id	sid	tid	token	lemma	pos
cana-1177	1	1	communications	communication	NOUN
cana-1177	1	2	on	on	ADP
cana-1177	1	3	applied	apply	VERB
cana-1177	1	4	nonlinear	nonlinear	ADJ
cana-1177	1	5	analysis	analysis	NOUN
cana-1177	1	6	issn	issn	NOUN
cana-1177	1	7	:	:	PUNCT
cana-1177	1	8	1074	1074	NUM
cana-1177	1	9	-	-	PUNCT
cana-1177	1	10	133x	133x	NUM
cana-1177	1	11	vol	vol	NOUN
cana-1177	1	12	31	31	NUM
cana-1177	1	13	no	no	NOUN
cana-1177	1	14	.	.	PUNCT
cana-1177	2	1	6s	6s	NUM
cana-1177	2	2	(	(	PUNCT
cana-1177	2	3	2024	2024	NUM
cana-1177	2	4	)	)	PUNCT
cana-1177	2	5	179	179	NUM
cana-1177	3	1	https://internationalpubls.com	https://internationalpubls.com	NUM
cana-1177	3	2	improved	improve	VERB
cana-1177	3	3	methodology	methodology	NOUN
cana-1177	3	4	for	for	ADP
cana-1177	3	5	breast	breast	NOUN
cana-1177	3	6	cancer	cancer	NOUN
cana-1177	3	7	prediction	prediction	NOUN
cana-1177	3	8	through	through	ADP
cana-1177	3	9	integration	integration	NOUN
cana-1177	3	10	of	of	ADP
cana-1177	3	11	hard	hard	ADJ
cana-1177	3	12	voting	voting	NOUN
cana-1177	3	13	ensemble	ensemble	ADJ
cana-1177	3	14	classifier	classifier	NOUN
cana-1177	3	15	on	on	ADP
cana-1177	3	16	wdbc	wdbc	PROPN
cana-1177	3	17	data	datum	NOUN
cana-1177	3	18	set	set	VERB
cana-1177	3	19	archana	archana	PROPN
cana-1177	3	20	singh1	singh1	PROPN
cana-1177	3	21	,	,	PUNCT
cana-1177	3	22	kuldeep	kuldeep	PROPN
cana-1177	3	23	singh	singh	PROPN
cana-1177	3	24	kaswan2	kaswan2	PROPN
cana-1177	4	1	1,2department	1,2department	NUM
cana-1177	4	2	of	of	ADP
cana-1177	4	3	computer	computer	NOUN
cana-1177	4	4	science	science	PROPN
cana-1177	4	5	&	&	CCONJ
cana-1177	4	6	engineering	engineering	PROPN
cana-1177	4	7	,	,	PUNCT
cana-1177	4	8	galgotias	galgotias	PROPN
cana-1177	4	9	university	university	NOUN
cana-1177	4	10	,	,	PUNCT
cana-1177	4	11	greater	great	ADJ
cana-1177	4	12	noida	noida	PROPN
cana-1177	4	13	,	,	PUNCT
cana-1177	4	14	uttar	uttar	PROPN
cana-1177	4	15	pradesh	pradesh	PROPN
cana-1177	4	16	,	,	PUNCT
cana-1177	4	17	india	india	PROPN
cana-1177	4	18	.	.	PUNCT
cana-1177	5	1	article	article	PROPN
cana-1177	5	2	history	history	NOUN
cana-1177	5	3	:	:	PUNCT
cana-1177	5	4	received	receive	VERB
cana-1177	5	5	:	:	PUNCT
cana-1177	5	6	30	30	NUM
cana-1177	5	7	-	-	SYM
cana-1177	5	8	05	05	NUM
cana-1177	5	9	-	-	PUNCT
cana-1177	5	10	2024	2024	NUM
cana-1177	5	11	revised	revise	VERB
cana-1177	5	12	:	:	PUNCT
cana-1177	5	13	20	20	NUM
cana-1177	5	14	-	-	SYM
cana-1177	5	15	07	07	NUM
cana-1177	5	16	-	-	PUNCT
cana-1177	5	17	2024	2024	NUM
cana-1177	5	18	accepted	accept	VERB
cana-1177	5	19	:	:	PUNCT
cana-1177	5	20	02	02	NUM
cana-1177	5	21	-	-	PUNCT
cana-1177	5	22	08	08	NUM
cana-1177	5	23	-	-	PUNCT
cana-1177	5	24	2024	2024	NUM
cana-1177	5	25	abstract	abstract	NOUN
cana-1177	5	26	:	:	PUNCT
cana-1177	5	27	introduction	introduction	NOUN
cana-1177	5	28	:	:	PUNCT
cana-1177	5	29	disease	disease	NOUN
cana-1177	5	30	that	that	PRON
cana-1177	5	31	is	be	AUX
cana-1177	5	32	prevalent	prevalent	ADJ
cana-1177	5	33	and	and	CCONJ
cana-1177	5	34	highly	highly	ADV
cana-1177	5	35	fatal	fatal	ADJ
cana-1177	5	36	is	be	AUX
cana-1177	5	37	the	the	DET
cana-1177	5	38	breast	breast	NOUN
cana-1177	5	39	cancer	cancer	NOUN
cana-1177	5	40	disease	disease	NOUN
cana-1177	5	41	and	and	CCONJ
cana-1177	5	42	it	it	PRON
cana-1177	5	43	affects	affect	VERB
cana-1177	5	44	many	many	ADJ
cana-1177	5	45	people	people	NOUN
cana-1177	5	46	in	in	ADP
cana-1177	5	47	the	the	DET
cana-1177	5	48	world	world	NOUN
cana-1177	5	49	.	.	PUNCT
cana-1177	6	1	to	to	PART
cana-1177	6	2	effectively	effectively	ADV
cana-1177	6	3	prevent	prevent	VERB
cana-1177	6	4	the	the	DET
cana-1177	6	5	fatality	fatality	NOUN
cana-1177	6	6	rate	rate	NOUN
cana-1177	6	7	caused	cause	VERB
cana-1177	6	8	by	by	ADP
cana-1177	6	9	breast	breast	NOUN
cana-1177	6	10	cancer	cancer	NOUN
cana-1177	6	11	,	,	PUNCT
cana-1177	6	12	tools	tool	NOUN
cana-1177	6	13	need	need	VERB
cana-1177	6	14	to	to	PART
cana-1177	6	15	be	be	AUX
cana-1177	6	16	developed	develop	VERB
cana-1177	6	17	that	that	PRON
cana-1177	6	18	are	be	AUX
cana-1177	6	19	capable	capable	ADJ
cana-1177	6	20	of	of	ADP
cana-1177	6	21	early	early	ADJ
cana-1177	6	22	diagnosis	diagnosis	NOUN
cana-1177	6	23	and	and	CCONJ
cana-1177	6	24	efficient	efficient	ADJ
cana-1177	6	25	treatment	treatment	NOUN
cana-1177	6	26	.	.	PUNCT
cana-1177	7	1	researchers	researcher	NOUN
cana-1177	7	2	and	and	CCONJ
cana-1177	7	3	medical	medical	ADJ
cana-1177	7	4	experts	expert	NOUN
cana-1177	7	5	across	across	ADP
cana-1177	7	6	the	the	DET
cana-1177	7	7	world	world	NOUN
cana-1177	7	8	have	have	AUX
cana-1177	7	9	pointed	point	VERB
cana-1177	7	10	out	out	ADP
cana-1177	7	11	several	several	ADJ
cana-1177	7	12	diagnostic	diagnostic	ADJ
cana-1177	7	13	techniques	technique	NOUN
cana-1177	7	14	for	for	ADP
cana-1177	7	15	this	this	DET
cana-1177	7	16	sickness	sickness	NOUN
cana-1177	7	17	;	;	PUNCT
cana-1177	7	18	however	however	ADV
cana-1177	7	19	,	,	PUNCT
cana-1177	7	20	higher	high	ADJ
cana-1177	7	21	enhancement	enhancement	NOUN
cana-1177	7	22	of	of	ADP
cana-1177	7	23	such	such	ADJ
cana-1177	7	24	present	present	ADJ
cana-1177	7	25	methods	method	NOUN
cana-1177	7	26	is	be	AUX
cana-1177	7	27	still	still	ADV
cana-1177	7	28	needed	need	VERB
cana-1177	7	29	to	to	PART
cana-1177	7	30	enhance	enhance	VERB
cana-1177	7	31	a	a	DET
cana-1177	7	32	perfect	perfect	ADJ
cana-1177	7	33	and	and	CCONJ
cana-1177	7	34	effective	effective	ADJ
cana-1177	7	35	diagnosis	diagnosis	NOUN
cana-1177	7	36	of	of	ADP
cana-1177	7	37	this	this	DET
cana-1177	7	38	disease	disease	NOUN
cana-1177	7	39	.	.	PUNCT
cana-1177	8	1	objective	objective	NOUN
cana-1177	8	2	:	:	PUNCT
cana-1177	8	3	it	it	PRON
cana-1177	8	4	’s	’	VERB
cana-1177	8	5	an	an	DET
cana-1177	8	6	objective	objective	NOUN
cana-1177	8	7	of	of	ADP
cana-1177	8	8	this	this	DET
cana-1177	8	9	research	research	NOUN
cana-1177	8	10	to	to	PART
cana-1177	8	11	establish	establish	VERB
cana-1177	8	12	quick	quick	ADJ
cana-1177	8	13	and	and	CCONJ
cana-1177	8	14	precise	precise	ADJ
cana-1177	8	15	forecasts	forecast	NOUN
cana-1177	8	16	of	of	ADP
cana-1177	8	17	breast	breast	NOUN
cana-1177	8	18	cancer	cancer	NOUN
cana-1177	8	19	,	,	PUNCT
cana-1177	8	20	which	which	PRON
cana-1177	8	21	is	be	AUX
cana-1177	8	22	estimated	estimate	VERB
cana-1177	8	23	to	to	PART
cana-1177	8	24	rank	rank	VERB
cana-1177	8	25	second	second	ADV
cana-1177	8	26	as	as	ADP
cana-1177	8	27	a	a	DET
cana-1177	8	28	leading	lead	VERB
cana-1177	8	29	killer	killer	NOUN
cana-1177	8	30	of	of	ADP
cana-1177	8	31	women	woman	NOUN
cana-1177	8	32	globally	globally	ADV
cana-1177	8	33	.	.	PUNCT
cana-1177	9	1	methodology	methodology	NOUN
cana-1177	9	2	:	:	PUNCT
cana-1177	9	3	in	in	ADP
cana-1177	9	4	this	this	DET
cana-1177	9	5	paper	paper	NOUN
cana-1177	9	6	,	,	PUNCT
cana-1177	9	7	we	we	PRON
cana-1177	9	8	provide	provide	VERB
cana-1177	9	9	a	a	DET
cana-1177	9	10	methodology	methodology	NOUN
cana-1177	9	11	based	base	VERB
cana-1177	9	12	on	on	ADP
cana-1177	9	13	hard	hard	ADJ
cana-1177	9	14	voting	voting	NOUN
cana-1177	9	15	ensemble	ensemble	ADJ
cana-1177	9	16	classifier	classifier	NOUN
cana-1177	9	17	that	that	PRON
cana-1177	9	18	combines	combine	VERB
cana-1177	9	19	three	three	NUM
cana-1177	9	20	machine	machine	NOUN
cana-1177	9	21	learning	learn	VERB
cana-1177	9	22	algorithms	algorithm	NOUN
cana-1177	9	23	:	:	PUNCT
cana-1177	9	24	logistic	logistic	ADJ
cana-1177	9	25	regression	regression	NOUN
cana-1177	9	26	,	,	PUNCT
cana-1177	9	27	support	support	NOUN
cana-1177	9	28	vector	vector	NOUN
cana-1177	9	29	machine	machine	NOUN
cana-1177	9	30	and	and	CCONJ
cana-1177	9	31	decision	decision	NOUN
cana-1177	9	32	tree	tree	NOUN
cana-1177	9	33	to	to	PART
cana-1177	9	34	diagnose	diagnose	VERB
cana-1177	9	35	the	the	DET
cana-1177	9	36	kind	kind	NOUN
cana-1177	9	37	of	of	ADP
cana-1177	9	38	breast	breast	NOUN
cana-1177	9	39	cancer	cancer	NOUN
cana-1177	9	40	,	,	PUNCT
cana-1177	9	41	whether	whether	SCONJ
cana-1177	9	42	benign	benign	ADJ
cana-1177	9	43	or	or	CCONJ
cana-1177	9	44	malignant	malignant	ADJ
cana-1177	9	45	.	.	PUNCT
cana-1177	10	1	the	the	DET
cana-1177	10	2	proposed	propose	VERB
cana-1177	10	3	model	model	NOUN
cana-1177	10	4	’s	’s	PART
cana-1177	10	5	performance	performance	NOUN
cana-1177	10	6	is	be	AUX
cana-1177	10	7	evaluated	evaluate	VERB
cana-1177	10	8	in	in	ADP
cana-1177	10	9	this	this	DET
cana-1177	10	10	study	study	NOUN
cana-1177	10	11	using	use	VERB
cana-1177	10	12	the	the	DET
cana-1177	10	13	wisconsin	wisconsin	PROPN
cana-1177	10	14	diagnostic	diagnostic	PROPN
cana-1177	10	15	breast	breast	NOUN
cana-1177	10	16	cancer	cancer	NOUN
cana-1177	10	17	dataset	dataset	NOUN
cana-1177	10	18	(	(	PUNCT
cana-1177	10	19	wdbc	wdbc	PROPN
cana-1177	10	20	)	)	PUNCT
cana-1177	10	21	,	,	PUNCT
cana-1177	10	22	with	with	ADP
cana-1177	10	23	random	random	ADJ
cana-1177	10	24	oversampling	oversampling	NOUN
cana-1177	10	25	(	(	PUNCT
cana-1177	10	26	ros	ros	PROPN
cana-1177	10	27	)	)	PUNCT
cana-1177	10	28	being	be	AUX
cana-1177	10	29	used	use	VERB
cana-1177	10	30	to	to	PART
cana-1177	10	31	balance	balance	VERB
cana-1177	10	32	the	the	DET
cana-1177	10	33	dataset	dataset	NOUN
cana-1177	10	34	and	and	CCONJ
cana-1177	10	35	standard	standard	ADJ
cana-1177	10	36	scaler	scaler	NOUN
cana-1177	10	37	being	be	AUX
cana-1177	10	38	used	use	VERB
cana-1177	10	39	for	for	ADP
cana-1177	10	40	feature	feature	NOUN
cana-1177	10	41	scaling	scaling	NOUN
cana-1177	10	42	.	.	PUNCT
cana-1177	11	1	results	result	NOUN
cana-1177	11	2	:	:	PUNCT
cana-1177	11	3	the	the	DET
cana-1177	11	4	suggested	suggest	VERB
cana-1177	11	5	approach	approach	NOUN
cana-1177	11	6	achieved	achieve	VERB
cana-1177	11	7	an	an	DET
cana-1177	11	8	accuracy	accuracy	NOUN
cana-1177	11	9	of	of	ADP
cana-1177	11	10	0.9825	0.9825	NUM
cana-1177	11	11	,	,	PUNCT
cana-1177	11	12	a	a	DET
cana-1177	11	13	precision	precision	NOUN
cana-1177	11	14	of	of	ADP
cana-1177	11	15	0.9859	0.9859	NUM
cana-1177	11	16	,	,	PUNCT
cana-1177	11	17	a	a	DET
cana-1177	11	18	recall	recall	NOUN
cana-1177	11	19	of	of	ADP
cana-1177	11	20	0.9859	0.9859	NUM
cana-1177	11	21	,	,	PUNCT
cana-1177	11	22	f1	f1	NOUN
cana-1177	11	23	score	score	NOUN
cana-1177	11	24	of	of	ADP
cana-1177	11	25	0.9859and	0.9859and	NUM
cana-1177	11	26	auc	auc	NOUN
cana-1177	11	27	of	of	ADP
cana-1177	11	28	.9813	.9813	PROPN
cana-1177	11	29	.	.	PUNCT
cana-1177	12	1	using	use	VERB
cana-1177	12	2	a	a	DET
cana-1177	12	3	10	10	NUM
cana-1177	12	4	-	-	ADJ
cana-1177	12	5	fold	fold	ADJ
cana-1177	12	6	cross	cross	NOUN
cana-1177	12	7	validation	validation	NOUN
cana-1177	12	8	it	it	PRON
cana-1177	12	9	obtained	obtain	VERB
cana-1177	12	10	a	a	DET
cana-1177	12	11	mean	mean	ADJ
cana-1177	12	12	accuracy	accuracy	NOUN
cana-1177	12	13	of	of	ADP
cana-1177	12	14	.9738	.9738	PROPN
cana-1177	12	15	.	.	PUNCT
cana-1177	13	1	conclusions	conclusion	NOUN
cana-1177	13	2	:	:	PUNCT
cana-1177	13	3	the	the	DET
cana-1177	13	4	suggested	suggest	VERB
cana-1177	13	5	approach	approach	NOUN
cana-1177	13	6	yielded	yield	VERB
cana-1177	13	7	superior	superior	ADJ
cana-1177	13	8	results	result	NOUN
cana-1177	13	9	after	after	SCONJ
cana-1177	13	10	the	the	DET
cana-1177	13	11	individual	individual	ADJ
cana-1177	13	12	classifier	classifier	NOUN
cana-1177	13	13	and	and	CCONJ
cana-1177	13	14	many	many	ADJ
cana-1177	13	15	acknowledged	acknowledge	VERB
cana-1177	13	16	existing	exist	VERB
cana-1177	13	17	works	work	NOUN
cana-1177	13	18	are	be	AUX
cana-1177	13	19	directly	directly	ADV
cana-1177	13	20	compared	compare	VERB
cana-1177	13	21	with	with	ADP
cana-1177	13	22	the	the	DET
cana-1177	13	23	results	result	NOUN
cana-1177	13	24	.	.	PUNCT
cana-1177	14	1	keywords	keyword	NOUN
cana-1177	14	2	:	:	PUNCT
cana-1177	14	3	breast	breast	NOUN
cana-1177	14	4	cancer	cancer	NOUN
cana-1177	14	5	,	,	PUNCT
cana-1177	14	6	machine	machine	NOUN
cana-1177	14	7	learning	learning	NOUN
cana-1177	14	8	,	,	PUNCT
cana-1177	14	9	prediction	prediction	NOUN
cana-1177	14	10	,	,	PUNCT
cana-1177	14	11	wdbc	wdbc	NOUN
cana-1177	14	12	,	,	PUNCT
cana-1177	14	13	hard	hard	ADJ
cana-1177	14	14	voting	voting	NOUN
cana-1177	14	15	classifier	classifier	NOUN
cana-1177	14	16	1	1	NUM
cana-1177	14	17	.	.	PUNCT
cana-1177	14	18	introduction	introduction	NOUN
cana-1177	14	19	the	the	DET
cana-1177	14	20	most	most	ADV
cana-1177	14	21	prevalent	prevalent	ADJ
cana-1177	14	22	disease	disease	NOUN
cana-1177	14	23	in	in	ADP
cana-1177	14	24	women	woman	NOUN
cana-1177	14	25	to	to	PART
cana-1177	14	26	be	be	AUX
cana-1177	14	27	diagnosed	diagnose	VERB
cana-1177	14	28	with	with	ADP
cana-1177	14	29	and	and	CCONJ
cana-1177	14	30	the	the	DET
cana-1177	14	31	leading	lead	VERB
cana-1177	14	32	cause	cause	NOUN
cana-1177	14	33	of	of	ADP
cana-1177	14	34	cancer	cancer	NOUN
cana-1177	14	35	-	-	PUNCT
cana-1177	14	36	related	relate	VERB
cana-1177	14	37	deaths	death	NOUN
cana-1177	14	38	is	be	AUX
cana-1177	14	39	breast	breast	NOUN
cana-1177	14	40	cancer	cancer	NOUN
cana-1177	14	41	(	(	PUNCT
cana-1177	14	42	bc	bc	PROPN
cana-1177	14	43	)	)	PUNCT
cana-1177	14	44	.	.	PUNCT
cana-1177	15	1	in	in	ADP
cana-1177	15	2	2020	2020	NUM
cana-1177	15	3	,	,	PUNCT
cana-1177	15	4	2.3	2.3	NUM
cana-1177	15	5	million	million	NUM
cana-1177	15	6	women	woman	NOUN
cana-1177	15	7	received	receive	VERB
cana-1177	15	8	a	a	DET
cana-1177	15	9	breast	breast	NOUN
cana-1177	15	10	cancer	cancer	NOUN
cana-1177	15	11	diagnosis	diagnosis	NOUN
cana-1177	15	12	,	,	PUNCT
cana-1177	15	13	and	and	CCONJ
cana-1177	15	14	685,000	685,000	NUM
cana-1177	15	15	women	woman	NOUN
cana-1177	15	16	died	die	VERB
cana-1177	15	17	from	from	ADP
cana-1177	15	18	this	this	DET
cana-1177	15	19	disease	disease	NOUN
cana-1177	15	20	,	,	PUNCT
cana-1177	15	21	according	accord	VERB
cana-1177	15	22	to	to	ADP
cana-1177	15	23	the	the	DET
cana-1177	15	24	who	who	PRON
cana-1177	15	25	.	.	PUNCT
cana-1177	16	1	the	the	DET
cana-1177	16	2	“	"	PUNCT
cana-1177	16	3	world	world	PROPN
cana-1177	16	4	health	health	NOUN
cana-1177	16	5	organization	organization	NOUN
cana-1177	16	6	”	"	PUNCT
cana-1177	16	7	predicts	predict	VERB
cana-1177	16	8	that	that	SCONJ
cana-1177	16	9	963,000	963,000	NUM
cana-1177	16	10	women	woman	NOUN
cana-1177	16	11	will	will	AUX
cana-1177	16	12	lose	lose	VERB
cana-1177	16	13	their	their	PRON
cana-1177	16	14	lives	life	NOUN
cana-1177	16	15	to	to	ADP
cana-1177	16	16	breast	breast	NOUN
cana-1177	16	17	cancer	cancer	NOUN
cana-1177	16	18	globally	globally	ADV
cana-1177	16	19	in	in	ADP
cana-1177	16	20	2021.around	2021.around	ADP
cana-1177	16	21	the	the	DET
cana-1177	16	22	globe	globe	NOUN
cana-1177	16	23	females	female	NOUN
cana-1177	16	24	get	get	VERB
cana-1177	16	25	breast	breast	NOUN
cana-1177	16	26	cancer	cancer	NOUN
cana-1177	16	27	at	at	ADP
cana-1177	16	28	any	any	DET
cana-1177	16	29	age	age	NOUN
cana-1177	16	30	after	after	ADP
cana-1177	16	31	adolescence	adolescence	NOUN
cana-1177	16	32	while	while	SCONJ
cana-1177	16	33	the	the	DET
cana-1177	16	34	incidence	incidence	NOUN
cana-1177	16	35	rises	rise	VERB
cana-1177	16	36	with	with	ADP
cana-1177	16	37	age	age	NOUN
cana-1177	16	38	.	.	PUNCT
cana-1177	17	1	the	the	DET
cana-1177	17	2	most	most	ADV
cana-1177	17	3	significant	significant	ADJ
cana-1177	17	4	risk	risk	NOUN
cana-1177	17	5	factor	factor	NOUN
cana-1177	17	6	to	to	ADP
cana-1177	17	7	breast	breast	NOUN
cana-1177	17	8	cancer	cancer	NOUN
cana-1177	17	9	is	be	AUX
cana-1177	17	10	female	female	ADJ
cana-1177	17	11	gender	gender	NOUN
cana-1177	17	12	.	.	PUNCT
cana-1177	18	1	men	man	NOUN
cana-1177	18	2	are	be	AUX
cana-1177	18	3	influenced	influence	VERB
cana-1177	18	4	by	by	ADP
cana-1177	18	5	breast	breast	NOUN
cana-1177	18	6	cancer	cancer	NOUN
cana-1177	18	7	in	in	ADP
cana-1177	18	8	a	a	DET
cana-1177	18	9	range	range	NOUN
cana-1177	18	10	of	of	ADP
cana-1177	18	11	0.5–1	0.5–1	NOUN
cana-1177	18	12	%	%	NOUN
cana-1177	18	13	and	and	CCONJ
cana-1177	18	14	the	the	DET
cana-1177	18	15	care	care	NOUN
cana-1177	18	16	of	of	ADP
cana-1177	18	17	breast	breast	NOUN
cana-1177	18	18	cancer	cancer	NOUN
cana-1177	18	19	in	in	ADP
cana-1177	18	20	males	male	NOUN
cana-1177	18	21	is	be	AUX
cana-1177	18	22	based	base	VERB
cana-1177	18	23	on	on	ADP
cana-1177	18	24	the	the	DET
cana-1177	18	25	same	same	ADJ
cana-1177	18	26	concepts	concept	NOUN
cana-1177	18	27	as	as	ADP
cana-1177	18	28	in	in	ADP
cana-1177	18	29	women	woman	NOUN
cana-1177	18	30	[	[	X
cana-1177	18	31	1	1	NUM
cana-1177	18	32	]	]	PUNCT
cana-1177	18	33	.	.	PUNCT
cana-1177	19	1	breast	breast	NOUN
cana-1177	19	2	cancer	cancer	NOUN
cana-1177	19	3	have	have	VERB
