287	9	0.0377	0.0377	NUM
ejpam-5934	287	10	knn	knn	VERB
ejpam-5934	287	11	0.8868	0.8868	NUM
ejpam-5934	287	12	0.9056	0.9056	NUM
ejpam-5934	287	13	0.8844	0.8844	NUM
ejpam-5934	287	14	0.9025	0.9025	NUM
ejpam-5934	287	15	0.8936	0.8936	NUM
ejpam-5934	287	16	0.9094	0.9094	NUM
ejpam-5934	287	17	0.8870	0.8870	NUM
ejpam-5934	287	18	0.9043	0.9043	NUM
ejpam-5934	287	19	0.1509	0.1509	NUM
ejpam-5934	287	20	0.1321	0.1321	NUM
ejpam-5934	287	21	svm	svm	NOUN
ejpam-5934	287	22	0.9434	0.9434	NUM
ejpam-5934	287	23	0.9623	0.9623	NUM
ejpam-5934	287	24	0.9421	0.9421	NUM
ejpam-5934	287	25	0.9649	0.9649	NUM
ejpam-5934	287	26	0.9486	0.9486	NUM
ejpam-5934	287	27	0.9683	0.9683	NUM
ejpam-5934	287	28	0.9440	0.9440	NUM
ejpam-5934	287	29	0.9648	0.9648	NUM
ejpam-5934	288	1	0.0755	0.0755	NUM
ejpam-5934	288	2	0.0377	0.0377	NUM
ejpam-5934	288	3	kernel	kernel	NOUN
ejpam-5934	288	4	svm	svm	NOUN
ejpam-5934	288	5	0.9245	0.9245	NUM
ejpam-5934	288	6	0.9623	0.9623	NUM
ejpam-5934	288	7	0.9233	0.9233	NUM
ejpam-5934	288	8	0.9649	0.9649	NUM
ejpam-5934	288	9	0.9290	0.9290	NUM
ejpam-5934	288	10	0.9683	0.9683	NUM
ejpam-5934	288	11	0.9256	0.9256	NUM
ejpam-5934	288	12	0.9648	0.9648	NUM
ejpam-5934	288	13	0.0943	0.0943	NUM
ejpam-5934	288	14	0.0377	0.0377	NUM
ejpam-5934	288	15	nb	nb	ADP
ejpam-5934	288	16	0.8868	0.8868	NUM
ejpam-5934	288	17	0.9057	0.9057	NUM
ejpam-5934	288	18	0.9010	0.9010	NUM
ejpam-5934	288	19	0.9158	0.9158	NUM
ejpam-5934	288	20	0.9010	0.9010	NUM
ejpam-5934	288	21	0.9106	0.9106	NUM
ejpam-5934	288	22	0.8947	0.8947	NUM
ejpam-5934	288	23	0.9101	0.9101	NUM
ejpam-5934	288	24	0.1132	0.1132	NUM
ejpam-5934	288	25	0.1132	0.1132	NUM
ejpam-5934	288	26	dt	dt	NOUN
ejpam-5934	288	27	0.9245	0.9245	NUM
ejpam-5934	288	28	0.9434	0.9434	NUM
ejpam-5934	288	29	0.9216	0.9216	NUM
ejpam-5934	288	30	0.95	0.95	NUM
ejpam-5934	288	31	0.9290	0.9290	NUM
ejpam-5934	288	32	0.9524	0.9524	NUM
ejpam-5934	288	33	0.9233	0.9233	NUM
ejpam-5934	288	34	0.9473	0.9473	NUM
ejpam-5934	288	35	0.1132	0.1132	NUM
ejpam-5934	288	36	0.0566	0.0566	NUM
ejpam-5934	288	37	rf	rf	NUM
ejpam-5934	288	38	0.9245	0.9245	NUM
ejpam-5934	288	39	0.9245	0.9245	NUM
ejpam-5934	288	40	0.925	0.925	NUM
ejpam-5934	288	41	0.9365	0.9365	NUM
ejpam-5934	288	42	0.9264	0.9264	NUM
ejpam-5934	288	43	0.9365	0.9365	NUM
ejpam-5934	288	44	0.9241	0.9241	NUM
ejpam-5934	288	45	0.9298	0.9298	NUM
ejpam-5934	288	46	0.1132	0.1132	NUM
ejpam-5934	288	47	0.0755	0.0755	NUM
ejpam-5934	288	48	3.5.2	3.5.2	NUM
ejpam-5934	288	49	.	.	PUNCT
ejpam-5934	289	1	heart	heart	NOUN
ejpam-5934	289	2	attack	attack	NOUN
ejpam-5934	289	3	dataset	dataset	NOUN
ejpam-5934	289	4	table	table	NOUN
ejpam-5934	289	5	6	6	NUM
ejpam-5934	289	6	shows	show	VERB
ejpam-5934	289	7	that	that	SCONJ
ejpam-5934	289	8	applying	apply	VERB
ejpam-5934	289	9	rst	rst	NOUN
ejpam-5934	289	10	feature	feature	NOUN
ejpam-5934	289	11	selection	selection	NOUN
ejpam-5934	289	12	for	for	ADP
ejpam-5934	289	13	the	the	DET
ejpam-5934	289	14	heart	heart	NOUN
ejpam-5934	289	15	attack	attack	NOUN
ejpam-5934	289	16	dataset	dataset	VERB
ejpam-5934	289	17	significantly	significantly	ADV
ejpam-5934	289	18	enhances	enhance	VERB
ejpam-5934	289	19	classification	classification	NOUN
ejpam-5934	289	20	performance	performance	NOUN
ejpam-5934	289	21	for	for	ADP
ejpam-5934	289	22	several	several	ADJ
ejpam-5934	289	23	models	model	NOUN
ejpam-5934	289	24	.	.	PUNCT
ejpam-5934	290	1	lr	lr	NOUN
ejpam-5934	290	2	improving	improve	VERB
ejpam-5934	290	3	from	from	ADP
ejpam-5934	290	4	0.7424	0.7424	NUM
ejpam-5934	290	5	to	to	ADP
ejpam-5934	290	6	0.8101	0.8101	NUM
ejpam-5934	290	7	,	,	PUNCT
ejpam-5934	290	8	and	and	CCONJ
ejpam-5934	290	9	kernel	kernel	PROPN
ejpam-5934	290	10	svm	svm	PROPN
ejpam-5934	290	11	,	,	PUNCT
ejpam-5934	290	12	dt	dt	X
ejpam-5934	290	13	,	,	PUNCT
ejpam-5934	290	14	and	and	CCONJ
ejpam-5934	290	15	rf	rf	NOUN
ejpam-5934	290	16	achieving	achieve	VERB
ejpam-5934	290	17	high	high	ADJ
ejpam-5934	290	18	metrics	metric	NOUN
ejpam-5934	290	19	across	across	ADP
ejpam-5934	290	20	the	the	DET
ejpam-5934	290	21	board	board	NOUN
ejpam-5934	290	22	,	,	PUNCT
ejpam-5934	290	23	highlighting	highlight	VERB
ejpam-5934	290	24	the	the	DET
ejpam-5934	290	25	effectiveness	effectiveness	NOUN
ejpam-5934	290	26	of	of	ADP
ejpam-5934	290	27	rst	rst	PROPN
ejpam-5934	290	28	in	in	ADP
ejpam-5934	290	29	enhancing	enhance	VERB
ejpam-5934	290	30	model	model	NOUN
ejpam-5934	290	31	precision	precision	NOUN
ejpam-5934	290	32	and	and	CCONJ
ejpam-5934	290	33	accuracy	accuracy	NOUN
ejpam-5934	290	34	.	.	PUNCT
ejpam-5934	291	1	table	table	NOUN
ejpam-5934	291	2	6	6	NUM
ejpam-5934	291	3	:	:	PUNCT
ejpam-5934	291	4	different	different	ADJ
ejpam-5934	291	5	ml	ml	NOUN
ejpam-5934	291	6	algorithms	algorithm	NOUN
ejpam-5934	291	7	on	on	ADP
ejpam-5934	291	8	heart	heart	NOUN
ejpam-5934	291	9	attack	attack	NOUN
ejpam-5934	291	10	dataset	dataset	VERB
ejpam-5934	291	11	ml	ml	PROPN
ejpam-5934	291	12	model	model	NOUN
ejpam-5934	291	13	accuracy	accuracy	PROPN
ejpam-5934	291	14	precision	precision	NOUN
ejpam-5934	291	15	recall	recall	NOUN
ejpam-5934	291	16	f1	f1	PROPN
ejpam-5934	291	17	score	score	NOUN
ejpam-5934	291	18	mae	mae	PROPN
ejpam-5934	291	19	before	before	ADP
ejpam-5934	291	20	rst	rst	PROPN
ejpam-5934	291	21	after	after	ADP
ejpam-5934	291	22	rst	rst	PROPN
ejpam-5934	291	23	before	before	ADP
ejpam-5934	291	24	rst	rst	PROPN
ejpam-5934	291	25	after	after	ADP
ejpam-5934	291	26	rst	rst	PROPN
ejpam-5934	291	27	before	before	ADP
ejpam-5934	291	28	rst	rst	PROPN
ejpam-5934	291	29	after	after	ADP
ejpam-5934	291	30	rst	rst	PROPN
ejpam-5934	291	31	before	before	ADP
ejpam-5934	291	32	rst	rst	PROPN
ejpam-5934	291	33	after	after	ADP
ejpam-5934	291	34	rst	rst	PROPN
ejpam-5934	291	35	before	before	ADP
ejpam-5934	291	36	rst	rst	PROPN
ejpam-5934	291	37	after	after	SCONJ
ejpam-5934	291	38	rst	rst	PROPN
ejpam-5934	291	39	lr	lr	VERB
ejpam-5934	291	40	0.7424	0.7424	NUM
ejpam-5934	291	41	0.8101	0.8101	NUM
ejpam-5934	292	1	0.7471	0.7471	NUM
ejpam-5934	292	2	0.8864	0.8864	NUM
ejpam-5934	292	3	0.8355	0.8355	NUM
ejpam-5934	292	4	0.7697	0.7697	NUM
ejpam-5934	292	5	0.7888	0.7888	NUM
ejpam-5934	292	6	0.8239	0.8239	NUM
ejpam-5934	292	7	0.2576	0.2576	NUM
ejpam-5934	292	8	0.1894	0.1894	NUM
ejpam-5934	292	9	knn	knn	NOUN
ejpam-5934	293	1	0.625	0.625	NUM
ejpam-5934	293	2	0.9811	0.9811	NUM
ejpam-5934	293	3	0.67096	0.67096	NUM
ejpam-5934	293	4	0.9868	0.9868	NUM
ejpam-5934	293	5	0.6842	0.6842	NUM
ejpam-5934	293	6	0.9803	0.9803	NUM
ejpam-5934	293	7	0.6775	0.6775	NUM
ejpam-5934	293	8	0.9835	0.9835	NUM
ejpam-5934	293	9	0.375	0.375	NUM
ejpam-5934	293	10	0.0189	0.0189	NUM
ejpam-5934	293	11	svm	svm	NOUN
ejpam-5934	293	12	0.7841	0.7841	NUM
ejpam-5934	293	13	0.7803	0.7803	NUM
ejpam-5934	293	14	0.8025	0.8025	NUM
ejpam-5934	293	15	1	1	NUM
ejpam-5934	293	16	0.8289	0.8289	NUM
ejpam-5934	293	17	0.6184	0.6184	NUM
ejpam-5934	293	18	0.8155	0.8155	NUM
ejpam-5934	293	19	0.7642	0.7642	NUM
ejpam-5934	293	20	0.2159	0.2159	NUM
ejpam-5934	293	21	0.2197	0.2197	NUM
ejpam-5934	293	22	kernel	kernel	NOUN
ejpam-5934	293	23	svm	svm	VERB
ejpam-5934	293	24	0.6856	0.6856	NUM
ejpam-5934	293	25	0.8106	0.8106	NUM
ejpam-5934	293	26	0.6885	0.6885	NUM
ejpam-5934	293	27	1	1	NUM
ejpam-5934	293	28	0.8289	0.8289	NUM
ejpam-5934	293	29	0.6711	0.6711	NUM
ejpam-5934	293	30	0.7522	0.7522	NUM
ejpam-5934	293	31	0.8031	0.8031	NUM
ejpam-5934	293	32	0.3144	0.3144	NUM
ejpam-5934	293	33	0.1894	0.1894	NUM
ejpam-5934	293	34	nb	nb	NOUN
ejpam-5934	293	35	0.6894	0.6894	NUM
ejpam-5934	293	36	0.7121	0.7121	NUM
ejpam-5934	293	37	0.9861	0.9861	NUM
ejpam-5934	293	38	1	1	NUM
ejpam-5934	293	39	0.4671	0.4671	NUM
ejpam-5934	293	40	0.5	0.5	NUM
ejpam-5934	293	41	0.6339	0.6339	NUM
ejpam-5934	293	42	0.6667	0.6667	NUM
ejpam-5934	293	43	0.3106	0.3106	NUM
ejpam-5934	293	44	0.2879	0.2879	NUM
ejpam-5934	293	45	dt	dt	NUM
ejpam-5934	293	46	0.9962	0.9962	NUM
ejpam-5934	293	47	0.9886	0.9886	NUM
ejpam-5934	294	1	0.9935	0.9935	NUM
ejpam-5934	294	2	0.9806	0.9806	NUM
ejpam-5934	294	3	1	1	NUM
ejpam-5934	294	4	1	1	NUM
ejpam-5934	294	5	0.9967	0.9967	NUM
ejpam-5934	294	6	0.9902	0.9902	NUM
ejpam-5934	294	7	0.0038	0.0038	NUM
ejpam-5934	294	8	0.0114	0.0114	NUM
ejpam-5934	294	9	rf	rf	NOUN
ejpam-5934	294	10	0.9924	0.9924	NUM
ejpam-5934	294	11	0.9962	0.9962	NUM
ejpam-5934	294	12	1	1	NUM
ejpam-5934	295	1	0.9935	0.9935	NUM
ejpam-5934	295	2	0.9868	0.9868	NUM
ejpam-5934	295	3	1	1	NUM
ejpam-5934	295	4	0.9934	0.9934	NUM
ejpam-5934	295	5	0.967	0.967	NUM
ejpam-5934	295	6	0.0076	0.0076	NUM
ejpam-5934	295	7	0.0038	0.0038	NUM
ejpam-5934	295	8	t.	t.	NOUN
ejpam-5934	295	9	ashika	ashika	NOUN
ejpam-5934	295	10	,	,	PUNCT
ejpam-5934	295	11	g.	g.	PROPN
ejpam-5934	295	12	h.	h.	PROPN
ejpam-5934	295	13	grace	grace	PROPN
ejpam-5934	295	14	/	/	SYM
ejpam-5934	295	15	eur	eur	PROPN
ejpam-5934	295	16	.	.	PUNCT
ejpam-5934	296	1	j.	j.	PROPN
ejpam-5934	296	2	pure	pure	PROPN
ejpam-5934	296	3	appl	appl	PROPN
ejpam-5934	296	4	.	.	PROPN
ejpam-5934	296	5	math	math	PROPN
ejpam-5934	296	6	,	,	PUNCT
ejpam-5934	296	7	18	18	NUM
ejpam-5934	296	8	(	(	PUNCT
ejpam-5934	296	9	2	2	NUM
ejpam-5934	296	10	)	)	PUNCT
ejpam-5934	296	11	(	(	PUNCT
ejpam-5934	296	12	2025	2025	NUM
ejpam-5934	296	13	)	)	PUNCT
ejpam-5934	296	14	,	,	PUNCT
ejpam-5934	296	15	5934	5934	NUM
ejpam-5934	296	16	16	16	NUM
ejpam-5934	296	17	of	of	ADP
ejpam-5934	296	18	22	22	NUM
ejpam-5934	296	19	3.5.3	3.5.3	NUM
ejpam-5934	296	20	.	.	PUNCT
ejpam-5934	297	1	obesity	obesity	NOUN
ejpam-5934	297	2	dataset	dataset	VERB
ejpam-5934	297	3	rst	rst	PROPN
ejpam-5934	297	4	feature	feature	NOUN
ejpam-5934	297	5	selection	selection	NOUN
ejpam-5934	297	6	maintains	maintain	VERB
ejpam-5934	297	7	high	high	ADJ
ejpam-5934	297	8	classification	classification	NOUN
ejpam-5934	297	9	performance	performance	NOUN
ejpam-5934	297	10	for	for	ADP
ejpam-5934	297	11	dt	dt	NOUN
ejpam-5934	297	12	with	with	ADP
ejpam-5934	297	13	perfect	perfect	ADJ
ejpam-5934	297	14	metrics	metric	NOUN
ejpam-5934	297	15	across	across	ADP
ejpam-5934	297	16	all	all	DET
ejpam-5934	297	17	evaluation	evaluation	NOUN
ejpam-5934	297	18	measures	measure	NOUN
ejpam-5934	297	19	,	,	PUNCT
ejpam-5934	297	20	while	while	SCONJ
ejpam-5934	297	21	rf	rf	NOUN
ejpam-5934	297	22	experiences	experience	VERB
ejpam-5934	297	23	a	a	DET
ejpam-5934	297	24	slight	slight	ADJ
ejpam-5934	297	25	decline	decline	NOUN
ejpam-5934	297	26	in	in	ADP
ejpam-5934	297	27	accuracy	accuracy	NOUN
ejpam-5934	297	28	from	from	ADP
ejpam-5934	297	29	1	1	NUM
ejpam-5934	297	30	to	to	ADP
ejpam-5934	297	31	0.9091	0.9091	NUM
ejpam-5934	297	32	,	,	PUNCT
ejpam-5934	297	33	showcasing	showcase	VERB
ejpam-5934	297	34	the	the	DET
ejpam-5934	297	35	robustness	robustness	NOUN
ejpam-5934	297	36	of	of	ADP
ejpam-5934	297	37	dt	dt	NOUN
ejpam-5934	297	38	and	and	CCONJ
ejpam-5934	297	39	rf	rf	PRON
ejpam-5934	297	40	even	even	ADV
ejpam-5934	297	41	after	after	ADP
ejpam-5934	297	42	feature	feature	NOUN
ejpam-5934	297	43	selection	selection	NOUN
ejpam-5934	297	44	.	.	PUNCT
ejpam-5934	298	1	table	table	NOUN
ejpam-5934	298	2	7	7	NUM
ejpam-5934	298	3	:	:	PUNCT
ejpam-5934	298	4	different	different	ADJ
ejpam-5934	298	5	ml	ml	NOUN
ejpam-5934	298	6	algorithms	algorithm	NOUN
ejpam-5934	298	7	on	on	ADP
ejpam-5934	298	8	obesity	obesity	NOUN
ejpam-5934	298	9	dataset	dataset	VERB
ejpam-5934	298	10	ml	ml	ADP
ejpam-5934	298	11	model	model	NOUN
ejpam-5934	298	12	accuracy	accuracy	PROPN
ejpam-5934	298	13	precision	precision	NOUN
ejpam-5934	298	14	recall	recall	NOUN
ejpam-5934	298	15	f1	f1	PROPN
ejpam-5934	298	16	score	score	NOUN
ejpam-5934	298	17	mae	mae	PROPN
ejpam-5934	298	18	before	before	ADP
ejpam-5934	298	19	rst	rst	PROPN
ejpam-5934	298	20	after	after	ADP
ejpam-5934	298	21	rst	rst	PROPN
ejpam-5934	298	22	before	before	ADP
ejpam-5934	298	23	rst	rst	PROPN
ejpam-5934	298	24	after	after	ADP
ejpam-5934	298	25	rst	rst	PROPN
ejpam-5934	298	26	before	before	ADP
ejpam-5934	298	27	rst	rst	PROPN
ejpam-5934	298	28	after	after	ADP
ejpam-5934	298	29	rst	rst	PROPN
ejpam-5934	298	30	before	before	ADP
ejpam-5934	298	31	rst	rst	PROPN
ejpam-5934	298	32	after	after	ADP
ejpam-5934	298	33	rst	rst	PROPN
ejpam-5934	298	34	before	before	ADP
ejpam-5934	298	35	rst	rst	PROPN
ejpam-5934	298	36	after	after	SCONJ
ejpam-5934	298	37	rst	rst	PROPN
ejpam-5934	298	38	lr	lr	VERB
ejpam-5934	298	39	0.7727	0.7727	NUM
ejpam-5934	298	40	0.7727	0.7727	NUM
ejpam-5934	298	41	0.7917	0.7917	NUM
ejpam-5934	298	42	0.7917	0.7917	NUM
ejpam-5934	298	43	0.7917	0.7917	NUM
ejpam-5934	298	44	0.7917	0.7917	NUM
ejpam-5934	298	45	0.6881	0.6881	NUM
ejpam-5934	298	46	0.6881	0.6881	NUM
ejpam-5934	298	47	0.3182	0.3182	NUM
ejpam-5934	298	48	0.3182	0.3182	NUM
ejpam-5934	299	1	knn	knn	NOUN
ejpam-5934	299	2	0.7727	0.7727	NUM
ejpam-5934	299	3	0.7727	0.7727	NUM
ejpam-5934	299	4	0.7875	0.7875	NUM
ejpam-5934	300	1	0.7875	0.7875	NUM
ejpam-5934	300	2	0.7708	0.7708	NUM
ejpam-5934	300	3	0.7708	0.7708	NUM
ejpam-5934	300	4	0.7261	0.7261	NUM
ejpam-5934	300	5	0.7261	0.7261	NUM
ejpam-5934	300	6	0.4545	0.4545	NUM
ejpam-5934	300	7	0.4545	0.4545	NUM
ejpam-5934	300	8	svm	svm	NOUN
ejpam-5934	300	9	0.8636	0.8636	NUM
ejpam-5934	300	10	0.8636	0.8636	NUM
ejpam-5934	300	11	0.8542	0.8542	NUM
ejpam-5934	300	12	0.8542	0.8542	NUM
ejpam-5934	301	1	0.8889	0.8889	NUM
ejpam-5934	301	2	0.875	0.875	NUM
ejpam-5934	301	3	0.8496	0.8496	NUM
ejpam-5934	301	4	0.83095	0.83095	NUM
ejpam-5934	301	5	0.2727	0.2727	NUM
ejpam-5934	301	6	0.2272	0.2272	NUM
ejpam-5934	301	7	kernel	kernel	NOUN
ejpam-5934	301	8	svm	svm	VERB
ejpam-5934	301	9	0.6818	0.6818	NUM
ejpam-5934	301	10	0.6818	0.6818	NUM
ejpam-5934	301	11	0.5063	0.5063	NUM
ejpam-5934	301	12	0.5063	0.5063	NUM
ejpam-5934	301	13	0.6875	0.6875	NUM
ejpam-5934	301	14	0.6875	0.6875	NUM
ejpam-5934	301	15	0.5761	0.5761	NUM
ejpam-5934	301	16	0.5761	0.5761	NUM
ejpam-5934	301	17	0.6364	0.6364	NUM
ejpam-5934	301	18	0.6364	0.6364	NUM
ejpam-5934	301	19	nb	nb	NOUN
ejpam-5934	301	20	0.7727	0.7727	NUM
ejpam-5934	301	21	0.7727	0.7727	NUM
ejpam-5934	301	22	0.8438	0.8438	NUM
ejpam-5934	301	23	0.8438	0.8438	NUM
ejpam-5934	301	24	0.7917	0.7917	NUM
ejpam-5934	301	25	0.7917	0.7917	NUM
ejpam-5934	301	26	0.7078	0.7078	NUM
ejpam-5934	301	27	0.7078	0.7078	NUM
ejpam-5934	301	28	0.2273	0.2273	NUM
ejpam-5934	301	29	0.2273	0.2273	NUM
ejpam-5934	301	30	dt	dt	NOUN
ejpam-5934	301	31	1	1	NUM
ejpam-5934	301	32	1	1	NUM
ejpam-5934	301	33	1	1	NUM
ejpam-5934	301	34	1	1	NUM
ejpam-5934	301	35	1	1	NUM
ejpam-5934	301	36	1	1	NUM
ejpam-5934	301	37	1	1	NUM
ejpam-5934	301	38	1	1	NUM
ejpam-5934	301	39	0	0	NUM
ejpam-5934	301	40	0	0	NUM
ejpam-5934	302	1	rf	rf	NUM
ejpam-5934	302	2	1	1	NUM
ejpam-5934	302	3	0.9091	0.9091	NUM
ejpam-5934	302	4	1	1	NUM
ejpam-5934	302	5	0.9167	0.9167	NUM
ejpam-5934	302	6	1	1	NUM
ejpam-5934	302	7	0.9167	0.9167	NUM
ejpam-5934	302	8	1	1	NUM
ejpam-5934	302	9	0.9	0.9	NUM
ejpam-5934	302	10	0	0	NUM
ejpam-5934	303	1	0.1818	0.1818	NUM
ejpam-5934	303	2	table	table	NOUN
ejpam-5934	303	3	7	7	NUM
ejpam-5934	303	4	shows	show	VERB
ejpam-5934	303	5	that	that	SCONJ
ejpam-5934	303	6	the	the	DET
ejpam-5934	303	7	dt	dt	PROPN
ejpam-5934	303	8	classifier	classifier	NOUN
ejpam-5934	303	9	achieved	achieve	VERB
ejpam-5934	303	10	perfect	perfect	ADJ
ejpam-5934	303	11	scores	score	NOUN
ejpam-5934	303	12	both	both	CCONJ
ejpam-5934	303	13	before	before	ADP
ejpam-5934	303	14	and	and	CCONJ