cana-1177	19	4	several	several	ADJ
cana-1177	19	5	stages	stage	NOUN
cana-1177	19	6	each	each	PRON
cana-1177	19	7	characterized	characterize	VERB
cana-1177	19	8	by	by	ADP
cana-1177	19	9	the	the	DET
cana-1177	19	10	extent	extent	NOUN
cana-1177	19	11	of	of	ADP
cana-1177	19	12	the	the	DET
cana-1177	19	13	disease	disease	NOUN
cana-1177	19	14	and	and	CCONJ
cana-1177	19	15	the	the	DET
cana-1177	19	16	spread	spread	NOUN
cana-1177	19	17	of	of	ADP
cana-1177	19	18	cancer	cancer	NOUN
cana-1177	19	19	cells	cell	NOUN
cana-1177	19	20	.	.	PUNCT
cana-1177	20	1	table	table	NOUN
cana-1177	20	2	1	1	NUM
cana-1177	20	3	underscores	underscore	VERB
cana-1177	20	4	the	the	DET
cana-1177	20	5	various	various	ADJ
cana-1177	20	6	stages	stage	NOUN
cana-1177	20	7	of	of	ADP
cana-1177	20	8	breast	breast	NOUN
cana-1177	20	9	cancer	cancer	NOUN
cana-1177	20	10	with	with	ADP
cana-1177	20	11	description	description	NOUN
cana-1177	20	12	.	.	PUNCT
cana-1177	21	1	according	accord	VERB
cana-1177	21	2	to	to	ADP
cana-1177	21	3	who	who	PRON
cana-1177	21	4	communications	communication	NOUN
cana-1177	21	5	on	on	ADP
cana-1177	21	6	applied	apply	VERB
cana-1177	21	7	nonlinear	nonlinear	ADJ
cana-1177	21	8	analysis	analysis	NOUN
cana-1177	21	9	issn	issn	NOUN
cana-1177	21	10	:	:	PUNCT
cana-1177	21	11	1074	1074	NUM
cana-1177	21	12	-	-	PUNCT
cana-1177	21	13	133x	133x	NUM
cana-1177	21	14	vol	vol	NOUN
cana-1177	21	15	31	31	NUM
cana-1177	21	16	no	no	NOUN
cana-1177	21	17	.	.	PUNCT
cana-1177	22	1	6s	6s	NUM
cana-1177	22	2	(	(	PUNCT
cana-1177	22	3	2024	2024	NUM
cana-1177	22	4	)	)	PUNCT
cana-1177	22	5	180	180	NUM
cana-1177	22	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-1177	22	7	information	information	NOUN
cana-1177	22	8	the	the	DET
cana-1177	22	9	breast	breast	NOUN
cana-1177	22	10	cancer	cancer	NOUN
cana-1177	22	11	deaths	death	NOUN
cana-1177	22	12	averted	avert	VERB
cana-1177	22	13	by	by	ADP
cana-1177	22	14	2.5	2.5	NUM
cana-1177	22	15	million	million	NUM
cana-1177	22	16	from	from	ADP
cana-1177	22	17	predicted	predict	VERB
cana-1177	22	18	deaths	death	NOUN
cana-1177	22	19	in	in	ADP
cana-1177	22	20	20	20	NUM
cana-1177	22	21	years	year	NOUN
cana-1177	22	22	(	(	PUNCT
cana-1177	22	23	by	by	ADP
cana-1177	22	24	2040	2040	NUM
cana-1177	22	25	)	)	PUNCT
cana-1177	22	26	.	.	PUNCT
cana-1177	23	1	this	this	DET
cana-1177	23	2	global	global	ADJ
cana-1177	23	3	initiative	initiative	NOUN
cana-1177	23	4	is	be	AUX
cana-1177	23	5	taken	take	VERB
cana-1177	23	6	by	by	ADP
cana-1177	23	7	world	world	NOUN
cana-1177	23	8	health	health	NOUN
cana-1177	23	9	organization	organization	NOUN
cana-1177	23	10	to	to	PART
cana-1177	23	11	reduce	reduce	VERB
cana-1177	23	12	breast	breast	NOUN
cana-1177	23	13	cancer	cancer	NOUN
cana-1177	23	14	deaths	death	NOUN
cana-1177	23	15	rate	rate	NOUN
cana-1177	24	1	[	[	X
cana-1177	24	2	1	1	NUM
cana-1177	24	3	]	]	PUNCT
cana-1177	24	4	.	.	PUNCT
cana-1177	25	1	to	to	PART
cana-1177	25	2	achieve	achieve	VERB
cana-1177	25	3	this	this	DET
cana-1177	25	4	initiative	initiative	NOUN
cana-1177	25	5	early	early	ADJ
cana-1177	25	6	identification	identification	NOUN
cana-1177	25	7	and	and	CCONJ
cana-1177	25	8	accurate	accurate	ADJ
cana-1177	25	9	diagnosis	diagnosis	NOUN
cana-1177	25	10	of	of	ADP
cana-1177	25	11	bc	bc	PROPN
cana-1177	25	12	is	be	AUX
cana-1177	25	13	most	most	ADV
cana-1177	25	14	essential	essential	ADJ
cana-1177	25	15	to	to	PART
cana-1177	25	16	improve	improve	VERB
cana-1177	25	17	patient	patient	ADJ
cana-1177	25	18	outcomes	outcome	NOUN
cana-1177	25	19	and	and	CCONJ
cana-1177	25	20	reduce	reduce	VERB
cana-1177	25	21	mortality	mortality	NOUN
cana-1177	25	22	rate	rate	NOUN
cana-1177	25	23	.	.	PUNCT
cana-1177	26	1	table	table	NOUN
cana-1177	26	2	1	1	NUM
cana-1177	26	3	stages	stage	NOUN
cana-1177	26	4	and	and	CCONJ
cana-1177	26	5	classification	classification	NOUN
cana-1177	26	6	of	of	ADP
cana-1177	26	7	breast	breast	NOUN
cana-1177	26	8	cancer	cancer	NOUN
cana-1177	26	9	stages	stage	VERB
cana-1177	26	10	description	description	NOUN
cana-1177	26	11	classification	classification	NOUN
cana-1177	26	12	stage	stage	NOUN
cana-1177	26	13	0	0	NUM
cana-1177	26	14	breast	breast	NOUN
cana-1177	26	15	milk	milk	NOUN
cana-1177	26	16	duct	duct	NOUN
cana-1177	26	17	-	-	PUNCT
cana-1177	26	18	confined	confine	VERB
cana-1177	26	19	non	non	ADJ
cana-1177	26	20	-	-	ADJ
cana-1177	26	21	invasive	invasive	ADJ
cana-1177	26	22	cancer	cancer	NOUN
cana-1177	26	23	cells	cell	NOUN
cana-1177	26	24	are	be	AUX
cana-1177	26	25	known	know	VERB
cana-1177	26	26	as	as	ADP
cana-1177	26	27	ductal	ductal	ADJ
cana-1177	26	28	carcinoma	carcinoma	NOUN
cana-1177	26	29	in	in	ADP
cana-1177	26	30	situ	situ	PROPN
cana-1177	26	31	(	(	PUNCT
cana-1177	26	32	dcis	dcis	NOUN
cana-1177	26	33	)	)	PUNCT
cana-1177	26	34	.	.	PUNCT
cana-1177	27	1	malignant	malignant	ADJ
cana-1177	27	2	stage	stage	NOUN
cana-1177	27	3	i	i	PRON
cana-1177	27	4	early	early	ADJ
cana-1177	27	5	-	-	PUNCT
cana-1177	27	6	stage	stage	NOUN
cana-1177	27	7	cancer	cancer	NOUN
cana-1177	27	8	where	where	SCONJ
cana-1177	27	9	the	the	DET
cana-1177	27	10	tumour	tumour	NOUN
cana-1177	27	11	size	size	NOUN
cana-1177	27	12	is	be	AUX
cana-1177	27	13	small	small	ADJ
cana-1177	27	14	and	and	CCONJ
cana-1177	27	15	has	have	AUX
cana-1177	27	16	not	not	PART
cana-1177	27	17	spread	spread	VERB
cana-1177	27	18	outside	outside	ADP
cana-1177	27	19	the	the	DET
cana-1177	27	20	breast	breast	NOUN
cana-1177	27	21	tissue	tissue	NOUN
cana-1177	27	22	.	.	PUNCT
cana-1177	28	1	malignant	malignant	ADJ
cana-1177	28	2	stage	stage	NOUN
cana-1177	28	3	ii	ii	PROPN
cana-1177	28	4	the	the	DET
cana-1177	28	5	cancer	cancer	NOUN
cana-1177	28	6	has	have	AUX
cana-1177	28	7	grown	grow	VERB
cana-1177	28	8	larger	large	ADJ
cana-1177	28	9	and	and	CCONJ
cana-1177	28	10	may	may	AUX
cana-1177	28	11	have	have	AUX
cana-1177	28	12	spread	spread	VERB
cana-1177	28	13	to	to	ADP
cana-1177	28	14	lymph	lymph	NOUN
cana-1177	28	15	nodes	node	NOUN
cana-1177	28	16	in	in	ADP
cana-1177	28	17	the	the	DET
cana-1177	28	18	vicinity	vicinity	NOUN
cana-1177	28	19	,	,	PUNCT
cana-1177	28	20	but	but	CCONJ
cana-1177	28	21	it	it	PRON
cana-1177	28	22	has	have	AUX
cana-1177	28	23	not	not	PART
cana-1177	28	24	yet	yet	ADV
cana-1177	28	25	reached	reach	VERB
cana-1177	28	26	distant	distant	ADJ
cana-1177	28	27	organs	organ	NOUN
cana-1177	28	28	.	.	PUNCT
cana-1177	29	1	malignant	malignant	ADJ
cana-1177	29	2	stage	stage	NOUN
cana-1177	29	3	iii	iii	X
cana-1177	29	4	locally	locally	ADV
cana-1177	29	5	advanced	advanced	ADJ
cana-1177	29	6	cancer	cancer	NOUN
cana-1177	29	7	that	that	PRON
cana-1177	29	8	has	have	AUX
cana-1177	29	9	spread	spread	VERB
cana-1177	29	10	to	to	ADP
cana-1177	29	11	nearby	nearby	ADJ
cana-1177	29	12	lymph	lymph	NOUN
cana-1177	29	13	nodes	node	NOUN
cana-1177	29	14	and	and	CCONJ
cana-1177	29	15	tissues	tissue	NOUN
cana-1177	29	16	but	but	CCONJ
cana-1177	29	17	not	not	PART
cana-1177	29	18	too	too	ADV
cana-1177	29	19	distant	distant	ADJ
cana-1177	29	20	organs	organ	NOUN
cana-1177	29	21	.	.	PUNCT
cana-1177	30	1	malignant	malignant	ADJ
cana-1177	30	2	stage	stage	NOUN
cana-1177	30	3	iv	iv	NUM
cana-1177	30	4	advanced	advanced	ADJ
cana-1177	30	5	cancer	cancer	NOUN
cana-1177	30	6	that	that	PRON
cana-1177	30	7	has	have	AUX
cana-1177	30	8	metastasized	metastasize	VERB
cana-1177	30	9	to	to	ADP
cana-1177	30	10	distant	distant	ADJ
cana-1177	30	11	organs	organ	NOUN
cana-1177	30	12	such	such	ADJ
cana-1177	30	13	as	as	ADP
cana-1177	30	14	the	the	DET
cana-1177	30	15	bones	bone	NOUN
cana-1177	30	16	,	,	PUNCT
cana-1177	30	17	lungs	lung	NOUN
cana-1177	30	18	,	,	PUNCT
cana-1177	30	19	liver	liver	NOUN
cana-1177	30	20	and	and	CCONJ
cana-1177	30	21	brain	brain	NOUN
cana-1177	30	22	.	.	PUNCT
cana-1177	31	1	malignant	malignant	ADJ
cana-1177	31	2	benign	benign	ADJ
cana-1177	31	3	abnormal	abnormal	ADJ
cana-1177	31	4	cells	cell	NOUN
cana-1177	31	5	or	or	CCONJ
cana-1177	31	6	growths	growth	NOUN
cana-1177	31	7	that	that	PRON
cana-1177	31	8	are	be	AUX
cana-1177	31	9	non	non	ADJ
cana-1177	31	10	-	-	ADJ
cana-1177	31	11	cancerous	cancerous	ADJ
cana-1177	31	12	and	and	CCONJ
cana-1177	31	13	not	not	PART
cana-1177	31	14	spreading	spread	VERB
cana-1177	31	15	to	to	ADP
cana-1177	31	16	the	the	DET
cana-1177	31	17	body	body	NOUN
cana-1177	31	18	's	's	PART
cana-1177	31	19	other	other	ADJ
cana-1177	31	20	regions	region	NOUN
cana-1177	31	21	.	.	PUNCT
cana-1177	32	1	benign	benign	ADJ
cana-1177	32	2	traditional	traditional	ADJ
cana-1177	32	3	diagnostic	diagnostic	ADJ
cana-1177	32	4	techniques	technique	NOUN
cana-1177	32	5	are	be	AUX
cana-1177	32	6	susceptible	susceptible	ADJ
cana-1177	32	7	to	to	ADP
cana-1177	32	8	human	human	ADJ
cana-1177	32	9	error	error	NOUN
cana-1177	32	10	.	.	PUNCT
cana-1177	33	1	machine	machine	NOUN
cana-1177	33	2	learning	learning	NOUN
cana-1177	33	3	(	(	PUNCT
cana-1177	33	4	ml	ml	NOUN
cana-1177	33	5	)	)	PUNCT
cana-1177	33	6	approaches	approach	NOUN
cana-1177	33	7	have	have	AUX
cana-1177	33	8	been	be	AUX
cana-1177	33	9	used	use	VERB
cana-1177	33	10	into	into	ADP
cana-1177	33	11	breast	breast	NOUN
cana-1177	33	12	cancer	cancer	NOUN
cana-1177	33	13	prediction	prediction	NOUN
cana-1177	33	14	with	with	ADP
cana-1177	33	15	hopeful	hopeful	ADJ
cana-1177	33	16	results	result	NOUN
cana-1177	33	17	in	in	ADP
cana-1177	33	18	recent	recent	ADJ
cana-1177	33	19	years	year	NOUN
cana-1177	33	20	providing	provide	VERB
cana-1177	33	21	accurate	accurate	ADJ
cana-1177	33	22	and	and	CCONJ
cana-1177	33	23	efficient	efficient	ADJ
cana-1177	33	24	tools	tool	NOUN
cana-1177	33	25	for	for	ADP
cana-1177	33	26	diagnosis	diagnosis	NOUN
cana-1177	33	27	and	and	CCONJ
cana-1177	33	28	risk	risk	NOUN
cana-1177	33	29	assessment	assessment	NOUN
cana-1177	33	30	.	.	PUNCT
cana-1177	34	1	by	by	ADP
cana-1177	34	2	leveraging	leverage	VERB
cana-1177	34	3	advanced	advanced	ADJ
cana-1177	34	4	algorithms	algorithm	NOUN
cana-1177	34	5	and	and	CCONJ
cana-1177	34	6	computational	computational	ADJ
cana-1177	34	7	techniques	technique	NOUN
cana-1177	34	8	ml	ml	NOUN
cana-1177	34	9	algorithms	algorithm	NOUN
cana-1177	34	10	can	can	AUX
cana-1177	34	11	analyse	analyse	VERB
cana-1177	34	12	vast	vast	ADJ
cana-1177	34	13	amounts	amount	NOUN
cana-1177	34	14	of	of	ADP
cana-1177	34	15	patient	patient	ADJ
cana-1177	34	16	data	datum	NOUN
cana-1177	34	17	including	include	VERB
cana-1177	34	18	imaging	imaging	NOUN
cana-1177	34	19	scans	scan	NOUN
cana-1177	34	20	,	,	PUNCT
cana-1177	34	21	genetic	genetic	ADJ
cana-1177	34	22	markers	marker	NOUN
cana-1177	34	23	,	,	PUNCT
cana-1177	34	24	and	and	CCONJ
cana-1177	34	25	clinical	clinical	ADJ
cana-1177	34	26	records	record	NOUN
cana-1177	34	27	,	,	PUNCT
cana-1177	34	28	to	to	PART
cana-1177	34	29	identify	identify	VERB
cana-1177	34	30	patterns	pattern	NOUN
cana-1177	34	31	and	and	CCONJ
cana-1177	34	32	relationships	relationship	NOUN
cana-1177	34	33	that	that	PRON
cana-1177	34	34	may	may	AUX
cana-1177	34	35	not	not	PART
cana-1177	34	36	be	be	AUX
cana-1177	34	37	apparent	apparent	ADJ
cana-1177	34	38	to	to	ADP
cana-1177	34	39	human	human	ADJ
cana-1177	34	40	observers	observer	NOUN
cana-1177	34	41	.	.	PUNCT
cana-1177	35	1	these	these	DET
cana-1177	35	2	algorithms	algorithm	NOUN
cana-1177	35	3	have	have	VERB
cana-1177	35	4	the	the	DET
cana-1177	35	5	potential	potential	NOUN
cana-1177	35	6	to	to	PART
cana-1177	35	7	improve	improve	VERB
cana-1177	35	8	early	early	ADJ
cana-1177	35	9	detection	detection	NOUN
cana-1177	35	10	rates	rate	NOUN
cana-1177	35	11	leading	lead	VERB
cana-1177	35	12	to	to	ADP
cana-1177	35	13	more	more	ADV
cana-1177	35	14	timely	timely	ADJ
cana-1177	35	15	interventions	intervention	NOUN
cana-1177	35	16	and	and	CCONJ
cana-1177	35	17	better	well	ADJ
cana-1177	35	18	patient	patient	ADJ
cana-1177	35	19	outcomes	outcome	NOUN
cana-1177	35	20	.	.	PUNCT
cana-1177	36	1	ongoing	ongoing	ADJ
cana-1177	36	2	research	research	NOUN
cana-1177	36	3	in	in	ADP
cana-1177	36	4	ml	ml	NOUN
cana-1177	36	5	continues	continue	VERB
cana-1177	36	6	to	to	PART
cana-1177	36	7	refine	refine	VERB
cana-1177	36	8	and	and	CCONJ
cana-1177	36	9	enhance	enhance	VERB
cana-1177	36	10	predictive	predictive	ADJ
cana-1177	36	11	models	model	NOUN
cana-1177	36	12	enabling	enable	VERB
cana-1177	36	13	the	the	DET
cana-1177	36	14	integration	integration	NOUN
cana-1177	36	15	of	of	ADP
cana-1177	36	16	emerging	emerge	VERB
cana-1177	36	17	technologies	technology	NOUN
cana-1177	36	18	such	such	ADJ
cana-1177	36	19	as	as	ADP
cana-1177	36	20	deep	deep	ADJ
cana-1177	36	21	learning	learning	NOUN
cana-1177	36	22	and	and	CCONJ
cana-1177	36	23	ensemble	ensemble	ADJ
cana-1177	36	24	methods	method	NOUN
cana-1177	36	25	to	to	PART
cana-1177	36	26	further	far	ADV
cana-1177	36	27	enhance	enhance	VERB
cana-1177	36	28	accuracy	accuracy	NOUN
cana-1177	36	29	and	and	CCONJ
cana-1177	36	30	reliability	reliability	NOUN
cana-1177	36	31	.	.	PUNCT
cana-1177	37	1	in	in	ADP
cana-1177	37	2	this	this	DET
cana-1177	37	3	paper	paper	NOUN
cana-1177	37	4	a	a	DET
cana-1177	37	5	hard	hard	ADJ
cana-1177	37	6	voting	voting	NOUN
cana-1177	37	7	-	-	PUNCT
cana-1177	37	8	based	base	VERB
cana-1177	37	9	classification	classification	NOUN
cana-1177	37	10	model	model	NOUN
cana-1177	37	11	is	be	AUX
cana-1177	37	12	purposed	purpose	VERB
cana-1177	37	13	to	to	PART
cana-1177	37	14	predict	predict	VERB
cana-1177	37	15	the	the	DET
cana-1177	37	16	breast	breast	NOUN
cana-1177	37	17	cancer	cancer	NOUN
cana-1177	37	18	.	.	PUNCT
cana-1177	38	1	standard	standard	ADJ
cana-1177	38	2	metrics	metric	NOUN
cana-1177	38	3	can	can	AUX
cana-1177	38	4	be	be	AUX
cana-1177	38	5	used	use	VERB
cana-1177	38	6	to	to	PART
cana-1177	38	7	assess	assess	VERB
cana-1177	38	8	the	the	DET
cana-1177	38	9	performance	performance	NOUN
cana-1177	38	10	of	of	ADP
cana-1177	38	11	the	the	DET
cana-1177	38	12	three	three	NUM
cana-1177	38	13	chosen	choose	VERB
cana-1177	38	14	classification	classification	NOUN
cana-1177	38	15	methods	method	NOUN
cana-1177	38	16	,	,	PUNCT
cana-1177	38	17	logistic	logistic	ADJ
cana-1177	38	18	regression	regression	NOUN
cana-1177	38	19	(	(	PUNCT
cana-1177	38	20	lr	lr	NOUN
cana-1177	38	21	)	)	PUNCT
cana-1177	38	22	,	,	PUNCT
cana-1177	38	23	support	support	NOUN
cana-1177	38	24	vector	vector	NOUN
cana-1177	38	25	machine	machine	NOUN
cana-1177	38	26	(	(	PUNCT
cana-1177	38	27	svm	svm	PROPN
cana-1177	38	28	)	)	PUNCT
cana-1177	38	29	,	,	PUNCT
cana-1177	38	30	and	and	CCONJ
cana-1177	38	31	decision	decision	NOUN
cana-1177	38	32	tree	tree	NOUN
cana-1177	38	33	(	(	PUNCT
cana-1177	38	34	dt	dt	PROPN
cana-1177	38	35	)	)	PUNCT
cana-1177	38	36	,	,	PUNCT
cana-1177	38	37	in	in	ADP
cana-1177	38	38	terms	term	NOUN
cana-1177	38	39	of	of	ADP
cana-1177	38	40	the	the	DET
cana-1177	38	41	class	class	NOUN
cana-1177	38	42	label	label	NOUN
cana-1177	38	43	decisions	decision	NOUN
cana-1177	38	44	they	they	PRON
cana-1177	38	45	make	make	VERB
cana-1177	38	46	.	.	PUNCT
cana-1177	39	1	wisconsin	wisconsin	PROPN
cana-1177	39	2	breast	breast	PROPN
cana-1177	39	3	cancer	cancer	NOUN
cana-1177	39	4	dataset	dataset	NOUN
cana-1177	39	5	(	(	PUNCT
cana-1177	39	6	wdbc	wdbc	PROPN
cana-1177	39	7	)	)	PUNCT
cana-1177	39	8	used	use	VERB
cana-1177	39	9	in	in	ADP
cana-1177	39	10	this	this	DET
cana-1177	39	11	work	work	NOUN
cana-1177	39	12	which	which	PRON
cana-1177	39	13	is	be	AUX
cana-1177	39	14	the	the	DET
cana-1177	39	15	publicly	publicly	ADV
cana-1177	39	16	available	available	ADJ
cana-1177	39	17	on	on	ADP
cana-1177	39	18	“	"	PUNCT
cana-1177	39	19	uci	uci	NOUN
cana-1177	39	20	machine	machine	NOUN
cana-1177	39	21	learning	learn	VERB
cana-1177	39	22	repository	repository	NOUN
cana-1177	39	23	”	"	PUNCT
cana-1177	39	24	.	.	PUNCT
cana-1177	40	1	2	2	X
cana-1177	40	2	.	.	X
cana-1177	40	3	literature	literature	NOUN
cana-1177	40	4	review	review	PROPN
cana-1177	40	5	machine	machine	NOUN
cana-1177	40	6	learning	learn	VERB
cana-1177	40	7	techniques	technique	NOUN
cana-1177	40	8	developed	develop	VERB
cana-1177	40	9	to	to	PART
cana-1177	40	10	study	study	VERB
cana-1177	40	11	breast	breast	NOUN
cana-1177	40	12	cancer	cancer	NOUN
cana-1177	40	13	have	have	AUX
cana-1177	40	14	attracted	attract	VERB
cana-1177	40	15	numerous	numerous	ADJ
cana-1177	40	16	investigational	investigational	ADJ
cana-1177	40	17	and	and	CCONJ
cana-1177	40	18	clinical	clinical	ADJ
cana-1177	40	19	areas	area	NOUN
cana-1177	40	20	,	,	PUNCT
cana-1177	40	21	it	it	PRON
cana-1177	40	22	follows	follow	VERB
cana-1177	40	23	that	that	SCONJ
cana-1177	40	24	a	a	DET
cana-1177	40	25	critical	critical	ADJ
cana-1177	40	26	assessment	assessment	NOUN
cana-1177	40	27	is	be	AUX
cana-1177	40	28	required	require	VERB
cana-1177	40	29	.	.	PUNCT
cana-1177	41	1	this	this	DET
cana-1177	41	2	section	section	NOUN
cana-1177	41	3	first	first	ADV
cana-1177	41	4	gives	give	VERB
cana-1177	41	5	a	a	DET
cana-1177	41	6	short	short	ADJ
cana-1177	41	7	overview	overview	NOUN
cana-1177	41	8	of	of	ADP
cana-1177	41	9	the	the	DET
cana-1177	41	10	earlier	early	ADJ
cana-1177	41	11	studies	study	NOUN
cana-1177	41	12	that	that	PRON
cana-1177	41	13	are	be	AUX
cana-1177	41	14	relevant	relevant	ADJ
cana-1177	41	15	to	to	ADP
cana-1177	41	16	this	this	DET
cana-1177	41	17	experiment	experiment	NOUN
cana-1177	41	18	in	in	ADP
cana-1177	41	19	order	order	NOUN
cana-1177	41	20	to	to	PART
cana-1177	41	21	set	set	VERB
cana-1177	41	22	up	up	ADP
cana-1177	41	23	the	the	DET
cana-1177	41	24	study	study	NOUN
cana-1177	41	25	.	.	PUNCT
cana-1177	42	1	jakhar	jakhar	PROPN
cana-1177	42	2	et	et	PROPN
cana-1177	42	3	al	al	PROPN
cana-1177	42	4	.	.	PROPN
cana-1177	42	5	,	,	PUNCT
cana-1177	42	6	(	(	PUNCT
cana-1177	42	7	2023	2023	NUM
cana-1177	42	8	)	)	PUNCT
cana-1177	43	1	[	[	X
cana-1177	43	2	2	2	X
cana-1177	43	3	]	]	PUNCT
cana-1177	43	4	proposed	propose	VERB
cana-1177	43	5	a	a	DET
cana-1177	43	6	hybrid	hybrid	ADJ
cana-1177	43	7	stack	stack	NOUN
cana-1177	43	8	-	-	PUNCT
cana-1177	43	9	based	base	VERB
cana-1177	43	10	ensemble	ensemble	ADJ
cana-1177	43	11	learning	learning	NOUN
cana-1177	43	12	framework	framework	NOUN
cana-1177	43	13	named	name	VERB
cana-1177	43	14	self	self	NOUN
cana-1177	43	15	for	for	ADP
cana-1177	43	16	identifying	identify	VERB
cana-1177	43	17	bc	bc	PROPN
cana-1177	43	18	and	and	CCONJ
cana-1177	43	19	achieving	achieve	VERB
cana-1177	43	20	an	an	DET
cana-1177	43	21	accuracy	accuracy	NOUN
cana-1177	43	22	of	of	ADP
cana-1177	43	23	98.80	98.80	NUM
cana-1177	43	24	%	%	NOUN
cana-1177	43	25	.	.	PUNCT
cana-1177	44	1	talatian	talatian	ADJ
cana-1177	44	2	et	et	PROPN
cana-1177	44	3	al	al	PROPN
cana-1177	44	4	.	.	PROPN
cana-1177	45	1	(	(	PUNCT
cana-1177	45	2	2021	2021	NUM
cana-1177	45	3	)	)	PUNCT
cana-1177	46	1	[	[	X
cana-1177	46	2	3	3	X
cana-1177	46	3	]	]	PUNCT
cana-1177	46	4	presented	present	VERB
cana-1177	46	5	an	an	DET
cana-1177	46	6	intelligent	intelligent	ADJ
cana-1177	46	7	ensemble	ensemble	ADJ
cana-1177	46	8	classification	classification	NOUN
cana-1177	46	9	method	method	NOUN
cana-1177	46	10	that	that	PRON
cana-1177	46	11	achieved	achieve	VERB
cana-1177	46	12	98.74	98.74	NUM
cana-1177	46	13	%	%	NOUN
cana-1177	46	14	accuracy	accuracy	NOUN
cana-1177	46	15	by	by	ADP
cana-1177	46	16	utilizing	utilize	VERB
cana-1177	46	17	both	both	CCONJ
cana-1177	46	18	evolutionary	evolutionary	ADJ
cana-1177	46	19	algorithms	algorithm	NOUN
cana-1177	46	20	and	and	CCONJ
cana-1177	46	21	multi	multi	ADJ
cana-1177	46	22	-	-	ADJ
cana-1177	46	23	layer	layer	ADJ
cana-1177	46	24	perceptron	perceptron	NOUN
cana-1177	46	25	-	-	PUNCT
cana-1177	46	26	based	base	VERB
cana-1177	46	27	neural	neural	ADJ
cana-1177	46	28	networks	network	NOUN
cana-1177	46	29	.	.	PUNCT
cana-1177	47	1	communications	communication	NOUN
cana-1177	47	2	on	on	ADP
cana-1177	47	3	applied	apply	VERB
cana-1177	47	4	nonlinear	nonlinear	ADJ
cana-1177	47	5	analysis	analysis	NOUN
cana-1177	47	6	issn	issn	NOUN
cana-1177	47	7	:	:	PUNCT
cana-1177	47	8	1074	1074	NUM
cana-1177	47	9	-	-	PUNCT
cana-1177	47	10	133x	133x	NUM
cana-1177	47	11	vol	vol	NOUN
cana-1177	47	12	31	31	NUM
cana-1177	47	13	no	no	NOUN
cana-1177	47	14	.	.	PUNCT
cana-1177	48	1	6s	6s	NUM
cana-1177	48	2	(	(	PUNCT
cana-1177	48	3	2024	2024	NUM
cana-1177	48	4	)	)	PUNCT
cana-1177	48	5	181	181	NUM
cana-1177	48	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-1177	48	7	the	the	DET
cana-1177	48	8	naseem	naseem	PROPN
cana-1177	48	9	et	et	PROPN
cana-1177	48	10	al	al	PROPN
cana-1177	48	11	.	.	PROPN
cana-1177	48	12	(	(	PUNCT
cana-1177	48	13	2022	2022	NUM
cana-1177	48	14	)	)	PUNCT
cana-1177	49	1	[	[	X
cana-1177	49	2	4	4	X
cana-1177	49	3	]	]	PUNCT
cana-1177	49	4	conducted	conduct	VERB
cana-1177	49	5	an	an	DET
cana-1177	49	6	automatic	automatic	ADJ
cana-1177	49	7	detection	detection	NOUN
cana-1177	49	8	framework	framework	NOUN
cana-1177	49	9	for	for	ADP
cana-1177	49	10	classifying	classify	VERB
cana-1177	49	11	and	and	CCONJ
cana-1177	49	12	prognosis	prognosis	NOUN
cana-1177	49	13	of	of	ADP
cana-1177	49	14	breast	breast	NOUN
cana-1177	49	15	cancer	cancer	NOUN
cana-1177	49	16	.	.	PUNCT
cana-1177	50	1	they	they	PRON
cana-1177	50	2	used	use	VERB
cana-1177	50	3	an	an	DET
cana-1177	50	4	ensemble	ensemble	NOUN
cana-1177	50	5	of	of	ADP
cana-1177	50	6	classifiers	classifier	NOUN
cana-1177	50	7	with	with	ADP
cana-1177	50	8	an	an	DET
cana-1177	50	9	accuracy	accuracy	NOUN
cana-1177	50	10	of	of	ADP
cana-1177	50	11	98.83	98.83	NUM
cana-1177	50	12	%	%	NOUN
cana-1177	50	13	.	.	PUNCT
cana-1177	51	1	srinivas	srinivas	PROPN
cana-1177	51	2	et	et	PROPN
cana-1177	51	3	al	al	PROPN
cana-1177	51	4	.	.	PROPN
cana-1177	51	5	,	,	PUNCT
cana-1177	51	6	(	(	PUNCT
cana-1177	51	7	2022	2022	NUM
cana-1177	51	8	)	)	PUNCT
cana-1177	52	1	[	[	X
cana-1177	52	2	5	5	NUM
cana-1177	52	3	]	]	PUNCT
cana-1177	52	4	evaluated	evaluate	VERB
cana-1177	52	5	a	a	DET
cana-1177	52	6	new	new	ADJ
cana-1177	52	7	classifier	classifier	NOUN
cana-1177	52	8	system	system	NOUN
cana-1177	52	9	for	for	ADP
cana-1177	52	10	use	use	NOUN
cana-1177	52	11	in	in	ADP
cana-1177	52	12	the	the	DET
cana-1177	52	13	detection	detection	NOUN
cana-1177	52	14	of	of	ADP
cana-1177	52	15	breast	breast	NOUN
cana-1177	52	16	cancer	cancer	NOUN
cana-1177	52	17	which	which	PRON
cana-1177	52	18	outperformed	outperform	VERB
cana-1177	52	19	the	the	DET
cana-1177	52	20	other	other	ADJ
cana-1177	52	21	known	know	VERB
cana-1177	52	22	classifiers	classifier	NOUN
cana-1177	52	23	by	by	ADP
cana-1177	52	24	a	a	DET
cana-1177	52	25	high	high	ADJ
cana-1177	52	26	degree	degree	NOUN
cana-1177	52	27	of	of	ADP
cana-1177	52	28	accurate	accurate	ADJ
cana-1177	52	29	classifications	classification	NOUN
cana-1177	52	30	with	with	ADP
cana-1177	52	31	a	a	DET
cana-1177	52	32	rate	rate	NOUN
cana-1177	52	33	of	of	ADP
cana-1177	52	34	98.50	98.50	NUM
cana-1177	52	35	%	%	NOUN
cana-1177	52	36	.	.	PUNCT
cana-1177	53	1	jabbar	jabbar	PROPN
cana-1177	53	2	et	et	PROPN
cana-1177	53	3	al	al	PROPN
cana-1177	53	4	.	.	PROPN
cana-1177	54	1	(	(	PUNCT
cana-1177	54	2	2021	2021	NUM
cana-1177	54	3	)	)	PUNCT
cana-1177	55	1	[	[	X
cana-1177	55	2	6	6	NUM
cana-1177	55	3	]	]	PUNCT
cana-1177	55	4	utilized	utilize	VERB
cana-1177	55	5	ml	ml	X
cana-1177	55	6	ensemble	ensemble	ADJ
cana-1177	55	7	models	model	NOUN
cana-1177	55	8	for	for	ADP
cana-1177	55	9	classification	classification	NOUN
cana-1177	55	10	of	of	ADP
cana-1177	55	11	breast	breast	NOUN
cana-1177	55	12	cancer	cancer	NOUN
cana-1177	55	13	dataset	dataset	NOUN
cana-1177	55	14	and	and	CCONJ
cana-1177	55	15	they	they	PRON
cana-1177	55	16	achieved	achieve	VERB
cana-1177	55	17	an	an	DET
cana-1177	55	18	accuracy	accuracy	NOUN
cana-1177	55	19	of	of	ADP
cana-1177	55	20	97.42	97.42	NUM
cana-1177	55	21	%	%	NOUN
cana-1177	55	22	.	.	PUNCT
cana-1177	56	1	alhayali	alhayali	PROPN
cana-1177	56	2	et	et	PROPN
cana-1177	56	3	al	al	PROPN
cana-1177	56	4	.	.	PROPN
cana-1177	56	5	,	,	PUNCT
cana-1177	56	6	(	(	PUNCT
cana-1177	56	7	2020	2020	NUM
cana-1177	56	8	)	)	PUNCT
cana-1177	57	1	[	[	X
cana-1177	57	2	7	7	X
cana-1177	57	3	]	]	PUNCT
cana-1177	57	4	served	serve	VERB
cana-1177	57	5	a	a	DET
cana-1177	57	6	relevant	relevant	ADJ
cana-1177	57	7	way	way	NOUN
cana-1177	57	8	based	base	VERB
cana-1177	57	9	an	an	DET
cana-1177	57	10	ensemble	ensemble	ADJ
cana-1177	57	11	hofeding	hofeding	NOUN
cana-1177	57	12	tree	tree	NOUN
cana-1177	57	13	and	and	CCONJ
cana-1177	57	14	naïve	naïve	ADJ
cana-1177	57	15	bayes	bayes	NOUN
cana-1177	57	16	classifiers	classifier	NOUN
cana-1177	57	17	and	and	CCONJ
cana-1177	57	18	an	an	DET
cana-1177	57	19	accuracy	accuracy	NOUN
cana-1177	57	20	of	of	ADP
cana-1177	57	21	95.99	95.99	NUM
cana-1177	57	22	%	%	NOUN
cana-1177	57	23	was	be	AUX
cana-1177	57	24	achieved	achieve	VERB
cana-1177	57	25	.	.	PUNCT
cana-1177	58	1	batool	batool	NOUN
cana-1177	58	2	&	&	CCONJ
cana-1177	58	3	byun	byun	NOUN
cana-1177	58	4	(	(	PUNCT
cana-1177	58	5	2024	2024	NUM
cana-1177	58	6	)	)	PUNCT
cana-1177	59	1	[	[	X
cana-1177	59	2	8	8	NUM
cana-1177	59	3	]	]	PUNCT
cana-1177	59	4	set	set	VERB
cana-1177	59	5	out	out	ADP
cana-1177	59	6	for	for	ADP
cana-1177	59	7	application	application	NOUN
cana-1177	59	8	of	of	ADP
cana-1177	59	9	adaptive	adaptive	ADJ
cana-1177	59	10	voting	voting	NOUN
cana-1177	59	11	ensemble	ensemble	ADJ
cana-1177	59	12	learning	learning	NOUN
cana-1177	59	13	algorithm	algorithm	NOUN
cana-1177	59	14	to	to	PART
cana-1177	59	15	identify	identify	VERB
cana-1177	59	16	breast	breast	NOUN
cana-1177	59	17	cancer	cancer	NOUN
cana-1177	59	18	with	with	ADP
cana-1177	59	19	the	the	DET
cana-1177	59	20	highest	high	ADJ
cana-1177	59	21	accuracy	accuracy	NOUN
cana-1177	59	22	of	of	ADP
cana-1177	59	23	97.60	97.60	NUM
cana-1177	59	24	%	%	NOUN
cana-1177	59	25	.	.	PUNCT
cana-1177	60	1	chaurasia	chaurasia	PROPN
cana-1177	60	2	et	et	PROPN
cana-1177	60	3	al	al	PROPN
cana-1177	60	4	.	.	PROPN
cana-1177	61	1	(	(	PUNCT
cana-1177	61	2	2018	2018	NUM
cana-1177	61	3	)	)	PUNCT
cana-1177	62	1	[	[	X
cana-1177	62	2	9	9	NUM
cana-1177	62	3	]	]	PUNCT
cana-1177	62	4	focused	focus	VERB
cana-1177	62	5	on	on	ADP
cana-1177	62	6	data	datum	NOUN
cana-1177	62	7	mining	mining	NOUN
cana-1177	62	8	tools	tool	NOUN
cana-1177	62	9	for	for	ADP
cana-1177	62	10	diagnosing	diagnose	VERB
cana-1177	62	11	breast	breast	NOUN
cana-1177	62	12	cancer	cancer	NOUN
cana-1177	62	13	benign	benign	NOUN
cana-1177	62	14	and	and	CCONJ
cana-1177	62	15	malignant	malignant	ADJ
cana-1177	62	16	with	with	ADP
cana-1177	62	17	the	the	DET
cana-1177	62	18	accuracy	accuracy	NOUN
cana-1177	62	19	value	value	NOUN
cana-1177	62	20	of	of	ADP
cana-1177	62	21	96	96	NUM
cana-1177	62	22	%	%	NOUN
cana-1177	62	23	.	.	PUNCT
cana-1177	63	1	hashim	hashim	PROPN
cana-1177	63	2	&	&	CCONJ
cana-1177	63	3	yassin	yassin	PROPN
cana-1177	63	4	(	(	PUNCT
cana-1177	63	5	2023	2023	NUM
cana-1177	63	6	)	)	PUNCT
cana-1177	64	1	[	[	X
cana-1177	64	2	10	10	NUM
cana-1177	64	3	]	]	PUNCT
cana-1177	64	4	used	use	VERB
cana-1177	64	5	soft	soft	ADJ
cana-1177	64	6	voting	voting	NOUN
cana-1177	64	7	classifier	classifier	NOUN
cana-1177	64	8	based	base	VERB
cana-1177	64	9	on	on	ADP
cana-1177	64	10	ml	ml	NOUN
cana-1177	64	11	models	model	NOUN
cana-1177	64	12	have	have	AUX
cana-1177	64	13	been	be	AUX
cana-1177	64	14	provided	provide	VERB
cana-1177	64	15	for	for	ADP
cana-1177	64	16	breast	breast	NOUN
cana-1177	64	17	cancer	cancer	NOUN
cana-1177	64	18	prediction	prediction	NOUN
cana-1177	64	19	and	and	CCONJ
cana-1177	64	20	which	which	PRON
cana-1177	64	21	is	be	AUX
cana-1177	64	22	able	able	ADJ
cana-1177	64	23	to	to	PART
cana-1177	64	24	give	give	VERB
cana-1177	64	25	up	up	ADP
cana-1177	64	26	to	to	ADP
cana-1177	64	27	99.30	99.30	NUM
cana-1177	64	28	%	%	NOUN
cana-1177	64	29	accuracy	accuracy	NOUN
cana-1177	64	30	.	.	PUNCT
cana-1177	65	1	sharma	sharma	PROPN
cana-1177	65	2	et	et	PROPN
cana-1177	65	3	al	al	PROPN
cana-1177	65	4	.	.	PROPN
cana-1177	65	5	(	(	PUNCT
cana-1177	65	6	2024	2024	NUM
cana-1177	65	7	)	)	PUNCT
cana-1177	66	1	[	[	X
cana-1177	66	2	11	11	NUM
cana-1177	66	3	]	]	PUNCT
cana-1177	66	4	proposed	propose	VERB
cana-1177	66	5	an	an	DET
cana-1177	66	6	ensemble	ensemble	ADJ
cana-1177	66	7	framework	framework	NOUN
cana-1177	66	8	for	for	ADP
cana-1177	66	9	bc	bc	PROPN
cana-1177	66	10	prediction	prediction	NOUN
cana-1177	66	11	with	with	ADP
cana-1177	66	12	97.66	97.66	NUM
cana-1177	66	13	%	%	NOUN
cana-1177	66	14	accuracy	accuracy	NOUN
cana-1177	66	15	value	value	NOUN
cana-1177	66	16	.	.	PUNCT
cana-1177	67	1	anastraj	anastraj	PROPN
cana-1177	67	2	&	&	CCONJ
cana-1177	67	3	chakravarthy	chakravarthy	PROPN
cana-1177	67	4	(	(	PUNCT
cana-1177	67	5	2019	2019	NUM
cana-1177	67	6	)	)	PUNCT
cana-1177	68	1	[	[	X
cana-1177	68	2	12	12	NUM
cana-1177	68	3	]	]	PUNCT
cana-1177	68	4	predict	predict	VERB
cana-1177	68	5	breast	breast	NOUN
cana-1177	68	6	cancer	cancer	NOUN
cana-1177	68	7	using	use	VERB
cana-1177	68	8	backpropagation	backpropagation	NOUN
cana-1177	68	9	with	with	ADP
cana-1177	68	10	deep	deep	ADJ
cana-1177	68	11	neural	neural	ADJ
cana-1177	68	12	networks	network	NOUN
cana-1177	68	13	and	and	CCONJ
cana-1177	68	14	getting	get	VERB
cana-1177	68	15	94	94	NUM
cana-1177	68	16	%	%	NOUN
cana-1177	68	17	accuracy	accuracy	NOUN
cana-1177	68	18	.	.	PUNCT
cana-1177	69	1	while	while	SCONJ
cana-1177	69	2	uddin	uddin	PROPN
cana-1177	69	3	et	et	PROPN
cana-1177	69	4	al	al	PROPN
cana-1177	69	5	.	.	PROPN
cana-1177	70	1	(	(	PUNCT
cana-1177	70	2	2023	2023	NUM
cana-1177	70	3	)	)	PUNCT
cana-1177	71	1	[	[	X
cana-1177	71	2	13	13	NUM
cana-1177	71	3	]	]	PUNCT
cana-1177	71	4	utilized	utilize	VERB
cana-1177	71	5	ml	ml	PROPN
cana-1177	71	6	for	for	ADP
cana-1177	71	7	bc	bc	PROPN
cana-1177	71	8	diagnosis	diagnosis	PROPN
cana-1177	71	9	achieving	achieve	VERB
cana-1177	71	10	accuracy	accuracy	NOUN
cana-1177	71	11	of	of	ADP
cana-1177	71	12	98.77	98.77	NUM
cana-1177	71	13	%	%	NOUN
cana-1177	71	14	.	.	PUNCT
cana-1177	72	1	table	table	NOUN
cana-1177	72	2	2	2	NUM
cana-1177	72	3	breast	breast	NOUN
cana-1177	72	4	cancer	cancer	NOUN
cana-1177	72	5	classification	classification	NOUN
cana-1177	72	6	summarization	summarization	NOUN
cana-1177	72	7	s.	s.	PROPN
cana-1177	73	1	no	no	PROPN
cana-1177	73	2	.	.	PUNCT
cana-1177	74	1	author	author	PROPN
cana-1177	74	2	&	&	CCONJ
cana-1177	74	3	year	year	PROPN
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cana-1177	74	5	used	use	VERB
cana-1177	74	6	datasets	dataset	NOUN
cana-1177	74	7	evaluation	evaluation	NOUN
cana-1177	74	8	metrices	metrice	NOUN
cana-1177	74	9	1	1	NUM
cana-1177	74	10	jakhar	jakhar	PROPN
cana-1177	74	11	et	et	PROPN
cana-1177	74	12	al	al	PROPN
cana-1177	74	13	.	.	PROPN
cana-1177	75	1	(	(	PUNCT
cana-1177	75	2	2023	2023	NUM
cana-1177	75	3	)	)	PUNCT
cana-1177	76	1	[	[	X
cana-1177	76	2	2	2	NUM
cana-1177	76	3	]	]	PUNCT
cana-1177	76	4	stack	stack	NOUN
cana-1177	76	5	based	base	VERB
cana-1177	76	6	ensemble	ensemble	ADJ
cana-1177	76	7	wdbc	wdbc	NOUN
cana-1177	76	8	(	(	PUNCT
cana-1177	76	9	699	699	NUM
cana-1177	76	10	instances	instance	NOUN
cana-1177	76	11	)	)	PUNCT
cana-1177	76	12	accuracy=	accuracy=	PUNCT
cana-1177	76	13	.9880	.9880	PROPN
cana-1177	76	14	precision=	precision=	NUM
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cana-1177	77	1	recall=	recall=	NUM
cana-1177	77	2	0.9909	0.9909	NUM
cana-1177	77	3	f1	f1	NOUN
cana-1177	77	4	score=	score=	NUM
cana-1177	77	5	0.9909	0.9909	NUM
cana-1177	77	6	2	2	NUM
cana-1177	77	7	jakhar	jakhar	PROPN
cana-1177	77	8	et	et	PROPN
cana-1177	77	9	al	al	PROPN
cana-1177	77	10	.	.	PROPN
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cana-1177	78	3	)	)	PUNCT
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cana-1177	79	2	2	2	NUM
cana-1177	79	3	]	]	PUNCT
cana-1177	79	4	stack	stack	NOUN
cana-1177	79	5	based	base	VERB
cana-1177	79	6	ensemble	ensemble	ADJ
cana-1177	79	7	breakhis	breakhis	ADJ
cana-1177	79	8	accuracy=	accuracy=	NUM
cana-1177	79	9	0.9435	0.9435	NUM
cana-1177	79	10	precision=	precision=	NUM
cana-1177	79	11	0.9245	0.9245	NUM
cana-1177	79	12	recall=	recall=	NUM
cana-1177	79	13	0.9596	0.9596	NUM
cana-1177	79	14	f1	f1	NOUN
cana-1177	79	15	score=	score=	NUM
cana-1177	79	16	0.9417	0.9417	NUM
cana-1177	79	17	3	3	NUM
cana-1177	79	18	talatian	talatian	PROPN
cana-1177	79	19	et	et	PROPN
cana-1177	79	20	al	al	PROPN
cana-1177	79	21	.	.	PROPN
cana-1177	79	22	(	(	PUNCT
cana-1177	79	23	2021	2021	NUM
cana-1177	79	24	)	)	PUNCT
cana-1177	80	1	[	[	X
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cana-1177	80	7	(	(	PUNCT
cana-1177	80	8	mlp	mlp	PROPN
cana-1177	80	9	-	-	PUNCT
cana-1177	80	10	nn	nn	NOUN
cana-1177	80	11	)	)	PUNCT
cana-1177	80	12	and	and	CCONJ
cana-1177	80	13	evolutionary	evolutionary	ADJ
cana-1177	80	14	algorithm	algorithm	NOUN
cana-1177	80	15	wbcd	wbcd	ADP
cana-1177	80	16	(	(	PUNCT
cana-1177	80	17	699	699	NUM
cana-1177	80	18	instances	instance	NOUN
cana-1177	80	19	)	)	PUNCT
cana-1177	80	20	accuracy=	accuracy=	CCONJ
cana-1177	80	21	.9874	.9874	PROPN
cana-1177	80	22	4	4	NUM
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cana-1177	80	24	et	et	PROPN
cana-1177	80	25	al	al	PROPN
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cana-1177	81	1	(	(	PUNCT