ejpam-5934	303	15	after	after	ADP
ejpam-5934	303	16	rst	rst	NOUN
ejpam-5934	303	17	-	-	PUNCT
ejpam-5934	303	18	based	base	VERB
ejpam-5934	303	19	feature	feature	NOUN
ejpam-5934	303	20	reduction	reduction	NOUN
ejpam-5934	303	21	for	for	ADP
ejpam-5934	303	22	the	the	DET
ejpam-5934	303	23	obesity	obesity	NOUN
ejpam-5934	303	24	dataset	dataset	NOUN
ejpam-5934	303	25	.	.	PUNCT
ejpam-5934	304	1	given	give	VERB
ejpam-5934	304	2	the	the	DET
ejpam-5934	304	3	small	small	ADJ
ejpam-5934	304	4	dataset	dataset	NOUN
ejpam-5934	304	5	size	size	NOUN
ejpam-5934	304	6	,	,	PUNCT
ejpam-5934	304	7	such	such	ADJ
ejpam-5934	304	8	uniform	uniform	ADJ
ejpam-5934	304	9	performance	performance	NOUN
ejpam-5934	304	10	strongly	strongly	ADV
ejpam-5934	304	11	indicates	indicate	VERB
ejpam-5934	304	12	overfitting	overfitte	VERB
ejpam-5934	304	13	,	,	PUNCT
ejpam-5934	304	14	where	where	SCONJ
ejpam-5934	304	15	the	the	DET
ejpam-5934	304	16	model	model	NOUN
ejpam-5934	304	17	memorizes	memorize	VERB
ejpam-5934	304	18	patterns	pattern	NOUN
ejpam-5934	304	19	including	include	VERB
ejpam-5934	304	20	noise	noise	NOUN
ejpam-5934	304	21	rather	rather	ADV
ejpam-5934	304	22	than	than	ADP
ejpam-5934	304	23	generalizing	generalize	VERB
ejpam-5934	304	24	effectively	effectively	ADV
ejpam-5934	304	25	.	.	PUNCT
ejpam-5934	305	1	in	in	ADP
ejpam-5934	305	2	contrast	contrast	NOUN
ejpam-5934	305	3	,	,	PUNCT
ejpam-5934	305	4	the	the	DET
ejpam-5934	305	5	rf	rf	NOUN
ejpam-5934	305	6	model	model	NOUN
ejpam-5934	305	7	,	,	PUNCT
ejpam-5934	305	8	which	which	PRON
ejpam-5934	305	9	also	also	ADV
ejpam-5934	305	10	achieved	achieve	VERB
ejpam-5934	305	11	1.0	1.0	NUM
ejpam-5934	305	12	before	before	ADP
ejpam-5934	305	13	rst	rst	PROPN
ejpam-5934	305	14	,	,	PUNCT
ejpam-5934	305	15	dropped	drop	VERB
ejpam-5934	305	16	slightly	slightly	ADV
ejpam-5934	305	17	to	to	ADP
ejpam-5934	305	18	0.9091	0.9091	NUM
ejpam-5934	305	19	after	after	ADP
ejpam-5934	305	20	rst	rst	PROPN
ejpam-5934	305	21	,	,	PUNCT
ejpam-5934	305	22	reflecting	reflect	VERB
ejpam-5934	305	23	its	its	PRON
ejpam-5934	305	24	ensemble	ensemble	ADJ
ejpam-5934	305	25	robustness	robustness	NOUN
ejpam-5934	305	26	and	and	CCONJ
ejpam-5934	305	27	sensitivity	sensitivity	NOUN
ejpam-5934	305	28	to	to	ADP
ejpam-5934	305	29	the	the	DET
ejpam-5934	305	30	removal	removal	NOUN
ejpam-5934	305	31	of	of	ADP
ejpam-5934	305	32	marginally	marginally	ADV
ejpam-5934	305	33	informative	informative	ADJ
ejpam-5934	305	34	features	feature	NOUN
ejpam-5934	305	35	.	.	PUNCT
ejpam-5934	306	1	compared	compare	VERB
ejpam-5934	306	2	to	to	ADP
ejpam-5934	306	3	svm	svm	PROPN
ejpam-5934	306	4	(	(	PUNCT
ejpam-5934	306	5	0.8636	0.8636	NUM
ejpam-5934	306	6	)	)	PUNCT
ejpam-5934	306	7	and	and	CCONJ
ejpam-5934	306	8	lr	lr	X
ejpam-5934	306	9	(	(	PUNCT
ejpam-5934	306	10	0.7727	0.7727	NUM
ejpam-5934	306	11	)	)	PUNCT
ejpam-5934	306	12	,	,	PUNCT
ejpam-5934	306	13	rf	rf	PRON
ejpam-5934	306	14	maintains	maintain	VERB
ejpam-5934	306	15	stronger	strong	ADJ
ejpam-5934	306	16	generalization	generalization	NOUN
ejpam-5934	306	17	,	,	PUNCT
ejpam-5934	306	18	making	make	VERB
ejpam-5934	306	19	it	it	PRON
ejpam-5934	306	20	a	a	DET
ejpam-5934	306	21	more	more	ADV
ejpam-5934	306	22	reliable	reliable	ADJ
ejpam-5934	306	23	choice	choice	NOUN
ejpam-5934	306	24	for	for	ADP
ejpam-5934	306	25	small	small	ADJ
ejpam-5934	306	26	datasets	dataset	NOUN
ejpam-5934	306	27	under	under	ADP
ejpam-5934	306	28	feature	feature	NOUN
ejpam-5934	306	29	reduction	reduction	NOUN
ejpam-5934	306	30	.	.	PUNCT
ejpam-5934	307	1	3.5.4	3.5.4	NUM
ejpam-5934	307	2	.	.	PUNCT
ejpam-5934	307	3	online	online	ADJ
ejpam-5934	307	4	food	food	NOUN
ejpam-5934	307	5	delivery	delivery	NOUN
ejpam-5934	307	6	dataset	dataset	VERB
ejpam-5934	307	7	rst	rst	PROPN
ejpam-5934	307	8	feature	feature	NOUN
ejpam-5934	307	9	selection	selection	NOUN
ejpam-5934	307	10	leads	lead	VERB
ejpam-5934	307	11	to	to	ADP
ejpam-5934	307	12	improved	improved	ADJ
ejpam-5934	307	13	performance	performance	NOUN
ejpam-5934	307	14	in	in	ADP
ejpam-5934	307	15	classifiers	classifier	NOUN
ejpam-5934	307	16	like	like	ADP
ejpam-5934	307	17	knn	knn	PROPN
ejpam-5934	307	18	,	,	PUNCT
ejpam-5934	307	19	kernel	kernel	PROPN
ejpam-5934	307	20	svm	svm	PROPN
ejpam-5934	307	21	,	,	PUNCT
ejpam-5934	307	22	and	and	CCONJ
ejpam-5934	307	23	dt	dt	X
ejpam-5934	307	24	,	,	PUNCT
ejpam-5934	307	25	especially	especially	ADV
ejpam-5934	307	26	enhancing	enhance	VERB
ejpam-5934	307	27	recall	recall	NOUN
ejpam-5934	307	28	and	and	CCONJ
ejpam-5934	307	29	f1	f1	NOUN
ejpam-5934	307	30	scores	score	NOUN
ejpam-5934	307	31	across	across	ADP
ejpam-5934	307	32	these	these	DET
ejpam-5934	307	33	models	model	NOUN
ejpam-5934	307	34	.	.	PUNCT
ejpam-5934	308	1	table	table	NOUN
ejpam-5934	308	2	8	8	NUM
ejpam-5934	308	3	describes	describe	VERB
ejpam-5934	308	4	the	the	DET
ejpam-5934	308	5	online	online	ADJ
ejpam-5934	308	6	food	food	NOUN
ejpam-5934	308	7	delivery	delivery	NOUN
ejpam-5934	308	8	dataset	dataset	NOUN
ejpam-5934	308	9	,	,	PUNCT
ejpam-5934	308	10	where	where	SCONJ
ejpam-5934	308	11	some	some	DET
ejpam-5934	308	12	algorithms	algorithm	NOUN
ejpam-5934	308	13	show	show	VERB
ejpam-5934	308	14	improvement	improvement	NOUN
ejpam-5934	308	15	,	,	PUNCT
ejpam-5934	308	16	while	while	SCONJ
ejpam-5934	308	17	others	other	NOUN
ejpam-5934	308	18	yield	yield	VERB
ejpam-5934	308	19	comparable	comparable	ADJ
ejpam-5934	308	20	results	result	NOUN
ejpam-5934	308	21	.	.	PUNCT
ejpam-5934	309	1	t.	t.	ADJ
ejpam-5934	309	2	ashika	ashika	PROPN
ejpam-5934	309	3	,	,	PUNCT
ejpam-5934	309	4	g.	g.	PROPN
ejpam-5934	309	5	h.	h.	PROPN
ejpam-5934	309	6	grace	grace	PROPN
ejpam-5934	309	7	/	/	SYM
ejpam-5934	309	8	eur	eur	PROPN
ejpam-5934	309	9	.	.	PUNCT
ejpam-5934	310	1	j.	j.	PROPN
ejpam-5934	310	2	pure	pure	PROPN
ejpam-5934	310	3	appl	appl	PROPN
ejpam-5934	310	4	.	.	PROPN
ejpam-5934	310	5	math	math	PROPN
ejpam-5934	310	6	,	,	PUNCT
ejpam-5934	310	7	18	18	NUM
ejpam-5934	310	8	(	(	PUNCT
ejpam-5934	310	9	2	2	NUM
ejpam-5934	310	10	)	)	PUNCT
ejpam-5934	310	11	(	(	PUNCT
ejpam-5934	310	12	2025	2025	NUM
ejpam-5934	310	13	)	)	PUNCT
ejpam-5934	310	14	,	,	PUNCT
ejpam-5934	310	15	5934	5934	NUM
ejpam-5934	310	16	17	17	NUM
ejpam-5934	310	17	of	of	ADP
ejpam-5934	310	18	22	22	NUM
ejpam-5934	310	19	table	table	NOUN
ejpam-5934	310	20	8	8	NUM
ejpam-5934	310	21	:	:	PUNCT
ejpam-5934	310	22	different	different	ADJ
ejpam-5934	310	23	ml	ml	NOUN
ejpam-5934	310	24	algorithms	algorithm	NOUN
ejpam-5934	310	25	on	on	ADP
ejpam-5934	310	26	online	online	ADJ
ejpam-5934	310	27	food	food	NOUN
ejpam-5934	310	28	delivery	delivery	NOUN
ejpam-5934	310	29	dataset	dataset	VERB
ejpam-5934	310	30	ml	ml	PROPN
ejpam-5934	310	31	model	model	NOUN
ejpam-5934	310	32	accuracy	accuracy	PROPN
ejpam-5934	310	33	precision	precision	NOUN
ejpam-5934	310	34	recall	recall	NOUN
ejpam-5934	310	35	f1	f1	PROPN
ejpam-5934	310	36	score	score	NOUN
ejpam-5934	310	37	mae	mae	PROPN
ejpam-5934	310	38	before	before	ADP
ejpam-5934	310	39	rst	rst	PROPN
ejpam-5934	310	40	after	after	ADP
ejpam-5934	310	41	rst	rst	PROPN
ejpam-5934	310	42	before	before	ADP
ejpam-5934	310	43	rst	rst	PROPN
ejpam-5934	310	44	after	after	ADP
ejpam-5934	310	45	rst	rst	PROPN
ejpam-5934	310	46	before	before	ADP
ejpam-5934	310	47	rst	rst	PROPN
ejpam-5934	310	48	after	after	ADP
ejpam-5934	310	49	rst	rst	PROPN
ejpam-5934	310	50	before	before	ADP
ejpam-5934	310	51	rst	rst	PROPN
ejpam-5934	310	52	after	after	ADP
ejpam-5934	310	53	rst	rst	PROPN
ejpam-5934	310	54	before	before	ADP
ejpam-5934	310	55	rst	rst	PROPN
ejpam-5934	310	56	after	after	SCONJ
ejpam-5934	310	57	rst	rst	PROPN
ejpam-5934	310	58	lr	lr	VERB
ejpam-5934	310	59	0.7526	0.7526	NUM
ejpam-5934	310	60	0.7308	0.7308	NUM
ejpam-5934	310	61	0.7526	0.7526	NUM
ejpam-5934	310	62	0.8305	0.8305	NUM
ejpam-5934	310	63	1	1	NUM
ejpam-5934	310	64	0.8167	0.8167	NUM
ejpam-5934	310	65	0.8588	0.8588	NUM
ejpam-5934	310	66	0.8235	0.8235	NUM
ejpam-5934	310	67	0.2474	0.2474	NUM
ejpam-5934	310	68	0.2692	0.2692	NUM
ejpam-5934	310	69	knn	knn	NOUN
ejpam-5934	310	70	0.7216	0.7216	NUM
ejpam-5934	310	71	0.7564	0.7564	NUM
ejpam-5934	310	72	0.7614	0.7614	NUM
ejpam-5934	311	1	0.7971	0.7971	NUM
ejpam-5934	311	2	0.917	0.917	NUM
ejpam-5934	311	3	0.9167	0.9167	NUM
ejpam-5934	311	4	0.8323	0.8323	NUM
ejpam-5934	311	5	0.8527	0.8527	NUM
ejpam-5934	311	6	0.2784	0.2784	NUM
ejpam-5934	311	7	0.2436	0.2436	NUM
ejpam-5934	311	8	svm	svm	NOUN
ejpam-5934	311	9	0.7526	0.7526	NUM
ejpam-5934	311	10	0.7308	0.7308	NUM
ejpam-5934	311	11	0.7526	0.7526	NUM
ejpam-5934	311	12	0.8305	0.8305	NUM
ejpam-5934	311	13	1	1	NUM
ejpam-5934	311	14	0.8167	0.8167	NUM
ejpam-5934	311	15	0.8588	0.8588	NUM
ejpam-5934	311	16	0.8235	0.8235	NUM
ejpam-5934	311	17	0.2474	0.2474	NUM
ejpam-5934	311	18	0.2692	0.2692	NUM
ejpam-5934	311	19	kernel	kernel	NOUN
ejpam-5934	311	20	svm	svm	VERB
ejpam-5934	311	21	0.7526	0.7526	NUM
ejpam-5934	311	22	0.7564	0.7564	NUM
ejpam-5934	311	23	0.7526	0.7526	NUM
ejpam-5934	312	1	0.7971	0.7971	NUM
ejpam-5934	312	2	1	1	NUM
ejpam-5934	312	3	0.9167	0.9167	NUM
ejpam-5934	312	4	0.8588	0.8588	NUM
ejpam-5934	312	5	0.8527	0.8527	NUM
ejpam-5934	312	6	0.2474	0.2474	NUM
ejpam-5934	312	7	0.2436	0.2436	NUM
ejpam-5934	312	8	nb	nb	NOUN
ejpam-5934	312	9	0.7526	0.7526	NUM
ejpam-5934	312	10	0.7308	0.7308	NUM
ejpam-5934	312	11	0.7526	0.7526	NUM
ejpam-5934	312	12	0.8305	0.8305	NUM
ejpam-5934	312	13	1	1	NUM
ejpam-5934	312	14	0.8167	0.8167	NUM
ejpam-5934	312	15	0.8588	0.8588	NUM
ejpam-5934	312	16	0.8235	0.8235	NUM
ejpam-5934	312	17	0.2474	0.2474	NUM
ejpam-5934	312	18	0.2692	0.2692	NUM
ejpam-5934	312	19	dt	dt	NOUN
ejpam-5934	312	20	0.7423	0.7423	NUM
ejpam-5934	312	21	0.7564	0.7564	NUM
ejpam-5934	312	22	0.75	0.75	NUM
ejpam-5934	312	23	0.7971	0.7971	NUM
ejpam-5934	312	24	0.9863	0.9863	NUM
ejpam-5934	312	25	0.9167	0.9167	NUM
ejpam-5934	312	26	0.8521	0.8521	NUM
ejpam-5934	312	27	0.8527	0.8527	NUM
ejpam-5934	312	28	0.2577	0.2577	NUM
ejpam-5934	312	29	0.2436	0.2436	NUM
ejpam-5934	312	30	rf	rf	NUM
ejpam-5934	312	31	0.7526	0.7526	NUM
ejpam-5934	312	32	0.7308	0.7308	NUM
ejpam-5934	312	33	0.7526	0.7526	NUM
ejpam-5934	312	34	0.8305	0.8305	NUM
ejpam-5934	312	35	1	1	NUM
ejpam-5934	312	36	0.8167	0.8167	NUM
ejpam-5934	312	37	0.8588	0.8588	NUM
ejpam-5934	312	38	0.8235	0.8235	NUM
ejpam-5934	312	39	0.2474	0.2474	NUM
ejpam-5934	312	40	0.2692	0.2692	NUM
ejpam-5934	312	41	3.5.5	3.5.5	NUM
ejpam-5934	312	42	.	.	PUNCT
ejpam-5934	312	43	breast	breast	NOUN
ejpam-5934	312	44	cancer	cancer	NOUN
ejpam-5934	312	45	dataset	dataset	VERB
ejpam-5934	312	46	rst	rst	PROPN
ejpam-5934	312	47	feature	feature	NOUN
ejpam-5934	312	48	selection	selection	NOUN
ejpam-5934	312	49	results	result	NOUN
ejpam-5934	312	50	in	in	ADP
ejpam-5934	312	51	consistent	consistent	ADJ
ejpam-5934	312	52	performance	performance	NOUN
ejpam-5934	312	53	for	for	ADP
ejpam-5934	312	54	most	most	ADJ
ejpam-5934	312	55	classifiers	classifier	NOUN
ejpam-5934	312	56	,	,	PUNCT
ejpam-5934	312	57	with	with	ADP
ejpam-5934	312	58	knn	knn	PROPN
ejpam-5934	312	59	showing	show	VERB
ejpam-5934	312	60	a	a	DET
ejpam-5934	312	61	slight	slight	ADJ
ejpam-5934	312	62	reduction	reduction	NOUN
ejpam-5934	312	63	in	in	ADP
ejpam-5934	312	64	precision	precision	NOUN
ejpam-5934	312	65	but	but	CCONJ
ejpam-5934	312	66	maintaining	maintain	VERB
ejpam-5934	312	67	high	high	ADJ
ejpam-5934	312	68	recall	recall	NOUN
ejpam-5934	312	69	and	and	CCONJ
ejpam-5934	312	70	f1	f1	NOUN
ejpam-5934	312	71	scores	score	NOUN
ejpam-5934	312	72	,	,	PUNCT
ejpam-5934	312	73	while	while	SCONJ
ejpam-5934	312	74	rf	rf	PRON
ejpam-5934	312	75	and	and	CCONJ
ejpam-5934	312	76	nb	nb	INTJ
ejpam-5934	312	77	demonstrate	demonstrate	VERB
ejpam-5934	312	78	stable	stable	ADJ
ejpam-5934	312	79	accuracy	accuracy	NOUN
ejpam-5934	312	80	,	,	PUNCT
ejpam-5934	312	81	highlighting	highlight	VERB
ejpam-5934	312	82	the	the	DET
ejpam-5934	312	83	utility	utility	NOUN
ejpam-5934	312	84	of	of	ADP
ejpam-5934	312	85	rst	rst	PROPN
ejpam-5934	312	86	in	in	ADP
ejpam-5934	312	87	retaining	retain	VERB
ejpam-5934	312	88	essential	essential	ADJ
ejpam-5934	312	89	classification	classification	NOUN
ejpam-5934	312	90	performance	performance	NOUN
ejpam-5934	312	91	.	.	PUNCT
ejpam-5934	313	1	table	table	NOUN
ejpam-5934	313	2	9	9	NUM
ejpam-5934	313	3	describes	describe	VERB
ejpam-5934	313	4	the	the	DET
ejpam-5934	313	5	breast	breast	NOUN
ejpam-5934	313	6	cancer	cancer	NOUN
ejpam-5934	313	7	dataset	dataset	NOUN
ejpam-5934	313	8	,	,	PUNCT
ejpam-5934	313	9	where	where	SCONJ
ejpam-5934	313	10	rst	rst	PROPN
ejpam-5934	313	11	yields	yield	VERB
ejpam-5934	313	12	comparable	comparable	ADJ
ejpam-5934	313	13	results	result	NOUN
ejpam-5934	313	14	.	.	PUNCT
ejpam-5934	314	1	table	table	NOUN
ejpam-5934	314	2	9	9	NUM
ejpam-5934	314	3	:	:	PUNCT
ejpam-5934	314	4	different	different	ADJ
ejpam-5934	314	5	ml	ml	NOUN
ejpam-5934	314	6	algorithms	algorithm	NOUN
ejpam-5934	314	7	on	on	ADP
ejpam-5934	314	8	breast	breast	NOUN
ejpam-5934	314	9	cancer	cancer	NOUN
ejpam-5934	314	10	dataset	dataset	VERB
ejpam-5934	314	11	ml	ml	PROPN
ejpam-5934	314	12	model	model	NOUN
ejpam-5934	314	13	accuracy	accuracy	PROPN
ejpam-5934	314	14	precision	precision	NOUN
ejpam-5934	314	15	recall	recall	NOUN
ejpam-5934	314	16	f1	f1	PROPN
ejpam-5934	314	17	score	score	NOUN
ejpam-5934	314	18	mae	mae	PROPN
ejpam-5934	314	19	before	before	ADP
ejpam-5934	314	20	rst	rst	PROPN
ejpam-5934	314	21	after	after	ADP
ejpam-5934	314	22	rst	rst	PROPN
ejpam-5934	314	23	before	before	ADP
ejpam-5934	314	24	rst	rst	PROPN
ejpam-5934	314	25	after	after	ADP
ejpam-5934	314	26	rst	rst	PROPN
ejpam-5934	314	27	before	before	ADP
ejpam-5934	314	28	rst	rst	PROPN
ejpam-5934	314	29	after	after	ADP
ejpam-5934	314	30	rst	rst	PROPN
ejpam-5934	314	31	before	before	ADP
ejpam-5934	314	32	rst	rst	PROPN
ejpam-5934	314	33	after	after	ADP
ejpam-5934	314	34	rst	rst	PROPN
ejpam-5934	314	35	before	before	ADP
ejpam-5934	314	36	rst	rst	PROPN
ejpam-5934	314	37	after	after	SCONJ
ejpam-5934	314	38	rst	rst	PROPN
ejpam-5934	314	39	lr	lr	VERB
ejpam-5934	314	40	0.9571	0.9571	NUM
ejpam-5934	314	41	0.9429	0.9429	NUM
ejpam-5934	314	42	0.9551	0.9551	NUM
ejpam-5934	315	1	0.9467	0.9467	NUM
ejpam-5934	315	2	0.9551	0.9551	NUM
ejpam-5934	315	3	0.9337	0.9337	NUM
ejpam-5934	315	4	0.9551	0.9551	NUM
ejpam-5934	315	5	0.9393	0.9393	NUM
ejpam-5934	315	6	0.0857	0.0857	NUM
ejpam-5934	315	7	0.1143	0.1143	NOUN
ejpam-5934	315	8	knn	knn	VERB
ejpam-5934	316	1	0.9643	0.9643	NUM
ejpam-5934	316	2	0.95	0.95	NUM
ejpam-5934	316	3	0.9640	0.9640	NUM
ejpam-5934	316	4	0.94896	0.94896	NUM
ejpam-5934	316	5	0.96096	0.96096	NUM
ejpam-5934	316	6	0.94598	0.94598	NUM
ejpam-5934	316	7	0.9624	0.9624	NUM
ejpam-5934	317	1	0.9474	0.9474	NUM
ejpam-5934	317	2	0.0714	0.0714	NUM
ejpam-5934	317	3	0.1	0.1	NUM
ejpam-5934	317	4	svm	svm	PROPN
ejpam-5934	317	5	0.9572	0.9572	NUM
ejpam-5934	317	6	0.9357	0.9357	NUM
ejpam-5934	317	7	0.9551	0.9551	NUM
ejpam-5934	317	8	0.9339	0.9339	NUM
ejpam-5934	317	9	0.9551	0.9551	NUM
ejpam-5934	317	10	0.9310	0.9310	NUM
ejpam-5934	317	11	0.9551	0.9551	NUM
ejpam-5934	317	12	0.9324	0.9324	NUM
ejpam-5934	317	13	0.0857	0.0857	NUM
ejpam-5934	317	14	0.1286	0.1286	NUM
ejpam-5934	317	15	kernel	kernel	NOUN
ejpam-5934	317	16	svm	svm	VERB
ejpam-5934	317	17	0.9571	0.9571	NUM
ejpam-5934	317	18	0.9429	0.9429	NUM