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cana-1177	81	3	)	)	PUNCT
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cana-1177	82	7	,	,	PUNCT
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cana-1177	82	9	,	,	PUNCT
cana-1177	82	10	dt	dt	X
cana-1177	82	11	,	,	PUNCT
cana-1177	82	12	and	and	CCONJ
cana-1177	82	13	k	k	X
cana-1177	82	14	-	-	PUNCT
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cana-1177	82	16	wdbc	wdbc	NOUN
cana-1177	82	17	(	(	PUNCT
cana-1177	82	18	569	569	NUM
cana-1177	82	19	instances	instance	NOUN
cana-1177	82	20	)	)	PUNCT
cana-1177	82	21	accuracy=	accuracy=	NUM
cana-1177	82	22	.9883	.9883	NOUN
cana-1177	82	23	5	5	NUM
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cana-1177	82	25	et	et	PROPN
cana-1177	82	26	al	al	PROPN
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cana-1177	82	29	2022	2022	NUM
cana-1177	82	30	)	)	PUNCT
cana-1177	83	1	[	[	X
cana-1177	83	2	5	5	NUM
cana-1177	83	3	]	]	SYM
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cana-1177	83	5	,	,	PUNCT
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cana-1177	83	9	wdbc	wdbc	PROPN
cana-1177	83	10	(	(	PUNCT
cana-1177	83	11	569	569	NUM
cana-1177	83	12	instances	instance	NOUN
cana-1177	83	13	)	)	PUNCT
cana-1177	84	1	accuracy=	accuracy=	NUM
cana-1177	84	2	0.985	0.985	NUM
cana-1177	84	3	precision=	precision=	NUM
cana-1177	84	4	0.970	0.970	NUM
cana-1177	84	5	recall=	recall=	NUM
cana-1177	84	6	0.990	0.990	NUM
cana-1177	84	7	f1	f1	NOUN
cana-1177	84	8	score=	score=	NUM
cana-1177	84	9	0.980	0.980	NUM
cana-1177	84	10	6	6	NUM
cana-1177	84	11	jabbar	jabbar	NOUN
cana-1177	84	12	et	et	PROPN
cana-1177	84	13	al	al	PROPN
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cana-1177	85	1	(	(	PUNCT
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cana-1177	85	3	)	)	PUNCT
cana-1177	86	1	[	[	X
cana-1177	86	2	6	6	X
cana-1177	86	3	]	]	PUNCT
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cana-1177	86	6	and	and	CCONJ
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cana-1177	86	8	basis	basis	NOUN
cana-1177	86	9	function	function	NOUN
cana-1177	86	10	wbcd	wbcd	ADP
cana-1177	86	11	(	(	PUNCT
cana-1177	86	12	699	699	NUM
cana-1177	86	13	instances	instance	NOUN
cana-1177	86	14	)	)	PUNCT
cana-1177	86	15	accuracy=.9742	accuracy=.9742	ADV
cana-1177	86	16	precision=	precision=	NUM
cana-1177	86	17	.9672	.9672	NOUN
cana-1177	86	18	7	7	NUM
cana-1177	86	19	alhayali	alhayali	VERB
cana-1177	86	20	et	et	PROPN
cana-1177	86	21	al	al	PROPN
cana-1177	86	22	.	.	PROPN
cana-1177	87	1	(	(	PUNCT
cana-1177	87	2	2020	2020	NUM
cana-1177	87	3	)	)	PUNCT
cana-1177	88	1	[	[	X
cana-1177	88	2	7	7	X
cana-1177	88	3	]	]	PUNCT
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cana-1177	88	5	tree	tree	NOUN
cana-1177	88	6	and	and	CCONJ
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cana-1177	88	9	wbcd	wbcd	ADJ
cana-1177	88	10	(	(	PUNCT
cana-1177	88	11	699	699	NUM
cana-1177	88	12	instances	instance	NOUN
cana-1177	88	13	)	)	PUNCT
cana-1177	88	14	accuracy=	accuracy=	NUM
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cana-1177	88	16	8	8	NUM
cana-1177	88	17	batool	batool	NOUN
cana-1177	88	18	&	&	CCONJ
cana-1177	88	19	beyon	beyon	NOUN
cana-1177	88	20	(	(	PUNCT
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cana-1177	88	22	)	)	PUNCT
cana-1177	89	1	[	[	X
cana-1177	89	2	8	8	X
cana-1177	89	3	]	]	X
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cana-1177	89	7	wdbc	wdbc	NOUN
cana-1177	89	8	(	(	PUNCT
cana-1177	89	9	569	569	NUM
cana-1177	89	10	instances	instance	NOUN
cana-1177	89	11	)	)	PUNCT
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cana-1177	89	13	=	=	SYM
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cana-1177	89	15	precision=	precision=	NUM
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cana-1177	89	18	=	=	SYM
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cana-1177	89	20	,	,	PUNCT
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cana-1177	89	23	=	=	SYM
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cana-1177	90	1	(	(	PUNCT
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cana-1177	91	6	(	(	PUNCT
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cana-1177	91	8	instances	instance	NOUN
cana-1177	91	9	)	)	PUNCT
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cana-1177	91	11	=	=	SYM
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cana-1177	91	14	=	=	NOUN
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cana-1177	91	19	al	al	PROPN
cana-1177	91	20	.	.	PROPN
cana-1177	92	1	(	(	PUNCT
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cana-1177	92	3	)	)	PUNCT
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cana-1177	93	6	(	(	PUNCT
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cana-1177	93	9	)	)	PUNCT
cana-1177	93	10	accuracy	accuracy	NOUN
cana-1177	93	11	=	=	SYM
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cana-1177	93	13	precision	precision	NOUN
cana-1177	93	14	=	=	SYM
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cana-1177	93	16	11	11	NUM
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cana-1177	93	18	&	&	CCONJ
cana-1177	93	19	yassin	yassin	PROPN
cana-1177	93	20	(	(	PUNCT
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cana-1177	93	22	)	)	PUNCT
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cana-1177	94	3	]	]	X
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cana-1177	94	10	instances	instance	NOUN
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cana-1177	95	1	=	=	SYM
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cana-1177	95	3	precision	precision	NOUN
cana-1177	95	4	=	=	NOUN
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cana-1177	95	7	=	=	NOUN
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cana-1177	95	10	on	on	ADP
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cana-1177	95	12	nonlinear	nonlinear	ADJ
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cana-1177	95	14	issn	issn	NOUN
cana-1177	95	15	:	:	PUNCT
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cana-1177	95	17	-	-	PUNCT
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cana-1177	96	2	(	(	PUNCT
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cana-1177	96	4	)	)	PUNCT
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cana-1177	96	9	=	=	NOUN
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cana-1177	96	11	auc	auc	X
cana-1177	96	12	=	=	PUNCT
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cana-1177	96	19	.	.	PROPN
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cana-1177	98	3	]	]	PUNCT
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cana-1177	99	3	]	]	PUNCT
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cana-1177	99	20	accuracy=.94	accuracy=.94	PROPN
cana-1177	99	21	14	14	NUM
cana-1177	99	22	uddin	uddin	NOUN
cana-1177	99	23	et	et	PROPN
cana-1177	99	24	al	al	PROPN
cana-1177	99	25	.	.	PROPN
cana-1177	100	1	(	(	PUNCT
cana-1177	100	2	2023	2023	NUM
cana-1177	100	3	)	)	PUNCT
cana-1177	101	1	[	[	X
cana-1177	101	2	13	13	NUM
cana-1177	101	3	]	]	X
cana-1177	101	4	voting	voting	NOUN
cana-1177	101	5	classifier	classifier	NOUN
cana-1177	101	6	[	[	X
cana-1177	101	7	lr+svm	lr+svm	NOUN
cana-1177	101	8	]	]	PUNCT
cana-1177	101	9	wdbc	wdbc	NOUN
cana-1177	101	10	(	(	PUNCT
cana-1177	101	11	569	569	NUM
cana-1177	101	12	instances	instance	NOUN
cana-1177	101	13	)	)	PUNCT
cana-1177	101	14	accuracy=.9877	accuracy=.9877	PROPN
cana-1177	101	15	precision=.9883	precision=.9883	PROPN
cana-1177	101	16	recall=.9854	recall=.9854	PROPN
cana-1177	101	17	f1	f1	PROPN
cana-1177	101	18	score=	score=	NUM
cana-1177	101	19	.9868	.9868	VERB
cana-1177	101	20	these	these	DET
cana-1177	101	21	studies	study	NOUN
cana-1177	101	22	validate	validate	VERB
cana-1177	101	23	the	the	DET
cana-1177	101	24	effectiveness	effectiveness	NOUN
cana-1177	101	25	of	of	ADP
cana-1177	101	26	ml	ml	ADP
cana-1177	101	27	algorithms	algorithm	NOUN
cana-1177	101	28	in	in	ADP
cana-1177	101	29	accurately	accurately	ADV
cana-1177	101	30	predicting	predict	VERB
cana-1177	101	31	breast	breast	NOUN
cana-1177	101	32	cancer	cancer	NOUN
cana-1177	101	33	outcomes	outcome	NOUN
cana-1177	101	34	by	by	ADP
cana-1177	101	35	taking	take	VERB
cana-1177	101	36	various	various	ADJ
cana-1177	101	37	measures	measure	NOUN
cana-1177	101	38	of	of	ADP
cana-1177	101	39	evaluation	evaluation	NOUN
cana-1177	101	40	.	.	PUNCT
cana-1177	102	1	these	these	DET
cana-1177	102	2	findings	finding	NOUN
cana-1177	102	3	highlight	highlight	VERB
cana-1177	102	4	the	the	DET
cana-1177	102	5	potential	potential	NOUN
cana-1177	102	6	of	of	ADP
cana-1177	102	7	ml	ml	NOUN
cana-1177	102	8	in	in	ADP
cana-1177	102	9	assisting	assist	VERB
cana-1177	102	10	clinicians	clinician	NOUN
cana-1177	102	11	with	with	ADP
cana-1177	102	12	early	early	ADJ
cana-1177	102	13	diagnosis	diagnosis	NOUN
cana-1177	102	14	and	and	CCONJ
cana-1177	102	15	personalized	personalized	ADJ
cana-1177	102	16	treatment	treatment	NOUN
cana-1177	102	17	.	.	PUNCT
cana-1177	103	1	previous	previous	ADJ
cana-1177	103	2	research	research	NOUN
cana-1177	103	3	shown	show	VERB
cana-1177	103	4	in	in	ADP
cana-1177	103	5	table	table	NOUN
cana-1177	103	6	2	2	NUM
cana-1177	103	7	employing	employ	VERB
cana-1177	103	8	a	a	DET
cana-1177	103	9	variety	variety	NOUN
cana-1177	103	10	of	of	ADP
cana-1177	103	11	classifiers	classifier	NOUN
cana-1177	103	12	has	have	AUX
cana-1177	103	13	produced	produce	VERB
cana-1177	103	14	encouraging	encouraging	ADJ
cana-1177	103	15	results	result	NOUN
cana-1177	103	16	.	.	PUNCT
cana-1177	104	1	but	but	CCONJ
cana-1177	104	2	prior	prior	ADJ
cana-1177	104	3	research	research	NOUN
cana-1177	104	4	has	have	AUX
cana-1177	104	5	shown	show	VERB
cana-1177	104	6	that	that	SCONJ
cana-1177	104	7	employing	employ	VERB
cana-1177	104	8	an	an	DET
cana-1177	104	9	ensemble	ensemble	NOUN
cana-1177	104	10	of	of	ADP
cana-1177	104	11	classifiers	classifier	NOUN
cana-1177	104	12	enhances	enhance	VERB
cana-1177	104	13	the	the	DET
cana-1177	104	14	outcomes	outcome	NOUN
cana-1177	104	15	.	.	PUNCT
cana-1177	105	1	to	to	PART
cana-1177	105	2	overcome	overcome	VERB
cana-1177	105	3	this	this	DET
cana-1177	105	4	gap	gap	NOUN
cana-1177	105	5	,	,	PUNCT
cana-1177	105	6	we	we	PRON
cana-1177	105	7	purpose	purpose	VERB
cana-1177	105	8	a	a	DET
cana-1177	105	9	model	model	NOUN
cana-1177	105	10	in	in	ADP
cana-1177	105	11	this	this	DET
cana-1177	105	12	study	study	NOUN
cana-1177	105	13	that	that	PRON
cana-1177	105	14	improves	improve	VERB
cana-1177	105	15	the	the	DET
cana-1177	105	16	outcomes	outcome	NOUN
cana-1177	105	17	of	of	ADP
cana-1177	105	18	breast	breast	NOUN
cana-1177	105	19	cancer	cancer	NOUN
cana-1177	105	20	diagnosis	diagnosis	NOUN
cana-1177	105	21	by	by	ADP
cana-1177	105	22	utilizing	utilize	VERB
cana-1177	105	23	many	many	ADJ
cana-1177	105	24	classifiers	classifier	NOUN
cana-1177	105	25	or	or	CCONJ
cana-1177	105	26	an	an	DET
cana-1177	105	27	ensemble	ensemble	NOUN
cana-1177	105	28	of	of	ADP
cana-1177	105	29	classifiers	classifier	NOUN
cana-1177	105	30	.	.	PUNCT
cana-1177	106	1	3	3	X
cana-1177	106	2	.	.	NUM
cana-1177	106	3	purposed	purpose	VERB
cana-1177	106	4	methodology	methodology	NOUN
cana-1177	106	5	the	the	DET
cana-1177	106	6	dataset	dataset	NOUN
cana-1177	106	7	and	and	CCONJ
cana-1177	106	8	classification	classification	NOUN
cana-1177	106	9	models	model	NOUN
cana-1177	106	10	used	use	VERB
cana-1177	106	11	to	to	PART
cana-1177	106	12	improve	improve	VERB
cana-1177	106	13	classifier	classifier	NOUN
cana-1177	106	14	compression	compression	NOUN
cana-1177	106	15	are	be	AUX
cana-1177	106	16	described	describe	VERB
cana-1177	106	17	in	in	ADP
cana-1177	106	18	this	this	DET
cana-1177	106	19	section	section	NOUN
cana-1177	106	20	.	.	PUNCT
cana-1177	107	1	in	in	ADP
cana-1177	107	2	order	order	NOUN
cana-1177	107	3	to	to	PART
cana-1177	107	4	develop	develop	VERB
cana-1177	107	5	an	an	DET
cana-1177	107	6	appropriate	appropriate	ADJ
cana-1177	107	7	model	model	NOUN
cana-1177	107	8	for	for	ADP
cana-1177	107	9	the	the	DET
cana-1177	107	10	high	high	ADJ
cana-1177	107	11	-	-	PUNCT
cana-1177	107	12	precision	precision	NOUN
cana-1177	107	13	prediction	prediction	NOUN
cana-1177	107	14	of	of	ADP
cana-1177	107	15	breast	breast	NOUN
cana-1177	107	16	cancer	cancer	NOUN
cana-1177	107	17	the	the	DET
cana-1177	107	18	primary	primary	ADJ
cana-1177	107	19	stages	stage	NOUN
cana-1177	107	20	of	of	ADP
cana-1177	107	21	the	the	DET
cana-1177	107	22	suggested	suggest	VERB
cana-1177	107	23	architecture	architecture	NOUN
cana-1177	107	24	are	be	AUX
cana-1177	107	25	depicted	depict	VERB
cana-1177	107	26	in	in	ADP
cana-1177	107	27	fig.1	fig.1	PROPN
cana-1177	107	28	.	.	PUNCT
cana-1177	108	1	main	main	ADJ
cana-1177	108	2	areas	area	NOUN
cana-1177	108	3	are	be	AUX
cana-1177	108	4	covered	cover	VERB
cana-1177	108	5	by	by	ADP
cana-1177	108	6	our	our	PRON
cana-1177	108	7	suggested	suggest	VERB
cana-1177	108	8	methodology	methodology	NOUN
cana-1177	108	9	:	:	PUNCT
cana-1177	108	10	data	datum	NOUN
cana-1177	108	11	preprocessing	preprocessing	NOUN
cana-1177	108	12	,	,	PUNCT
cana-1177	108	13	balancing	balance	VERB
cana-1177	108	14	the	the	DET
cana-1177	108	15	dataset	dataset	NOUN
cana-1177	108	16	,	,	PUNCT
cana-1177	108	17	scaling	scale	VERB
cana-1177	108	18	the	the	DET
cana-1177	108	19	features	feature	NOUN
cana-1177	108	20	and	and	CCONJ
cana-1177	108	21	cross	cross	VERB
cana-1177	108	22	validation	validation	NOUN
cana-1177	108	23	.	.	PUNCT
cana-1177	109	1	the	the	DET
cana-1177	109	2	dataset	dataset	NOUN
cana-1177	109	3	is	be	AUX
cana-1177	109	4	balanced	balance	VERB
cana-1177	109	5	using	use	VERB
cana-1177	109	6	the	the	DET
cana-1177	109	7	random	random	ADJ
cana-1177	109	8	over	over	ADP
cana-1177	109	9	sampling	sample	VERB
cana-1177	109	10	(	(	PUNCT
cana-1177	109	11	ros	ros	PROPN
cana-1177	109	12	)	)	PUNCT
cana-1177	109	13	approach	approach	NOUN
cana-1177	109	14	and	and	CCONJ
cana-1177	109	15	the	the	DET
cana-1177	109	16	features	feature	NOUN
cana-1177	109	17	were	be	AUX
cana-1177	109	18	scaled	scale	VERB
cana-1177	109	19	using	use	VERB
cana-1177	109	20	a	a	DET
cana-1177	109	21	standard	standard	ADJ
cana-1177	109	22	scaler	scaler	NOUN
cana-1177	109	23	method	method	NOUN
cana-1177	109	24	.	.	PUNCT
cana-1177	110	1	hard	hard	ADJ
cana-1177	110	2	voting	voting	NOUN
cana-1177	110	3	classifier	classifier	NOUN
cana-1177	110	4	is	be	AUX
cana-1177	110	5	used	use	VERB
cana-1177	110	6	to	to	PART
cana-1177	110	7	make	make	VERB
cana-1177	110	8	the	the	DET
cana-1177	110	9	prediction	prediction	NOUN
cana-1177	110	10	and	and	CCONJ
cana-1177	110	11	evaluate	evaluate	VERB
cana-1177	110	12	the	the	DET
cana-1177	110	13	model	model	NOUN
cana-1177	110	14	performance	performance	NOUN
cana-1177	110	15	based	base	VERB
cana-1177	110	16	on	on	ADP
cana-1177	110	17	the	the	DET
cana-1177	110	18	training	training	NOUN
cana-1177	110	19	data	datum	NOUN
cana-1177	110	20	findings	finding	NOUN
cana-1177	110	21	.	.	PUNCT
cana-1177	111	1	procedure	procedure	NOUN
cana-1177	111	2	of	of	ADP
cana-1177	111	3	purposed	purposed	ADJ
cana-1177	111	4	methodology	methodology	NOUN
cana-1177	111	5	1	1	NUM
cana-1177	111	6	.	.	PUNCT
cana-1177	111	7	load	load	NOUN
cana-1177	111	8	dataset	dataset	NOUN
cana-1177	111	9	.	.	PUNCT
cana-1177	112	1	2	2	X
cana-1177	112	2	.	.	X
cana-1177	112	3	check	check	VERB
cana-1177	112	4	for	for	ADP
cana-1177	112	5	any	any	DET
cana-1177	112	6	such	such	ADJ
cana-1177	112	7	empty	empty	ADJ
cana-1177	112	8	values	value	NOUN
cana-1177	112	9	or	or	CCONJ
cana-1177	112	10	nan	nan	PROPN
cana-1177	112	11	’s	’s	NOUN
cana-1177	112	12	in	in	ADP
cana-1177	112	13	the	the	DET
cana-1177	112	14	dataset	dataset	NOUN
cana-1177	112	15	.	.	PUNCT
cana-1177	113	1	3	3	X
cana-1177	113	2	.	.	X
cana-1177	113	3	if	if	SCONJ
cana-1177	113	4	na	na	ADV
cana-1177	113	5	or	or	CCONJ
cana-1177	113	6	missing	miss	VERB
cana-1177	113	7	value	value	NOUN
cana-1177	113	8	is	be	AUX
cana-1177	113	9	from	from	ADP
cana-1177	113	10	the	the	DET
cana-1177	113	11	data	datum	NOUN
cana-1177	113	12	,	,	PUNCT
cana-1177	113	13	try	try	VERB
cana-1177	113	14	to	to	PART
cana-1177	113	15	replace	replace	VERB
cana-1177	113	16	it	it	PRON
cana-1177	113	17	with	with	ADP
cana-1177	113	18	the	the	DET
cana-1177	113	19	appropriate	appropriate	ADJ
cana-1177	113	20	value	value	NOUN
cana-1177	113	21	.	.	PUNCT
cana-1177	114	1	4	4	X
cana-1177	114	2	.	.	X
cana-1177	114	3	map	map	VERB
cana-1177	114	4	the	the	DET
cana-1177	114	5	target	target	NOUN