ejpam-5934	317	19	0.9551	0.9551	NUM
ejpam-5934	317	20	0.9401	0.9401	NUM
ejpam-5934	317	21	0.9551	0.9551	NUM
ejpam-5934	317	22	0.9401	0.9401	NUM
ejpam-5934	317	23	0.9551	0.9551	NUM
ejpam-5934	317	24	0.9401	0.9401	NUM
ejpam-5934	317	25	0.0857	0.0857	NUM
ejpam-5934	317	26	0.1143	0.1143	NOUN
ejpam-5934	317	27	nb	nb	ADP
ejpam-5934	317	28	0.9643	0.9643	NUM
ejpam-5934	317	29	0.9429	0.9429	NUM
ejpam-5934	317	30	0.9594	0.9594	NUM
ejpam-5934	317	31	0.9401	0.9401	NUM
ejpam-5934	317	32	0.9674	0.9674	NUM
ejpam-5934	317	33	0.9401	0.9401	NUM
ejpam-5934	317	34	0.9629	0.9629	NUM
ejpam-5934	317	35	0.9401	0.9401	NUM
ejpam-5934	317	36	0.0714	0.0714	NUM
ejpam-5934	317	37	0.1143	0.1143	NUM
ejpam-5934	317	38	dt	dt	X
ejpam-5934	317	39	0.9357	0.9357	NUM
ejpam-5934	317	40	0.9286	0.9286	NUM
ejpam-5934	317	41	0.9461	0.9461	NUM
ejpam-5934	317	42	0.9356	0.9356	NUM
ejpam-5934	317	43	0.9214	0.9214	NUM
ejpam-5934	317	44	0.9155	0.9155	NUM
ejpam-5934	317	45	0.9309	0.9309	NUM
ejpam-5934	317	46	0.9235	0.9235	NUM
ejpam-5934	317	47	0.1286	0.1286	NUM
ejpam-5934	317	48	0.1429	0.1429	NUM
ejpam-5934	317	49	rf	rf	NOUN
ejpam-5934	317	50	0.9286	0.9286	NUM
ejpam-5934	317	51	0.9429	0.9429	NUM
ejpam-5934	317	52	0.9313	0.9313	NUM
ejpam-5934	317	53	0.9467	0.9467	NUM
ejpam-5934	317	54	0.9187	0.9187	NUM
ejpam-5934	317	55	0.9337	0.9337	NUM
ejpam-5934	317	56	0.9241	0.9241	NUM
ejpam-5934	317	57	0.9393	0.9393	NUM
ejpam-5934	317	58	0.1429	0.1429	NUM
ejpam-5934	317	59	0.1143	0.1143	NOUN
ejpam-5934	317	60	in	in	ADP
ejpam-5934	317	61	conclusion	conclusion	NOUN
ejpam-5934	317	62	,	,	PUNCT
ejpam-5934	317	63	the	the	DET
ejpam-5934	317	64	comparison	comparison	NOUN
ejpam-5934	317	65	of	of	ADP
ejpam-5934	317	66	results	result	NOUN
ejpam-5934	317	67	before	before	ADV
ejpam-5934	317	68	and	and	CCONJ
ejpam-5934	317	69	after	after	ADP
ejpam-5934	317	70	applying	apply	VERB
ejpam-5934	317	71	rst	rst	NOUN
ejpam-5934	317	72	feature	feature	NOUN
ejpam-5934	317	73	selection	selection	NOUN
ejpam-5934	317	74	highlights	highlight	VERB
ejpam-5934	317	75	its	its	PRON
ejpam-5934	317	76	significant	significant	ADJ
ejpam-5934	317	77	impact	impact	NOUN
ejpam-5934	317	78	on	on	ADP
ejpam-5934	317	79	enhancing	enhance	VERB
ejpam-5934	317	80	classification	classification	NOUN
ejpam-5934	317	81	performance	performance	NOUN
ejpam-5934	317	82	across	across	ADP
ejpam-5934	317	83	various	various	ADJ
ejpam-5934	317	84	datasets	dataset	NOUN
ejpam-5934	317	85	.	.	PUNCT
ejpam-5934	318	1	rst	rst	PROPN
ejpam-5934	318	2	consistently	consistently	ADV
ejpam-5934	318	3	improves	improve	VERB
ejpam-5934	318	4	or	or	CCONJ
ejpam-5934	318	5	maintains	maintain	VERB
ejpam-5934	318	6	high	high	ADJ
ejpam-5934	318	7	performance	performance	NOUN
ejpam-5934	318	8	for	for	ADP
ejpam-5934	318	9	multiple	multiple	ADJ
ejpam-5934	318	10	ml	ml	NOUN
ejpam-5934	318	11	models	model	NOUN
ejpam-5934	318	12	.	.	PUNCT
ejpam-5934	319	1	while	while	SCONJ
ejpam-5934	319	2	some	some	DET
ejpam-5934	319	3	models	model	NOUN
ejpam-5934	319	4	,	,	PUNCT
ejpam-5934	319	5	such	such	ADJ
ejpam-5934	319	6	as	as	ADP
ejpam-5934	319	7	lr	lr	NOUN
ejpam-5934	319	8	and	and	CCONJ
ejpam-5934	319	9	kernel	kernel	PROPN
ejpam-5934	319	10	svm	svm	PROPN
ejpam-5934	319	11	,	,	PUNCT
ejpam-5934	319	12	show	show	VERB
ejpam-5934	319	13	considerable	considerable	ADJ
ejpam-5934	319	14	improvements	improvement	NOUN
ejpam-5934	319	15	,	,	PUNCT
ejpam-5934	319	16	others	other	NOUN
ejpam-5934	319	17	like	like	ADP
ejpam-5934	319	18	rf	rf	PRON
ejpam-5934	319	19	exhibit	exhibit	VERB
ejpam-5934	319	20	slight	slight	ADJ
ejpam-5934	319	21	variations	variation	NOUN
ejpam-5934	319	22	in	in	ADP
ejpam-5934	319	23	performance	performance	NOUN
ejpam-5934	319	24	,	,	PUNCT
ejpam-5934	319	25	yet	yet	CCONJ
ejpam-5934	319	26	still	still	ADV
ejpam-5934	319	27	retain	retain	VERB
ejpam-5934	319	28	their	their	PRON
ejpam-5934	319	29	robustness	robustness	NOUN
ejpam-5934	319	30	.	.	PUNCT
ejpam-5934	320	1	overall	overall	ADV
ejpam-5934	320	2	,	,	PUNCT
ejpam-5934	320	3	rst	rst	PROPN
ejpam-5934	320	4	proves	prove	VERB
ejpam-5934	320	5	to	to	PART
ejpam-5934	320	6	be	be	AUX
ejpam-5934	320	7	an	an	DET
ejpam-5934	320	8	effective	effective	ADJ
ejpam-5934	320	9	method	method	NOUN
ejpam-5934	320	10	for	for	ADP
ejpam-5934	320	11	reducing	reduce	VERB
ejpam-5934	320	12	dimensionality	dimensionality	NOUN
ejpam-5934	320	13	while	while	SCONJ
ejpam-5934	320	14	preserving	preserve	VERB
ejpam-5934	320	15	or	or	CCONJ
ejpam-5934	320	16	enhancing	enhance	VERB
ejpam-5934	320	17	essential	essential	ADJ
ejpam-5934	320	18	classification	classification	NOUN
ejpam-5934	320	19	capabilities	capability	NOUN
ejpam-5934	320	20	,	,	PUNCT
ejpam-5934	320	21	thus	thus	ADV
ejpam-5934	320	22	improving	improve	VERB
ejpam-5934	320	23	model	model	NOUN
ejpam-5934	320	24	efficiency	efficiency	NOUN
ejpam-5934	320	25	and	and	CCONJ
ejpam-5934	320	26	performance	performance	NOUN
ejpam-5934	320	27	across	across	ADP
ejpam-5934	320	28	diverse	diverse	ADJ
ejpam-5934	320	29	datasets	dataset	NOUN
ejpam-5934	320	30	.	.	PUNCT
ejpam-5934	321	1	t.	t.	ADJ
ejpam-5934	321	2	ashika	ashika	PROPN
ejpam-5934	321	3	,	,	PUNCT
ejpam-5934	321	4	g.	g.	PROPN
ejpam-5934	321	5	h.	h.	PROPN
ejpam-5934	321	6	grace	grace	PROPN
ejpam-5934	321	7	/	/	SYM
ejpam-5934	321	8	eur	eur	PROPN
ejpam-5934	321	9	.	.	PUNCT
ejpam-5934	322	1	j.	j.	PROPN
ejpam-5934	322	2	pure	pure	PROPN
ejpam-5934	322	3	appl	appl	PROPN
ejpam-5934	322	4	.	.	PROPN
ejpam-5934	322	5	math	math	PROPN
ejpam-5934	322	6	,	,	PUNCT
ejpam-5934	322	7	18	18	NUM
ejpam-5934	322	8	(	(	PUNCT
ejpam-5934	322	9	2	2	NUM
ejpam-5934	322	10	)	)	PUNCT
ejpam-5934	322	11	(	(	PUNCT
ejpam-5934	322	12	2025	2025	NUM
ejpam-5934	322	13	)	)	PUNCT
ejpam-5934	322	14	,	,	PUNCT
ejpam-5934	322	15	5934	5934	NUM
ejpam-5934	322	16	18	18	NUM
ejpam-5934	322	17	of	of	ADP
ejpam-5934	322	18	22	22	NUM
ejpam-5934	322	19	3.6	3.6	NUM
ejpam-5934	322	20	.	.	PUNCT
ejpam-5934	323	1	statistical	statistical	ADJ
ejpam-5934	323	2	validation	validation	NOUN
ejpam-5934	323	3	in	in	ADP
ejpam-5934	323	4	this	this	DET
ejpam-5934	323	5	study	study	NOUN
ejpam-5934	323	6	,	,	PUNCT
ejpam-5934	323	7	the	the	DET
ejpam-5934	323	8	impact	impact	NOUN
ejpam-5934	323	9	of	of	ADP
ejpam-5934	323	10	rst	rst	PROPN
ejpam-5934	323	11	based	base	VERB
ejpam-5934	323	12	feature	feature	NOUN
ejpam-5934	323	13	selection	selection	NOUN
ejpam-5934	323	14	on	on	ADP
ejpam-5934	323	15	the	the	DET
ejpam-5934	323	16	performance	performance	NOUN
ejpam-5934	323	17	of	of	ADP
ejpam-5934	323	18	classification	classification	NOUN
ejpam-5934	323	19	models	model	NOUN
ejpam-5934	323	20	across	across	ADP
ejpam-5934	323	21	five	five	NUM
ejpam-5934	323	22	datasets	dataset	NOUN
ejpam-5934	323	23	was	be	AUX
ejpam-5934	323	24	evaluated	evaluate	VERB
ejpam-5934	323	25	.	.	PUNCT
ejpam-5934	324	1	to	to	PART
ejpam-5934	324	2	statistically	statistically	ADV
ejpam-5934	324	3	validate	validate	VERB
ejpam-5934	324	4	the	the	DET
ejpam-5934	324	5	observed	observed	ADJ
ejpam-5934	324	6	improvements	improvement	NOUN
ejpam-5934	324	7	,	,	PUNCT
ejpam-5934	324	8	paired	pair	VERB
ejpam-5934	324	9	t	t	NOUN
ejpam-5934	324	10	-	-	PUNCT
ejpam-5934	324	11	tests	test	NOUN
ejpam-5934	324	12	on	on	ADP
ejpam-5934	324	13	performance	performance	NOUN
ejpam-5934	324	14	metrics	metric	NOUN
ejpam-5934	324	15	was	be	AUX
ejpam-5934	324	16	conducted	conduct	VERB
ejpam-5934	324	17	,	,	PUNCT
ejpam-5934	324	18	comparing	compare	VERB
ejpam-5934	324	19	model	model	NOUN
ejpam-5934	324	20	results	result	NOUN
ejpam-5934	324	21	before	before	ADP
ejpam-5934	324	22	and	and	CCONJ
ejpam-5934	324	23	after	after	ADP
ejpam-5934	324	24	rst	rst	NOUN
ejpam-5934	324	25	-	-	PUNCT
ejpam-5934	324	26	based	base	VERB
ejpam-5934	324	27	feature	feature	NOUN
ejpam-5934	324	28	selection	selection	NOUN
ejpam-5934	324	29	.	.	PUNCT
ejpam-5934	325	1	the	the	DET
ejpam-5934	325	2	p	p	NOUN
ejpam-5934	325	3	-	-	PUNCT
ejpam-5934	325	4	values	value	NOUN
ejpam-5934	325	5	for	for	ADP
ejpam-5934	325	6	each	each	DET
ejpam-5934	325	7	performance	performance	NOUN
ejpam-5934	325	8	metric	metric	ADJ
ejpam-5934	325	9	across	across	ADP
ejpam-5934	325	10	the	the	DET
ejpam-5934	325	11	five	five	NUM
ejpam-5934	325	12	datasets	dataset	NOUN
ejpam-5934	325	13	are	be	AUX
ejpam-5934	325	14	summarized	summarize	VERB
ejpam-5934	325	15	in	in	ADP
ejpam-5934	325	16	table	table	NOUN
ejpam-5934	325	17	10	10	NUM
ejpam-5934	325	18	.	.	PUNCT
ejpam-5934	326	1	table	table	NOUN
ejpam-5934	326	2	10	10	NUM
ejpam-5934	326	3	:	:	PUNCT
ejpam-5934	326	4	p	p	X
ejpam-5934	326	5	-	-	PUNCT
ejpam-5934	326	6	values	value	NOUN
ejpam-5934	326	7	from	from	ADP
ejpam-5934	326	8	paired	pair	VERB
ejpam-5934	326	9	t	t	NOUN
ejpam-5934	326	10	-	-	PUNCT
ejpam-5934	326	11	tests	test	NOUN
ejpam-5934	326	12	comparing	compare	VERB
ejpam-5934	326	13	performance	performance	NOUN
ejpam-5934	326	14	metrics	metric	NOUN
ejpam-5934	326	15	before	before	ADV
ejpam-5934	326	16	and	and	CCONJ
ejpam-5934	326	17	after	after	ADP
ejpam-5934	326	18	rst	rst	NOUN
ejpam-5934	326	19	-	-	PUNCT
ejpam-5934	326	20	based	base	VERB
ejpam-5934	326	21	feature	feature	NOUN
ejpam-5934	326	22	selection	selection	NOUN
ejpam-5934	326	23	metric	metric	ADJ
ejpam-5934	326	24	seeds	seed	NOUN
ejpam-5934	326	25	heart	heart	NOUN
ejpam-5934	326	26	attack	attack	NOUN
ejpam-5934	326	27	obesity	obesity	NOUN
ejpam-5934	326	28	online	online	ADJ
ejpam-5934	326	29	food	food	NOUN
ejpam-5934	326	30	delivery	delivery	NOUN
ejpam-5934	326	31	breast	breast	NOUN
ejpam-5934	326	32	cancer	cancer	NOUN
ejpam-5934	326	33	accuracy	accuracy	NOUN
ejpam-5934	326	34	0.1536	0.1536	NUM
ejpam-5934	326	35	0.3559	0.3559	NUM
ejpam-5934	326	36	0.5902	0.5902	NUM
ejpam-5934	326	37	0.0524	0.0524	NUM
ejpam-5934	326	38	0.00468	0.00468	NUM
ejpam-5934	326	39	precision	precision	NOUN
ejpam-5934	326	40	0.0455	0.0455	NUM
ejpam-5934	327	1	0.3559	0.3559	NUM
ejpam-5934	327	2	0.0001	0.0001	NUM
ejpam-5934	327	3	0.0632	0.0632	NUM
ejpam-5934	327	4	0.00122	0.00122	NUM
ejpam-5934	327	5	recall	recall	VERB
ejpam-5934	327	6	0.8392	0.8392	NUM
ejpam-5934	327	7	0.2814	0.2814	NUM
ejpam-5934	327	8	0.0042	0.0042	NUM
ejpam-5934	327	9	0.0489	0.0489	NUM
ejpam-5934	327	10	0.00254	0.00254	NUM
ejpam-5934	327	11	f1	f1	NOUN
ejpam-5934	327	12	score	score	NOUN
ejpam-5934	327	13	0.2754	0.2754	NUM
ejpam-5934	327	14	0.2743	0.2743	NUM
ejpam-5934	327	15	0.0827	0.0827	NUM
ejpam-5934	327	16	0.0522	0.0522	NUM
ejpam-5934	327	17	0.00248	0.00248	NUM
ejpam-5934	327	18	based	base	VERB
ejpam-5934	327	19	on	on	ADP
ejpam-5934	327	20	the	the	DET
ejpam-5934	327	21	results	result	NOUN
ejpam-5934	327	22	presented	present	VERB
ejpam-5934	327	23	in	in	ADP
ejpam-5934	327	24	table	table	NOUN
ejpam-5934	327	25	10	10	NUM
ejpam-5934	327	26	,	,	PUNCT
ejpam-5934	327	27	the	the	DET
ejpam-5934	327	28	paired	pair	VERB
ejpam-5934	327	29	t	t	NOUN
ejpam-5934	327	30	-	-	PUNCT
ejpam-5934	327	31	tests	test	NOUN
ejpam-5934	327	32	confirm	confirm	VERB
ejpam-5934	327	33	that	that	PRON
ejpam-5934	327	34	precision	precision	NOUN
ejpam-5934	327	35	and	and	CCONJ
ejpam-5934	327	36	recall	recall	NOUN
ejpam-5934	327	37	show	show	VERB
ejpam-5934	327	38	statistically	statistically	ADV
ejpam-5934	327	39	significant	significant	ADJ
ejpam-5934	327	40	improvements	improvement	NOUN
ejpam-5934	327	41	in	in	ADP
ejpam-5934	327	42	several	several	ADJ
ejpam-5934	327	43	datasets	dataset	NOUN
ejpam-5934	327	44	,	,	PUNCT
ejpam-5934	327	45	particularly	particularly	ADV
ejpam-5934	327	46	obesity	obesity	NOUN
ejpam-5934	327	47	,	,	PUNCT
ejpam-5934	327	48	online	online	ADJ
ejpam-5934	327	49	food	food	NOUN
ejpam-5934	327	50	delivery	delivery	NOUN
ejpam-5934	327	51	,	,	PUNCT
ejpam-5934	327	52	and	and	CCONJ
ejpam-5934	327	53	breast	breast	NOUN
ejpam-5934	327	54	cancer	cancer	NOUN
ejpam-5934	327	55	.	.	PUNCT
ejpam-5934	328	1	this	this	PRON
ejpam-5934	328	2	indicates	indicate	VERB
ejpam-5934	328	3	that	that	SCONJ
ejpam-5934	328	4	rst	rst	NOUN
ejpam-5934	328	5	-	-	PUNCT
ejpam-5934	328	6	based	base	VERB
ejpam-5934	328	7	feature	feature	NOUN
ejpam-5934	328	8	selection	selection	NOUN
ejpam-5934	328	9	enhances	enhance	VERB
ejpam-5934	328	10	the	the	DET
ejpam-5934	328	11	model	model	NOUN
ejpam-5934	328	12	’s	’s	PART
ejpam-5934	328	13	ability	ability	NOUN
ejpam-5934	328	14	to	to	PART
ejpam-5934	328	15	accurately	accurately	ADV
ejpam-5934	328	16	identify	identify	VERB
ejpam-5934	328	17	and	and	CCONJ
ejpam-5934	328	18	classify	classify	VERB
ejpam-5934	328	19	positive	positive	ADJ
ejpam-5934	328	20	instances	instance	NOUN
ejpam-5934	328	21	.	.	PUNCT
ejpam-5934	329	1	while	while	SCONJ
ejpam-5934	329	2	accuracy	accuracy	NOUN
ejpam-5934	329	3	did	do	AUX
ejpam-5934	329	4	not	not	PART
ejpam-5934	329	5	significantly	significantly	ADV
ejpam-5934	329	6	improve	improve	VERB
ejpam-5934	329	7	in	in	ADP
ejpam-5934	329	8	most	most	ADJ
ejpam-5934	329	9	cases	case	NOUN
ejpam-5934	329	10	,	,	PUNCT
ejpam-5934	329	11	marginal	marginal	ADJ
ejpam-5934	329	12	gains	gain	NOUN
ejpam-5934	329	13	were	be	AUX
ejpam-5934	329	14	observed	observe	VERB
ejpam-5934	329	15	in	in	ADP
ejpam-5934	329	16	the	the	DET
ejpam-5934	329	17	online	online	ADJ
ejpam-5934	329	18	food	food	NOUN
ejpam-5934	329	19	delivery	delivery	NOUN
ejpam-5934	329	20	and	and	CCONJ
ejpam-5934	329	21	breast	breast	NOUN
ejpam-5934	329	22	cancer	cancer	NOUN
ejpam-5934	329	23	datasets	dataset	NOUN
ejpam-5934	329	24	.	.	PUNCT
ejpam-5934	330	1	similarly	similarly	ADV
ejpam-5934	330	2	,	,	PUNCT
ejpam-5934	330	3	f1	f1	NOUN
ejpam-5934	330	4	-	-	PUNCT
ejpam-5934	330	5	score	score	NOUN
ejpam-5934	330	6	showed	show	VERB
ejpam-5934	330	7	borderline	borderline	NOUN
ejpam-5934	330	8	significance	significance	NOUN
ejpam-5934	330	9	in	in	ADP
ejpam-5934	330	10	some	some	DET
ejpam-5934	330	11	scenarios	scenario	NOUN
ejpam-5934	330	12	,	,	PUNCT
ejpam-5934	330	13	suggesting	suggest	VERB
ejpam-5934	330	14	a	a	DET
ejpam-5934	330	15	balanced	balanced	ADJ
ejpam-5934	330	16	enhancement	enhancement	NOUN
ejpam-5934	330	17	in	in	ADP
ejpam-5934	330	18	both	both	DET
ejpam-5934	330	19	precision	precision	NOUN
ejpam-5934	330	20	and	and	CCONJ
ejpam-5934	330	21	recall	recall	NOUN
ejpam-5934	330	22	.	.	PUNCT
ejpam-5934	331	1	by	by	ADP
ejpam-5934	331	2	evaluating	evaluate	VERB
ejpam-5934	331	3	a	a	DET
ejpam-5934	331	4	range	range	NOUN
ejpam-5934	331	5	of	of	ADP
ejpam-5934	331	6	performance	performance	NOUN
ejpam-5934	331	7	metrics	metric	NOUN
ejpam-5934	331	8	,	,	PUNCT
ejpam-5934	331	9	comprehensive	comprehensive	ADJ
ejpam-5934	331	10	assessment	assessment	NOUN
ejpam-5934	331	11	of	of	ADP
ejpam-5934	331	12	model	model	NOUN
ejpam-5934	331	13	behaviour	behaviour	NOUN
ejpam-5934	331	14	is	be	AUX
ejpam-5934	331	15	ensured	ensure	VERB
ejpam-5934	331	16	.	.	PUNCT
ejpam-5934	332	1	notably	notably	ADV
ejpam-5934	332	2	,	,	PUNCT
ejpam-5934	332	3	improvements	improvement	NOUN
ejpam-5934	332	4	in	in	ADP
ejpam-5934	332	5	precision	precision	NOUN
ejpam-5934	332	6	and	and	CCONJ
ejpam-5934	332	7	recall	recall	NOUN
ejpam-5934	332	8	are	be	AUX
ejpam-5934	332	9	especially	especially	ADV
ejpam-5934	332	10	critical	critical	ADJ
ejpam-5934	332	11	in	in	ADP
ejpam-5934	332	12	medical	medical	ADJ
ejpam-5934	332	13	and	and	CCONJ
ejpam-5934	332	14	sensitive	sensitive	ADJ
ejpam-5934	332	15	applications	application	NOUN
ejpam-5934	332	16	,	,	PUNCT
ejpam-5934	332	17	where	where	SCONJ
ejpam-5934	332	18	minimizing	minimize	VERB
ejpam-5934	332	19	false	false	ADJ
ejpam-5934	332	20	positives	positive	NOUN
ejpam-5934	332	21	and	and	CCONJ
ejpam-5934	332	22	false	false	ADJ
ejpam-5934	332	23	negatives	negative	NOUN
ejpam-5934	332	24	is	be	AUX
ejpam-5934	332	25	essential	essential	ADJ
ejpam-5934	332	26	.	.	PUNCT
ejpam-5934	333	1	the	the	DET
ejpam-5934	333	2	inclusion	inclusion	NOUN
ejpam-5934	333	3	of	of	ADP
ejpam-5934	333	4	statistical	statistical	ADJ
ejpam-5934	333	5	validation	validation	NOUN
ejpam-5934	333	6	addresses	address	NOUN
ejpam-5934	333	7	the	the	DET
ejpam-5934	333	8	credibility	credibility	NOUN
ejpam-5934	333	9	of	of	ADP
ejpam-5934	333	10	the	the	DET
ejpam-5934	333	11	findings	finding	NOUN
ejpam-5934	333	12	.	.	PUNCT
ejpam-5934	334	1	these	these	DET
ejpam-5934	334	2	results	result	NOUN
ejpam-5934	334	3	support	support	VERB
ejpam-5934	334	4	the	the	DET
ejpam-5934	334	5	conclusion	conclusion	NOUN
ejpam-5934	334	6	that	that	SCONJ
ejpam-5934	334	7	rst	rst	VERB
ejpam-5934	334	8	-	-	PUNCT
ejpam-5934	334	9	based	base	VERB
ejpam-5934	334	10	feature	feature	NOUN
ejpam-5934	334	11	selection	selection	NOUN
ejpam-5934	334	12	is	be	AUX
ejpam-5934	334	13	an	an	DET
ejpam-5934	334	14	effective	effective	ADJ
ejpam-5934	334	15	and	and	CCONJ
ejpam-5934	334	16	valuable	valuable	ADJ
ejpam-5934	334	17	technique	technique	NOUN
ejpam-5934	334	18	for	for	ADP
ejpam-5934	334	19	enhancing	enhance	VERB
ejpam-5934	334	20	classification	classification	NOUN
ejpam-5934	334	21	performance	performance	NOUN
ejpam-5934	334	22	across	across	ADP
ejpam-5934	334	23	diverse	diverse	ADJ
ejpam-5934	334	24	datasets	dataset	NOUN
ejpam-5934	334	25	,	,	PUNCT
ejpam-5934	334	26	reinforcing	reinforce	VERB
ejpam-5934	334	27	its	its	PRON
ejpam-5934	334	28	potential	potential	NOUN
ejpam-5934	334	29	for	for	ADP
ejpam-5934	334	30	broader	broad	ADJ
ejpam-5934	334	31	application	application	NOUN
ejpam-5934	334	32	in	in	ADP
ejpam-5934	334	33	ml	ml	NOUN
ejpam-5934	334	34	tasks	task	NOUN
ejpam-5934	334	35	.	.	PUNCT
ejpam-5934	335	1	4	4	X
ejpam-5934	335	2	.	.	X
ejpam-5934	335	3	discussion	discussion	NOUN
ejpam-5934	335	4	although	although	SCONJ
ejpam-5934	335	5	rst	rst	PROPN
ejpam-5934	335	6	may	may	AUX
ejpam-5934	335	7	result	result	VERB
ejpam-5934	335	8	in	in	ADP
ejpam-5934	335	9	marginally	marginally	ADV
ejpam-5934	335	10	lower	low	ADJ
ejpam-5934	335	11	classification	classification	NOUN
ejpam-5934	335	12	metrics	metric	NOUN
ejpam-5934	335	13	in	in	ADP
ejpam-5934	335	14	certain	certain	ADJ
ejpam-5934	335	15	cases	case	NOUN
ejpam-5934	335	16	,	,	PUNCT
ejpam-5934	335	17	its	its	PRON
ejpam-5934	335	18	value	value	NOUN
ejpam-5934	335	19	extends	extend	VERB
ejpam-5934	335	20	beyond	beyond	ADP
ejpam-5934	335	21	predictive	predictive	ADJ
ejpam-5934	335	22	accuracy	accuracy	NOUN
ejpam-5934	335	23	.	.	PUNCT
ejpam-5934	336	1	as	as	ADP
ejpam-5934	336	2	a	a	DET
ejpam-5934	336	3	feature	feature	NOUN
ejpam-5934	336	4	selection	selection	NOUN
ejpam-5934	336	5	method	method	NOUN
ejpam-5934	336	6	,	,	PUNCT
ejpam-5934	336	7	rst	rst	NOUN
ejpam-5934	336	8	excels	excel	NOUN
ejpam-5934	336	9	in	in	ADP
ejpam-5934	336	10	enhancing	enhance	VERB
ejpam-5934	336	11	model	model	NOUN
ejpam-5934	336	12	interpretability	interpretability	NOUN
ejpam-5934	336	13	,	,	PUNCT
ejpam-5934	336	14	reducing	reduce	VERB
ejpam-5934	336	15	computational	computational	ADJ
ejpam-5934	336	16	complexity	complexity	NOUN
ejpam-5934	336	17	,	,	PUNCT
ejpam-5934	336	18	and	and	CCONJ
ejpam-5934	336	19	minimizing	minimize	VERB
ejpam-5934	336	20	overfitting	overfitting	NOUN
ejpam-5934	336	21	.	.	PUNCT
ejpam-5934	337	1	these	these	DET
ejpam-5934	337	2	advantages	advantage	NOUN
ejpam-5934	337	3	are	be	AUX
ejpam-5934	337	4	particularly	particularly	ADV
ejpam-5934	337	5	important	important	ADJ
ejpam-5934	337	6	in	in	ADP
ejpam-5934	337	7	fields	field	NOUN
ejpam-5934	337	8	like	like	ADP
ejpam-5934	337	9	healthcare	healthcare	NOUN
ejpam-5934	337	10	,	,	PUNCT
ejpam-5934	337	11	where	where	SCONJ
ejpam-5934	337	12	both	both	DET
ejpam-5934	337	13	transparency	transparency	NOUN
ejpam-5934	337	14	and	and	CCONJ
ejpam-5934	337	15	efficiency	efficiency	NOUN
ejpam-5934	337	16	are	be	AUX
ejpam-5934	337	17	crucial	crucial	ADJ
ejpam-5934	337	18	.	.	PUNCT
ejpam-5934	338	1	the	the	DET
ejpam-5934	338	2	results	result	NOUN
ejpam-5934	338	3	of	of	ADP
ejpam-5934	338	4	this	this	DET
ejpam-5934	338	5	study	study	NOUN
ejpam-5934	338	6	indicate	indicate	VERB
ejpam-5934	338	7	that	that	SCONJ
ejpam-5934	338	8	rst	rst	VERB
ejpam-5934	338	9	-	-	PUNCT
ejpam-5934	338	10	based	base	VERB
ejpam-5934	338	11	feature	feature	NOUN
ejpam-5934	338	12	selection	selection	NOUN
ejpam-5934	338	13	consistently	consistently	ADV
ejpam-5934	338	14	preserves	preserve	VERB
ejpam-5934	338	15	or	or	CCONJ
ejpam-5934	338	16	improves	improve	VERB
ejpam-5934	338	17	classification	classification	NOUN
ejpam-5934	338	18	performance	performance	NOUN
ejpam-5934	338	19	across	across	ADP
ejpam-5934	338	20	various	various	ADJ
ejpam-5934	338	21	datasets	dataset	NOUN
ejpam-5934	338	22	.	.	PUNCT
ejpam-5934	339	1	for	for	ADP
ejpam-5934	339	2	instance	instance	NOUN
ejpam-5934	339	3	,	,	PUNCT
ejpam-5934	339	4	in	in	ADP
ejpam-5934	339	5	the	the	DET
ejpam-5934	339	6	high	high	ADV
ejpam-5934	339	7	-	-	PUNCT
ejpam-5934	339	8	dimensional	dimensional	ADJ
ejpam-5934	339	9	online	online	ADJ
ejpam-5934	339	10	food	food	NOUN
ejpam-5934	339	11	delivery	delivery	NOUN
ejpam-5934	339	12	dataset	dataset	NOUN
ejpam-5934	339	13	(	(	PUNCT
ejpam-5934	339	14	54	54	NUM
ejpam-5934	339	15	features	feature	NOUN
ejpam-5934	339	16	)	)	PUNCT
ejpam-5934	339	17	,	,	PUNCT
ejpam-5934	339	18	rst	rst	PROPN
ejpam-5934	339	19	reduced	reduce	VERB
ejpam-5934	339	20	the	the	DET
ejpam-5934	339	21	feature	feature	NOUN
ejpam-5934	339	22	set	set	VERB
ejpam-5934	339	23	to	to	ADP
ejpam-5934	339	24	just	just	ADV
ejpam-5934	339	25	4	4	NUM
ejpam-5934	339	26	attributes	attribute	NOUN
ejpam-5934	339	27	,	,	PUNCT
ejpam-5934	339	28	improving	improve	VERB
ejpam-5934	339	29	knn	knn	NOUN
ejpam-5934	339	30	accuracy	accuracy	NOUN
ejpam-5934	339	31	from	from	ADP
ejpam-5934	339	32	0.7216	0.7216	NUM
ejpam-5934	339	33	to	to	ADP
ejpam-5934	339	34	0.7564	0.7564	NUM
ejpam-5934	339	35	.	.	PUNCT
ejpam-5934	340	1	in	in	ADP
ejpam-5934	340	2	the	the	DET
ejpam-5934	340	3	low	low	ADJ
ejpam-5934	340	4	-	-	PUNCT
ejpam-5934	340	5	dimensional	dimensional	ADJ
ejpam-5934	340	6	seeds	seed	NOUN
ejpam-5934	340	7	dataset	dataset	NOUN
ejpam-5934	340	8	,	,	PUNCT
ejpam-5934	340	9	rst	rst	PROPN
ejpam-5934	340	10	t.	t.	NOUN
ejpam-5934	340	11	ashika	ashika	PROPN
ejpam-5934	340	12	,	,	PUNCT
ejpam-5934	340	13	g.	g.	PROPN
ejpam-5934	340	14	h.	h.	PROPN
ejpam-5934	340	15	grace	grace	PROPN
ejpam-5934	340	16	/	/	SYM
ejpam-5934	340	17	eur	eur	PROPN
ejpam-5934	340	18	.	.	PUNCT
ejpam-5934	341	1	j.	j.	PROPN
ejpam-5934	341	2	pure	pure	PROPN
ejpam-5934	341	3	appl	appl	PROPN
ejpam-5934	341	4	.	.	PROPN
ejpam-5934	341	5	math	math	PROPN
ejpam-5934	341	6	,	,	PUNCT
ejpam-5934	341	7	18	18	NUM
ejpam-5934	341	8	(	(	PUNCT
ejpam-5934	341	9	2	2	NUM
ejpam-5934	341	10	)	)	PUNCT
ejpam-5934	341	11	(	(	PUNCT
ejpam-5934	341	12	2025	2025	NUM
ejpam-5934	341	13	)	)	PUNCT
ejpam-5934	341	14	,	,	PUNCT
ejpam-5934	341	15	5934	5934	NUM
ejpam-5934	341	16	19	19	NUM
ejpam-5934	341	17	of	of	ADP
ejpam-5934	341	18	22	22	NUM
ejpam-5934	341	19	reduced	reduce	VERB
ejpam-5934	341	20	the	the	DET
ejpam-5934	341	21	features	feature	NOUN
ejpam-5934	341	22	from	from	ADP
ejpam-5934	341	23	7	7	NUM
ejpam-5934	341	24	to	to	ADP
ejpam-5934	341	25	2	2	NUM
ejpam-5934	341	26	,	,	PUNCT
ejpam-5934	341	27	increasing	increase	VERB
ejpam-5934	341	28	svm	svm	ADJ
ejpam-5934	341	29	accuracy	accuracy	NOUN
ejpam-5934	341	30	from	from	ADP
ejpam-5934	341	31	0.9421	0.9421	NUM
ejpam-5934	341	32	to	to	ADP
ejpam-5934	341	33	0.9649	0.9649	NUM
ejpam-5934	341	34	.	.	PUNCT
ejpam-5934	342	1	larger	large	ADJ
ejpam-5934	342	2	datasets	dataset	NOUN
ejpam-5934	342	3	,	,	PUNCT
ejpam-5934	342	4	such	such	ADJ
ejpam-5934	342	5	as	as	ADP
ejpam-5934	342	6	the	the	DET
ejpam-5934	342	7	breast	breast	NOUN
ejpam-5934	342	8	cancer	cancer	NOUN
ejpam-5934	342	9	dataset	dataset	NOUN
ejpam-5934	342	10	(	(	PUNCT
ejpam-5934	342	11	699	699	NUM
ejpam-5934	342	12	instances	instance	NOUN
ejpam-5934	342	13	)	)	PUNCT
ejpam-5934	342	14	,	,	PUNCT
ejpam-5934	342	15	also	also	ADV
ejpam-5934	342	16	showed	show	VERB
ejpam-5934	342	17	improvements	improvement	NOUN
ejpam-5934	342	18	(	(	PUNCT
ejpam-5934	342	19	e.g.	e.g.	ADV
ejpam-5934	342	20	,	,	PUNCT
ejpam-5934	342	21	rf	rf	ADJ
ejpam-5934	342	22	accuracy	accuracy	NOUN
ejpam-5934	342	23	increased	increase	VERB
ejpam-5934	342	24	from	from	ADP
ejpam-5934	342	25	0.9286	0.9286	NUM
ejpam-5934	342	26	to	to	ADP
ejpam-5934	342	27	0.9429	0.9429	NUM
ejpam-5934	342	28	)	)	PUNCT
ejpam-5934	342	29	,	,	PUNCT
ejpam-5934	342	30	demonstrating	demonstrate	VERB
ejpam-5934	342	31	that	that	SCONJ
ejpam-5934	342	32	rst	rst	PROPN
ejpam-5934	342	33	scales	scale	VERB
ejpam-5934	342	34	effectively	effectively	ADV
ejpam-5934	342	35	with	with	ADP
ejpam-5934	342	36	dataset	dataset	ADJ
ejpam-5934	342	37	size	size	NOUN
ejpam-5934	342	38	.	.	PUNCT
ejpam-5934	343	1	model	model	NOUN
ejpam-5934	343	2	-	-	PUNCT
ejpam-5934	343	3	specific	specific	ADJ
ejpam-5934	343	4	analysis	analysis	NOUN
ejpam-5934	343	5	revealed	reveal	VERB
ejpam-5934	343	6	that	that	SCONJ
ejpam-5934	343	7	algorithms	algorithm	NOUN
ejpam-5934	343	8	sensitive	sensitive	ADJ
ejpam-5934	343	9	to	to	ADP
ejpam-5934	343	10	feature	feature	NOUN
ejpam-5934	343	11	space	space	NOUN
ejpam-5934	343	12	,	,	PUNCT
ejpam-5934	343	13	such	such	ADJ
ejpam-5934	343	14	as	as	ADP
ejpam-5934	343	15	lr	lr	NOUN
ejpam-5934	343	16	and	and	CCONJ
ejpam-5934	343	17	svm	svm	PROPN
ejpam-5934	343	18	,	,	PUNCT
ejpam-5934	343	19	benefitted	benefit	VERB
ejpam-5934	343	20	the	the	DET
ejpam-5934	343	21	most	most	ADJ
ejpam-5934	343	22	from	from	ADP
ejpam-5934	343	23	rst	rst	PROPN
ejpam-5934	343	24	,	,	PUNCT
ejpam-5934	343	25	as	as	SCONJ
ejpam-5934	343	26	seen	see	VERB
ejpam-5934	343	27	in	in	ADP
ejpam-5934	343	28	the	the	DET
ejpam-5934	343	29	seeds	seed	NOUN
ejpam-5934	343	30	dataset	dataset	NOUN
ejpam-5934	343	31	,	,	PUNCT
ejpam-5934	343	32	where	where	SCONJ
ejpam-5934	343	33	lr	lr	NOUN
ejpam-5934	343	34	improved	improve	VERB
ejpam-5934	343	35	from	from	ADP
ejpam-5934	343	36	0.9245	0.9245	NUM
ejpam-5934	343	37	to	to	ADP
ejpam-5934	343	38	0.9623	0.9623	NUM
ejpam-5934	343	39	.	.	PUNCT
ejpam-5934	344	1	on	on	ADP
ejpam-5934	344	2	the	the	DET
ejpam-5934	344	3	other	other	ADJ
ejpam-5934	344	4	hand	hand	NOUN
ejpam-5934	344	5	,	,	PUNCT
ejpam-5934	344	6	ensemble	ensemble	ADJ
ejpam-5934	344	7	models	model	NOUN
ejpam-5934	344	8	like	like	ADP
ejpam-5934	344	9	rf	rf	NOUN
ejpam-5934	344	10	,	,	PUNCT
ejpam-5934	344	11	which	which	PRON
ejpam-5934	344	12	are	be	AUX
ejpam-5934	344	13	robust	robust	ADJ
ejpam-5934	344	14	to	to	PART
ejpam-5934	344	15	redundant	redundant	VERB
ejpam-5934	344	16	features	feature	NOUN
ejpam-5934	344	17	,	,	PUNCT
ejpam-5934	344	18	showed	show	VERB
ejpam-5934	344	19	smaller	small	ADJ
ejpam-5934	344	20	improvements	improvement	NOUN
ejpam-5934	344	21	or	or	CCONJ
ejpam-5934	344	22	slight	slight	ADJ
ejpam-5934	344	23	performance	performance	NOUN
ejpam-5934	344	24	degradation	degradation	NOUN
ejpam-5934	344	25	,	,	PUNCT
ejpam-5934	344	26	such	such	ADJ
ejpam-5934	344	27	as	as	ADP
ejpam-5934	344	28	in	in	ADP
ejpam-5934	344	29	the	the	DET
ejpam-5934	344	30	obesity	obesity	NOUN
ejpam-5934	344	31	dataset	dataset	NOUN
ejpam-5934	344	32	(	(	PUNCT
ejpam-5934	344	33	rf	rf	ADJ
ejpam-5934	344	34	accuracy	accuracy	NOUN
ejpam-5934	344	35	dropped	drop	VERB
ejpam-5934	344	36	from	from	ADP
ejpam-5934	344	37	1.0	1.0	NUM
ejpam-5934	344	38	to	to	ADP
ejpam-5934	344	39	0.9091	0.9091	NUM
ejpam-5934	344	40	)	)	PUNCT
ejpam-5934	344	41	.	.	PUNCT
ejpam-5934	345	1	rst	rst	PROPN
ejpam-5934	345	2	’s	’s	PART
ejpam-5934	345	3	impact	impact	NOUN
ejpam-5934	345	4	also	also	ADV
ejpam-5934	345	5	varied	vary	VERB
ejpam-5934	345	6	depending	depend	VERB
ejpam-5934	345	7	on	on	ADP
ejpam-5934	345	8	the	the	DET
ejpam-5934	345	9	dataset	dataset	NOUN
ejpam-5934	345	10	characteristics	characteristic	NOUN
ejpam-5934	345	11	.	.	PUNCT
ejpam-5934	346	1	in	in	ADP
ejpam-5934	346	2	balanced	balanced	ADJ
ejpam-5934	346	3	datasets	dataset	NOUN
ejpam-5934	346	4	like	like	ADP
ejpam-5934	346	5	seeds	seed	NOUN
ejpam-5934	346	6	,	,	PUNCT
ejpam-5934	346	7	improvements	improvement	NOUN
ejpam-5934	346	8	were	be	AUX
ejpam-5934	346	9	consistent	consistent	ADJ
ejpam-5934	346	10	across	across	ADP
ejpam-5934	346	11	classifiers	classifier	NOUN
ejpam-5934	346	12	,	,	PUNCT
ejpam-5934	346	13	while	while	SCONJ
ejpam-5934	346	14	in	in	ADP
ejpam-5934	346	15	imbalanced	imbalanced	ADJ
ejpam-5934	346	16	datasets	dataset	NOUN
ejpam-5934	346	17	like	like	ADP
ejpam-5934	346	18	heart	heart	NOUN
ejpam-5934	346	19	attack	attack	NOUN
ejpam-5934	346	20	,	,	PUNCT
ejpam-5934	346	21	the	the	DET
ejpam-5934	346	22	effects	effect	NOUN
ejpam-5934	346	23	were	be	AUX
ejpam-5934	346	24	more	more	ADV
ejpam-5934	346	25	varied	varied	ADJ
ejpam-5934	346	26	.	.	PUNCT
ejpam-5934	347	1	for	for	ADP
ejpam-5934	347	2	example	example	NOUN
ejpam-5934	347	3	,	,	PUNCT
ejpam-5934	347	4	knn	knn	PROPN
ejpam-5934	347	5	in	in	ADP
ejpam-5934	347	6	heart	heart	NOUN
ejpam-5934	347	7	attack	attack	NOUN
ejpam-5934	347	8	improved	improve	VERB
ejpam-5934	347	9	significantly	significantly	ADV
ejpam-5934	347	10	from	from	ADP
ejpam-5934	347	11	0.625	0.625	NUM
ejpam-5934	347	12	to	to	ADP
ejpam-5934	347	13	0.9811	0.9811	NUM
ejpam-5934	347	14	,	,	PUNCT
ejpam-5934	347	15	likely	likely	ADJ
ejpam-5934	347	16	due	due	ADJ
ejpam-5934	347	17	to	to	ADP
ejpam-5934	347	18	rst	rst	PROPN
ejpam-5934	347	19	’s	’s	PART
ejpam-5934	347	20	focus	focus	NOUN
ejpam-5934	347	21	on	on	ADP
ejpam-5934	347	22	features	feature	NOUN
ejpam-5934	347	23	associated	associate	VERB
ejpam-5934	347	24	with	with	ADP
ejpam-5934	347	25	the	the	DET
ejpam-5934	347	26	majority	majority	NOUN
ejpam-5934	347	27	class	class	NOUN
ejpam-5934	347	28	.	.	PUNCT
ejpam-5934	348	1	despite	despite	SCONJ
ejpam-5934	348	2	these	these	DET
ejpam-5934	348	3	benefits	benefit	NOUN
ejpam-5934	348	4	,	,	PUNCT
ejpam-5934	348	5	rst	rst	PROPN
ejpam-5934	348	6	has	have	VERB
ejpam-5934	348	7	limitations	limitation	NOUN
ejpam-5934	348	8	,	,	PUNCT
ejpam-5934	348	9	including	include	VERB
ejpam-5934	348	10	the	the	DET
ejpam-5934	348	11	need	need	NOUN
ejpam-5934	348	12	for	for	ADP
ejpam-5934	348	13	discretization	discretization	NOUN
ejpam-5934	348	14	of	of	ADP
ejpam-5934	348	15	continuous	continuous	ADJ
ejpam-5934	348	16	attributes	attribute	NOUN
ejpam-5934	348	17	,	,	PUNCT
ejpam-5934	348	18	which	which	PRON
ejpam-5934	348	19	can	can	AUX
ejpam-5934	348	20	introduce	introduce	VERB
ejpam-5934	348	21	quantization	quantization	NOUN
ejpam-5934	348	22	bias	bias	NOUN
ejpam-5934	348	23	or	or	CCONJ
ejpam-5934	348	24	reduce	reduce	VERB
ejpam-5934	348	25	information	information	NOUN
ejpam-5934	348	26	precision	precision	NOUN
ejpam-5934	348	27	.	.	PUNCT
ejpam-5934	349	1	additionally	additionally	ADV
ejpam-5934	349	2	,	,	PUNCT
ejpam-5934	349	3	rst	rst	PROPN