cana-1177	114	6	variable	variable	ADJ
cana-1177	114	7	values	value	NOUN
cana-1177	114	8	:	:	PUNCT
cana-1177	114	9	let	let	VERB
cana-1177	114	10	's	us	PRON
cana-1177	114	11	say	say	VERB
cana-1177	114	12	'	'	PUNCT
cana-1177	114	13	m	m	VERB
cana-1177	114	14	'	'	PUNCT
cana-1177	114	15	is	be	AUX
cana-1177	114	16	0	0	NUM
cana-1177	114	17	.	.	PUNCT
cana-1177	115	1	if	if	SCONJ
cana-1177	115	2	'	'	PUNCT
cana-1177	115	3	b	b	X
cana-1177	115	4	'	'	PUNCT
cana-1177	115	5	is	be	AUX
cana-1177	115	6	1	1	NUM
cana-1177	115	7	,	,	PUNCT
cana-1177	115	8	replace	replace	VERB
cana-1177	115	9	with	with	ADP
cana-1177	115	10	it	it	PRON
cana-1177	115	11	.	.	PUNCT
cana-1177	116	1	5	5	X
cana-1177	116	2	.	.	X
cana-1177	116	3	distribute	distribute	VERB
cana-1177	116	4	or	or	CCONJ
cana-1177	116	5	apportion	apportion	NOUN
cana-1177	116	6	x	x	SYM
cana-1177	116	7	features	feature	NOUN
cana-1177	116	8	and	and	CCONJ
cana-1177	116	9	the	the	DET
cana-1177	116	10	y	y	PROPN
cana-1177	116	11	target	target	NOUN
cana-1177	116	12	variable	variable	NOUN
cana-1177	116	13	from	from	ADP
cana-1177	116	14	the	the	DET
cana-1177	116	15	data	data	NOUN
cana-1177	116	16	file	file	NOUN
cana-1177	116	17	.	.	PUNCT
cana-1177	117	1	6	6	X
cana-1177	117	2	.	.	X
cana-1177	117	3	split	split	VERB
cana-1177	117	4	the	the	DET
cana-1177	117	5	dataset	dataset	NOUN
cana-1177	117	6	into	into	ADP
cana-1177	117	7	two	two	NUM
cana-1177	117	8	pieces	piece	NOUN
cana-1177	117	9	:	:	PUNCT
cana-1177	117	10	training	training	NOUN
cana-1177	117	11	and	and	CCONJ
cana-1177	117	12	testing	testing	NOUN
cana-1177	117	13	sets	set	NOUN
cana-1177	117	14	(	(	PUNCT
cana-1177	117	15	x_train	x_train	PROPN
cana-1177	117	16	,	,	PUNCT
cana-1177	117	17	x_test	x_test	NUM
cana-1177	117	18	,	,	PUNCT
cana-1177	117	19	y_train	y_train	PRON
cana-1177	117	20	,	,	PUNCT
cana-1177	117	21	y_test	y_test	NUM
cana-1177	117	22	)	)	PUNCT
cana-1177	117	23	.	.	PUNCT
cana-1177	118	1	7	7	X
cana-1177	118	2	.	.	X
cana-1177	118	3	perform	perform	VERB
cana-1177	118	4	random	random	ADJ
cana-1177	118	5	over	over	ADP
cana-1177	118	6	sampling	sample	VERB
cana-1177	118	7	to	to	PART
cana-1177	118	8	equalize	equalize	VERB
cana-1177	118	9	the	the	DET
cana-1177	118	10	unbalanced	unbalanced	ADJ
cana-1177	118	11	distribution	distribution	NOUN
cana-1177	118	12	of	of	ADP
cana-1177	118	13	classes	class	NOUN
cana-1177	118	14	.	.	PUNCT
cana-1177	119	1	8	8	X
cana-1177	119	2	.	.	X
cana-1177	119	3	run	run	VERB
cana-1177	119	4	the	the	DET
cana-1177	119	5	features	feature	NOUN
cana-1177	119	6	through	through	ADP
cana-1177	119	7	the	the	DET
cana-1177	119	8	standardscaler	standardscaler	NOUN
cana-1177	119	9	function	function	NOUN
cana-1177	119	10	.	.	PUNCT
cana-1177	120	1	9	9	X
cana-1177	120	2	.	.	X
cana-1177	120	3	train	train	VERB
cana-1177	120	4	the	the	DET
cana-1177	120	5	models	model	NOUN
cana-1177	120	6	:	:	PUNCT
cana-1177	120	7	logistic	logistic	ADJ
cana-1177	120	8	regression	regression	NOUN
cana-1177	120	9	,	,	PUNCT
cana-1177	120	10	svm	svm	ADJ
cana-1177	120	11	,	,	PUNCT
cana-1177	120	12	decision	decision	NOUN
cana-1177	120	13	trees	tree	NOUN
cana-1177	120	14	.	.	PUNCT
cana-1177	121	1	10	10	NUM
cana-1177	121	2	.	.	PUNCT
cana-1177	121	3	create	create	VERB
cana-1177	121	4	hard	hard	ADJ
cana-1177	121	5	voting	voting	NOUN
cana-1177	121	6	classifier	classifier	NOUN
cana-1177	121	7	implementation	implementation	NOUN
cana-1177	121	8	with	with	ADP
cana-1177	121	9	loaded	load	VERB
cana-1177	121	10	models	model	NOUN
cana-1177	121	11	into	into	ADP
cana-1177	121	12	the	the	DET
cana-1177	121	13	script	script	NOUN
cana-1177	121	14	.	.	PUNCT
cana-1177	122	1	11	11	NUM
cana-1177	122	2	.	.	X
cana-1177	123	1	train	train	VERB
cana-1177	123	2	the	the	DET
cana-1177	123	3	hard	hard	ADJ
cana-1177	123	4	voting	voting	NOUN
cana-1177	123	5	classifier	classifier	NOUN
cana-1177	123	6	using	use	VERB
cana-1177	123	7	the	the	DET
cana-1177	123	8	resampled	resample	VERB
cana-1177	123	9	and	and	CCONJ
cana-1177	123	10	scaled	scale	VERB
cana-1177	123	11	training	training	NOUN
cana-1177	123	12	data	datum	NOUN
cana-1177	123	13	.	.	PUNCT
cana-1177	124	1	12	12	NUM
cana-1177	124	2	.	.	PUNCT
cana-1177	125	1	make	make	VERB
cana-1177	125	2	predictions	prediction	NOUN
cana-1177	125	3	and	and	CCONJ
cana-1177	125	4	evaluate	evaluate	VERB
cana-1177	125	5	each	each	DET
cana-1177	125	6	classifier	classifier	NOUN
cana-1177	125	7	on	on	ADP
cana-1177	125	8	test	test	NOUN
cana-1177	125	9	set	set	VERB
cana-1177	125	10	.	.	PUNCT
cana-1177	126	1	13	13	NUM
cana-1177	126	2	.	.	PUNCT
cana-1177	127	1	perform	perform	VERB
cana-1177	127	2	10	10	NUM
cana-1177	127	3	-	-	ADJ
cana-1177	127	4	fold	fold	ADJ
cana-1177	127	5	data	datum	NOUN
cana-1177	127	6	cross	cross	NOUN
cana-1177	127	7	-	-	NOUN
cana-1177	127	8	validation	validation	NOUN
cana-1177	127	9	on	on	ADP
cana-1177	127	10	voting	voting	NOUN
cana-1177	127	11	classifier	classifier	NOUN
cana-1177	127	12	and	and	CCONJ
cana-1177	127	13	compute	compute	VERB
cana-1177	127	14	the	the	DET
cana-1177	127	15	mean	mean	ADJ
cana-1177	127	16	crossvalidation	crossvalidation	NOUN
cana-1177	127	17	accuracy	accuracy	NOUN
cana-1177	127	18	value	value	NOUN
cana-1177	127	19	.	.	PUNCT
cana-1177	128	1	communications	communication	NOUN
cana-1177	128	2	on	on	ADP
cana-1177	128	3	applied	apply	VERB
cana-1177	128	4	nonlinear	nonlinear	ADJ
cana-1177	128	5	analysis	analysis	NOUN
cana-1177	128	6	issn	issn	NOUN
cana-1177	128	7	:	:	PUNCT
cana-1177	128	8	1074	1074	NUM
cana-1177	128	9	-	-	PUNCT
cana-1177	128	10	133x	133x	NUM
cana-1177	128	11	vol	vol	NOUN
cana-1177	128	12	31	31	NUM
cana-1177	128	13	no	no	NOUN
cana-1177	128	14	.	.	PUNCT
cana-1177	129	1	6s	6s	NUM
cana-1177	129	2	(	(	PUNCT
cana-1177	129	3	2024	2024	NUM
cana-1177	129	4	)	)	PUNCT
cana-1177	129	5	183	183	NUM
cana-1177	129	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-1177	129	7	fig	fig	NOUN
cana-1177	129	8	.	.	PUNCT
cana-1177	130	1	2	2	NUM
cana-1177	130	2	highlights	highlight	NOUN
cana-1177	130	3	the	the	DET
cana-1177	130	4	flowchart	flowchart	NOUN
cana-1177	130	5	of	of	ADP
cana-1177	130	6	the	the	DET
cana-1177	130	7	method	method	NOUN
cana-1177	130	8	being	be	AUX
cana-1177	130	9	discussed	discuss	VERB
cana-1177	130	10	in	in	ADP
cana-1177	130	11	this	this	DET
cana-1177	130	12	paper	paper	NOUN
cana-1177	130	13	to	to	PART
cana-1177	130	14	show	show	VERB
cana-1177	130	15	the	the	DET
cana-1177	130	16	process	process	NOUN
cana-1177	130	17	flow	flow	NOUN
cana-1177	130	18	beginning	begin	VERB
cana-1177	130	19	from	from	ADP
cana-1177	130	20	data	datum	NOUN
cana-1177	130	21	collection	collection	NOUN
cana-1177	130	22	and	and	CCONJ
cana-1177	130	23	steps	step	NOUN
cana-1177	130	24	down	down	ADP
cana-1177	130	25	to	to	ADP
cana-1177	130	26	the	the	DET
cana-1177	130	27	analysis	analysis	NOUN
cana-1177	130	28	stage	stage	NOUN
cana-1177	130	29	.	.	PUNCT
cana-1177	131	1	a	a	DET
cana-1177	131	2	flowchart	flowchart	NOUN
cana-1177	131	3	is	be	AUX
cana-1177	131	4	useful	useful	ADJ
cana-1177	131	5	in	in	ADP
cana-1177	131	6	showing	show	VERB
cana-1177	131	7	flow	flow	NOUN
cana-1177	131	8	and	and	CCONJ
cana-1177	131	9	relationships	relationship	NOUN
cana-1177	131	10	in	in	ADP
cana-1177	131	11	a	a	DET
cana-1177	131	12	process	process	NOUN
cana-1177	131	13	.	.	PUNCT
cana-1177	132	1	fig.1	fig.1	PROPN
cana-1177	132	2	.	.	PROPN
cana-1177	132	3	purposed	purpose	VERB
cana-1177	132	4	architecture	architecture	NOUN
cana-1177	132	5	for	for	ADP
cana-1177	132	6	breast	breast	NOUN
cana-1177	132	7	cancer	cancer	NOUN
cana-1177	132	8	prediction	prediction	NOUN
cana-1177	132	9	fig.2	fig.2	PROPN
cana-1177	132	10	.	.	PUNCT
cana-1177	133	1	flowchart	flowchart	NOUN
cana-1177	133	2	of	of	ADP
cana-1177	133	3	purposed	purposed	ADJ
cana-1177	133	4	methodology	methodology	NOUN
cana-1177	133	5	in	in	ADP
cana-1177	133	6	our	our	PRON
cana-1177	133	7	approach	approach	NOUN
cana-1177	134	1	,	,	PUNCT
cana-1177	134	2	we	we	PRON
cana-1177	134	3	employ	employ	VERB
cana-1177	134	4	voting	voting	NOUN
cana-1177	134	5	-	-	PUNCT
cana-1177	134	6	based	base	VERB
cana-1177	134	7	ensemble	ensemble	ADJ
cana-1177	134	8	learning	learning	NOUN
cana-1177	134	9	also	also	ADV
cana-1177	134	10	known	know	VERB
cana-1177	134	11	as	as	ADP
cana-1177	134	12	the	the	DET
cana-1177	134	13	super	super	ADV
cana-1177	134	14	learning	learning	NOUN
cana-1177	134	15	in	in	ADP
cana-1177	134	16	order	order	NOUN
cana-1177	134	17	to	to	PART
cana-1177	134	18	develop	develop	VERB
cana-1177	134	19	the	the	DET
cana-1177	134	20	model	model	NOUN
cana-1177	134	21	which	which	PRON
cana-1177	134	22	is	be	AUX
cana-1177	134	23	achieved	achieve	VERB
cana-1177	134	24	by	by	ADP
cana-1177	134	25	modelling	model	VERB
cana-1177	134	26	variety	variety	NOUN
cana-1177	134	27	of	of	ADP
cana-1177	134	28	classification	classification	NOUN
cana-1177	134	29	models	model	NOUN
cana-1177	134	30	.	.	PUNCT
cana-1177	135	1	algorithm	algorithm	NOUN
cana-1177	135	2	1	1	NUM
cana-1177	135	3	describes	describe	VERB
cana-1177	135	4	the	the	DET
cana-1177	135	5	purposed	purposed	ADJ
cana-1177	135	6	framework	framework	NOUN
cana-1177	135	7	steps	step	NOUN
cana-1177	135	8	,	,	PUNCT
cana-1177	135	9	inputs	input	NOUN
cana-1177	135	10	in	in	ADP
cana-1177	135	11	table	table	NOUN
cana-1177	135	12	3	3	NUM
cana-1177	135	13	are	be	AUX
cana-1177	135	14	described	describe	VERB
cana-1177	135	15	through	through	ADP
cana-1177	135	16	symbols	symbol	NOUN
cana-1177	135	17	in	in	ADP
cana-1177	135	18	the	the	DET
cana-1177	135	19	algorithm	algorithm	NOUN
cana-1177	135	20	.	.	PUNCT
cana-1177	136	1	algorithm	algorithm	NOUN
cana-1177	136	2	1	1	NUM
cana-1177	136	3	:	:	PUNCT
cana-1177	136	4	purposed	purpose	VERB
cana-1177	136	5	ensemble	ensemble	ADJ
cana-1177	136	6	framework	framework	NOUN
cana-1177	136	7	for	for	ADP
cana-1177	136	8	breast	breast	NOUN
cana-1177	136	9	cancer	cancer	NOUN
cana-1177	136	10	prediction	prediction	NOUN
cana-1177	137	1	d	d	NOUN
cana-1177	137	2	’	'	PUNCT
cana-1177	137	3	=	=	SYM
cana-1177	137	4	n(d	n(d	PROPN
cana-1177	137	5	)	)	PUNCT
cana-1177	137	6	/*normalisation	/*normalisation	PROPN
cana-1177	137	7	of	of	ADP
cana-1177	137	8	dataset*/	dataset*/	PROPN
cana-1177	137	9	m=0	m=0	PROPN
cana-1177	137	10	,	,	PUNCT
cana-1177	137	11	b=1	b=1	PUNCT
cana-1177	137	12	/	/	SYM
cana-1177	137	13	*	*	PUNCT
cana-1177	137	14	map	map	VERB
cana-1177	137	15	the	the	DET
cana-1177	137	16	target	target	NOUN
cana-1177	137	17	variables*/	variables*/	NOUN
cana-1177	137	18	let	let	VERB
cana-1177	137	19	g	g	NOUN
cana-1177	137	20	=	=	SYM
cana-1177	137	21	{	{	PUNCT
cana-1177	137	22	g1	g1	PROPN
cana-1177	137	23	,	,	PUNCT
cana-1177	137	24	g2	g2	PROPN
cana-1177	137	25	,	,	PUNCT
cana-1177	137	26	g3	g3	PROPN
cana-1177	137	27	..	..	PUNCT
cana-1177	137	28	.	.	PUNCT
cana-1177	138	1	gn	gn	INTJ
cana-1177	138	2	}	}	PUNCT
cana-1177	138	3	/*dataset*/	/*dataset*/	PUNCT
cana-1177	139	1	c	c	NOUN
cana-1177	139	2	=	=	SYM
cana-1177	139	3	{	{	PUNCT
cana-1177	139	4	c1	c1	PROPN
cana-1177	139	5	,	,	PUNCT
cana-1177	139	6	c2	c2	PROPN
cana-1177	139	7	,	,	PUNCT
cana-1177	139	8	c3	c3	PROPN
cana-1177	139	9	,	,	PUNCT
cana-1177	139	10	...	...	PUNCT
cana-1177	140	1	cn	cn	X
cana-1177	140	2	}	}	PUNCT
cana-1177	140	3	/*the	/*the	SYM
cana-1177	140	4	set	set	NOUN
cana-1177	140	5	of	of	ADP
cana-1177	140	6	ml	ml	INTJ
cana-1177	140	7	ensemble	ensemble	VERB
cana-1177	140	8	classifiers*/	classifiers*/	PROPN
cana-1177	140	9	x=	x=	PUNCT
cana-1177	141	1	the	the	DET
cana-1177	141	2	80	80	NUM
cana-1177	141	3	%	%	NOUN
cana-1177	141	4	dataset	dataset	NOUN
cana-1177	141	5	for	for	ADP
cana-1177	141	6	training	training	NOUN
cana-1177	141	7	,	,	PUNCT
cana-1177	141	8	x	x	PRON
cana-1177	141	9	⃀	⃀	NOUN
cana-1177	141	10	g	g	PROPN
cana-1177	141	11	/*80	/*80	PROPN
cana-1177	141	12	%	%	NOUN
cana-1177	141	13	of	of	ADP
cana-1177	141	14	the	the	DET
cana-1177	141	15	dataset	dataset	NOUN
cana-1177	141	16	*	*	PUNCT
cana-1177	141	17	/	/	SYM
cana-1177	141	18	y=	y=	PRON
cana-1177	141	19	the	the	DET
cana-1177	141	20	20	20	NUM
cana-1177	141	21	%	%	NOUN
cana-1177	141	22	dataset	dataset	NOUN
cana-1177	141	23	for	for	ADP
cana-1177	141	24	testing	testing	NOUN
cana-1177	141	25	,	,	PUNCT
cana-1177	141	26	y	y	PROPN
cana-1177	141	27	⃀	⃀	NOUN
cana-1177	141	28	g	g	PROPN
cana-1177	141	29	/*20	/*20	NOUN
cana-1177	142	1	%	%	NOUN
cana-1177	142	2	of	of	ADP
cana-1177	142	3	the	the	DET
cana-1177	142	4	dataset	dataset	NOUN
cana-1177	142	5	*	*	PUNCT
cana-1177	142	6	/	/	SYM
cana-1177	142	7	x’=	x’=	PROPN
cana-1177	142	8	bs(x	bs(x	PUNCT
cana-1177	142	9	)	)	PUNCT
cana-1177	142	10	/	/	SYM
cana-1177	143	1	*	*	PUNCT
cana-1177	143	2	balancing	balancing	NOUN
cana-1177	143	3	and	and	CCONJ
cana-1177	143	4	scaling	scale	VERB
cana-1177	143	5	the	the	DET
cana-1177	143	6	training	training	NOUN
cana-1177	143	7	set*/	set*/	X
cana-1177	143	8	v	v	NOUN
cana-1177	143	9	=	=	VERB
cana-1177	143	10	voting	voting	NOUN
cana-1177	143	11	classifier	classifier	NOUN
cana-1177	143	12	p	p	NOUN
cana-1177	143	13	=	=	PUNCT
cana-1177	143	14	n	n	PROPN
cana-1177	143	15	(	(	PUNCT
cana-1177	143	16	g	g	NOUN
cana-1177	143	17	)	)	PUNCT
cana-1177	143	18	/*where	/*where	PUNCT
cana-1177	144	1	p	p	NOUN
cana-1177	144	2	is	be	AUX
cana-1177	144	3	no	no	PRON
cana-1177	144	4	.	.	PUNCT
cana-1177	144	5	of	of	ADP
cana-1177	144	6	attributes	attribute	NOUN
cana-1177	144	7	of	of	ADP
cana-1177	144	8	dataset*/	dataset*/	NOUN
cana-1177	144	9	begin	begin	VERB
cana-1177	144	10	m(i	m(i	PRON
cana-1177	144	11	)	)	PUNCT
cana-1177	144	12	=	=	PUNCT
cana-1177	144	13	c(i	c(i	PROPN
cana-1177	144	14	)	)	PUNCT
cana-1177	144	15	/	/	PUNCT
cana-1177	145	1	*	*	PUNCT
cana-1177	145	2	training	train	VERB
cana-1177	145	3	the	the	DET
cana-1177	145	4	model	model	NOUN
cana-1177	145	5	on	on	ADP
cana-1177	145	6	x’*/	x’*/	PROPN
cana-1177	146	1	next	next	ADV
cana-1177	147	1	i	i	PRON
cana-1177	147	2	/*loop	/*loop	PUNCT
cana-1177	147	3	where	where	SCONJ
cana-1177	147	4	i	i	PRON
cana-1177	147	5	is	be	AUX
cana-1177	147	6	a	a	DET
cana-1177	147	7	variable*/	variable*/	ADJ
cana-1177	147	8	mo	mo	NOUN
cana-1177	147	9	=	=	PROPN
cana-1177	147	10	mo	mo	PROPN
cana-1177	147	11	∪	∪	PROPN
cana-1177	147	12	v	v	PROPN
cana-1177	147	13	/*union	/*union	PROPN
cana-1177	147	14	of	of	ADP
cana-1177	147	15	model	model	NOUN
cana-1177	147	16	and	and	CCONJ
cana-1177	147	17	voting	vote	VERB
cana-1177	147	18	classifier*/	classifier*/	NOUN
cana-1177	147	19	communications	communication	NOUN
cana-1177	147	20	on	on	ADP
cana-1177	147	21	applied	apply	VERB
cana-1177	147	22	nonlinear	nonlinear	ADJ
cana-1177	147	23	analysis	analysis	NOUN
cana-1177	147	24	issn	issn	NOUN
cana-1177	147	25	:	:	PUNCT
cana-1177	147	26	1074	1074	NUM
cana-1177	147	27	-	-	PUNCT
cana-1177	147	28	133x	133x	NUM
cana-1177	147	29	vol	vol	NOUN
cana-1177	147	30	31	31	NUM
cana-1177	147	31	no	no	NOUN
cana-1177	147	32	.	.	PUNCT
cana-1177	148	1	6s	6s	NUM
cana-1177	148	2	(	(	PUNCT
cana-1177	148	3	2024	2024	NUM
cana-1177	148	4	)	)	PUNCT
cana-1177	148	5	184	184	NUM
cana-1177	148	6	https://internationalpubls.com	https://internationalpubls.com	NUM
cana-1177	148	7	end	end	NOUN
cana-1177	148	8	result	result	NOUN
cana-1177	148	9	←mo	←mo	NOUN
cana-1177	148	10	classifies	classify	VERB
cana-1177	148	11	y	y	PROPN
cana-1177	148	12	predict←	predict←	PROPN
cana-1177	148	13	cross	cross	ADJ
cana-1177	148	14	-	-	ADJ
cana-1177	148	15	validation	validation	ADJ
cana-1177	148	16	table	table	NOUN
cana-1177	148	17	3	3	NUM
cana-1177	148	18	the	the	DET
cana-1177	148	19	symbols	symbol	NOUN
cana-1177	148	20	are	be	AUX
cana-1177	148	21	presented	present	VERB
cana-1177	148	22	in	in	ADP
cana-1177	148	23	algorithm	algorithm	NOUN
cana-1177	148	24	1	1	NUM
cana-1177	149	1	s.	s.	PROPN
cana-1177	149	2	no	no	PROPN
cana-1177	149	3	.	.	PUNCT
cana-1177	150	1	symbols	symbol	NOUN
cana-1177	150	2	description	description	NOUN
cana-1177	150	3	1	1	NUM
cana-1177	150	4	d	d	NOUN
cana-1177	150	5	dataset	dataset	VERB
cana-1177	150	6	2	2	NUM
cana-1177	150	7	d	d	NOUN
cana-1177	150	8	’	'	PUNCT
cana-1177	150	9	normalized	normalized	AUX
cana-1177	150	10	dataset	dataset	VERB
cana-1177	150	11	3	3	NUM
cana-1177	150	12	m	m	NOUN
cana-1177	150	13	malignant	malignant	ADJ
cana-1177	150	14	4	4	NUM
cana-1177	150	15	b	b	NOUN
cana-1177	150	16	benign	benign	ADJ
cana-1177	150	17	5	5	NUM
cana-1177	150	18	n	n	NOUN
cana-1177	150	19	normalization	normalization	NOUN
cana-1177	150	20	6	6	NUM
cana-1177	150	21	g	g	NOUN
cana-1177	150	22	attributes	attribute	NOUN
cana-1177	150	23	of	of	ADP
cana-1177	150	24	datasets	dataset	NOUN