ejpam-5934	349	4	can	can	AUX
ejpam-5934	349	5	be	be	AUX
ejpam-5934	349	6	sensitive	sensitive	ADJ
ejpam-5934	349	7	to	to	ADP
ejpam-5934	349	8	noisy	noisy	ADJ
ejpam-5934	349	9	or	or	CCONJ
ejpam-5934	349	10	overlapping	overlap	VERB
ejpam-5934	349	11	data	datum	NOUN
ejpam-5934	349	12	.	.	PUNCT
ejpam-5934	350	1	the	the	DET
ejpam-5934	350	2	qr	qr	PROPN
ejpam-5934	350	3	algorithm	algorithm	NOUN
ejpam-5934	350	4	,	,	PUNCT
ejpam-5934	350	5	while	while	SCONJ
ejpam-5934	350	6	computationally	computationally	ADV
ejpam-5934	350	7	efficient	efficient	ADJ
ejpam-5934	350	8	,	,	PUNCT
ejpam-5934	350	9	may	may	AUX
ejpam-5934	350	10	not	not	PART
ejpam-5934	350	11	always	always	ADV
ejpam-5934	350	12	identify	identify	VERB
ejpam-5934	350	13	the	the	DET
ejpam-5934	350	14	globally	globally	ADV
ejpam-5934	350	15	optimal	optimal	ADJ
ejpam-5934	350	16	reduct	reduct	NOUN
ejpam-5934	350	17	.	.	PUNCT
ejpam-5934	351	1	future	future	ADJ
ejpam-5934	351	2	research	research	NOUN
ejpam-5934	351	3	could	could	AUX
ejpam-5934	351	4	address	address	VERB
ejpam-5934	351	5	these	these	DET
ejpam-5934	351	6	issues	issue	NOUN
ejpam-5934	351	7	by	by	ADP
ejpam-5934	351	8	integrating	integrate	VERB
ejpam-5934	351	9	advanced	advanced	ADJ
ejpam-5934	351	10	discretization	discretization	NOUN
ejpam-5934	351	11	techniques	technique	NOUN
ejpam-5934	351	12	,	,	PUNCT
ejpam-5934	351	13	noise	noise	NOUN
ejpam-5934	351	14	handling	handling	NOUN
ejpam-5934	351	15	methods	method	NOUN
ejpam-5934	351	16	,	,	PUNCT
ejpam-5934	351	17	and	and	CCONJ
ejpam-5934	351	18	metaheuristic	metaheuristic	ADV
ejpam-5934	351	19	-	-	PUNCT
ejpam-5934	351	20	based	base	VERB
ejpam-5934	351	21	feature	feature	NOUN
ejpam-5934	351	22	selection	selection	NOUN
ejpam-5934	351	23	strategies	strategy	NOUN
ejpam-5934	351	24	to	to	PART
ejpam-5934	351	25	enhance	enhance	VERB
ejpam-5934	351	26	rst	rst	PROPN
ejpam-5934	351	27	’s	’s	PART
ejpam-5934	351	28	robustness	robustness	NOUN
ejpam-5934	351	29	and	and	CCONJ
ejpam-5934	351	30	scalability	scalability	NOUN
ejpam-5934	351	31	.	.	PUNCT
ejpam-5934	352	1	5	5	X
ejpam-5934	352	2	.	.	X
ejpam-5934	352	3	conclusion	conclusion	NOUN
ejpam-5934	352	4	the	the	DET
ejpam-5934	352	5	study	study	NOUN
ejpam-5934	352	6	presents	present	VERB
ejpam-5934	352	7	a	a	DET
ejpam-5934	352	8	two	two	NUM
ejpam-5934	352	9	-	-	PUNCT
ejpam-5934	352	10	phase	phase	NOUN
ejpam-5934	352	11	evaluation	evaluation	NOUN
ejpam-5934	352	12	framework	framework	NOUN
ejpam-5934	352	13	to	to	PART
ejpam-5934	352	14	assess	assess	VERB
ejpam-5934	352	15	the	the	DET
ejpam-5934	352	16	impact	impact	NOUN
ejpam-5934	352	17	of	of	ADP
ejpam-5934	352	18	rst	rst	PROPN
ejpam-5934	352	19	on	on	ADP
ejpam-5934	352	20	classification	classification	NOUN
ejpam-5934	352	21	performance	performance	NOUN
ejpam-5934	352	22	.	.	PUNCT
ejpam-5934	353	1	in	in	ADP
ejpam-5934	353	2	the	the	DET
ejpam-5934	353	3	first	first	ADJ
ejpam-5934	353	4	phase	phase	NOUN
ejpam-5934	353	5	,	,	PUNCT
ejpam-5934	353	6	standard	standard	ADJ
ejpam-5934	353	7	ml	ml	NOUN
ejpam-5934	353	8	models	model	NOUN
ejpam-5934	353	9	are	be	AUX
ejpam-5934	353	10	applied	apply	VERB
ejpam-5934	353	11	to	to	ADP
ejpam-5934	353	12	raw	raw	ADJ
ejpam-5934	353	13	datasets	dataset	NOUN
ejpam-5934	353	14	.	.	PUNCT
ejpam-5934	354	1	in	in	ADP
ejpam-5934	354	2	the	the	DET
ejpam-5934	354	3	second	second	ADJ
ejpam-5934	354	4	phase	phase	NOUN
ejpam-5934	354	5	,	,	PUNCT
ejpam-5934	354	6	rst	rst	NOUN
ejpam-5934	354	7	-	-	PUNCT
ejpam-5934	354	8	based	base	VERB
ejpam-5934	354	9	feature	feature	NOUN
ejpam-5934	354	10	selection	selection	NOUN
ejpam-5934	354	11	was	be	AUX
ejpam-5934	354	12	implemented	implement	VERB
ejpam-5934	354	13	using	use	VERB
ejpam-5934	354	14	the	the	DET
ejpam-5934	354	15	qr	qr	PROPN
ejpam-5934	354	16	algorithm	algorithm	NOUN
ejpam-5934	354	17	,	,	PUNCT
ejpam-5934	354	18	and	and	CCONJ
ejpam-5934	354	19	classifier	classifier	NOUN
ejpam-5934	354	20	performance	performance	NOUN
ejpam-5934	354	21	was	be	AUX
ejpam-5934	354	22	re	re	VERB
ejpam-5934	354	23	-	-	VERB
ejpam-5934	354	24	evaluated	evaluate	VERB
ejpam-5934	354	25	on	on	ADP
ejpam-5934	354	26	the	the	DET
ejpam-5934	354	27	reduced	reduce	VERB
ejpam-5934	354	28	feature	feature	NOUN
ejpam-5934	354	29	sets	set	NOUN
ejpam-5934	354	30	.	.	PUNCT
ejpam-5934	355	1	overall	overall	ADV
ejpam-5934	355	2	,	,	PUNCT
ejpam-5934	355	3	rst	rst	PROPN
ejpam-5934	355	4	generally	generally	ADV
ejpam-5934	355	5	enhanced	enhance	VERB
ejpam-5934	355	6	or	or	CCONJ
ejpam-5934	355	7	maintained	maintain	VERB
ejpam-5934	355	8	classification	classification	NOUN
ejpam-5934	355	9	performance	performance	NOUN
ejpam-5934	355	10	across	across	ADP
ejpam-5934	355	11	the	the	DET
ejpam-5934	355	12	five	five	NUM
ejpam-5934	355	13	datasets	dataset	NOUN
ejpam-5934	355	14	examined	examine	VERB
ejpam-5934	355	15	.	.	PUNCT
ejpam-5934	356	1	notable	notable	ADJ
ejpam-5934	356	2	improvements	improvement	NOUN
ejpam-5934	356	3	were	be	AUX
ejpam-5934	356	4	observed	observe	VERB
ejpam-5934	356	5	for	for	ADP
ejpam-5934	356	6	models	model	NOUN
ejpam-5934	356	7	such	such	ADJ
ejpam-5934	356	8	as	as	ADP
ejpam-5934	356	9	lr	lr	PROPN
ejpam-5934	356	10	,	,	PUNCT
ejpam-5934	356	11	svm	svm	ADJ
ejpam-5934	356	12	,	,	PUNCT
ejpam-5934	356	13	and	and	CCONJ
ejpam-5934	356	14	knn	knn	PROPN
ejpam-5934	356	15	,	,	PUNCT
ejpam-5934	356	16	particularly	particularly	ADV
ejpam-5934	356	17	in	in	ADP
ejpam-5934	356	18	datasets	dataset	NOUN
ejpam-5934	356	19	where	where	SCONJ
ejpam-5934	356	20	redundant	redundant	ADJ
ejpam-5934	356	21	or	or	CCONJ
ejpam-5934	356	22	noisy	noisy	ADJ
ejpam-5934	356	23	features	feature	NOUN
ejpam-5934	356	24	were	be	AUX
ejpam-5934	356	25	effectively	effectively	ADV
ejpam-5934	356	26	eliminated	eliminate	VERB
ejpam-5934	356	27	.	.	PUNCT
ejpam-5934	357	1	however	however	ADV
ejpam-5934	357	2	,	,	PUNCT
ejpam-5934	357	3	slight	slight	ADJ
ejpam-5934	357	4	performance	performance	NOUN
ejpam-5934	357	5	declines	decline	NOUN
ejpam-5934	357	6	occurred	occur	VERB
ejpam-5934	357	7	in	in	ADP
ejpam-5934	357	8	certain	certain	ADJ
ejpam-5934	357	9	cases	case	NOUN
ejpam-5934	357	10	,	,	PUNCT
ejpam-5934	357	11	for	for	ADP
ejpam-5934	357	12	example	example	NOUN
ejpam-5934	357	13	,	,	PUNCT
ejpam-5934	357	14	rf	rf	ADJ
ejpam-5934	357	15	on	on	ADP
ejpam-5934	357	16	the	the	DET
ejpam-5934	357	17	obesity	obesity	NOUN
ejpam-5934	357	18	dataset	dataset	NOUN
ejpam-5934	357	19	(	(	PUNCT
ejpam-5934	357	20	accuracy	accuracy	NOUN
ejpam-5934	357	21	declined	decline	VERB
ejpam-5934	357	22	from	from	ADP
ejpam-5934	357	23	1.0	1.0	NUM
ejpam-5934	357	24	to	to	ADP
ejpam-5934	357	25	0.9091	0.9091	NUM
ejpam-5934	357	26	)	)	PUNCT
ejpam-5934	357	27	and	and	CCONJ
ejpam-5934	357	28	svm	svm	VERB
ejpam-5934	357	29	on	on	ADP
ejpam-5934	357	30	the	the	DET
ejpam-5934	357	31	breast	breast	NOUN
ejpam-5934	357	32	cancer	cancer	NOUN
ejpam-5934	357	33	dataset	dataset	NOUN
ejpam-5934	357	34	(	(	PUNCT
ejpam-5934	357	35	from	from	ADP
ejpam-5934	357	36	0.9572	0.9572	NUM
ejpam-5934	357	37	to	to	ADP
ejpam-5934	357	38	0.9357	0.9357	NUM
ejpam-5934	357	39	)	)	PUNCT
ejpam-5934	357	40	.	.	PUNCT
ejpam-5934	358	1	these	these	DET
ejpam-5934	358	2	declines	decline	NOUN
ejpam-5934	358	3	may	may	AUX
ejpam-5934	358	4	be	be	AUX
ejpam-5934	358	5	attributed	attribute	VERB
ejpam-5934	358	6	to	to	ADP
ejpam-5934	358	7	the	the	DET
ejpam-5934	358	8	removal	removal	NOUN
ejpam-5934	358	9	of	of	ADP
ejpam-5934	358	10	minor	minor	ADJ
ejpam-5934	358	11	yet	yet	CCONJ
ejpam-5934	358	12	informative	informative	ADJ
ejpam-5934	358	13	features	feature	NOUN
ejpam-5934	358	14	during	during	ADP
ejpam-5934	358	15	the	the	DET
ejpam-5934	358	16	reduction	reduction	NOUN
ejpam-5934	358	17	process	process	NOUN
ejpam-5934	358	18	.	.	PUNCT
ejpam-5934	359	1	such	such	ADJ
ejpam-5934	359	2	outcomes	outcome	NOUN
ejpam-5934	359	3	underscore	underscore	VERB
ejpam-5934	359	4	that	that	SCONJ
ejpam-5934	359	5	while	while	SCONJ
ejpam-5934	359	6	rst	rst	NOUN
ejpam-5934	359	7	enhances	enhance	VERB
ejpam-5934	359	8	model	model	NOUN
ejpam-5934	359	9	interpretability	interpretability	NOUN
ejpam-5934	359	10	and	and	CCONJ
ejpam-5934	359	11	computational	computational	ADJ
ejpam-5934	359	12	efficiency	efficiency	NOUN
ejpam-5934	359	13	,	,	PUNCT
ejpam-5934	359	14	its	its	PRON
ejpam-5934	359	15	effectiveness	effectiveness	NOUN
ejpam-5934	359	16	can	can	AUX
ejpam-5934	359	17	vary	vary	VERB
ejpam-5934	359	18	depending	depend	VERB
ejpam-5934	359	19	on	on	ADP
ejpam-5934	359	20	dataset	dataset	NOUN
ejpam-5934	359	21	-	-	PUNCT
ejpam-5934	359	22	specific	specific	ADJ
ejpam-5934	359	23	factors	factor	NOUN
ejpam-5934	359	24	such	such	ADJ
ejpam-5934	359	25	as	as	ADP
ejpam-5934	359	26	sample	sample	NOUN
ejpam-5934	359	27	size	size	NOUN
ejpam-5934	359	28	,	,	PUNCT
ejpam-5934	359	29	class	class	NOUN
ejpam-5934	359	30	balance	balance	NOUN
ejpam-5934	359	31	,	,	PUNCT
ejpam-5934	359	32	and	and	CCONJ
ejpam-5934	359	33	feature	feature	NOUN
ejpam-5934	359	34	dependencies	dependency	NOUN
ejpam-5934	359	35	.	.	PUNCT
ejpam-5934	360	1	to	to	PART
ejpam-5934	360	2	address	address	VERB
ejpam-5934	360	3	the	the	DET
ejpam-5934	360	4	limitations	limitation	NOUN
ejpam-5934	360	5	of	of	ADP
ejpam-5934	360	6	the	the	DET
ejpam-5934	360	7	qr	qr	PROPN
ejpam-5934	360	8	algorithm	algorithm	NOUN
ejpam-5934	360	9	and	and	CCONJ
ejpam-5934	360	10	improve	improve	VERB
ejpam-5934	360	11	generalizability	generalizability	NOUN
ejpam-5934	360	12	,	,	PUNCT
ejpam-5934	360	13	future	future	ADJ
ejpam-5934	360	14	research	research	NOUN
ejpam-5934	360	15	could	could	AUX
ejpam-5934	360	16	explore	explore	VERB
ejpam-5934	360	17	hybrid	hybrid	ADJ
ejpam-5934	360	18	approaches	approach	NOUN
ejpam-5934	360	19	.	.	PUNCT
ejpam-5934	361	1	integrating	integrate	VERB
ejpam-5934	361	2	rst	rst	PROPN
ejpam-5934	361	3	with	with	ADP
ejpam-5934	361	4	metaheuristic	metaheuristic	ADJ
ejpam-5934	361	5	optimization	optimization	NOUN
ejpam-5934	361	6	techniques	technique	NOUN
ejpam-5934	361	7	such	such	ADJ
ejpam-5934	361	8	as	as	ADP
ejpam-5934	361	9	genetic	genetic	ADJ
ejpam-5934	361	10	algorithms	algorithms	NOUN
ejpam-5934	361	11	may	may	AUX
ejpam-5934	361	12	enhance	enhance	VERB
ejpam-5934	361	13	reduct	reduct	PROPN
ejpam-5934	361	14	selection	selection	NOUN
ejpam-5934	361	15	by	by	ADP
ejpam-5934	361	16	evolving	evolve	VERB
ejpam-5934	361	17	multiple	multiple	ADJ
ejpam-5934	361	18	candidate	candidate	NOUN
ejpam-5934	361	19	subsets	subset	NOUN
ejpam-5934	361	20	in	in	ADP
ejpam-5934	361	21	parallel	parallel	NOUN
ejpam-5934	361	22	potentially	potentially	ADV
ejpam-5934	361	23	identifying	identify	VERB
ejpam-5934	361	24	more	more	ADJ
ejpam-5934	361	25	discriminative	discriminative	NOUN
ejpam-5934	361	26	feature	feature	NOUN
ejpam-5934	361	27	sets	set	NOUN
ejpam-5934	361	28	for	for	ADP
ejpam-5934	361	29	complex	complex	ADJ
ejpam-5934	361	30	,	,	PUNCT
ejpam-5934	361	31	high	high	ADJ
ejpam-5934	361	32	-	-	PUNCT
ejpam-5934	361	33	dimensional	dimensional	ADJ
ejpam-5934	361	34	datasets	dataset	NOUN
ejpam-5934	361	35	.	.	PUNCT
ejpam-5934	362	1	additionally	additionally	ADV
ejpam-5934	362	2	,	,	PUNCT
ejpam-5934	362	3	combining	combine	VERB
ejpam-5934	362	4	rst	rst	PROPN
ejpam-5934	362	5	with	with	ADP
ejpam-5934	362	6	dl	dl	PROPN
ejpam-5934	362	7	could	could	AUX
ejpam-5934	362	8	capitalize	capitalize	VERB
ejpam-5934	362	9	on	on	ADP
ejpam-5934	362	10	rst	rst	PROPN
ejpam-5934	362	11	’s	’s	PART
ejpam-5934	362	12	interpretability	interpretability	NOUN
ejpam-5934	362	13	and	and	CCONJ
ejpam-5934	362	14	dl	dl	PROPN
ejpam-5934	362	15	’s	’s	NOUN
ejpam-5934	362	16	representational	representational	ADJ
ejpam-5934	362	17	power	power	NOUN
ejpam-5934	362	18	.	.	PUNCT
ejpam-5934	363	1	for	for	ADP
ejpam-5934	363	2	int	int	PROPN
ejpam-5934	363	3	.	.	PUNCT
ejpam-5934	364	1	ashika	ashika	PROPN
ejpam-5934	364	2	,	,	PUNCT
ejpam-5934	364	3	g.	g.	PROPN
ejpam-5934	364	4	h.	h.	PROPN
ejpam-5934	364	5	grace	grace	PROPN
ejpam-5934	364	6	/	/	SYM
ejpam-5934	364	7	eur	eur	PROPN
ejpam-5934	364	8	.	.	PUNCT
ejpam-5934	365	1	j.	j.	PROPN
ejpam-5934	365	2	pure	pure	PROPN
ejpam-5934	365	3	appl	appl	PROPN
ejpam-5934	365	4	.	.	PROPN
ejpam-5934	365	5	math	math	PROPN
ejpam-5934	365	6	,	,	PUNCT
ejpam-5934	365	7	18	18	NUM
ejpam-5934	365	8	(	(	PUNCT
ejpam-5934	365	9	2	2	NUM
ejpam-5934	365	10	)	)	PUNCT
ejpam-5934	365	11	(	(	PUNCT
ejpam-5934	365	12	2025	2025	NUM
ejpam-5934	365	13	)	)	PUNCT
ejpam-5934	365	14	,	,	PUNCT
ejpam-5934	365	15	5934	5934	NUM
ejpam-5934	365	16	20	20	NUM
ejpam-5934	365	17	of	of	ADP
ejpam-5934	365	18	22	22	NUM
ejpam-5934	365	19	stance	stance	NOUN
ejpam-5934	365	20	,	,	PUNCT
ejpam-5934	365	21	rst	rst	ADJ
ejpam-5934	365	22	-	-	PUNCT
ejpam-5934	365	23	reduced	reduce	VERB
ejpam-5934	365	24	features	feature	NOUN
ejpam-5934	365	25	could	could	AUX
ejpam-5934	365	26	be	be	AUX
ejpam-5934	365	27	used	use	VERB
ejpam-5934	365	28	as	as	ADP
ejpam-5934	365	29	inputs	input	NOUN
ejpam-5934	365	30	to	to	ADP
ejpam-5934	365	31	feedforward	feedforward	NOUN
ejpam-5934	365	32	or	or	CCONJ
ejpam-5934	365	33	convolutional	convolutional	ADJ
ejpam-5934	365	34	neural	neural	ADJ
ejpam-5934	365	35	networks	network	NOUN
ejpam-5934	365	36	,	,	PUNCT
ejpam-5934	365	37	reducing	reduce	VERB
ejpam-5934	365	38	training	training	NOUN
ejpam-5934	365	39	time	time	NOUN
ejpam-5934	365	40	and	and	CCONJ
ejpam-5934	365	41	mitigating	mitigate	VERB
ejpam-5934	365	42	overfitting	overfitting	NOUN
ejpam-5934	365	43	by	by	ADP
ejpam-5934	365	44	focusing	focus	VERB
ejpam-5934	365	45	on	on	ADP
ejpam-5934	365	46	the	the	DET
ejpam-5934	365	47	most	most	ADV
ejpam-5934	365	48	relevant	relevant	ADJ
ejpam-5934	365	49	predictors	predictor	NOUN
ejpam-5934	365	50	.	.	PUNCT
ejpam-5934	366	1	references	reference	NOUN
ejpam-5934	366	2	[	[	X
ejpam-5934	366	3	1	1	NUM
ejpam-5934	366	4	]	]	PUNCT
ejpam-5934	366	5	zdzis	zdzis	NOUN
ejpam-5934	366	6	law	law	NOUN
ejpam-5934	366	7	pawlak	pawlak	NOUN
ejpam-5934	366	8	.	.	PUNCT
ejpam-5934	367	1	rough	rough	ADJ
ejpam-5934	367	2	sets	set	NOUN
ejpam-5934	367	3	.	.	PUNCT
ejpam-5934	368	1	international	international	ADJ
ejpam-5934	368	2	journal	journal	PROPN
ejpam-5934	368	3	of	of	ADP
ejpam-5934	368	4	computer	computer	PROPN
ejpam-5934	368	5	&	&	CCONJ
ejpam-5934	368	6	information	information	NOUN
ejpam-5934	368	7	sciences	sciences	PROPN
ejpam-5934	368	8	,	,	PUNCT
ejpam-5934	368	9	11:341–356	11:341–356	NUM
ejpam-5934	368	10	,	,	PUNCT
ejpam-5934	368	11	1982	1982	NUM
ejpam-5934	368	12	.	.	PUNCT
ejpam-5934	369	1	[	[	X
ejpam-5934	369	2	2	2	X
ejpam-5934	369	3	]	]	PUNCT
ejpam-5934	369	4	rafael	rafael	PROPN
ejpam-5934	369	5	bello	bello	PROPN
ejpam-5934	369	6	and	and	CCONJ
ejpam-5934	369	7	rafael	rafael	PROPN
ejpam-5934	369	8	falcon	falcon	PROPN
ejpam-5934	369	9	.	.	PUNCT
ejpam-5934	370	1	rough	rough	ADJ
ejpam-5934	370	2	sets	set	NOUN
ejpam-5934	370	3	in	in	ADP
ejpam-5934	370	4	machine	machine	NOUN
ejpam-5934	370	5	learning	learning	NOUN
ejpam-5934	370	6	:	:	PUNCT
ejpam-5934	370	7	a	a	DET
ejpam-5934	370	8	review	review	NOUN
ejpam-5934	370	9	.	.	PUNCT
ejpam-5934	371	1	thriving	thrive	VERB
ejpam-5934	371	2	rough	rough	ADJ
ejpam-5934	371	3	sets	set	NOUN
ejpam-5934	371	4	:	:	PUNCT
ejpam-5934	371	5	10th	10th	ADJ
ejpam-5934	371	6	anniversary	anniversary	NOUN
ejpam-5934	371	7	-	-	PUNCT
ejpam-5934	371	8	honoring	honor	VERB