cana-1177	150	25	7	7	NUM
cana-1177	150	26	c	c	NOUN
cana-1177	150	27	classifiers	classifier	NOUN
cana-1177	150	28	8	8	NUM
cana-1177	150	29	x	x	NOUN
cana-1177	150	30	training	training	NOUN
cana-1177	150	31	set	set	NOUN
cana-1177	150	32	9	9	NUM
cana-1177	150	33	y	y	PROPN
cana-1177	150	34	testing	testing	NOUN
cana-1177	150	35	set	set	VERB
cana-1177	150	36	10	10	NUM
cana-1177	150	37	v	v	NOUN
cana-1177	150	38	voting	voting	NOUN
cana-1177	150	39	classifier	classifier	NOUN
cana-1177	150	40	11	11	NUM
cana-1177	150	41	x	x	NOUN
cana-1177	150	42	’	'	PUNCT
cana-1177	150	43	balanced	balanced	ADJ
cana-1177	150	44	and	and	CCONJ
cana-1177	150	45	scaled	scale	VERB
cana-1177	150	46	set	set	VERB
cana-1177	150	47	12	12	NUM
cana-1177	150	48	bs	bs	NOUN
cana-1177	150	49	balancing	balancing	NOUN
cana-1177	150	50	&	&	CCONJ
cana-1177	150	51	scaling	scale	VERB
cana-1177	150	52	13	13	NUM
cana-1177	150	53	p	p	NOUN
cana-1177	150	54	number	number	NOUN
cana-1177	150	55	of	of	ADP
cana-1177	150	56	attributes	attribute	NOUN
cana-1177	150	57	14	14	NUM
cana-1177	150	58	i	i	PRON
cana-1177	150	59	variable	variable	ADJ
cana-1177	150	60	15	15	NUM
cana-1177	150	61	mo	mo	PROPN
cana-1177	150	62	model	model	NOUN
cana-1177	150	63	3.1	3.1	NUM
cana-1177	150	64	.	.	PUNCT
cana-1177	151	1	dataset	dataset	VERB
cana-1177	151	2	description	description	NOUN
cana-1177	151	3	and	and	CCONJ
cana-1177	151	4	preprocessing	preprocesse	VERB
cana-1177	151	5	most	most	ADV
cana-1177	151	6	popular	popular	ADJ
cana-1177	151	7	benchmark	benchmark	NOUN
cana-1177	151	8	dataset	dataset	NOUN
cana-1177	151	9	for	for	ADP
cana-1177	151	10	breast	breast	NOUN
cana-1177	151	11	cancer	cancer	NOUN
cana-1177	151	12	classification	classification	NOUN
cana-1177	151	13	tasks	task	NOUN
cana-1177	151	14	is	be	AUX
cana-1177	151	15	the	the	DET
cana-1177	151	16	“	"	PUNCT
cana-1177	151	17	wisconsin	wisconsin	PROPN
cana-1177	151	18	breast	breast	NOUN
cana-1177	151	19	cancer	cancer	NOUN
cana-1177	151	20	diagnostic	diagnostic	NOUN
cana-1177	151	21	(	(	PUNCT
cana-1177	151	22	wdbc	wdbc	PROPN
cana-1177	151	23	)	)	PUNCT
cana-1177	151	24	”	"	PUNCT
cana-1177	151	25	dataset	dataset	NOUN
cana-1177	151	26	obtained	obtain	VERB
cana-1177	151	27	from	from	ADP
cana-1177	151	28	the	the	DET
cana-1177	151	29	uci	uci	PROPN
cana-1177	151	30	ml	ml	PROPN
cana-1177	151	31	repository	repository	NOUN
cana-1177	151	32	is	be	AUX
cana-1177	151	33	utilized	utilize	VERB
cana-1177	151	34	in	in	ADP
cana-1177	151	35	this	this	DET
cana-1177	151	36	work	work	NOUN
cana-1177	151	37	.	.	PUNCT
cana-1177	152	1	the	the	DET
cana-1177	152	2	features	feature	NOUN
cana-1177	152	3	in	in	ADP
cana-1177	152	4	this	this	DET
cana-1177	152	5	dataset	dataset	NOUN
cana-1177	152	6	which	which	PRON
cana-1177	152	7	indicate	indicate	VERB
cana-1177	152	8	the	the	DET
cana-1177	152	9	properties	property	NOUN
cana-1177	152	10	of	of	ADP
cana-1177	152	11	cell	cell	NOUN
cana-1177	152	12	nuclei	nucleus	NOUN
cana-1177	152	13	were	be	AUX
cana-1177	152	14	calculated	calculate	VERB
cana-1177	152	15	from	from	ADP
cana-1177	152	16	digital	digital	ADJ
cana-1177	152	17	pictures	picture	NOUN
cana-1177	152	18	of	of	ADP
cana-1177	152	19	fine	fine	ADJ
cana-1177	152	20	needle	needle	NOUN
cana-1177	152	21	aspirates	aspirate	NOUN
cana-1177	152	22	(	(	PUNCT
cana-1177	152	23	fna	fna	PROPN
cana-1177	152	24	)	)	PUNCT
cana-1177	152	25	of	of	ADP
cana-1177	152	26	breast	breast	NOUN
cana-1177	152	27	masses	masse	NOUN
cana-1177	152	28	.	.	PUNCT
cana-1177	153	1	it	it	PRON
cana-1177	153	2	is	be	AUX
cana-1177	153	3	composed	compose	VERB
cana-1177	153	4	of	of	ADP
cana-1177	153	5	569	569	NUM
cana-1177	153	6	examples	example	NOUN
cana-1177	153	7	each	each	PRON
cana-1177	153	8	of	of	ADP
cana-1177	153	9	which	which	PRON
cana-1177	153	10	has	have	VERB
cana-1177	153	11	30	30	NUM
cana-1177	153	12	attributes	attribute	NOUN
cana-1177	153	13	(	(	PUNCT
cana-1177	153	14	such	such	ADJ
cana-1177	153	15	as	as	ADP
cana-1177	153	16	radius	radius	NOUN
cana-1177	153	17	,	,	PUNCT
cana-1177	153	18	texture	texture	ADJ
cana-1177	153	19	,	,	PUNCT
cana-1177	153	20	perimeter	perimeter	NOUN
cana-1177	153	21	,	,	PUNCT
cana-1177	153	22	area	area	NOUN
cana-1177	153	23	,	,	PUNCT
cana-1177	153	24	smoothness	smoothness	NOUN
cana-1177	153	25	,	,	PUNCT
cana-1177	153	26	compactness	compactness	NOUN
cana-1177	153	27	,	,	PUNCT
cana-1177	153	28	concavity	concavity	NOUN
cana-1177	153	29	,	,	PUNCT
cana-1177	153	30	concave	concave	NOUN
cana-1177	153	31	points	point	NOUN
cana-1177	153	32	,	,	PUNCT
cana-1177	153	33	symmetry	symmetry	NOUN
cana-1177	153	34	,	,	PUNCT
cana-1177	153	35	and	and	CCONJ
cana-1177	153	36	fractal	fractal	ADJ
cana-1177	153	37	dimension	dimension	NOUN
cana-1177	153	38	)	)	PUNCT
cana-1177	153	39	that	that	PRON
cana-1177	153	40	were	be	AUX
cana-1177	153	41	extracted	extract	VERB
cana-1177	153	42	from	from	ADP
cana-1177	153	43	photographs	photograph	NOUN
cana-1177	153	44	of	of	ADP
cana-1177	153	45	cell	cell	NOUN
cana-1177	153	46	nuclei	nucleus	NOUN
cana-1177	153	47	[	[	X
cana-1177	153	48	14	14	NUM
cana-1177	153	49	]	]	PUNCT
cana-1177	153	50	.	.	PUNCT
cana-1177	154	1	the	the	DET
cana-1177	154	2	diagnostic	diagnostic	ADJ
cana-1177	154	3	which	which	PRON
cana-1177	154	4	indicates	indicate	VERB
cana-1177	154	5	the	the	DET
cana-1177	154	6	kind	kind	NOUN
cana-1177	154	7	of	of	ADP
cana-1177	154	8	breast	breast	NOUN
cana-1177	154	9	mass	mass	NOUN
cana-1177	154	10	and	and	CCONJ
cana-1177	154	11	is	be	AUX
cana-1177	154	12	classified	classify	VERB
cana-1177	154	13	as	as	ADP
cana-1177	154	14	either	either	CCONJ
cana-1177	154	15	malignant	malignant	ADJ
cana-1177	154	16	(	(	PUNCT
cana-1177	154	17	m	m	NOUN
cana-1177	154	18	)	)	PUNCT
cana-1177	154	19	or	or	CCONJ
cana-1177	154	20	benign	benign	ADJ
cana-1177	154	21	(	(	PUNCT
cana-1177	154	22	b	b	NOUN
cana-1177	154	23	)	)	PUNCT
cana-1177	154	24	is	be	AUX
cana-1177	154	25	the	the	DET
cana-1177	154	26	target	target	NOUN
cana-1177	154	27	variable	variable	NOUN
cana-1177	154	28	in	in	ADP
cana-1177	154	29	this	this	DET
cana-1177	154	30	dataset	dataset	NOUN
cana-1177	154	31	.	.	PUNCT
cana-1177	155	1	the	the	DET
cana-1177	155	2	dataset	dataset	NOUN
cana-1177	155	3	is	be	AUX
cana-1177	155	4	useful	useful	ADJ
cana-1177	155	5	for	for	ADP
cana-1177	155	6	creating	create	VERB
cana-1177	155	7	and	and	CCONJ
cana-1177	155	8	assessing	assess	VERB
cana-1177	155	9	ml	ml	NOUN
cana-1177	155	10	models	model	NOUN
cana-1177	155	11	for	for	ADP
cana-1177	155	12	breast	breast	NOUN
cana-1177	155	13	cancer	cancer	NOUN
cana-1177	155	14	diagnosis	diagnosis	NOUN
cana-1177	155	15	because	because	SCONJ
cana-1177	155	16	it	it	PRON
cana-1177	155	17	offers	offer	VERB
cana-1177	155	18	a	a	DET
cana-1177	155	19	thorough	thorough	ADJ
cana-1177	155	20	description	description	NOUN
cana-1177	155	21	of	of	ADP
cana-1177	155	22	the	the	DET
cana-1177	155	23	features	feature	NOUN
cana-1177	155	24	of	of	ADP
cana-1177	155	25	the	the	DET
cana-1177	155	26	disease	disease	NOUN
cana-1177	155	27	.	.	PUNCT
cana-1177	156	1	fig.3	fig.3	PROPN
cana-1177	156	2	shows	show	VERB
cana-1177	156	3	the	the	DET
cana-1177	156	4	class	class	NOUN
cana-1177	156	5	distribution	distribution	NOUN
cana-1177	156	6	of	of	ADP
cana-1177	156	7	breast	breast	NOUN
cana-1177	156	8	cancer	cancer	NOUN
cana-1177	156	9	of	of	ADP
cana-1177	156	10	wdbc	wdbc	NOUN
cana-1177	156	11	with	with	ADP
cana-1177	156	12	569	569	NUM
cana-1177	156	13	instances	instance	NOUN
cana-1177	156	14	.	.	PUNCT
cana-1177	157	1	fig.3	fig.3	PROPN
cana-1177	157	2	.	.	PUNCT
cana-1177	157	3	class	class	NOUN
cana-1177	157	4	distribution	distribution	NOUN
cana-1177	157	5	of	of	ADP
cana-1177	157	6	breast	breast	NOUN
cana-1177	157	7	cancer	cancer	NOUN
cana-1177	157	8	of	of	ADP
cana-1177	157	9	wdbc	wdbc	PROPN
cana-1177	157	10	communications	communication	NOUN
cana-1177	157	11	on	on	ADP
cana-1177	157	12	applied	apply	VERB
cana-1177	157	13	nonlinear	nonlinear	ADJ
cana-1177	157	14	analysis	analysis	NOUN
cana-1177	157	15	issn	issn	NOUN
cana-1177	157	16	:	:	PUNCT
cana-1177	157	17	1074	1074	NUM
cana-1177	157	18	-	-	PUNCT
cana-1177	157	19	133x	133x	NUM
cana-1177	157	20	vol	vol	NOUN
cana-1177	157	21	31	31	NUM
cana-1177	157	22	no	no	NOUN
cana-1177	157	23	.	.	PUNCT
cana-1177	158	1	6s	6s	NUM
cana-1177	158	2	(	(	PUNCT
cana-1177	158	3	2024	2024	NUM
cana-1177	158	4	)	)	PUNCT
cana-1177	158	5	185	185	NUM
cana-1177	158	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-1177	158	7	3.1.1	3.1.1	NUM
cana-1177	158	8	.	.	PUNCT
cana-1177	159	1	splitting	split	VERB
cana-1177	159	2	the	the	DET
cana-1177	159	3	dataset	dataset	NOUN
cana-1177	159	4	we	we	PRON
cana-1177	159	5	obtained	obtain	VERB
cana-1177	159	6	data	datum	NOUN
cana-1177	159	7	from	from	ADP
cana-1177	159	8	the	the	DET
cana-1177	159	9	uci	uci	PROPN
cana-1177	159	10	ml	ml	NOUN
cana-1177	159	11	repository	repository	NOUN
cana-1177	159	12	as	as	ADV
cana-1177	159	13	well	well	ADV
cana-1177	159	14	and	and	CCONJ
cana-1177	159	15	through	through	ADP
cana-1177	159	16	the	the	DET
cana-1177	159	17	insightful	insightful	ADJ
cana-1177	159	18	study	study	NOUN
cana-1177	159	19	,	,	PUNCT
cana-1177	159	20	we	we	PRON
cana-1177	159	21	discarded	discard	VERB
cana-1177	159	22	outliers	outlier	NOUN
cana-1177	159	23	.	.	PUNCT
cana-1177	160	1	the	the	DET
cana-1177	160	2	next	next	ADJ
cana-1177	160	3	step	step	NOUN
cana-1177	160	4	was	be	AUX
cana-1177	160	5	to	to	PART
cana-1177	160	6	divide	divide	VERB
cana-1177	160	7	the	the	DET
cana-1177	160	8	data	datum	NOUN
cana-1177	160	9	into	into	ADP
cana-1177	160	10	20	20	NUM
cana-1177	160	11	%	%	NOUN
cana-1177	160	12	testing	testing	NOUN
cana-1177	160	13	section	section	NOUN
cana-1177	160	14	and	and	CCONJ
cana-1177	160	15	80	80	NUM
cana-1177	160	16	%	%	NOUN
cana-1177	160	17	section	section	NOUN
cana-1177	160	18	for	for	ADP
cana-1177	160	19	training	training	NOUN
cana-1177	160	20	.	.	PUNCT
cana-1177	161	1	such	such	ADJ
cana-1177	161	2	ideas	idea	NOUN
cana-1177	161	3	play	play	VERB
cana-1177	161	4	an	an	DET
cana-1177	161	5	important	important	ADJ
cana-1177	161	6	role	role	NOUN
cana-1177	161	7	in	in	ADP
cana-1177	161	8	every	every	DET
cana-1177	161	9	stage	stage	NOUN
cana-1177	161	10	of	of	ADP
cana-1177	161	11	our	our	PRON
cana-1177	161	12	metalogical	metalogical	ADJ
cana-1177	161	13	framework	framework	NOUN
cana-1177	161	14	.	.	PUNCT
cana-1177	162	1	the	the	DET
cana-1177	162	2	dataset	dataset	NOUN
cana-1177	162	3	is	be	AUX
cana-1177	162	4	initially	initially	ADV
cana-1177	162	5	split	split	VERB
cana-1177	162	6	into	into	ADP
cana-1177	162	7	two	two	NUM
cana-1177	162	8	categories	category	NOUN
cana-1177	162	9	:	:	PUNCT
cana-1177	162	10	x	x	PUNCT
cana-1177	162	11	represents	represent	VERB
cana-1177	162	12	all	all	DET
cana-1177	162	13	features	feature	NOUN
cana-1177	162	14	not	not	PART
cana-1177	162	15	including	include	VERB
cana-1177	162	16	the	the	DET
cana-1177	162	17	target	target	NOUN
cana-1177	162	18	,	,	PUNCT
cana-1177	162	19	and	and	CCONJ
cana-1177	162	20	y	y	PROPN
cana-1177	162	21	represents	represent	VERB
cana-1177	162	22	the	the	DET
cana-1177	162	23	target	target	NOUN
cana-1177	162	24	.	.	PUNCT
cana-1177	163	1	next	next	ADV
cana-1177	163	2	,	,	PUNCT
cana-1177	163	3	we	we	PRON
cana-1177	163	4	'll	will	AUX
cana-1177	163	5	use	use	VERB
cana-1177	163	6	the	the	DET
cana-1177	163	7	train	train	NOUN
cana-1177	163	8	_	_	PRON
cana-1177	163	9	test	test	NOUN
cana-1177	163	10	_	_	PUNCT
cana-1177	163	11	split	split	ADJ
cana-1177	163	12	procedure	procedure	NOUN
cana-1177	163	13	to	to	PART
cana-1177	163	14	divide	divide	VERB
cana-1177	163	15	the	the	DET
cana-1177	163	16	dataset	dataset	NOUN
cana-1177	163	17	into	into	ADP
cana-1177	163	18	training	training	NOUN
cana-1177	163	19	and	and	CCONJ
cana-1177	163	20	testing	testing	NOUN
cana-1177	163	21	sets	set	NOUN
cana-1177	163	22	.	.	PUNCT
cana-1177	164	1	training	training	NOUN
cana-1177	164	2	data	datum	NOUN
cana-1177	164	3	are	be	AUX
cana-1177	164	4	utilized	utilize	VERB
cana-1177	164	5	to	to	PART
cana-1177	164	6	educate	educate	VERB
cana-1177	164	7	the	the	DET
cana-1177	164	8	model	model	NOUN
cana-1177	164	9	while	while	SCONJ
cana-1177	164	10	testing	testing	NOUN
cana-1177	164	11	data	datum	NOUN
cana-1177	164	12	are	be	AUX
cana-1177	164	13	employed	employ	VERB
cana-1177	164	14	to	to	PART
cana-1177	164	15	evaluate	evaluate	VERB
cana-1177	164	16	the	the	DET
cana-1177	164	17	model	model	NOUN
cana-1177	164	18	's	's	PART
cana-1177	164	19	functionality	functionality	NOUN
cana-1177	164	20	following	follow	VERB
cana-1177	164	21	training	training	NOUN
cana-1177	164	22	.	.	PUNCT
cana-1177	165	1	the	the	DET
cana-1177	165	2	partition	partition	NOUN
cana-1177	165	3	of	of	ADP
cana-1177	165	4	training	training	NOUN
cana-1177	165	5	and	and	CCONJ
cana-1177	165	6	testing	testing	NOUN
cana-1177	165	7	set	set	VERB
cana-1177	165	8	in	in	ADP
cana-1177	165	9	our	our	PRON
cana-1177	165	10	work	work	NOUN
cana-1177	165	11	is	be	AUX
cana-1177	165	12	depicted	depict	VERB
cana-1177	165	13	in	in	ADP
cana-1177	165	14	fig.4	fig.4	PROPN
cana-1177	165	15	.	.	PUNCT
cana-1177	166	1	fig.4	fig.4	PROPN
cana-1177	166	2	.	.	PUNCT
cana-1177	167	1	the	the	DET
cana-1177	167	2	partition	partition	NOUN
cana-1177	167	3	of	of	ADP
cana-1177	167	4	dataset	dataset	NOUN
cana-1177	167	5	into	into	ADP
cana-1177	167	6	training	training	NOUN
cana-1177	167	7	and	and	CCONJ
cana-1177	167	8	testing	testing	NOUN
cana-1177	167	9	set	set	VERB
cana-1177	167	10	this	this	DET
cana-1177	167	11	stage	stage	NOUN
cana-1177	167	12	is	be	AUX
cana-1177	167	13	crucial	crucial	ADJ
cana-1177	167	14	for	for	ADP
cana-1177	167	15	getting	get	VERB
cana-1177	167	16	our	our	PRON
cana-1177	167	17	dataset	dataset	NOUN
cana-1177	167	18	ready	ready	ADJ
cana-1177	167	19	for	for	ADP
cana-1177	167	20	the	the	DET
cana-1177	167	21	following	follow	VERB
cana-1177	167	22	stages	stage	NOUN
cana-1177	167	23	.	.	PUNCT
cana-1177	168	1	the	the	DET
cana-1177	168	2	models	model	NOUN
cana-1177	168	3	are	be	AUX
cana-1177	168	4	able	able	ADJ
cana-1177	168	5	to	to	PART
cana-1177	168	6	identify	identify	VERB
cana-1177	168	7	breast	breast	NOUN
cana-1177	168	8	cancer	cancer	NOUN
cana-1177	168	9	once	once	SCONJ
cana-1177	168	10	they	they	PRON
cana-1177	168	11	have	have	AUX
cana-1177	168	12	been	be	AUX
cana-1177	168	13	trained	train	VERB
cana-1177	168	14	on	on	ADP
cana-1177	168	15	the	the	DET
cana-1177	168	16	training	training	NOUN
cana-1177	168	17	set	set	NOUN
cana-1177	168	18	.	.	PUNCT
cana-1177	169	1	3.1.2	3.1.2	X
cana-1177	169	2	.	.	PUNCT
cana-1177	169	3	balancing	balance	VERB
cana-1177	169	4	the	the	DET
cana-1177	169	5	dataset	dataset	NOUN
cana-1177	169	6	the	the	DET
cana-1177	169	7	class	class	NOUN
cana-1177	169	8	balancing	balancing	NOUN
cana-1177	169	9	,	,	PUNCT
cana-1177	169	10	which	which	PRON
cana-1177	169	11	takes	take	VERB
cana-1177	169	12	place	place	NOUN
cana-1177	169	13	in	in	ADP
cana-1177	169	14	many	many	ADJ
cana-1177	169	15	cases	case	NOUN
cana-1177	169	16	where	where	SCONJ
cana-1177	169	17	there	there	PRON
cana-1177	169	18	are	be	VERB
cana-1177	169	19	imbalanced	imbalanced	ADJ
cana-1177	169	20	categories	category	NOUN
cana-1177	169	21	(	(	PUNCT
cana-1177	169	22	such	such	ADJ
cana-1177	169	23	as	as	ADP
cana-1177	169	24	in	in	ADP
cana-1177	169	25	medical	medical	ADJ
cana-1177	169	26	diagnosis	diagnosis	NOUN
cana-1177	169	27	)	)	PUNCT
cana-1177	169	28	requires	require	VERB
cana-1177	169	29	means	mean	NOUN
cana-1177	169	30	that	that	PRON
cana-1177	169	31	will	will	AUX
cana-1177	169	32	help	help	VERB
cana-1177	169	33	straighten	straighten	VERB
cana-1177	169	34	out	out	ADP
cana-1177	169	35	the	the	DET
cana-1177	169	36	uneven	uneven	ADJ
cana-1177	169	37	distribution	distribution	NOUN
cana-1177	169	38	among	among	ADP
cana-1177	169	39	the	the	DET
cana-1177	169	40	classes	class	NOUN
cana-1177	169	41	.	.	PUNCT
cana-1177	170	1	therefore	therefore	ADV
cana-1177	170	2	,	,	PUNCT
cana-1177	170	3	in	in	ADP
cana-1177	170	4	this	this	DET
cana-1177	170	5	situation	situation	NOUN
cana-1177	170	6	,	,	PUNCT
cana-1177	170	7	random	random	ADJ
cana-1177	170	8	over	over	ADP
cana-1177	170	9	sampling	sample	VERB
cana-1177	170	10	(	(	PUNCT
cana-1177	170	11	ros	ros	PROPN
cana-1177	170	12	)	)	PUNCT
cana-1177	170	13	method	method	NOUN
cana-1177	170	14	is	be	AUX
cana-1177	170	15	applied	apply	VERB
cana-1177	170	16	,	,	PUNCT
cana-1177	170	17	which	which	PRON
cana-1177	170	18	makes	make	VERB
cana-1177	170	19	multiply	multiply	NOUN
cana-1177	170	20	copies	copy	NOUN