ejpam-5934	371	9	professor	professor	NOUN
ejpam-5934	371	10	zdzis	zdzis	NOUN
ejpam-5934	371	11	law	law	NOUN
ejpam-5934	371	12	pawlak	pawlak	NOUN
ejpam-5934	371	13	’s	’s	PART
ejpam-5934	371	14	life	life	NOUN
ejpam-5934	371	15	and	and	CCONJ
ejpam-5934	371	16	legacy	legacy	NOUN
ejpam-5934	371	17	&	&	CCONJ
ejpam-5934	371	18	35	35	NUM
ejpam-5934	371	19	years	year	NOUN
ejpam-5934	371	20	of	of	ADP
ejpam-5934	371	21	rough	rough	ADJ
ejpam-5934	371	22	sets	set	NOUN
ejpam-5934	371	23	,	,	PUNCT
ejpam-5934	371	24	pages	page	NOUN
ejpam-5934	371	25	87–118	87–118	NUM
ejpam-5934	371	26	,	,	PUNCT
ejpam-5934	371	27	2017	2017	NUM
ejpam-5934	371	28	.	.	PUNCT
ejpam-5934	372	1	[	[	X
ejpam-5934	372	2	3	3	X
ejpam-5934	372	3	]	]	X
ejpam-5934	372	4	senthilkumar	senthilkumar	PROPN
ejpam-5934	372	5	mohan	mohan	PROPN
ejpam-5934	372	6	,	,	PUNCT
ejpam-5934	372	7	chandrasegar	chandrasegar	NOUN
ejpam-5934	372	8	thirumalai	thirumalai	NOUN
ejpam-5934	372	9	,	,	PUNCT
ejpam-5934	372	10	and	and	CCONJ
ejpam-5934	372	11	gautam	gautam	PROPN
ejpam-5934	372	12	srivastava	srivastava	PROPN
ejpam-5934	372	13	.	.	PUNCT
ejpam-5934	373	1	effective	effective	ADJ
ejpam-5934	373	2	heart	heart	NOUN
ejpam-5934	373	3	disease	disease	NOUN
ejpam-5934	373	4	prediction	prediction	NOUN
ejpam-5934	373	5	using	use	VERB
ejpam-5934	373	6	hybrid	hybrid	ADJ
ejpam-5934	373	7	machine	machine	NOUN
ejpam-5934	373	8	learning	learn	VERB
ejpam-5934	373	9	techniques	technique	NOUN
ejpam-5934	373	10	.	.	PUNCT
ejpam-5934	374	1	ieee	ieee	NOUN
ejpam-5934	374	2	access	access	NOUN
ejpam-5934	374	3	,	,	PUNCT
ejpam-5934	374	4	7:81542–81554	7:81542–81554	NUM
ejpam-5934	374	5	,	,	PUNCT
ejpam-5934	374	6	2019	2019	NUM
ejpam-5934	374	7	.	.	PUNCT
ejpam-5934	375	1	[	[	X
ejpam-5934	375	2	4	4	NUM
ejpam-5934	375	3	]	]	X
ejpam-5934	375	4	sujogya	sujogya	PROPN
ejpam-5934	375	5	mishra	mishra	PROPN
ejpam-5934	375	6	,	,	PUNCT
ejpam-5934	375	7	sp	sp	ADP
ejpam-5934	375	8	mohanty	mohanty	NOUN
ejpam-5934	375	9	,	,	PUNCT
ejpam-5934	375	10	and	and	CCONJ
ejpam-5934	375	11	sk	sk	ADP
ejpam-5934	375	12	pradhan	pradhan	PROPN
ejpam-5934	375	13	.	.	PUNCT
ejpam-5934	376	1	reasons	reason	NOUN
ejpam-5934	376	2	for	for	ADP
ejpam-5934	376	3	employees	employee	NOUN
ejpam-5934	376	4	need	need	VERB
ejpam-5934	376	5	justice	justice	NOUN
ejpam-5934	376	6	from	from	ADP
ejpam-5934	376	7	legal	legal	ADJ
ejpam-5934	376	8	bodies	body	NOUN
ejpam-5934	376	9	:	:	PUNCT
ejpam-5934	376	10	a	a	DET
ejpam-5934	376	11	rough	rough	ADJ
ejpam-5934	376	12	set	set	NOUN
ejpam-5934	376	13	approach	approach	NOUN
ejpam-5934	376	14	.	.	PUNCT
ejpam-5934	377	1	in	in	ADP
ejpam-5934	377	2	2016	2016	NUM
ejpam-5934	377	3	3rd	3rd	ADJ
ejpam-5934	377	4	international	international	ADJ
ejpam-5934	377	5	conference	conference	NOUN
ejpam-5934	377	6	on	on	ADP
ejpam-5934	377	7	computing	compute	VERB
ejpam-5934	377	8	for	for	ADP
ejpam-5934	377	9	sustainable	sustainable	ADJ
ejpam-5934	377	10	global	global	ADJ
ejpam-5934	377	11	development	development	NOUN
ejpam-5934	377	12	(	(	PUNCT
ejpam-5934	377	13	indiacom	indiacom	NOUN
ejpam-5934	377	14	)	)	PUNCT
ejpam-5934	377	15	,	,	PUNCT
ejpam-5934	377	16	pages	page	NOUN
ejpam-5934	377	17	2018–2022	2018–2022	NUM
ejpam-5934	377	18	.	.	PUNCT
ejpam-5934	377	19	ieee	ieee	PROPN
ejpam-5934	377	20	,	,	PUNCT
ejpam-5934	377	21	2016	2016	NUM
ejpam-5934	377	22	.	.	PUNCT
ejpam-5934	378	1	[	[	X
ejpam-5934	378	2	5	5	X
ejpam-5934	378	3	]	]	X
ejpam-5934	378	4	subrata	subrata	PROPN
ejpam-5934	378	5	kumar	kumar	PROPN
ejpam-5934	378	6	nayak	nayak	PROPN
ejpam-5934	378	7	,	,	PUNCT
ejpam-5934	378	8	sateesh	sateesh	NOUN
ejpam-5934	378	9	kumar	kumar	PROPN
ejpam-5934	378	10	pradhan	pradhan	PROPN
ejpam-5934	378	11	,	,	PUNCT
ejpam-5934	378	12	sujogya	sujogya	PROPN
ejpam-5934	378	13	mishra	mishra	PROPN
ejpam-5934	378	14	,	,	PUNCT
ejpam-5934	378	15	sipali	sipali	ADJ
ejpam-5934	378	16	pradhan	pradhan	PROPN
ejpam-5934	378	17	,	,	PUNCT
ejpam-5934	378	18	and	and	CCONJ
ejpam-5934	378	19	pk	pk	NOUN
ejpam-5934	378	20	pattnaik	pattnaik	NOUN
ejpam-5934	378	21	.	.	PUNCT
ejpam-5934	379	1	rough	rough	ADJ
ejpam-5934	379	2	set	set	NOUN
ejpam-5934	379	3	technique	technique	NOUN
ejpam-5934	379	4	to	to	PART
ejpam-5934	379	5	predict	predict	VERB
ejpam-5934	379	6	symptoms	symptom	NOUN
ejpam-5934	379	7	for	for	ADP
ejpam-5934	379	8	malaria	malaria	NOUN
ejpam-5934	379	9	.	.	PUNCT
ejpam-5934	380	1	in	in	ADP
ejpam-5934	380	2	2021	2021	NUM
ejpam-5934	380	3	8th	8th	ADJ
ejpam-5934	380	4	international	international	ADJ
ejpam-5934	380	5	conference	conference	NOUN
ejpam-5934	380	6	on	on	ADP
ejpam-5934	380	7	computing	compute	VERB
ejpam-5934	380	8	for	for	ADP
ejpam-5934	380	9	sustainable	sustainable	ADJ
ejpam-5934	380	10	global	global	ADJ
ejpam-5934	380	11	development	development	NOUN
ejpam-5934	380	12	(	(	PUNCT
ejpam-5934	380	13	indiacom	indiacom	NOUN
ejpam-5934	380	14	)	)	PUNCT
ejpam-5934	380	15	,	,	PUNCT
ejpam-5934	380	16	pages	page	NOUN
ejpam-5934	380	17	312–317	312–317	NUM
ejpam-5934	380	18	.	.	PUNCT
ejpam-5934	380	19	ieee	ieee	NOUN
ejpam-5934	380	20	,	,	PUNCT
ejpam-5934	380	21	2021	2021	NUM
ejpam-5934	380	22	.	.	PUNCT
ejpam-5934	381	1	[	[	X
ejpam-5934	381	2	6	6	NUM
ejpam-5934	381	3	]	]	PUNCT
ejpam-5934	381	4	subhalaxmi	subhalaxmi	NOUN
ejpam-5934	381	5	das	das	PROPN
ejpam-5934	381	6	,	,	PUNCT
ejpam-5934	381	7	sateesh	sateesh	NOUN
ejpam-5934	381	8	kumar	kumar	PROPN
ejpam-5934	381	9	pradhan	pradhan	PROPN
ejpam-5934	381	10	,	,	PUNCT
ejpam-5934	381	11	sujogya	sujogya	PROPN
ejpam-5934	381	12	mishra	mishra	PROPN
ejpam-5934	381	13	,	,	PUNCT
ejpam-5934	381	14	sipali	sipali	ADJ
ejpam-5934	381	15	pradhan	pradhan	PROPN
ejpam-5934	381	16	,	,	PUNCT
ejpam-5934	381	17	and	and	CCONJ
ejpam-5934	381	18	pk	pk	X
ejpam-5934	381	19	pattnaik	pattnaik	NOUN
ejpam-5934	381	20	.	.	PUNCT
ejpam-5934	382	1	diagnosis	diagnosis	NOUN
ejpam-5934	382	2	of	of	ADP
ejpam-5934	382	3	cardiac	cardiac	ADJ
ejpam-5934	382	4	problem	problem	NOUN
ejpam-5934	382	5	using	use	VERB
ejpam-5934	382	6	rough	rough	ADJ
ejpam-5934	382	7	set	set	NOUN
ejpam-5934	382	8	theory	theory	NOUN
ejpam-5934	382	9	and	and	CCONJ
ejpam-5934	382	10	machine	machine	NOUN
ejpam-5934	382	11	learning	learning	NOUN
ejpam-5934	382	12	.	.	PUNCT
ejpam-5934	383	1	indian	indian	PROPN
ejpam-5934	383	2	journal	journal	PROPN
ejpam-5934	383	3	of	of	ADP
ejpam-5934	383	4	computer	computer	NOUN
ejpam-5934	383	5	science	science	NOUN
ejpam-5934	383	6	and	and	CCONJ
ejpam-5934	383	7	engineering	engineering	NOUN
ejpam-5934	383	8	,	,	PUNCT
ejpam-5934	383	9	13(4):1112–1131	13(4):1112–1131	NUM
ejpam-5934	383	10	,	,	PUNCT
ejpam-5934	383	11	2022	2022	NUM
ejpam-5934	383	12	.	.	PUNCT
ejpam-5934	384	1	[	[	X
ejpam-5934	384	2	7	7	X
ejpam-5934	384	3	]	]	X
ejpam-5934	384	4	rani	rani	ADJ
ejpam-5934	384	5	nuraeni	nuraeni	ADJ
ejpam-5934	384	6	and	and	CCONJ
ejpam-5934	384	7	sugiyarto	sugiyarto	NOUN
ejpam-5934	384	8	surono	surono	NOUN
ejpam-5934	384	9	.	.	PUNCT
ejpam-5934	385	1	rough	rough	ADJ
ejpam-5934	385	2	set	set	NOUN
ejpam-5934	385	3	theory	theory	NOUN
ejpam-5934	385	4	for	for	ADP
ejpam-5934	385	5	dimension	dimension	NOUN
ejpam-5934	385	6	reduction	reduction	NOUN
ejpam-5934	385	7	on	on	ADP
ejpam-5934	385	8	machine	machine	NOUN
ejpam-5934	385	9	learning	learning	NOUN
ejpam-5934	385	10	algorithm	algorithm	NOUN
ejpam-5934	385	11	.	.	PUNCT
ejpam-5934	386	1	jurnal	jurnal	ADJ
ejpam-5934	386	2	fourier	fourier	NOUN
ejpam-5934	386	3	,	,	PUNCT
ejpam-5934	386	4	10(1):29–37	10(1):29–37	NUM
ejpam-5934	386	5	,	,	PUNCT
ejpam-5934	386	6	2021	2021	NUM
ejpam-5934	386	7	.	.	PUNCT
ejpam-5934	387	1	[	[	X
ejpam-5934	387	2	8	8	NUM
ejpam-5934	387	3	]	]	X
ejpam-5934	387	4	lei	lei	X
ejpam-5934	387	5	lei	lei	PROPN
ejpam-5934	387	6	,	,	PUNCT
ejpam-5934	387	7	wei	wei	PROPN
ejpam-5934	387	8	chen	chen	PROPN
ejpam-5934	387	9	,	,	PUNCT
ejpam-5934	387	10	bing	bing	VERB
ejpam-5934	387	11	wu	wu	PROPN
ejpam-5934	387	12	,	,	PUNCT
ejpam-5934	387	13	chao	chao	PROPN
ejpam-5934	387	14	chen	chen	PROPN
ejpam-5934	387	15	,	,	PUNCT
ejpam-5934	387	16	and	and	CCONJ
ejpam-5934	387	17	wei	wei	PROPN
ejpam-5934	387	18	liu	liu	PROPN
ejpam-5934	387	19	.	.	PUNCT
ejpam-5934	388	1	a	a	DET
ejpam-5934	388	2	building	build	VERB
ejpam-5934	388	3	energy	energy	NOUN
ejpam-5934	388	4	consumption	consumption	NOUN
ejpam-5934	388	5	prediction	prediction	NOUN
ejpam-5934	388	6	model	model	NOUN
ejpam-5934	388	7	based	base	VERB
ejpam-5934	388	8	on	on	ADP
ejpam-5934	388	9	rough	rough	ADJ
ejpam-5934	388	10	set	set	NOUN
ejpam-5934	388	11	theory	theory	NOUN
ejpam-5934	388	12	and	and	CCONJ
ejpam-5934	388	13	deep	deep	ADJ
ejpam-5934	388	14	learning	learning	NOUN
ejpam-5934	388	15	algorithms	algorithm	NOUN
ejpam-5934	388	16	.	.	PUNCT
ejpam-5934	389	1	energy	energy	NOUN
ejpam-5934	389	2	and	and	CCONJ
ejpam-5934	389	3	buildings	building	NOUN
ejpam-5934	389	4	,	,	PUNCT
ejpam-5934	389	5	240:110886	240:110886	NUM
ejpam-5934	389	6	,	,	PUNCT
ejpam-5934	389	7	2021	2021	NUM
ejpam-5934	389	8	.	.	PUNCT
ejpam-5934	390	1	[	[	X
ejpam-5934	390	2	9	9	NUM
ejpam-5934	390	3	]	]	SYM
ejpam-5934	390	4	ra	ra	NOUN
ejpam-5934	390	5	lukshmi	lukshmi	NOUN
ejpam-5934	390	6	,	,	PUNCT
ejpam-5934	390	7	pv	pv	NOUN
ejpam-5934	390	8	geetha	geetha	NOUN
ejpam-5934	390	9	,	,	PUNCT
ejpam-5934	390	10	and	and	CCONJ
ejpam-5934	390	11	p	p	DET
ejpam-5934	390	12	venkatesan	venkatesan	NOUN
ejpam-5934	390	13	.	.	PUNCT
ejpam-5934	391	1	rough	rough	ADJ
ejpam-5934	391	2	set	set	NOUN
ejpam-5934	391	3	theory	theory	NOUN
ejpam-5934	391	4	approach	approach	NOUN
ejpam-5934	391	5	for	for	ADP
ejpam-5934	391	6	attribute	attribute	NOUN
ejpam-5934	391	7	reduction	reduction	NOUN
ejpam-5934	391	8	.	.	PUNCT
ejpam-5934	392	1	int	int	NOUN
ejpam-5934	392	2	.	.	PUNCT
ejpam-5934	393	1	j.	j.	PROPN
ejpam-5934	393	2	autom	autom	PROPN
ejpam-5934	393	3	.	.	PUNCT
ejpam-5934	394	1	artif	artif	INTJ
ejpam-5934	394	2	.	.	PUNCT
ejpam-5934	395	1	intell	intell	PROPN
ejpam-5934	395	2	,	,	PUNCT
ejpam-5934	395	3	1(3):70–80	1(3):70–80	NUM
ejpam-5934	395	4	,	,	PUNCT
ejpam-5934	395	5	2013	2013	NUM
ejpam-5934	395	6	.	.	PUNCT
ejpam-5934	396	1	[	[	X
ejpam-5934	396	2	10	10	NUM
ejpam-5934	396	3	]	]	X
ejpam-5934	396	4	vamsidhar	vamsidhar	PROPN
ejpam-5934	396	5	talasila	talasila	NOUN
ejpam-5934	396	6	,	,	PUNCT
ejpam-5934	396	7	kotakonda	kotakonda	PROPN
ejpam-5934	396	8	madhubabu	madhubabu	PROPN
ejpam-5934	396	9	,	,	PUNCT
ejpam-5934	396	10	meghana	meghana	PROPN
ejpam-5934	396	11	chakravarthy	chakravarthy	PROPN
ejpam-5934	396	12	mahadasyam	mahadasyam	PROPN
ejpam-5934	396	13	,	,	PUNCT
ejpam-5934	396	14	naga	naga	PROPN
ejpam-5934	396	15	jyothi	jyothi	PROPN
ejpam-5934	396	16	atchala	atchala	PROPN
ejpam-5934	396	17	,	,	PUNCT
ejpam-5934	396	18	and	and	CCONJ
ejpam-5934	396	19	lakshmi	lakshmi	PROPN
ejpam-5934	396	20	sowjanya	sowjanya	PROPN
ejpam-5934	396	21	kande	kande	PROPN
ejpam-5934	396	22	.	.	PUNCT
ejpam-5934	397	1	the	the	DET
ejpam-5934	397	2	prediction	prediction	NOUN
ejpam-5934	397	3	of	of	ADP
ejpam-5934	397	4	diseases	disease	NOUN
ejpam-5934	397	5	using	use	VERB
ejpam-5934	397	6	rough	rough	ADJ
ejpam-5934	397	7	set	set	NOUN
ejpam-5934	397	8	theory	theory	NOUN
ejpam-5934	397	9	with	with	ADP
ejpam-5934	397	10	recurrent	recurrent	ADJ
ejpam-5934	397	11	neural	neural	ADJ
ejpam-5934	397	12	network	network	NOUN
ejpam-5934	397	13	in	in	ADP
ejpam-5934	397	14	big	big	ADJ
ejpam-5934	397	15	data	datum	NOUN
ejpam-5934	397	16	analytics	analytic	NOUN
ejpam-5934	397	17	.	.	PUNCT
ejpam-5934	398	1	international	international	ADJ
ejpam-5934	398	2	journal	journal	NOUN
ejpam-5934	398	3	of	of	ADP
ejpam-5934	398	4	intelligent	intelligent	ADJ
ejpam-5934	398	5	engineering	engineering	NOUN
ejpam-5934	398	6	&	&	CCONJ
ejpam-5934	398	7	systems	system	NOUN
ejpam-5934	398	8	,	,	PUNCT
ejpam-5934	398	9	13(5	13(5	NUM
ejpam-5934	398	10	)	)	PUNCT
ejpam-5934	398	11	,	,	PUNCT
ejpam-5934	398	12	2020	2020	NUM
ejpam-5934	398	13	.	.	PUNCT
ejpam-5934	399	1	[	[	X
ejpam-5934	399	2	11	11	NUM
ejpam-5934	399	3	]	]	PUNCT
ejpam-5934	399	4	touhid	touhid	VERB
ejpam-5934	399	5	mohammad	mohammad	PROPN
ejpam-5934	399	6	hossain	hossain	PROPN
ejpam-5934	399	7	,	,	PUNCT
ejpam-5934	399	8	junzo	junzo	NOUN
ejpam-5934	399	9	watada	watada	PROPN
ejpam-5934	399	10	,	,	PUNCT
ejpam-5934	399	11	izzatdin	izzatdin	VERB
ejpam-5934	399	12	a	a	DET
ejpam-5934	399	13	aziz	aziz	NOUN
ejpam-5934	399	14	,	,	PUNCT
ejpam-5934	399	15	and	and	CCONJ
ejpam-5934	399	16	maman	maman	PROPN
ejpam-5934	399	17	hermana	hermana	PROPN
ejpam-5934	399	18	.	.	PUNCT
ejpam-5934	400	1	machine	machine	NOUN
ejpam-5934	400	2	learning	learn	VERB
ejpam-5934	400	3	in	in	ADP
ejpam-5934	400	4	electrofacies	electrofacie	NOUN
ejpam-5934	400	5	classification	classification	NOUN
ejpam-5934	400	6	and	and	CCONJ
ejpam-5934	400	7	subsurface	subsurface	NOUN
ejpam-5934	400	8	lithology	lithology	NOUN
ejpam-5934	400	9	interpretation	interpretation	NOUN
ejpam-5934	400	10	:	:	PUNCT
ejpam-5934	400	11	a	a	DET
ejpam-5934	400	12	rough	rough	ADJ
ejpam-5934	400	13	set	set	NOUN
ejpam-5934	400	14	theory	theory	NOUN
ejpam-5934	400	15	approach	approach	NOUN
ejpam-5934	400	16	.	.	PUNCT
ejpam-5934	401	1	applied	apply	VERB
ejpam-5934	401	2	sciences	science	NOUN
ejpam-5934	401	3	,	,	PUNCT
ejpam-5934	401	4	10(17):5940	10(17):5940	NUM
ejpam-5934	401	5	,	,	PUNCT
ejpam-5934	401	6	2020	2020	NUM
ejpam-5934	401	7	.	.	PUNCT
ejpam-5934	402	1	[	[	X
ejpam-5934	402	2	12	12	NUM
ejpam-5934	402	3	]	]	X
ejpam-5934	402	4	yılmaz	yılmaz	PROPN
ejpam-5934	402	5	kaya	kaya	PROPN
ejpam-5934	402	6	and	and	CCONJ
ejpam-5934	402	7	murat	murat	PROPN
ejpam-5934	402	8	uyar	uyar	PROPN
ejpam-5934	402	9	.	.	PUNCT
ejpam-5934	403	1	a	a	DET
ejpam-5934	403	2	hybrid	hybrid	ADJ
ejpam-5934	403	3	decision	decision	NOUN
ejpam-5934	403	4	support	support	NOUN
ejpam-5934	403	5	system	system	NOUN
ejpam-5934	403	6	based	base	VERB
ejpam-5934	403	7	on	on	ADP
ejpam-5934	403	8	rough	rough	ADJ
ejpam-5934	403	9	set	set	NOUN
ejpam-5934	403	10	and	and	CCONJ
ejpam-5934	403	11	extreme	extreme	ADJ
ejpam-5934	403	12	learning	learning	NOUN
ejpam-5934	403	13	machine	machine	NOUN
ejpam-5934	403	14	for	for	ADP
ejpam-5934	403	15	diagnosis	diagnosis	NOUN
ejpam-5934	403	16	of	of	ADP
ejpam-5934	403	17	hepatitis	hepatitis	NOUN
ejpam-5934	403	18	disease	disease	NOUN
ejpam-5934	403	19	.	.	PUNCT
ejpam-5934	403	20	applied	apply	VERB
ejpam-5934	403	21	soft	soft	ADJ
ejpam-5934	403	22	computing	computing	NOUN
ejpam-5934	403	23	,	,	PUNCT
ejpam-5934	403	24	13(8):3429–3438	13(8):3429–3438	NUM
ejpam-5934	403	25	,	,	PUNCT
ejpam-5934	403	26	2013	2013	NUM
ejpam-5934	403	27	.	.	PUNCT
ejpam-5934	404	1	t.	t.	NOUN
ejpam-5934	404	2	ashika	ashika	PROPN
ejpam-5934	404	3	,	,	PUNCT
ejpam-5934	404	4	g.	g.	PROPN
ejpam-5934	404	5	h.	h.	PROPN
ejpam-5934	404	6	grace	grace	PROPN
ejpam-5934	404	7	/	/	SYM
ejpam-5934	404	8	eur	eur	PROPN
ejpam-5934	404	9	.	.	PUNCT
ejpam-5934	405	1	j.	j.	PROPN
ejpam-5934	405	2	pure	pure	PROPN
ejpam-5934	405	3	appl	appl	PROPN
ejpam-5934	405	4	.	.	PROPN
ejpam-5934	405	5	math	math	PROPN
ejpam-5934	405	6	,	,	PUNCT
ejpam-5934	405	7	18	18	NUM
ejpam-5934	405	8	(	(	PUNCT
ejpam-5934	405	9	2	2	NUM
ejpam-5934	405	10	)	)	PUNCT
ejpam-5934	405	11	(	(	PUNCT
ejpam-5934	405	12	2025	2025	NUM
ejpam-5934	405	13	)	)	PUNCT
ejpam-5934	405	14	,	,	PUNCT
ejpam-5934	405	15	5934	5934	NUM
ejpam-5934	405	16	21	21	NUM
ejpam-5934	405	17	of	of	ADP
ejpam-5934	405	18	22	22	NUM
ejpam-5934	405	19	[	[	X
ejpam-5934	405	20	13	13	NUM
ejpam-5934	405	21	]	]	X
ejpam-5934	405	22	hui	hui	PROPN
ejpam-5934	405	23	-	-	PUNCT
ejpam-5934	405	24	ling	ling	PROPN
ejpam-5934	405	25	chen	chen	PROPN
ejpam-5934	405	26	,	,	PUNCT
ejpam-5934	405	27	bo	bo	PROPN
ejpam-5934	405	28	yang	yang	PROPN
ejpam-5934	405	29	,	,	PUNCT
ejpam-5934	405	30	jie	jie	PROPN
ejpam-5934	405	31	liu	liu	PROPN
ejpam-5934	405	32	,	,	PUNCT
ejpam-5934	405	33	and	and	CCONJ
ejpam-5934	405	34	da	da	NOUN
ejpam-5934	405	35	-	-	ADJ
ejpam-5934	405	36	you	you	PRON
ejpam-5934	405	37	liu	liu	PROPN
ejpam-5934	405	38	.	.	PUNCT
ejpam-5934	406	1	a	a	DET
ejpam-5934	406	2	support	support	NOUN
ejpam-5934	406	3	vector	vector	NOUN
ejpam-5934	406	4	machine	machine	NOUN
ejpam-5934	406	5	classifier	classifier	NOUN
ejpam-5934	406	6	with	with	ADP
ejpam-5934	406	7	rough	rough	ADJ
ejpam-5934	406	8	set	set	NOUN
ejpam-5934	406	9	-	-	PUNCT
ejpam-5934	406	10	based	base	VERB
ejpam-5934	406	11	feature	feature	NOUN
ejpam-5934	406	12	selection	selection	NOUN
ejpam-5934	406	13	for	for	ADP
ejpam-5934	406	14	breast	breast	NOUN
ejpam-5934	406	15	cancer	cancer	NOUN
ejpam-5934	406	16	diagnosis	diagnosis	NOUN
ejpam-5934	406	17	.	.	PUNCT
ejpam-5934	407	1	expert	expert	NOUN
ejpam-5934	407	2	systems	system	NOUN
ejpam-5934	407	3	with	with	ADP
ejpam-5934	407	4	applications	application	NOUN
ejpam-5934	407	5	,	,	PUNCT
ejpam-5934	407	6	38(7):9014–9022	38(7):9014–9022	NUM
ejpam-5934	407	7	,	,	PUNCT
ejpam-5934	407	8	2011	2011	NUM
ejpam-5934	407	9	.	.	PUNCT
ejpam-5934	408	1	[	[	X
ejpam-5934	408	2	14	14	NUM
ejpam-5934	408	3	]	]	X
ejpam-5934	408	4	asma	asma	PROPN
ejpam-5934	408	5	trabelsi	trabelsi	PROPN
ejpam-5934	408	6	,	,	PUNCT
ejpam-5934	408	7	zied	zie	VERB
ejpam-5934	408	8	elouedi	elouedi	PROPN
ejpam-5934	408	9	,	,	PUNCT
ejpam-5934	408	10	and	and	CCONJ
ejpam-5934	408	11	eric	eric	PROPN
ejpam-5934	408	12	lefevre	lefevre	PROPN
ejpam-5934	408	13	.	.	PUNCT
ejpam-5934	409	1	an	an	DET
ejpam-5934	409	2	ensemble	ensemble	ADJ
ejpam-5934	409	3	classifier	classifier	NOUN
ejpam-5934	409	4	through	through	ADP
ejpam-5934	409	5	rough	rough	ADJ
ejpam-5934	409	6	set	set	ADJ
ejpam-5934	409	7	reducts	reduct	NOUN
ejpam-5934	409	8	for	for	ADP
ejpam-5934	409	9	handling	handle	VERB
ejpam-5934	409	10	data	datum	NOUN
ejpam-5934	409	11	with	with	ADP
ejpam-5934	409	12	evidential	evidential	ADJ
ejpam-5934	409	13	attributes	attribute	NOUN
ejpam-5934	409	14	.	.	PUNCT
ejpam-5934	410	1	information	information	NOUN
ejpam-5934	410	2	sciences	sciences	PROPN
ejpam-5934	410	3	,	,	PUNCT
ejpam-5934	410	4	635:414–429	635:414–429	NUM
ejpam-5934	410	5	,	,	PUNCT
ejpam-5934	410	6	2023	2023	NUM
ejpam-5934	410	7	.	.	PUNCT
ejpam-5934	411	1	[	[	X
ejpam-5934	411	2	15	15	NUM
ejpam-5934	411	3	]	]	X
ejpam-5934	411	4	ping	ping	NOUN
ejpam-5934	411	5	-	-	PUNCT
ejpam-5934	411	6	feng	feng	PROPN
ejpam-5934	411	7	pai	pai	PROPN
ejpam-5934	411	8	,	,	PUNCT
ejpam-5934	411	9	shi	shi	PROPN
ejpam-5934	411	10	-	-	PUNCT
ejpam-5934	411	11	yu	yu	PROPN
ejpam-5934	411	12	chen	chen	PROPN
ejpam-5934	411	13	,	,	PUNCT
ejpam-5934	411	14	chao	chao	PROPN
ejpam-5934	411	15	-	-	PUNCT
ejpam-5934	411	16	wei	wei	PROPN
ejpam-5934	411	17	huang	huang	PROPN
ejpam-5934	411	18	,	,	PUNCT
ejpam-5934	411	19	and	and	CCONJ
ejpam-5934	411	20	ya	ya	PROPN
ejpam-5934	411	21	-	-	PUNCT
ejpam-5934	411	22	hsin	hsin	PROPN
ejpam-5934	411	23	chang	chang	PROPN
ejpam-5934	411	24	.	.	PUNCT
ejpam-5934	412	1	analyzing	analyze	VERB
ejpam-5934	412	2	foreign	foreign	ADJ
ejpam-5934	412	3	exchange	exchange	NOUN
ejpam-5934	412	4	rates	rate	NOUN
ejpam-5934	412	5	by	by	ADP
ejpam-5934	412	6	rough	rough	ADJ
ejpam-5934	412	7	set	set	NOUN
ejpam-5934	412	8	theory	theory	NOUN
ejpam-5934	412	9	and	and	CCONJ
ejpam-5934	412	10	directed	direct	VERB
ejpam-5934	412	11	acyclic	acyclic	ADJ
ejpam-5934	412	12	graph	graph	NOUN
ejpam-5934	412	13	support	support	NOUN
ejpam-5934	412	14	vector	vector	NOUN
ejpam-5934	412	15	machines	machine	NOUN
ejpam-5934	412	16	.	.	PUNCT
ejpam-5934	413	1	expert	expert	NOUN
ejpam-5934	413	2	systems	system	NOUN
ejpam-5934	413	3	with	with	ADP
ejpam-5934	413	4	applications	application	NOUN
ejpam-5934	413	5	,	,	PUNCT
ejpam-5934	413	6	37(8):5993–5998	37(8):5993–5998	NUM
ejpam-5934	413	7	,	,	PUNCT
ejpam-5934	413	8	2010	2010	NUM
ejpam-5934	413	9	.	.	PUNCT
ejpam-5934	414	1	[	[	X
ejpam-5934	414	2	16	16	NUM
ejpam-5934	414	3	]	]	X
ejpam-5934	414	4	essam	essam	PROPN
ejpam-5934	414	5	debie	debie	PROPN
ejpam-5934	414	6	,	,	PUNCT
ejpam-5934	414	7	kamran	kamran	PROPN
ejpam-5934	414	8	shafi	shafi	PROPN
ejpam-5934	414	9	,	,	PUNCT
ejpam-5934	414	10	chris	chris	PROPN
ejpam-5934	414	11	lokan	lokan	PROPN
ejpam-5934	414	12	,	,	PUNCT
ejpam-5934	414	13	and	and	CCONJ
ejpam-5934	414	14	kathryn	kathryn	PROPN
ejpam-5934	414	15	merrick	merrick	PROPN
ejpam-5934	414	16	.	.	PUNCT
ejpam-5934	415	1	reduct	reduct	PROPN
ejpam-5934	415	2	based	base	VERB
ejpam-5934	415	3	ensemble	ensemble	ADJ
ejpam-5934	415	4	of	of	ADP
ejpam-5934	415	5	learning	learn	VERB
ejpam-5934	415	6	classifier	classifier	NOUN
ejpam-5934	415	7	system	system	NOUN
ejpam-5934	415	8	for	for	ADP
ejpam-5934	415	9	real	real	ADV
ejpam-5934	415	10	-	-	PUNCT
ejpam-5934	415	11	valued	value	VERB
ejpam-5934	415	12	classification	classification	NOUN
ejpam-5934	415	13	problems	problem	NOUN
ejpam-5934	415	14	.	.	PUNCT
ejpam-5934	416	1	in	in	ADP
ejpam-5934	416	2	2013	2013	NUM
ejpam-5934	416	3	ieee	ieee	NOUN
ejpam-5934	416	4	symposium	symposium	NOUN
ejpam-5934	416	5	on	on	ADP
ejpam-5934	416	6	computational	computational	ADJ
ejpam-5934	416	7	intelligence	intelligence	NOUN
ejpam-5934	416	8	and	and	CCONJ
ejpam-5934	416	9	ensemble	ensemble	ADJ
ejpam-5934	416	10	learning	learning	NOUN
ejpam-5934	416	11	(	(	PUNCT
ejpam-5934	416	12	ciel	ciel	PROPN
ejpam-5934	416	13	)	)	PUNCT
ejpam-5934	416	14	,	,	PUNCT
ejpam-5934	416	15	pages	page	NOUN
ejpam-5934	416	16	66–73	66–73	NUM
ejpam-5934	416	17	.	.	PUNCT
ejpam-5934	417	1	ieee	ieee	PROPN
ejpam-5934	417	2	,	,	PUNCT
ejpam-5934	417	3	2013	2013	NUM
ejpam-5934	417	4	.	.	PUNCT
ejpam-5934	418	1	[	[	X
ejpam-5934	418	2	17	17	NUM
ejpam-5934	418	3	]	]	PUNCT
ejpam-5934	418	4	georg	georg	NOUN
ejpam-5934	418	5	peters	peters	PROPN
ejpam-5934	418	6	and	and	CCONJ
ejpam-5934	418	7	simon	simon	PROPN
ejpam-5934	418	8	poon	poon	NOUN
ejpam-5934	418	9	.	.	PUNCT
ejpam-5934	419	1	analyzing	analyze	VERB
ejpam-5934	419	2	it	it	PRON
ejpam-5934	419	3	business	business	NOUN
ejpam-5934	419	4	values	value	NOUN
ejpam-5934	419	5	–	–	PUNCT
ejpam-5934	419	6	a	a	DET
ejpam-5934	419	7	dominance	dominance	NOUN
ejpam-5934	419	8	based	base	VERB
ejpam-5934	419	9	rough	rough	ADJ
ejpam-5934	419	10	sets	set	NOUN
ejpam-5934	419	11	approach	approach	NOUN
ejpam-5934	419	12	perspective	perspective	NOUN
ejpam-5934	419	13	.	.	PUNCT
ejpam-5934	420	1	expert	expert	NOUN
ejpam-5934	420	2	systems	system	NOUN
ejpam-5934	420	3	with	with	ADP
ejpam-5934	420	4	applications	application	NOUN
ejpam-5934	420	5	,	,	PUNCT
ejpam-5934	420	6	38(9):11120	38(9):11120	NUM
ejpam-5934	420	7	–	–	PUNCT
ejpam-5934	420	8	11128	11128	NUM
ejpam-5934	420	9	,	,	PUNCT
ejpam-5934	420	10	2011	2011	NUM
ejpam-5934	420	11	.	.	PUNCT
ejpam-5934	421	1	[	[	X
ejpam-5934	421	2	18	18	NUM
ejpam-5934	421	3	]	]	X
ejpam-5934	421	4	andrzej	andrzej	PROPN
ejpam-5934	421	5	janusz	janusz	PROPN
ejpam-5934	421	6	,	,	PUNCT
ejpam-5934	421	7	andżelika	andżelika	X
ejpam-5934	421	8	zalewska	zalewska	X
ejpam-5934	421	9	,	,	PUNCT
ejpam-5934	421	10	lukasz	lukasz	PROPN
ejpam-5934	421	11	wawrowski	wawrowski	NOUN
ejpam-5934	421	12	,	,	PUNCT
ejpam-5934	421	13	piotr	piotr	PROPN
ejpam-5934	421	14	biczyk	biczyk	PROPN
ejpam-5934	421	15	,	,	PUNCT
ejpam-5934	421	16	jan	jan	PROPN
ejpam-5934	421	17	ludziejewski	ludziejewski	PROPN
ejpam-5934	421	18	,	,	PUNCT
ejpam-5934	421	19	marek	marek	PROPN
ejpam-5934	421	20	sikora	sikora	PROPN
ejpam-5934	421	21	,	,	PUNCT
ejpam-5934	421	22	and	and	CCONJ
ejpam-5934	421	23	dominik	dominik	PROPN
ejpam-5934	421	24	ślezak	ślezak	PROPN
ejpam-5934	421	25	.	.	PUNCT
ejpam-5934	422	1	brightbox	brightbox	NOUN
ejpam-5934	422	2	—	—	PUNCT
ejpam-5934	422	3	a	a	DET
ejpam-5934	422	4	rough	rough	ADJ
ejpam-5934	422	5	set	set	NOUN
ejpam-5934	422	6	based	base	VERB
ejpam-5934	422	7	technology	technology	NOUN
ejpam-5934	422	8	for	for	ADP
ejpam-5934	422	9	diagnosing	diagnose	VERB
ejpam-5934	422	10	mistakes	mistake	NOUN
ejpam-5934	422	11	of	of	ADP
ejpam-5934	422	12	machine	machine	NOUN
ejpam-5934	422	13	learning	learning	NOUN
ejpam-5934	422	14	models	model	NOUN
ejpam-5934	422	15	.	.	PUNCT
ejpam-5934	423	1	applied	apply	VERB
ejpam-5934	423	2	soft	soft	ADJ
ejpam-5934	423	3	computing	computing	NOUN
ejpam-5934	423	4	,	,	PUNCT
ejpam-5934	423	5	141:110285	141:110285	NUM
ejpam-5934	423	6	,	,	PUNCT
ejpam-5934	423	7	2023	2023	NUM
ejpam-5934	423	8	.	.	PUNCT
ejpam-5934	424	1	[	[	X
ejpam-5934	424	2	19	19	NUM
ejpam-5934	424	3	]	]	PUNCT
ejpam-5934	424	4	alessio	alessio	PROPN
ejpam-5934	424	5	ferone	ferone	PROPN
ejpam-5934	424	6	.	.	PUNCT
ejpam-5934	425	1	feature	feature	NOUN
ejpam-5934	425	2	selection	selection	NOUN
ejpam-5934	425	3	based	base	VERB
ejpam-5934	425	4	on	on	ADP
ejpam-5934	425	5	composition	composition	NOUN
ejpam-5934	425	6	of	of	ADP
ejpam-5934	425	7	rough	rough	ADJ
ejpam-5934	425	8	sets	set	NOUN
ejpam-5934	425	9	induced	induce	VERB
ejpam-5934	425	10	by	by	ADP
ejpam-5934	425	11	feature	feature	NOUN
ejpam-5934	425	12	granulation	granulation	NOUN
ejpam-5934	425	13	.	.	PUNCT
ejpam-5934	426	1	international	international	ADJ
ejpam-5934	426	2	journal	journal	PROPN
ejpam-5934	426	3	of	of	ADP
ejpam-5934	426	4	approximate	approximate	ADJ
ejpam-5934	426	5	reasoning	reasoning	NOUN
ejpam-5934	426	6	,	,	PUNCT
ejpam-5934	426	7	101:276–292	101:276–292	NUM
ejpam-5934	426	8	,	,	PUNCT
ejpam-5934	426	9	2018	2018	NUM
ejpam-5934	426	10	.	.	PUNCT
ejpam-5934	427	1	[	[	X
ejpam-5934	427	2	20	20	NUM
ejpam-5934	427	3	]	]	PUNCT
ejpam-5934	427	4	jie	jie	PROPN
ejpam-5934	427	5	zhao	zhao	PROPN
ejpam-5934	427	6	,	,	PUNCT
ejpam-5934	427	7	dai	dai	PROPN
ejpam-5934	427	8	-	-	PUNCT
ejpam-5934	427	9	yang	yang	PROPN
ejpam-5934	427	10	wu	wu	PROPN
ejpam-5934	427	11	,	,	PUNCT
ejpam-5934	427	12	yong	yong	PROPN
ejpam-5934	427	13	-	-	PUNCT
ejpam-5934	427	14	xin	xin	PROPN
ejpam-5934	427	15	zhou	zhou	PROPN
ejpam-5934	427	16	,	,	PUNCT
ejpam-5934	427	17	jia	jia	PROPN
ejpam-5934	427	18	-	-	PUNCT
ejpam-5934	427	19	ming	ming	PROPN
ejpam-5934	427	20	liang	liang	PROPN
ejpam-5934	427	21	,	,	PUNCT
ejpam-5934	427	22	wenhong	wenhong	PROPN
ejpam-5934	427	23	wei	wei	PROPN
ejpam-5934	427	24	,	,	PUNCT
ejpam-5934	427	25	and	and	CCONJ
ejpam-5934	427	26	yun	yun	PROPN
ejpam-5934	427	27	li	li	PROPN
ejpam-5934	427	28	.	.	PROPN
ejpam-5934	428	1	rough	rough	ADJ
ejpam-5934	428	2	set	set	NOUN
ejpam-5934	428	3	theory	theory	NOUN
ejpam-5934	428	4	-	-	PUNCT
ejpam-5934	428	5	based	base	VERB
ejpam-5934	428	6	group	group	NOUN
ejpam-5934	428	7	incremental	incremental	ADJ
ejpam-5934	428	8	approach	approach	NOUN
ejpam-5934	428	9	to	to	ADP
ejpam-5934	428	10	feature	feature	NOUN
ejpam-5934	428	11	selection	selection	NOUN
ejpam-5934	428	12	.	.	PUNCT
ejpam-5934	429	1	information	information	NOUN
ejpam-5934	429	2	sciences	sciences	PROPN
ejpam-5934	429	3	,	,	PUNCT
ejpam-5934	429	4	675:120733	675:120733	NUM
ejpam-5934	429	5	,	,	PUNCT
ejpam-5934	429	6	2024	2024	NUM
ejpam-5934	429	7	.	.	PUNCT
ejpam-5934	430	1	[	[	X
ejpam-5934	430	2	21	21	NUM
ejpam-5934	430	3	]	]	PUNCT
ejpam-5934	430	4	moaad	moaad	NOUN
ejpam-5934	430	5	almania	almania	PROPN
ejpam-5934	430	6	,	,	PUNCT
ejpam-5934	430	7	anazida	anazida	PROPN
ejpam-5934	430	8	zainal	zainal	PROPN
ejpam-5934	430	9	,	,	PUNCT
ejpam-5934	430	10	fuad	fuad	PROPN
ejpam-5934	430	11	a	a	DET
ejpam-5934	430	12	ghaleb	ghaleb	NOUN
ejpam-5934	430	13	,	,	PUNCT
ejpam-5934	430	14	ahmad	ahmad	PROPN
ejpam-5934	430	15	alnawasrah	alnawasrah	PROPN
ejpam-5934	430	16	,	,	PUNCT
ejpam-5934	430	17	and	and	CCONJ
ejpam-5934	430	18	mahmoud	mahmoud	PROPN
ejpam-5934	430	19	al	al	PROPN
ejpam-5934	430	20	qerom	qerom	PROPN
ejpam-5934	430	21	.	.	PUNCT
ejpam-5934	431	1	two	two	NUM
ejpam-5934	431	2	-	-	PUNCT
ejpam-5934	431	3	level	level	NOUN
ejpam-5934	431	4	feature	feature	NOUN
ejpam-5934	431	5	selection	selection	NOUN
ejpam-5934	431	6	for	for	ADP
ejpam-5934	431	7	enhanced	enhanced	ADJ
ejpam-5934	431	8	accuracy	accuracy	NOUN
ejpam-5934	431	9	and	and	CCONJ
ejpam-5934	431	10	reduced	reduce	VERB
ejpam-5934	431	11	computational	computational	ADJ
ejpam-5934	431	12	overhead	overhead	NOUN
ejpam-5934	431	13	in	in	ADP
ejpam-5934	431	14	intrusion	intrusion	NOUN
ejpam-5934	431	15	detection	detection	NOUN
ejpam-5934	431	16	systems	system	NOUN
ejpam-5934	431	17	using	use	VERB
ejpam-5934	431	18	rough	rough	ADJ
ejpam-5934	431	19	set	set	NOUN
ejpam-5934	431	20	theory	theory	NOUN
ejpam-5934	431	21	and	and	CCONJ
ejpam-5934	431	22	binary	binary	ADJ
ejpam-5934	431	23	particle	particle	NOUN
ejpam-5934	431	24	swarm	swarm	NOUN
ejpam-5934	431	25	optimization	optimization	NOUN
ejpam-5934	431	26	.	.	PUNCT
ejpam-5934	432	1	journal	journal	PROPN
ejpam-5934	432	2	of	of	ADP
ejpam-5934	432	3	robotics	robotic	NOUN
ejpam-5934	432	4	and	and	CCONJ
ejpam-5934	432	5	control	control	PROPN
ejpam-5934	432	6	(	(	PUNCT
ejpam-5934	432	7	jrc	jrc	PROPN
ejpam-5934	432	8	)	)	PUNCT
ejpam-5934	432	9	,	,	PUNCT
ejpam-5934	432	10	6(1):262–271	6(1):262–271	NUM
ejpam-5934	432	11	,	,	PUNCT
ejpam-5934	432	12	2025	2025	NUM
ejpam-5934	432	13	.	.	PUNCT
ejpam-5934	433	1	[	[	X
ejpam-5934	433	2	22	22	NUM
ejpam-5934	433	3	]	]	X
ejpam-5934	433	4	nasser	nasser	PROPN
ejpam-5934	433	5	alsabilah	alsabilah	PROPN
ejpam-5934	433	6	and	and	CCONJ
ejpam-5934	433	7	danda	danda	PROPN
ejpam-5934	433	8	b	b	PROPN
ejpam-5934	433	9	rawat	rawat	PROPN
ejpam-5934	433	10	.	.	PUNCT
ejpam-5934	434	1	joint	joint	ADJ
ejpam-5934	434	2	rough	rough	ADJ
ejpam-5934	434	3	set	set	NOUN
ejpam-5934	434	4	theory	theory	NOUN
ejpam-5934	434	5	and	and	CCONJ
ejpam-5934	434	6	xgboost	xgboost	ADV
ejpam-5934	434	7	based	base	VERB
ejpam-5934	434	8	learning	learn	VERB
ejpam-5934	434	9	for	for	ADP
ejpam-5934	434	10	network	network	NOUN
ejpam-5934	434	11	intrusion	intrusion	NOUN
ejpam-5934	434	12	detection	detection	NOUN
ejpam-5934	434	13	system	system	NOUN
ejpam-5934	434	14	.	.	PUNCT
ejpam-5934	435	1	ieee	ieee	NOUN
ejpam-5934	435	2	internet	internet	NOUN
ejpam-5934	435	3	of	of	ADP
ejpam-5934	435	4	things	thing	NOUN
ejpam-5934	435	5	journal	journal	NOUN
ejpam-5934	435	6	,	,	PUNCT
ejpam-5934	435	7	2025	2025	NUM
ejpam-5934	435	8	.	.	PUNCT
ejpam-5934	436	1	[	[	X
ejpam-5934	436	2	23	23	NUM
ejpam-5934	436	3	]	]	PUNCT
ejpam-5934	436	4	vk	vk	PROPN
ejpam-5934	436	5	hanuman	hanuman	PROPN
ejpam-5934	436	6	turaga	turaga	PROPN
ejpam-5934	436	7	and	and	CCONJ
ejpam-5934	436	8	srilatha	srilatha	PROPN
ejpam-5934	436	9	chebrolu	chebrolu	PROPN
ejpam-5934	436	10	.	.	PUNCT
ejpam-5934	437	1	efficient	efficient	ADJ
ejpam-5934	437	2	and	and	CCONJ
ejpam-5934	437	3	fast	fast	ADJ
ejpam-5934	437	4	algorithm	algorithm	NOUN
ejpam-5934	437	5	for	for	ADP
ejpam-5934	437	6	attribute	attribute	NOUN
ejpam-5934	437	7	reduction	reduction	NOUN
ejpam-5934	437	8	of	of	ADP
ejpam-5934	437	9	large	large	ADJ
ejpam-5934	437	10	dimensional	dimensional	ADJ
ejpam-5934	437	11	data	datum	NOUN
ejpam-5934	437	12	using	use	VERB
ejpam-5934	437	13	rough	rough	ADJ