cana-1177	170	21	of	of	ADP
cana-1177	170	22	minority	minority	NOUN
cana-1177	170	23	class	class	NOUN
cana-1177	170	24	samples	sample	NOUN
cana-1177	170	25	to	to	PART
cana-1177	170	26	compensate	compensate	VERB
cana-1177	170	27	the	the	DET
cana-1177	170	28	disparity	disparity	NOUN
cana-1177	170	29	in	in	ADP
cana-1177	170	30	class	class	NOUN
cana-1177	170	31	distribution	distribution	NOUN
cana-1177	170	32	.	.	PUNCT
cana-1177	171	1	random	random	ADJ
cana-1177	171	2	over	over	ADP
cana-1177	171	3	sampler	sampler	NOUN
cana-1177	171	4	(	(	PUNCT
cana-1177	171	5	ros	ros	PROPN
cana-1177	171	6	):	):	PUNCT
cana-1177	171	7	the	the	DET
cana-1177	171	8	random	random	ADJ
cana-1177	171	9	over	over	ADP
cana-1177	171	10	sampler	sampler	NOUN
cana-1177	171	11	(	(	PUNCT
cana-1177	171	12	ros	ros	PROPN
cana-1177	171	13	)	)	PUNCT
cana-1177	171	14	technique	technique	NOUN
cana-1177	171	15	is	be	AUX
cana-1177	171	16	a	a	DET
cana-1177	171	17	method	method	NOUN
cana-1177	171	18	used	use	VERB
cana-1177	171	19	to	to	PART
cana-1177	171	20	address	address	VERB
cana-1177	171	21	class	class	NOUN
cana-1177	171	22	imbalance	imbalance	NOUN
cana-1177	171	23	in	in	ADP
cana-1177	171	24	datasets	dataset	NOUN
cana-1177	171	25	where	where	SCONJ
cana-1177	171	26	one	one	NUM
cana-1177	171	27	class	class	NOUN
cana-1177	171	28	significantly	significantly	ADV
cana-1177	171	29	out	out	ADP
cana-1177	171	30	numbers	number	NOUN
cana-1177	171	31	the	the	DET
cana-1177	171	32	other	other	ADJ
cana-1177	171	33	.	.	PUNCT
cana-1177	172	1	in	in	ADP
cana-1177	172	2	the	the	DET
cana-1177	172	3	context	context	NOUN
cana-1177	172	4	of	of	ADP
cana-1177	172	5	machine	machine	NOUN
cana-1177	172	6	learning	learn	VERB
cana-1177	172	7	this	this	DET
cana-1177	172	8	inequality	inequality	NOUN
cana-1177	172	9	can	can	AUX
cana-1177	172	10	lead	lead	VERB
cana-1177	172	11	to	to	ADP
cana-1177	172	12	biased	biased	ADJ
cana-1177	172	13	models	model	NOUN
cana-1177	172	14	that	that	PRON
cana-1177	172	15	favour	favour	VERB
cana-1177	172	16	the	the	DET
cana-1177	172	17	majority	majority	NOUN
cana-1177	172	18	class	class	NOUN
cana-1177	172	19	ensuing	ensue	VERB
cana-1177	172	20	in	in	ADP
cana-1177	172	21	poor	poor	ADJ
cana-1177	172	22	performance	performance	NOUN
cana-1177	172	23	for	for	ADP
cana-1177	172	24	the	the	DET
cana-1177	172	25	minority	minority	NOUN
cana-1177	172	26	class	class	NOUN
cana-1177	172	27	.	.	PUNCT
cana-1177	173	1	ros	ros	PROPN
cana-1177	173	2	works	work	VERB
cana-1177	173	3	by	by	ADP
cana-1177	173	4	randomly	randomly	ADV
cana-1177	173	5	duplicating	duplicate	VERB
cana-1177	173	6	instances	instance	NOUN
cana-1177	173	7	from	from	ADP
cana-1177	173	8	the	the	DET
cana-1177	173	9	minority	minority	NOUN
cana-1177	173	10	class	class	NOUN
cana-1177	173	11	until	until	SCONJ
cana-1177	173	12	both	both	DET
cana-1177	173	13	classes	class	NOUN
cana-1177	173	14	are	be	AUX
cana-1177	173	15	balanced	balanced	ADJ
cana-1177	173	16	.	.	PUNCT
cana-1177	174	1	this	this	DET
cana-1177	174	2	oversampling	oversampling	ADJ
cana-1177	174	3	technique	technique	NOUN
cana-1177	174	4	increases	increase	VERB
cana-1177	174	5	the	the	DET
cana-1177	174	6	representation	representation	NOUN
cana-1177	174	7	of	of	ADP
cana-1177	174	8	the	the	DET
cana-1177	174	9	minority	minority	NOUN
cana-1177	174	10	class	class	NOUN
cana-1177	174	11	and	and	CCONJ
cana-1177	174	12	providing	provide	VERB
cana-1177	174	13	more	more	ADJ
cana-1177	174	14	examples	example	NOUN
cana-1177	174	15	for	for	SCONJ
cana-1177	174	16	the	the	DET
cana-1177	174	17	model	model	NOUN
cana-1177	174	18	to	to	PART
cana-1177	174	19	learn	learn	VERB
cana-1177	174	20	from	from	ADP
cana-1177	174	21	during	during	ADP
cana-1177	174	22	training	training	NOUN
cana-1177	174	23	.	.	PUNCT
cana-1177	175	1	the	the	DET
cana-1177	175	2	motivation	motivation	NOUN
cana-1177	175	3	behind	behind	ADP
cana-1177	175	4	using	use	VERB
cana-1177	175	5	ros	ros	PROPN
cana-1177	175	6	is	be	AUX
cana-1177	175	7	to	to	PART
cana-1177	175	8	ensure	ensure	VERB
cana-1177	175	9	that	that	SCONJ
cana-1177	175	10	the	the	DET
cana-1177	175	11	model	model	NOUN
cana-1177	175	12	learns	learn	VERB
cana-1177	175	13	from	from	ADP
cana-1177	175	14	a	a	DET
cana-1177	175	15	more	more	ADV
cana-1177	175	16	balanced	balanced	ADJ
cana-1177	175	17	dataset	dataset	NOUN
cana-1177	175	18	which	which	PRON
cana-1177	175	19	can	can	AUX
cana-1177	175	20	improve	improve	VERB
cana-1177	175	21	its	its	PRON
cana-1177	175	22	ability	ability	NOUN
cana-1177	175	23	to	to	PART
cana-1177	175	24	correctly	correctly	ADV
cana-1177	175	25	classify	classify	VERB
cana-1177	175	26	instances	instance	NOUN
cana-1177	175	27	from	from	ADP
cana-1177	175	28	both	both	DET
cana-1177	175	29	classes	class	NOUN
cana-1177	175	30	.	.	PUNCT
cana-1177	176	1	this	this	DET
cana-1177	176	2	approach	approach	NOUN
cana-1177	176	3	helps	help	VERB
cana-1177	176	4	prevent	prevent	VERB
cana-1177	176	5	the	the	DET
cana-1177	176	6	model	model	NOUN
cana-1177	176	7	from	from	ADP
cana-1177	176	8	being	be	AUX
cana-1177	176	9	biased	bias	VERB
cana-1177	176	10	towards	towards	ADP
cana-1177	176	11	the	the	DET
cana-1177	176	12	majority	majority	NOUN
cana-1177	176	13	class	class	NOUN
cana-1177	176	14	and	and	CCONJ
cana-1177	176	15	improves	improve	VERB
cana-1177	176	16	its	its	PRON
cana-1177	176	17	overall	overall	ADJ
cana-1177	176	18	performance	performance	NOUN
cana-1177	176	19	and	and	CCONJ
cana-1177	176	20	generalization	generalization	NOUN
cana-1177	176	21	ability	ability	NOUN
cana-1177	176	22	.	.	PUNCT
cana-1177	177	1	fig.5	fig.5	PROPN
cana-1177	177	2	.	.	PUNCT
cana-1177	177	3	shows	show	VERB
cana-1177	177	4	the	the	DET
cana-1177	177	5	class	class	NOUN
cana-1177	177	6	distribution	distribution	NOUN
cana-1177	177	7	before	before	ADP
cana-1177	177	8	and	and	CCONJ
cana-1177	177	9	after	after	ADP
cana-1177	177	10	randomoversampler	randomoversampler	NOUN
cana-1177	177	11	on	on	ADP
cana-1177	177	12	training	training	NOUN
cana-1177	177	13	set	set	NOUN
cana-1177	177	14	.	.	PUNCT
cana-1177	178	1	communications	communication	NOUN
cana-1177	178	2	on	on	ADP
cana-1177	178	3	applied	apply	VERB
cana-1177	178	4	nonlinear	nonlinear	ADJ
cana-1177	178	5	analysis	analysis	NOUN
cana-1177	178	6	issn	issn	NOUN
cana-1177	178	7	:	:	PUNCT
cana-1177	178	8	1074	1074	NUM
cana-1177	178	9	-	-	PUNCT
cana-1177	178	10	133x	133x	NUM
cana-1177	178	11	vol	vol	NOUN
cana-1177	178	12	31	31	NUM
cana-1177	178	13	no	no	NOUN
cana-1177	178	14	.	.	PUNCT
cana-1177	179	1	6s	6s	NUM
cana-1177	179	2	(	(	PUNCT
cana-1177	179	3	2024	2024	NUM
cana-1177	179	4	)	)	PUNCT
cana-1177	179	5	186	186	NUM
cana-1177	179	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-1177	179	7	fig.5	fig.5	PROPN
cana-1177	179	8	.	.	PUNCT
cana-1177	180	1	class	class	NOUN
cana-1177	180	2	distribution	distribution	NOUN
cana-1177	180	3	before	before	ADP
cana-1177	180	4	and	and	CCONJ
cana-1177	180	5	after	after	ADP
cana-1177	180	6	randomoversampler	randomoversampler	NOUN
cana-1177	180	7	(	(	PUNCT
cana-1177	180	8	ros	ros	PROPN
cana-1177	180	9	)	)	PUNCT
cana-1177	180	10	on	on	ADP
cana-1177	180	11	training	training	NOUN
cana-1177	180	12	dataset	dataset	VERB
cana-1177	180	13	the	the	DET
cana-1177	180	14	wdbc	wdbc	NOUN
cana-1177	180	15	dataset	dataset	NOUN
cana-1177	180	16	is	be	AUX
cana-1177	180	17	divide	divide	ADJ
cana-1177	180	18	into	into	ADP
cana-1177	180	19	training	training	NOUN
cana-1177	180	20	(	(	PUNCT
cana-1177	180	21	455	455	NUM
cana-1177	180	22	instances	instance	NOUN
cana-1177	180	23	)	)	PUNCT
cana-1177	180	24	and	and	CCONJ
cana-1177	180	25	testing	testing	NOUN
cana-1177	180	26	(	(	PUNCT
cana-1177	180	27	114	114	NUM
cana-1177	180	28	instances	instance	NOUN
cana-1177	180	29	)	)	PUNCT
cana-1177	180	30	sets	set	NOUN
cana-1177	180	31	.	.	PUNCT
cana-1177	181	1	after	after	ADP
cana-1177	181	2	balancing	balance	VERB
cana-1177	181	3	with	with	ADP
cana-1177	181	4	ros	ros	PROPN
cana-1177	181	5	,	,	PUNCT
cana-1177	181	6	the	the	DET
cana-1177	181	7	training	training	NOUN
cana-1177	181	8	set	set	NOUN
cana-1177	181	9	exhibited	exhibit	VERB
cana-1177	181	10	a	a	DET
cana-1177	181	11	class	class	NOUN
cana-1177	181	12	distribution	distribution	NOUN
cana-1177	181	13	of	of	ADP
cana-1177	181	14	286	286	NUM
cana-1177	181	15	benign	benign	ADJ
cana-1177	181	16	(	(	PUNCT
cana-1177	181	17	b	b	NOUN
cana-1177	181	18	)	)	PUNCT
cana-1177	181	19	and	and	CCONJ
cana-1177	181	20	169	169	NUM
cana-1177	181	21	malignant	malignant	ADJ
cana-1177	181	22	(	(	PUNCT
cana-1177	181	23	m	m	NOUN
cana-1177	181	24	)	)	PUNCT
cana-1177	181	25	instances	instance	NOUN
cana-1177	181	26	into	into	ADP
cana-1177	181	27	572	572	NUM
cana-1177	181	28	instances	instance	NOUN
cana-1177	181	29	.	.	PUNCT
cana-1177	182	1	table	table	NOUN
cana-1177	182	2	4	4	NUM
cana-1177	182	3	shows	show	VERB
cana-1177	182	4	whole	whole	ADJ
cana-1177	182	5	description	description	NOUN
cana-1177	182	6	of	of	ADP
cana-1177	182	7	the	the	DET
cana-1177	182	8	class	class	NOUN
cana-1177	182	9	distribution	distribution	NOUN
cana-1177	182	10	of	of	ADP
cana-1177	182	11	wdbc	wdbc	NOUN
cana-1177	182	12	dataset	dataset	NOUN
cana-1177	182	13	used	use	VERB
cana-1177	182	14	in	in	ADP
cana-1177	182	15	this	this	DET
cana-1177	182	16	work	work	NOUN
cana-1177	182	17	.	.	PUNCT
cana-1177	183	1	table	table	NOUN
cana-1177	183	2	4	4	NUM
cana-1177	183	3	dataset	dataset	NOUN
cana-1177	183	4	distribution	distribution	NOUN
cana-1177	183	5	summary	summary	NOUN
cana-1177	183	6	wdbc	wdbc	VERB
cana-1177	183	7	after	after	ADP
cana-1177	183	8	splitting	split	VERB
cana-1177	183	9	training	training	NOUN
cana-1177	183	10	set	set	VERB
cana-1177	183	11	after	after	ADP
cana-1177	183	12	ros	ros	PROPN
cana-1177	183	13	training	training	NOUN
cana-1177	183	14	set	set	NOUN
cana-1177	183	15	testing	testing	NOUN
cana-1177	183	16	set	set	VERB
cana-1177	183	17	total	total	ADJ
cana-1177	183	18	instances	instance	NOUN
cana-1177	183	19	569	569	NUM
cana-1177	183	20	455	455	NUM
cana-1177	183	21	114	114	NUM
cana-1177	183	22	572	572	NUM
cana-1177	183	23	class	class	NOUN
cana-1177	183	24	distribution	distribution	NOUN
cana-1177	183	25	b=357	b=357	NOUN
cana-1177	183	26	,	,	PUNCT
cana-1177	183	27	m=212	m=212	PROPN
cana-1177	183	28	b=286	b=286	PROPN
cana-1177	183	29	,	,	PUNCT
cana-1177	183	30	m=169	m=169	NOUN
cana-1177	183	31	b=286	b=286	PROPN
cana-1177	183	32	,	,	PUNCT
cana-1177	183	33	m=286	m=286	PROPN
cana-1177	183	34	3.1.3	3.1.3	NUM
cana-1177	183	35	.	.	PUNCT
cana-1177	184	1	feature	feature	NOUN
cana-1177	184	2	scaling	scale	VERB
cana-1177	184	3	standard	standard	ADJ
cana-1177	184	4	scaler	scaler	NOUN
cana-1177	184	5	is	be	AUX
cana-1177	184	6	a	a	DET
cana-1177	184	7	feature	feature	NOUN
cana-1177	184	8	scaling	scale	VERB
cana-1177	184	9	technique	technique	NOUN
cana-1177	184	10	used	use	VERB
cana-1177	184	11	to	to	PART
cana-1177	184	12	normalize	normalize	VERB
cana-1177	184	13	the	the	DET
cana-1177	184	14	range	range	NOUN
cana-1177	184	15	of	of	ADP
cana-1177	184	16	independent	independent	ADJ
cana-1177	184	17	variables	variable	NOUN
cana-1177	184	18	or	or	CCONJ
cana-1177	184	19	features	feature	NOUN
cana-1177	184	20	in	in	ADP
cana-1177	184	21	a	a	DET
cana-1177	184	22	dataset	dataset	NOUN
cana-1177	184	23	.	.	PUNCT
cana-1177	185	1	because	because	SCONJ
cana-1177	185	2	it	it	PRON
cana-1177	185	3	guarantees	guarantee	VERB
cana-1177	185	4	that	that	SCONJ
cana-1177	185	5	features	feature	NOUN
cana-1177	185	6	are	be	AUX
cana-1177	185	7	on	on	ADP
cana-1177	185	8	a	a	DET
cana-1177	185	9	same	same	ADJ
cana-1177	185	10	scale	scale	NOUN
cana-1177	185	11	and	and	CCONJ
cana-1177	185	12	keeps	keep	VERB
cana-1177	185	13	some	some	DET
cana-1177	185	14	features	feature	NOUN
cana-1177	185	15	from	from	ADP
cana-1177	185	16	predominating	predominate	VERB
cana-1177	185	17	over	over	ADP
cana-1177	185	18	others	other	NOUN
cana-1177	185	19	during	during	ADP
cana-1177	185	20	model	model	NOUN
cana-1177	185	21	training	training	NOUN
cana-1177	185	22	,	,	PUNCT
cana-1177	185	23	this	this	DET
cana-1177	185	24	procedure	procedure	NOUN
cana-1177	185	25	is	be	AUX
cana-1177	185	26	essential	essential	ADJ
cana-1177	185	27	to	to	ADP
cana-1177	185	28	machine	machine	NOUN
cana-1177	185	29	learning	learning	NOUN
cana-1177	185	30	.	.	PUNCT
cana-1177	186	1	in	in	ADP
cana-1177	186	2	order	order	NOUN
cana-1177	186	3	to	to	PART
cana-1177	186	4	use	use	VERB
cana-1177	186	5	standard	standard	ADJ
cana-1177	186	6	scaler	scaler	NOUN
cana-1177	186	7	each	each	DET
cana-1177	186	8	feature	feature	NOUN
cana-1177	186	9	's	's	PART
cana-1177	186	10	mean	mean	ADJ
cana-1177	186	11	and	and	CCONJ
cana-1177	186	12	standard	standard	ADJ
cana-1177	186	13	deviation	deviation	NOUN
cana-1177	186	14	are	be	AUX
cana-1177	186	15	first	first	ADV
cana-1177	186	16	determined	determine	VERB
cana-1177	186	17	.	.	PUNCT
cana-1177	187	1	the	the	DET
cana-1177	187	2	feature	feature	NOUN
cana-1177	187	3	values	value	NOUN
cana-1177	187	4	are	be	AUX
cana-1177	187	5	then	then	ADV
cana-1177	187	6	transformed	transform	VERB
cana-1177	187	7	to	to	PART
cana-1177	187	8	have	have	VERB
cana-1177	187	9	a	a	DET
cana-1177	187	10	mean	mean	NOUN
cana-1177	187	11	of	of	ADP
cana-1177	187	12	0	0	NUM
cana-1177	187	13	and	and	CCONJ
cana-1177	187	14	a	a	DET
cana-1177	187	15	standard	standard	ADJ
cana-1177	187	16	deviation	deviation	NOUN
cana-1177	187	17	of	of	ADP
cana-1177	187	18	1	1	NUM
cana-1177	187	19	.	.	PUNCT
cana-1177	188	1	the	the	DET
cana-1177	188	2	aim	aim	NOUN
cana-1177	188	3	of	of	ADP
cana-1177	188	4	the	the	DET
cana-1177	188	5	ease	ease	NOUN
cana-1177	188	6	of	of	ADP
cana-1177	188	7	comparison	comparison	NOUN
cana-1177	188	8	of	of	ADP
cana-1177	188	9	traits	trait	NOUN
cana-1177	188	10	using	use	VERB
cana-1177	188	11	the	the	DET
cana-1177	188	12	standard	standard	ADJ
cana-1177	188	13	scaler	scaler	NOUN
cana-1177	188	14	is	be	AUX
cana-1177	188	15	to	to	PART
cana-1177	188	16	ensure	ensure	VERB
cana-1177	188	17	that	that	SCONJ
cana-1177	188	18	the	the	DET
cana-1177	188	19	model	model	NOUN
cana-1177	188	20	treats	treat	VERB
cana-1177	188	21	all	all	PRON
cana-1177	188	22	features	feature	VERB
cana-1177	188	23	equally	equally	ADV
cana-1177	188	24	and	and	CCONJ
cana-1177	188	25	during	during	ADP
cana-1177	188	26	the	the	DET
cana-1177	188	27	training	training	NOUN
cana-1177	188	28	session	session	NOUN
cana-1177	188	29	.	.	PUNCT
cana-1177	189	1	thereby	thereby	ADV
cana-1177	189	2	,	,	PUNCT
cana-1177	189	3	it	it	PRON
cana-1177	189	4	ensures	ensure	VERB
cana-1177	189	5	better	well	ADJ
cana-1177	189	6	rate	rate	NOUN
cana-1177	189	7	of	of	ADP
cana-1177	189	8	convergence	convergence	NOUN
cana-1177	189	9	of	of	ADP
cana-1177	189	10	optimization	optimization	NOUN
cana-1177	189	11	algorithms	algorithm	NOUN
cana-1177	189	12	and	and	CCONJ
cana-1177	189	13	it	it	PRON
cana-1177	189	14	addresses	address	VERB
cana-1177	189	15	and	and	CCONJ
cana-1177	189	16	prevents	prevent	VERB
cana-1177	189	17	numerical	numerical	ADJ
cana-1177	189	18	errors	error	NOUN
cana-1177	189	19	that	that	PRON
cana-1177	189	20	initializes	initialize	VERB
cana-1177	189	21	when	when	SCONJ
cana-1177	189	22	features	feature	NOUN
cana-1177	189	23	have	have	VERB
cana-1177	189	24	vastly	vastly	ADV
cana-1177	189	25	different	different	ADJ
cana-1177	189	26	scales	scale	NOUN
cana-1177	189	27	.	.	PUNCT
cana-1177	190	1	feature	feature	NOUN
cana-1177	190	2	scale	scale	NOUN
cana-1177	190	3	with	with	ADP
cana-1177	190	4	the	the	DET
cana-1177	190	5	standard	standard	ADJ
cana-1177	190	6	scaler	scaler	NOUN
cana-1177	190	7	implemented	implement	VERB
cana-1177	190	8	is	be	AUX
cana-1177	190	9	an	an	DET
cana-1177	190	10	indispensable	indispensable	ADJ
cana-1177	190	11	preprocessing	preprocessing	NOUN
cana-1177	190	12	step	step	NOUN
cana-1177	190	13	in	in	ADP
cana-1177	190	14	machine	machine	NOUN
cana-1177	190	15	learning	learning	NOUN
cana-1177	190	16	which	which	PRON
cana-1177	190	17	homogenously	homogenously	ADV
cana-1177	190	18	scales	scale	VERB
cana-1177	190	19	features	feature	NOUN
cana-1177	190	20	to	to	PART
cana-1177	190	21	have	have	VERB
cana-1177	190	22	a	a	DET
cana-1177	190	23	range	range	NOUN
cana-1177	190	24	within	within	ADP
cana-1177	190	25	similar	similar	ADJ
cana-1177	190	26	ranges	range	NOUN
cana-1177	190	27	,	,	PUNCT
cana-1177	190	28	leading	lead	VERB
cana-1177	190	29	to	to	ADP
cana-1177	190	30	more	more	ADV
cana-1177	190	31	stable	stable	ADJ
cana-1177	190	32	and	and	CCONJ
cana-1177	190	33	reliable	reliable	ADJ
cana-1177	190	34	models	model	NOUN