ejpam-5934	437	14	set	set	NOUN
ejpam-5934	437	15	theory	theory	NOUN
ejpam-5934	437	16	on	on	ADP
ejpam-5934	437	17	graphics	graphic	NOUN
ejpam-5934	437	18	processing	processing	NOUN
ejpam-5934	437	19	unit	unit	NOUN
ejpam-5934	437	20	.	.	PUNCT
ejpam-5934	438	1	arabian	arabian	ADJ
ejpam-5934	438	2	journal	journal	PROPN
ejpam-5934	438	3	for	for	ADP
ejpam-5934	438	4	science	science	NOUN
ejpam-5934	438	5	and	and	CCONJ
ejpam-5934	438	6	engineering	engineering	NOUN
ejpam-5934	438	7	,	,	PUNCT
ejpam-5934	438	8	50(2):1209–1231	50(2):1209–1231	NUM
ejpam-5934	438	9	,	,	PUNCT
ejpam-5934	438	10	2025	2025	NUM
ejpam-5934	438	11	.	.	PUNCT
ejpam-5934	439	1	[	[	X
ejpam-5934	439	2	24	24	NUM
ejpam-5934	439	3	]	]	PUNCT
ejpam-5934	439	4	kaggle	kaggle	VERB
ejpam-5934	439	5	.	.	PUNCT
ejpam-5934	440	1	seeds	seed	NOUN
ejpam-5934	440	2	dataset	dataset	PROPN
ejpam-5934	440	3	.	.	PUNCT
ejpam-5934	441	1	https://www.kaggle.com/datasets/rwzhang/	https://www.kaggle.com/datasets/rwzhang/	VERB
ejpam-5934	441	2	seeds	seed	NOUN
ejpam-5934	441	3	-	-	PUNCT
ejpam-5934	441	4	dataset	dataset	NOUN
ejpam-5934	441	5	.	.	PUNCT
ejpam-5934	442	1	[	[	X
ejpam-5934	442	2	25	25	NUM
ejpam-5934	442	3	]	]	PUNCT
ejpam-5934	442	4	kaggle	kaggle	PROPN
ejpam-5934	442	5	.	.	PUNCT
ejpam-5934	443	1	online	online	ADJ
ejpam-5934	443	2	food	food	NOUN
ejpam-5934	443	3	delivery	delivery	NOUN
ejpam-5934	443	4	preferences	preference	NOUN
ejpam-5934	443	5	(	(	PUNCT
ejpam-5934	443	6	bangalore	bangalore	NOUN
ejpam-5934	443	7	region	region	NOUN
ejpam-5934	443	8	)	)	PUNCT
ejpam-5934	443	9	.	.	PUNCT
ejpam-5934	444	1	https://www.kaggle	https://www.kaggle	PROPN
ejpam-5934	444	2	.	.	PUNCT
ejpam-5934	444	3	com	com	NOUN
ejpam-5934	444	4	/	/	SYM
ejpam-5934	444	5	datasets	dataset	NOUN
ejpam-5934	444	6	/	/	SYM
ejpam-5934	444	7	sujithmandala	sujithmandala	NOUN
ejpam-5934	444	8	/	/	SYM
ejpam-5934	444	9	obesity	obesity	NOUN
ejpam-5934	444	10	-	-	PUNCT
ejpam-5934	444	11	classification	classification	NOUN
ejpam-5934	444	12	-	-	PUNCT
ejpam-5934	444	13	dataset	dataset	NOUN
ejpam-5934	444	14	.	.	PUNCT
ejpam-5934	445	1	[	[	X
ejpam-5934	445	2	26	26	NUM
ejpam-5934	445	3	]	]	PUNCT
ejpam-5934	445	4	kaggle	kaggle	VERB
ejpam-5934	445	5	.	.	PUNCT
ejpam-5934	446	1	heart	heart	NOUN
ejpam-5934	446	2	disease	disease	NOUN
ejpam-5934	446	3	classification	classification	NOUN
ejpam-5934	446	4	dataset	dataset	NOUN
ejpam-5934	446	5	.	.	PUNCT
ejpam-5934	447	1	https://www.kaggle.com/datasets/	https://www.kaggle.com/datasets/	AUX
ejpam-5934	447	2	https://www.kaggle.com/datasets/rwzhang/seeds-dataset	https://www.kaggle.com/datasets/rwzhang/seeds-dataset	VERB
ejpam-5934	447	3	https://www.kaggle.com/datasets/rwzhang/seeds-dataset	https://www.kaggle.com/datasets/rwzhang/seeds-dataset	PROPN
ejpam-5934	447	4	https://www.kaggle.com/datasets/sujithmandala/obesity-classification-dataset	https://www.kaggle.com/datasets/sujithmandala/obesity-classification-dataset	VERB
ejpam-5934	447	5	https://www.kaggle.com/datasets/sujithmandala/obesity-classification-dataset	https://www.kaggle.com/datasets/sujithmandala/obesity-classification-dataset	VERB
ejpam-5934	447	6	https://www.kaggle.com/datasets/benroshan/online-food-delivery-preferencesbangalore-region/code	https://www.kaggle.com/datasets/benroshan/online-food-delivery-preferencesbangalore-region/code	PUNCT
ejpam-5934	447	7	t.	t.	NOUN
ejpam-5934	447	8	ashika	ashika	NOUN
ejpam-5934	447	9	,	,	PUNCT
ejpam-5934	447	10	g.	g.	PROPN
ejpam-5934	447	11	h.	h.	PROPN
ejpam-5934	447	12	grace	grace	PROPN
ejpam-5934	447	13	/	/	SYM
ejpam-5934	447	14	eur	eur	PROPN
ejpam-5934	447	15	.	.	PUNCT
ejpam-5934	448	1	j.	j.	PROPN
ejpam-5934	448	2	pure	pure	PROPN
ejpam-5934	448	3	appl	appl	PROPN
ejpam-5934	448	4	.	.	PROPN
ejpam-5934	448	5	math	math	PROPN
ejpam-5934	448	6	,	,	PUNCT
ejpam-5934	448	7	18	18	NUM
ejpam-5934	448	8	(	(	PUNCT
ejpam-5934	448	9	2	2	NUM
ejpam-5934	448	10	)	)	PUNCT
ejpam-5934	448	11	(	(	PUNCT
ejpam-5934	448	12	2025	2025	NUM
ejpam-5934	448	13	)	)	PUNCT
ejpam-5934	448	14	,	,	PUNCT
ejpam-5934	448	15	5934	5934	NUM
ejpam-5934	448	16	22	22	NUM
ejpam-5934	448	17	of	of	ADP
ejpam-5934	448	18	22	22	NUM
ejpam-5934	448	19	benroshan	benroshan	NOUN
ejpam-5934	448	20	/	/	SYM
ejpam-5934	448	21	online	online	ADJ
ejpam-5934	448	22	-	-	PUNCT
ejpam-5934	448	23	food	food	NOUN
ejpam-5934	448	24	-	-	PUNCT
ejpam-5934	448	25	delivery	delivery	NOUN
ejpam-5934	448	26	-	-	PUNCT
ejpam-5934	448	27	preferencesbangalore	preferencesbangalore	NOUN
ejpam-5934	448	28	-	-	PUNCT
ejpam-5934	448	29	region	region	NOUN
ejpam-5934	448	30	/	/	SYM
ejpam-5934	448	31	code	code	NOUN
ejpam-5934	448	32	.	.	PUNCT
ejpam-5934	449	1	[	[	X
ejpam-5934	449	2	27	27	NUM
ejpam-5934	449	3	]	]	PUNCT
ejpam-5934	449	4	kaggle	kaggle	NOUN
ejpam-5934	449	5	.	.	PUNCT
ejpam-5934	450	1	obesity	obesity	NOUN
ejpam-5934	450	2	classification	classification	NOUN
ejpam-5934	450	3	dataset	dataset	NOUN
ejpam-5934	450	4	.	.	PUNCT
ejpam-5934	451	1	https://www.kaggle.com/datasets/	https://www.kaggle.com/datasets/	ADJ
ejpam-5934	451	2	benroshan	benroshan	NOUN
ejpam-5934	451	3	/	/	SYM
ejpam-5934	451	4	online	online	ADJ
ejpam-5934	451	5	-	-	PUNCT
ejpam-5934	451	6	food	food	NOUN
ejpam-5934	451	7	-	-	PUNCT
ejpam-5934	451	8	delivery	delivery	NOUN
ejpam-5934	451	9	-	-	PUNCT
ejpam-5934	451	10	preferencesbangalore	preferencesbangalore	NOUN
ejpam-5934	451	11	-	-	PUNCT
ejpam-5934	451	12	region	region	NOUN
ejpam-5934	451	13	/	/	SYM
ejpam-5934	451	14	data	datum	NOUN
ejpam-5934	451	15	.	.	PUNCT
ejpam-5934	452	1	[	[	X
ejpam-5934	452	2	28	28	NUM
ejpam-5934	452	3	]	]	X
ejpam-5934	452	4	uci	uci	PROPN
ejpam-5934	452	5	.	.	PROPN
ejpam-5934	452	6	breast	breast	PROPN
ejpam-5934	452	7	cancer	cancer	PROPN
ejpam-5934	452	8	wisconsin	wisconsin	PROPN
ejpam-5934	452	9	original	original	ADJ
ejpam-5934	452	10	dataset	dataset	NOUN
ejpam-5934	452	11	.	.	PUNCT
ejpam-5934	453	1	https://archive.ics.uci.edu/	https://archive.ics.uci.edu/	VERB
ejpam-5934	453	2	dataset/15	dataset/15	PROPN
ejpam-5934	453	3	/	/	SYM
ejpam-5934	453	4	breast+cancer+wisconsin+original	breast+cancer+wisconsin+original	NOUN
ejpam-5934	453	5	.	.	PUNCT
ejpam-5934	454	1	[	[	X
ejpam-5934	454	2	29	29	NUM
ejpam-5934	454	3	]	]	PUNCT
ejpam-5934	454	4	alessio	alessio	PROPN
ejpam-5934	454	5	ferone	ferone	PROPN
ejpam-5934	454	6	and	and	CCONJ
ejpam-5934	454	7	antonio	antonio	PROPN
ejpam-5934	454	8	maratea	maratea	PROPN
ejpam-5934	454	9	.	.	PUNCT
ejpam-5934	455	1	adaptive	adaptive	ADJ
ejpam-5934	455	2	quick	quick	ADJ
ejpam-5934	455	3	reduct	reduct	NOUN
ejpam-5934	455	4	for	for	ADP
ejpam-5934	455	5	feature	feature	NOUN
ejpam-5934	455	6	drift	drift	NOUN
ejpam-5934	455	7	detection	detection	NOUN
ejpam-5934	455	8	.	.	PUNCT
ejpam-5934	456	1	algorithms	algorithm	NOUN
ejpam-5934	456	2	,	,	PUNCT
ejpam-5934	456	3	14(2):58	14(2):58	NUM
ejpam-5934	456	4	,	,	PUNCT
ejpam-5934	456	5	2021	2021	NUM
ejpam-5934	456	6	.	.	PUNCT
ejpam-5934	457	1	[	[	X
ejpam-5934	457	2	30	30	NUM
ejpam-5934	457	3	]	]	X
ejpam-5934	457	4	vladimir	vladimir	PROPN
ejpam-5934	457	5	nasteski	nasteski	PROPN
ejpam-5934	457	6	.	.	PUNCT
ejpam-5934	458	1	an	an	DET
ejpam-5934	458	2	overview	overview	NOUN
ejpam-5934	458	3	of	of	ADP
ejpam-5934	458	4	the	the	DET
ejpam-5934	458	5	supervised	supervised	ADJ
ejpam-5934	458	6	machine	machine	NOUN
ejpam-5934	458	7	learning	learning	NOUN
ejpam-5934	458	8	methods	method	NOUN
ejpam-5934	458	9	.	.	PUNCT
ejpam-5934	459	1	horizons	horizon	NOUN
ejpam-5934	459	2	.	.	PUNCT
ejpam-5934	460	1	b	b	X
ejpam-5934	460	2	,	,	PUNCT
ejpam-5934	460	3	4(51	4(51	NUM
ejpam-5934	460	4	-	-	SYM
ejpam-5934	460	5	62):56	62):56	NUM
ejpam-5934	460	6	,	,	PUNCT
ejpam-5934	460	7	2017	2017	NUM
ejpam-5934	460	8	.	.	PUNCT
ejpam-5934	461	1	[	[	X
ejpam-5934	461	2	31	31	NUM
ejpam-5934	461	3	]	]	PUNCT
ejpam-5934	461	4	batta	batta	PROPN
ejpam-5934	461	5	mahesh	mahesh	PROPN
ejpam-5934	461	6	et	et	PROPN
ejpam-5934	461	7	al	al	PROPN
ejpam-5934	461	8	.	.	PROPN
ejpam-5934	461	9	machine	machine	NOUN
ejpam-5934	461	10	learning	learn	VERB
ejpam-5934	461	11	algorithms	algorithm	NOUN
ejpam-5934	461	12	-	-	PUNCT
ejpam-5934	461	13	a	a	DET
ejpam-5934	461	14	review	review	NOUN
ejpam-5934	461	15	.	.	PUNCT
ejpam-5934	462	1	international	international	ADJ
ejpam-5934	462	2	journal	journal	PROPN
ejpam-5934	462	3	of	of	ADP
ejpam-5934	462	4	science	science	NOUN
ejpam-5934	462	5	and	and	CCONJ
ejpam-5934	462	6	research	research	NOUN
ejpam-5934	462	7	(	(	PUNCT
ejpam-5934	462	8	ijsr).[internet	ijsr).[internet	X
ejpam-5934	462	9	]	]	X
ejpam-5934	462	10	,	,	PUNCT
ejpam-5934	462	11	9(1):381–386	9(1):381–386	NUM
ejpam-5934	462	12	,	,	PUNCT
ejpam-5934	462	13	2020	2020	NUM
ejpam-5934	462	14	.	.	PUNCT
ejpam-5934	463	1	[	[	X
ejpam-5934	463	2	32	32	NUM
ejpam-5934	463	3	]	]	X
ejpam-5934	463	4	yichuan	yichuan	PROPN
ejpam-5934	463	5	tang	tang	PROPN
ejpam-5934	463	6	.	.	PUNCT
ejpam-5934	464	1	deep	deep	ADJ
ejpam-5934	464	2	learning	learning	NOUN
ejpam-5934	464	3	using	use	VERB
ejpam-5934	464	4	support	support	NOUN
ejpam-5934	464	5	vector	vector	NOUN
ejpam-5934	464	6	machines	machine	NOUN
ejpam-5934	464	7	.	.	PUNCT
ejpam-5934	465	1	corr	corr	PROPN
ejpam-5934	465	2	,	,	PUNCT
ejpam-5934	465	3	abs/1306.0239	abs/1306.0239	NUM
ejpam-5934	465	4	,	,	PUNCT
ejpam-5934	465	5	2(1	2(1	NUM
ejpam-5934	465	6	)	)	PUNCT
ejpam-5934	465	7	,	,	PUNCT
ejpam-5934	465	8	2013	2013	NUM
ejpam-5934	465	9	.	.	PUNCT
ejpam-5934	466	1	[	[	X
ejpam-5934	466	2	33	33	NUM
ejpam-5934	466	3	]	]	PUNCT
ejpam-5934	466	4	arti	arti	NOUN
ejpam-5934	466	5	patle	patle	NOUN
ejpam-5934	466	6	and	and	CCONJ
ejpam-5934	466	7	deepak	deepak	PROPN
ejpam-5934	466	8	singh	singh	PROPN
ejpam-5934	466	9	chouhan	chouhan	PROPN
ejpam-5934	466	10	.	.	PUNCT
ejpam-5934	467	1	svm	svm	PROPN
ejpam-5934	467	2	kernel	kernel	PROPN
ejpam-5934	467	3	functions	function	NOUN
ejpam-5934	467	4	for	for	ADP
ejpam-5934	467	5	classification	classification	NOUN
ejpam-5934	467	6	.	.	PUNCT
ejpam-5934	468	1	in	in	ADP
ejpam-5934	468	2	2013	2013	NUM
ejpam-5934	468	3	international	international	ADJ
ejpam-5934	468	4	conference	conference	NOUN
ejpam-5934	468	5	on	on	ADP
ejpam-5934	468	6	advances	advance	NOUN
ejpam-5934	468	7	in	in	ADP
ejpam-5934	468	8	technology	technology	NOUN
ejpam-5934	468	9	and	and	CCONJ
ejpam-5934	468	10	engineering	engineering	NOUN
ejpam-5934	468	11	(	(	PUNCT
ejpam-5934	468	12	icate	icate	NOUN
ejpam-5934	468	13	)	)	PUNCT
ejpam-5934	468	14	,	,	PUNCT
ejpam-5934	468	15	pages	page	NOUN
ejpam-5934	468	16	1–9	1–9	PROPN
ejpam-5934	468	17	.	.	PROPN
ejpam-5934	468	18	ieee	ieee	PROPN
ejpam-5934	468	19	,	,	PUNCT
ejpam-5934	468	20	2013	2013	NUM
ejpam-5934	468	21	.	.	PUNCT
ejpam-5934	469	1	[	[	X
ejpam-5934	469	2	34	34	NUM
ejpam-5934	469	3	]	]	X
ejpam-5934	469	4	leo	leo	PROPN
ejpam-5934	469	5	breiman	breiman	PROPN
ejpam-5934	469	6	.	.	PUNCT
ejpam-5934	470	1	random	random	ADJ
ejpam-5934	470	2	forests	forest	NOUN
ejpam-5934	470	3	.	.	PUNCT
ejpam-5934	471	1	machine	machine	NOUN
ejpam-5934	471	2	learning	learning	PROPN
ejpam-5934	471	3	,	,	PUNCT
ejpam-5934	471	4	45:5–32	45:5–32	NUM
ejpam-5934	471	5	,	,	PUNCT
ejpam-5934	471	6	2001	2001	NUM
ejpam-5934	471	7	.	.	PUNCT
ejpam-5934	472	1	https://www.kaggle.com/datasets/benroshan/online-food-delivery-preferencesbangalore-region/code	https://www.kaggle.com/datasets/benroshan/online-food-delivery-preferencesbangalore-region/code	X
ejpam-5934	472	2	https://www.kaggle.com/datasets/benroshan/online-food-delivery-preferencesbangalore-region/code	https://www.kaggle.com/datasets/benroshan/online-food-delivery-preferencesbangalore-region/code	PUNCT
ejpam-5934	473	1	https://www.kaggle.com/datasets/benroshan/online-food-delivery-preferencesbangalore-region/data	https://www.kaggle.com/datasets/benroshan/online-food-delivery-preferencesbangalore-region/data	PUNCT
ejpam-5934	474	1	https://www.kaggle.com/datasets/benroshan/online-food-delivery-preferencesbangalore-region/data	https://www.kaggle.com/datasets/benroshan/online-food-delivery-preferencesbangalore-region/data	PROPN
ejpam-5934	474	2	https://archive.ics.uci.edu/dataset/15/breast+cancer+wisconsin+original	https://archive.ics.uci.edu/dataset/15/breast+cancer+wisconsin+original	ADJ
ejpam-5934	474	3	https://archive.ics.uci.edu/dataset/15/breast+cancer+wisconsin+original	https://archive.ics.uci.edu/dataset/15/breast+cancer+wisconsin+original	ADJ
ejpam-5934	474	4	introduction	introduction	NOUN
ejpam-5934	474	5	related	relate	VERB
ejpam-5934	474	6	work	work	NOUN
ejpam-5934	474	7	motivation	motivation	NOUN
ejpam-5934	474	8	and	and	CCONJ
ejpam-5934	474	9	novelty	novelty	NOUN
ejpam-5934	474	10	contribution	contribution	NOUN
ejpam-5934	474	11	materials	material	NOUN
ejpam-5934	474	12	and	and	CCONJ
ejpam-5934	474	13	methods	method	NOUN
ejpam-5934	474	14	proposed	propose	VERB
ejpam-5934	474	15	work	work	NOUN
ejpam-5934	474	16	dataset	dataset	VERB
ejpam-5934	474	17	description	description	NOUN
ejpam-5934	474	18	data	datum	NOUN
ejpam-5934	474	19	preprocessing	preprocesse	VERB
ejpam-5934	474	20	rough	rough	ADJ
ejpam-5934	474	21	set	set	NOUN
ejpam-5934	474	22	theory	theory	NOUN
ejpam-5934	474	23	rst	rst	PROPN
ejpam-5934	474	24	qr	qr	PROPN
ejpam-5934	474	25	algorithm	algorithm	NOUN
ejpam-5934	474	26	models	model	NOUN
ejpam-5934	474	27	of	of	ADP
ejpam-5934	474	28	ml	ml	NOUN
ejpam-5934	474	29	evaluation	evaluation	NOUN
ejpam-5934	474	30	metrics	metric	NOUN
ejpam-5934	474	31	experimental	experimental	ADJ
ejpam-5934	474	32	results	result	NOUN
ejpam-5934	474	33	experimental	experimental	ADJ
ejpam-5934	474	34	setup	setup	NOUN
ejpam-5934	474	35	feature	feature	NOUN
ejpam-5934	474	36	selection	selection	NOUN
ejpam-5934	474	37	classification	classification	NOUN
ejpam-5934	474	38	with	with	ADP
ejpam-5934	474	39	ml	ml	ADP
ejpam-5934	474	40	algorithms	algorithm	NOUN
ejpam-5934	474	41	using	use	VERB
ejpam-5934	474	42	original	original	ADJ
ejpam-5934	474	43	features	feature	NOUN
ejpam-5934	474	44	classification	classification	NOUN
ejpam-5934	474	45	with	with	ADP
ejpam-5934	474	46	ml	ml	ADP
ejpam-5934	474	47	algorithms	algorithm	NOUN
ejpam-5934	474	48	using	use	VERB
ejpam-5934	474	49	features	feature	NOUN
ejpam-5934	474	50	selected	select	VERB
ejpam-5934	474	51	by	by	ADP
ejpam-5934	474	52	rst	rst	PROPN
ejpam-5934	474	53	comparison	comparison	NOUN
ejpam-5934	474	54	of	of	ADP
ejpam-5934	474	55	results	result	NOUN
ejpam-5934	474	56	before	before	ADP
ejpam-5934	474	57	and	and	CCONJ
ejpam-5934	474	58	after	after	ADP
ejpam-5934	474	59	feature	feature	NOUN
ejpam-5934	474	60	selection	selection	NOUN
ejpam-5934	474	61	using	use	VERB
ejpam-5934	474	62	rst	rst	PROPN
ejpam-5934	474	63	seeds	seed	NOUN
ejpam-5934	474	64	dataset	dataset	VERB
ejpam-5934	474	65	heart	heart	NOUN
ejpam-5934	474	66	attack	attack	NOUN
ejpam-5934	474	67	dataset	dataset	VERB
ejpam-5934	474	68	obesity	obesity	NOUN
ejpam-5934	474	69	dataset	dataset	VERB
ejpam-5934	474	70	online	online	ADJ
ejpam-5934	474	71	food	food	NOUN
ejpam-5934	474	72	delivery	delivery	NOUN
ejpam-5934	474	73	dataset	dataset	NOUN
ejpam-5934	474	74	breast	breast	NOUN
ejpam-5934	474	75	cancer	cancer	NOUN
ejpam-5934	474	76	dataset	dataset	VERB
ejpam-5934	474	77	statistical	statistical	ADJ
ejpam-5934	474	78	validation	validation	NOUN
ejpam-5934	474	79	discussion	discussion	NOUN
ejpam-5934	474	80	conclusion	conclusion	NOUN