cana-1177	190	35	.	.	PUNCT
cana-1177	191	1	to	to	PART
cana-1177	191	2	standardize	standardize	VERB
cana-1177	191	3	the	the	DET
cana-1177	191	4	dataset	dataset	NOUN
cana-1177	191	5	by	by	ADP
cana-1177	191	6	removing	remove	VERB
cana-1177	191	7	the	the	DET
cana-1177	191	8	mean	mean	NOUN
cana-1177	191	9	and	and	CCONJ
cana-1177	191	10	scaling	scale	VERB
cana-1177	191	11	them	they	PRON
cana-1177	191	12	to	to	ADP
cana-1177	191	13	unit	unit	NOUN
cana-1177	191	14	variance	variance	NOUN
cana-1177	191	15	,	,	PUNCT
cana-1177	191	16	there	there	PRON
cana-1177	191	17	is	be	VERB
cana-1177	191	18	a	a	DET
cana-1177	191	19	machine	machine	NOUN
cana-1177	191	20	learning	learning	NOUN
cana-1177	191	21	technique	technique	NOUN
cana-1177	191	22	known	know	VERB
cana-1177	191	23	as	as	ADP
cana-1177	191	24	standardscaler	standardscaler	NOUN
cana-1177	191	25	[	[	X
cana-1177	191	26	10	10	NUM
cana-1177	191	27	]	]	PUNCT
cana-1177	191	28	.	.	PUNCT
cana-1177	192	1	the	the	DET
cana-1177	192	2	formula	formula	NOUN
cana-1177	192	3	for	for	ADP
cana-1177	192	4	standard	standard	ADJ
cana-1177	192	5	scaling	scaling	NOUN
cana-1177	192	6	(	(	PUNCT
cana-1177	192	7	z	z	NOUN
cana-1177	192	8	-	-	PUNCT
cana-1177	192	9	score	score	NOUN
cana-1177	192	10	normalization	normalization	NOUN
cana-1177	192	11	)	)	PUNCT
cana-1177	192	12	applied	apply	VERB
cana-1177	192	13	by	by	ADP
cana-1177	192	14	standardscaler	standardscaler	NOUN
cana-1177	192	15	is	be	AUX
cana-1177	192	16	:	:	PUNCT
cana-1177	192	17	𝑥′	𝑥′	PUNCT
cana-1177	192	18	=	=	PUNCT
cana-1177	193	1	𝑥	𝑥	DET
cana-1177	193	2	−	−	NOUN
cana-1177	193	3	𝜇	𝜇	ADP
cana-1177	193	4	𝜎	𝜎	X
cana-1177	193	5	(	(	PUNCT
cana-1177	193	6	1	1	NUM
cana-1177	193	7	)	)	PUNCT
cana-1177	193	8	where	where	SCONJ
cana-1177	193	9	x′	x′	PROPN
cana-1177	193	10	is	be	AUX
cana-1177	193	11	the	the	DET
cana-1177	193	12	feature	feature	NOUN
cana-1177	193	13	's	's	PART
cana-1177	193	14	standardized	standardized	ADJ
cana-1177	193	15	value	value	NOUN
cana-1177	193	16	,	,	PUNCT
cana-1177	193	17	x	x	X
cana-1177	193	18	is	be	AUX
cana-1177	193	19	the	the	DET
cana-1177	193	20	feature	feature	NOUN
cana-1177	193	21	's	's	PART
cana-1177	193	22	original	original	ADJ
cana-1177	193	23	value	value	NOUN
cana-1177	193	24	,	,	PUNCT
cana-1177	193	25	μ	μ	PROPN
cana-1177	193	26	is	be	AUX
cana-1177	193	27	the	the	DET
cana-1177	193	28	feature	feature	NOUN
cana-1177	193	29	values	value	NOUN
cana-1177	193	30	'	'	PART
cana-1177	193	31	mean	mean	NOUN
cana-1177	193	32	,	,	PUNCT
cana-1177	193	33	and	and	CCONJ
cana-1177	193	34	σ	σ	PROPN
cana-1177	193	35	is	be	AUX
cana-1177	193	36	their	their	PRON
cana-1177	193	37	standard	standard	ADJ
cana-1177	193	38	deviation	deviation	NOUN
cana-1177	193	39	.	.	PUNCT
cana-1177	194	1	communications	communication	NOUN
cana-1177	194	2	on	on	ADP
cana-1177	194	3	applied	apply	VERB
cana-1177	194	4	nonlinear	nonlinear	ADJ
cana-1177	194	5	analysis	analysis	NOUN
cana-1177	194	6	issn	issn	NOUN
cana-1177	194	7	:	:	PUNCT
cana-1177	194	8	1074	1074	NUM
cana-1177	194	9	-	-	PUNCT
cana-1177	194	10	133x	133x	NUM
cana-1177	194	11	vol	vol	NOUN
cana-1177	194	12	31	31	NUM
cana-1177	194	13	no	no	NOUN
cana-1177	194	14	.	.	PUNCT
cana-1177	195	1	6s	6s	NUM
cana-1177	195	2	(	(	PUNCT
cana-1177	195	3	2024	2024	NUM
cana-1177	195	4	)	)	PUNCT
cana-1177	195	5	187	187	NUM
cana-1177	195	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-1177	195	7	3.2	3.2	NUM
cana-1177	195	8	.	.	PUNCT
cana-1177	196	1	classification	classification	NOUN
cana-1177	196	2	models	model	NOUN
cana-1177	196	3	3.2.1	3.2.1	NUM
cana-1177	196	4	.	.	PUNCT
cana-1177	197	1	logistic	logistic	ADJ
cana-1177	197	2	regression	regression	NOUN
cana-1177	197	3	the	the	DET
cana-1177	197	4	algorithm	algorithm	NOUN
cana-1177	197	5	for	for	ADP
cana-1177	197	6	classification	classification	NOUN
cana-1177	197	7	lr	lr	NOUN
cana-1177	197	8	is	be	AUX
cana-1177	197	9	an	an	DET
cana-1177	197	10	approach	approach	NOUN
cana-1177	197	11	to	to	ADP
cana-1177	197	12	supervised	supervised	ADJ
cana-1177	197	13	learning	learning	NOUN
cana-1177	197	14	.	.	PUNCT
cana-1177	198	1	this	this	DET
cana-1177	198	2	method	method	NOUN
cana-1177	198	3	predicts	predict	VERB
cana-1177	198	4	the	the	DET
cana-1177	198	5	probability	probability	NOUN
cana-1177	198	6	of	of	ADP
cana-1177	198	7	a	a	DET
cana-1177	198	8	dichotomous	dichotomous	ADJ
cana-1177	198	9	target	target	NOUN
cana-1177	198	10	(	(	PUNCT
cana-1177	198	11	dependent	dependent	ADJ
cana-1177	198	12	)	)	PUNCT
cana-1177	198	13	variable	variable	NOUN
cana-1177	198	14	.	.	PUNCT
cana-1177	199	1	after	after	ADP
cana-1177	199	2	the	the	DET
cana-1177	199	3	computation	computation	NOUN
cana-1177	199	4	it	it	PRON
cana-1177	199	5	yields	yield	VERB
cana-1177	199	6	probabilistic	probabilistic	ADJ
cana-1177	199	7	values	value	NOUN
cana-1177	199	8	between	between	ADP
cana-1177	199	9	0	0	NUM
cana-1177	199	10	and	and	CCONJ
cana-1177	199	11	1	1	NUM
cana-1177	199	12	.	.	X
cana-1177	200	1	these	these	DET
cana-1177	200	2	probabilistic	probabilistic	ADJ
cana-1177	200	3	values	value	NOUN
cana-1177	200	4	are	be	AUX
cana-1177	200	5	the	the	DET
cana-1177	200	6	basis	basis	NOUN
cana-1177	200	7	for	for	ADP
cana-1177	200	8	the	the	DET
cana-1177	200	9	categorization	categorization	NOUN
cana-1177	200	10	that	that	PRON
cana-1177	200	11	the	the	DET
cana-1177	200	12	algorithm	algorithm	NOUN
cana-1177	200	13	uses	use	VERB
cana-1177	200	14	.	.	PUNCT
cana-1177	201	1	in	in	ADP
cana-1177	201	2	cases	case	NOUN
cana-1177	201	3	when	when	SCONJ
cana-1177	201	4	the	the	DET
cana-1177	201	5	technique	technique	NOUN
cana-1177	201	6	makes	make	VERB
cana-1177	201	7	use	use	NOUN
cana-1177	201	8	of	of	ADP
cana-1177	201	9	a	a	DET
cana-1177	201	10	sigmoid	sigmoid	NOUN
cana-1177	201	11	function	function	NOUN
cana-1177	201	12	(	(	PUNCT
cana-1177	201	13	0	0	NUM
cana-1177	201	14	=	=	SYM
cana-1177	201	15	output>=1	output>=1	NUM
cana-1177	201	16	)	)	PUNCT
cana-1177	201	17	,	,	PUNCT
cana-1177	201	18	lr	lr	NOUN
cana-1177	201	19	and	and	CCONJ
cana-1177	201	20	linear	linear	PROPN
cana-1177	201	21	regression	regression	NOUN
cana-1177	201	22	are	be	AUX
cana-1177	201	23	quite	quite	ADV
cana-1177	201	24	comparable	comparable	ADJ
cana-1177	201	25	.	.	PUNCT
cana-1177	202	1	the	the	DET
cana-1177	202	2	only	only	ADJ
cana-1177	202	3	thing	thing	NOUN
cana-1177	202	4	that	that	PRON
cana-1177	202	5	differs	differ	VERB
cana-1177	202	6	is	be	AUX
cana-1177	202	7	the	the	DET
cana-1177	202	8	hypothesis	hypothesis	NOUN
cana-1177	202	9	function	function	NOUN
cana-1177	202	10	;	;	PUNCT
cana-1177	202	11	however	however	ADV
cana-1177	202	12	,	,	PUNCT
cana-1177	202	13	a	a	DET
cana-1177	202	14	regression	regression	NOUN
cana-1177	202	15	function	function	NOUN
cana-1177	202	16	(	(	PUNCT
cana-1177	202	17	-∞<=output>=∞	-∞<=output>=∞	NUM
cana-1177	202	18	)	)	PUNCT
cana-1177	202	19	is	be	AUX
cana-1177	202	20	used	use	VERB
cana-1177	202	21	.	.	PUNCT
cana-1177	203	1	consequently	consequently	ADV
cana-1177	203	2	,	,	PUNCT
cana-1177	203	3	they	they	PRON
cana-1177	203	4	have	have	VERB
cana-1177	203	5	a	a	DET
cana-1177	203	6	variety	variety	NOUN
cana-1177	203	7	of	of	ADP
cana-1177	203	8	uses	use	NOUN
cana-1177	203	9	the	the	DET
cana-1177	203	10	former	former	ADJ
cana-1177	203	11	is	be	AUX
cana-1177	203	12	employed	employ	VERB
cana-1177	203	13	in	in	ADP
cana-1177	203	14	regression	regression	NOUN
cana-1177	203	15	,	,	PUNCT
cana-1177	203	16	while	while	SCONJ
cana-1177	203	17	the	the	DET
cana-1177	203	18	latter	latter	ADJ
cana-1177	203	19	is	be	AUX
cana-1177	203	20	used	use	VERB
cana-1177	203	21	in	in	ADP
cana-1177	203	22	classification	classification	NOUN
cana-1177	203	23	.	.	PUNCT
cana-1177	204	1	it	it	PRON
cana-1177	204	2	helps	help	VERB
cana-1177	204	3	understand	understand	VERB
cana-1177	204	4	dependent	dependent	ADJ
cana-1177	204	5	and	and	CCONJ
cana-1177	204	6	independent	independent	ADJ
cana-1177	204	7	variables	variable	NOUN
cana-1177	204	8	in	in	ADP
cana-1177	204	9	data	data	NOUN
cana-1177	204	10	analysis	analysis	NOUN
cana-1177	204	11	[	[	X
cana-1177	204	12	15	15	NUM
cana-1177	204	13	]	]	PUNCT
cana-1177	204	14	.	.	PUNCT
cana-1177	205	1	𝑃	𝑃	NOUN
cana-1177	205	2	=	=	SYM
cana-1177	205	3	𝑒𝑎+𝑏𝑋	𝑒𝑎+𝑏𝑋	NOUN
cana-1177	205	4	1	1	NUM
cana-1177	205	5	+	+	NUM
cana-1177	205	6	𝑒𝑎+𝑏𝑋	𝑒𝑎+𝑏𝑋	NOUN
cana-1177	205	7	(	(	PUNCT
cana-1177	205	8	2	2	NUM
cana-1177	205	9	)	)	PUNCT
cana-1177	205	10	where	where	SCONJ
cana-1177	205	11	a	a	PRON
cana-1177	205	12	is	be	AUX
cana-1177	205	13	the	the	DET
cana-1177	205	14	biased	biased	ADJ
cana-1177	205	15	or	or	CCONJ
cana-1177	205	16	intercept	intercept	NOUN
cana-1177	205	17	component	component	NOUN
cana-1177	205	18	,	,	PUNCT
cana-1177	205	19	b	b	PROPN
cana-1177	205	20	is	be	AUX
cana-1177	205	21	the	the	DET
cana-1177	205	22	coefficient	coefficient	NOUN
cana-1177	205	23	,	,	PUNCT
cana-1177	205	24	and	and	CCONJ
cana-1177	205	25	p	p	NOUN
cana-1177	205	26	is	be	AUX
cana-1177	205	27	the	the	DET
cana-1177	205	28	expected	expect	VERB
cana-1177	205	29	output	output	NOUN
cana-1177	205	30	for	for	ADP
cana-1177	205	31	a	a	DET
cana-1177	205	32	given	give	VERB
cana-1177	205	33	input	input	NOUN
cana-1177	205	34	value	value	NOUN
cana-1177	205	35	(	(	PUNCT
cana-1177	205	36	x	x	NOUN
cana-1177	205	37	)	)	PUNCT
cana-1177	205	38	.	.	PUNCT
cana-1177	206	1	3.2.2	3.2.2	X
cana-1177	206	2	.	.	PUNCT
cana-1177	207	1	svm	svm	VERB
cana-1177	207	2	strong	strong	ADJ
cana-1177	207	3	supervised	supervised	ADJ
cana-1177	207	4	learning	learn	VERB
cana-1177	207	5	algorithms	algorithm	NOUN
cana-1177	207	6	like	like	ADP
cana-1177	207	7	svm	svm	PROPN
cana-1177	207	8	are	be	AUX
cana-1177	207	9	employed	employ	VERB
cana-1177	207	10	for	for	ADP
cana-1177	207	11	both	both	PRON
cana-1177	207	12	regression	regression	NOUN
cana-1177	207	13	and	and	CCONJ
cana-1177	207	14	classification	classification	NOUN
cana-1177	207	15	problems	problem	NOUN
cana-1177	207	16	.	.	PUNCT
cana-1177	208	1	finding	find	VERB
cana-1177	208	2	the	the	DET
cana-1177	208	3	hyperplane	hyperplane	NOUN
cana-1177	208	4	that	that	PRON
cana-1177	208	5	optimally	optimally	ADV
cana-1177	208	6	divides	divide	VERB
cana-1177	208	7	the	the	DET
cana-1177	208	8	data	datum	NOUN
cana-1177	208	9	into	into	ADP
cana-1177	208	10	classes	class	NOUN
cana-1177	208	11	while	while	SCONJ
cana-1177	208	12	optimizing	optimize	VERB
cana-1177	208	13	the	the	DET
cana-1177	208	14	margin	margin	NOUN
cana-1177	208	15	between	between	ADP
cana-1177	208	16	them	they	PRON
cana-1177	208	17	is	be	AUX
cana-1177	208	18	the	the	DET
cana-1177	208	19	main	main	ADJ
cana-1177	208	20	goal	goal	NOUN
cana-1177	208	21	of	of	ADP
cana-1177	208	22	support	support	NOUN
cana-1177	208	23	vector	vector	NOUN
cana-1177	208	24	machines	machine	NOUN
cana-1177	208	25	(	(	PUNCT
cana-1177	208	26	svm	svm	PROPN
cana-1177	208	27	)	)	PUNCT
cana-1177	208	28	.	.	PUNCT
cana-1177	209	1	svm	svm	PROPN
cana-1177	209	2	determines	determine	VERB
cana-1177	209	3	the	the	DET
cana-1177	209	4	best	good	ADJ
cana-1177	209	5	hyperplane	hyperplane	NOUN
cana-1177	209	6	that	that	PRON
cana-1177	209	7	maximizes	maximize	VERB
cana-1177	209	8	the	the	DET
cana-1177	209	9	margin	margin	NOUN
cana-1177	209	10	that	that	PRON
cana-1177	209	11	is	be	AUX
cana-1177	209	12	,	,	PUNCT
cana-1177	209	13	the	the	DET
cana-1177	209	14	separation	separation	NOUN
cana-1177	209	15	between	between	ADP
cana-1177	209	16	the	the	DET
cana-1177	209	17	nearest	near	ADJ
cana-1177	209	18	data	data	NOUN
cana-1177	209	19	points	point	NOUN
cana-1177	209	20	(	(	PUNCT
cana-1177	209	21	support	support	NOUN
cana-1177	209	22	vectors	vector	NOUN
cana-1177	209	23	)	)	PUNCT
cana-1177	209	24	and	and	CCONJ
cana-1177	209	25	the	the	DET
cana-1177	209	26	hyperplane	hyperplane	NOUN
cana-1177	209	27	from	from	ADP
cana-1177	209	28	each	each	DET
cana-1177	209	29	class	class	NOUN
cana-1177	209	30	when	when	SCONJ
cana-1177	209	31	the	the	DET
cana-1177	209	32	data	data	NOUN
cana-1177	209	33	is	be	AUX
cana-1177	209	34	linearly	linearly	ADV
cana-1177	209	35	separable	separable	ADJ
cana-1177	209	36	[	[	X
cana-1177	209	37	16	16	NUM
cana-1177	209	38	]	]	PUNCT
cana-1177	209	39	.	.	PUNCT
cana-1177	210	1	the	the	DET
cana-1177	210	2	decision	decision	NOUN
cana-1177	210	3	boundary	boundary	ADJ
cana-1177	210	4	(	(	PUNCT
cana-1177	210	5	hyperplane	hyperplane	NOUN
cana-1177	210	6	)	)	PUNCT
cana-1177	210	7	of	of	ADP
cana-1177	210	8	svm	svm	PROPN
cana-1177	210	9	may	may	AUX
cana-1177	210	10	be	be	AUX
cana-1177	210	11	expressed	express	VERB
cana-1177	210	12	mathematically	mathematically	ADV
cana-1177	210	13	as	as	SCONJ
cana-1177	210	14	follows	follow	VERB
cana-1177	210	15	:	:	PUNCT
cana-1177	210	16	𝑤𝑇𝑥	𝑤𝑇𝑥	X
cana-1177	210	17	+	+	PUNCT
cana-1177	210	18	𝑏	𝑏	NOUN
cana-1177	210	19	=	=	SYM
cana-1177	210	20	0	0	NUM
cana-1177	210	21	(	(	PUNCT
cana-1177	210	22	3	3	NUM
cana-1177	210	23	)	)	PUNCT
cana-1177	210	24	where	where	SCONJ
cana-1177	210	25	x	x	PRON
cana-1177	210	26	is	be	AUX
cana-1177	210	27	the	the	DET
cana-1177	210	28	input	input	NOUN
cana-1177	210	29	feature	feature	NOUN
cana-1177	210	30	vector	vector	NOUN
cana-1177	210	31	,	,	PUNCT
cana-1177	210	32	b	b	PROPN
cana-1177	210	33	is	be	AUX
cana-1177	210	34	the	the	DET
cana-1177	210	35	bias	bias	NOUN
cana-1177	210	36	term	term	NOUN
cana-1177	210	37	,	,	PUNCT
cana-1177	210	38	and	and	CCONJ
cana-1177	210	39	wt	wt	ADP
cana-1177	210	40	stands	stand	VERB
cana-1177	210	41	for	for	ADP
cana-1177	210	42	the	the	DET
cana-1177	210	43	transpose	transpose	NOUN
cana-1177	210	44	of	of	ADP
cana-1177	210	45	w.	w.	PROPN
cana-1177	210	46	w	w	PROPN
cana-1177	210	47	is	be	AUX
cana-1177	210	48	the	the	DET
cana-1177	210	49	weight	weight	NOUN
cana-1177	210	50	vector	vector	NOUN
cana-1177	210	51	perpendicular	perpendicular	NOUN
cana-1177	210	52	to	to	ADP
cana-1177	210	53	the	the	DET
cana-1177	210	54	hyperplane	hyperplane	NOUN
cana-1177	210	55	.	.	PUNCT
cana-1177	211	1	3.2.3	3.2.3	X
cana-1177	211	2	.	.	X
cana-1177	211	3	decision	decision	NOUN
cana-1177	211	4	tree	tree	NOUN
cana-1177	211	5	dt	dt	PROPN
cana-1177	211	6	classifier	classifier	PROPN
cana-1177	211	7	is	be	AUX
cana-1177	211	8	a	a	DET
cana-1177	211	9	ml	ml	NOUN
cana-1177	211	10	method	method	NOUN
cana-1177	211	11	for	for	ADP
cana-1177	211	12	classification	classification	NOUN
cana-1177	211	13	.	.	PUNCT
cana-1177	212	1	with	with	ADP
cana-1177	212	2	the	the	DET
cana-1177	212	3	help	help	NOUN
cana-1177	212	4	of	of	ADP
cana-1177	212	5	this	this	DET
cana-1177	212	6	approach	approach	NOUN
cana-1177	212	7	different	different	ADJ
cana-1177	212	8	classes	class	NOUN
cana-1177	212	9	may	may	AUX
cana-1177	212	10	be	be	AUX
cana-1177	212	11	classified	classify	VERB
cana-1177	212	12	using	use	VERB
cana-1177	212	13	a	a	DET
cana-1177	212	14	tree	tree	NOUN
cana-1177	212	15	structure	structure	NOUN
cana-1177	212	16	called	call	VERB
cana-1177	212	17	a	a	DET
cana-1177	212	18	decision	decision	NOUN
cana-1177	212	19	tree	tree	NOUN
cana-1177	212	20	(	(	PUNCT
cana-1177	212	21	dt	dt	NOUN
cana-1177	212	22	)	)	PUNCT
cana-1177	212	23	in	in	ADP
cana-1177	212	24	which	which	PRON
cana-1177	212	25	each	each	DET
cana-1177	212	26	leaf	leaf	NOUN
cana-1177	212	27	node	node	NOUN
cana-1177	212	28	symbolizes	symbolize	VERB
cana-1177	212	29	the	the	DET
cana-1177	212	30	class	class	NOUN
cana-1177	212	31	that	that	SCONJ
cana-1177	212	32	the	the	DET
cana-1177	212	33	decision	decision	NOUN
cana-1177	212	34	represents	represent	VERB
cana-1177	212	35	,	,	PUNCT
cana-1177	212	36	internal	internal	ADJ
cana-1177	212	37	(	(	PUNCT
cana-1177	212	38	decision	decision	NOUN
cana-1177	212	39	)	)	PUNCT
cana-1177	212	40	nodes	node	NOUN
cana-1177	212	41	reflect	reflect	VERB
cana-1177	212	42	attributes	attribute	NOUN
cana-1177	212	43	of	of	ADP
cana-1177	212	44	a	a	DET
cana-1177	212	45	dataset	dataset	NOUN
cana-1177	212	46	that	that	PRON
cana-1177	212	47	is	be	AUX
cana-1177	212	48	used	use	VERB
cana-1177	212	49	to	to	PART
cana-1177	212	50	make	make	VERB
cana-1177	212	51	any	any	DET
cana-1177	212	52	choice	choice	NOUN
cana-1177	212	53	,	,	PUNCT
cana-1177	212	54	and	and	CCONJ
cana-1177	212	55	branches	branch	NOUN
cana-1177	212	56	indicate	indicate	VERB
cana-1177	212	57	decision	decision	NOUN
cana-1177	212	58	rules	rule	NOUN
cana-1177	212	59	.	.	PUNCT
cana-1177	213	1	in	in	ADP
cana-1177	213	2	essence	essence	NOUN
cana-1177	213	3	a	a	DET
cana-1177	213	4	dt	dt	NOUN
cana-1177	213	5	poses	pose	VERB
cana-1177	213	6	a	a	DET
cana-1177	213	7	question	question	NOUN
cana-1177	213	8	and	and	CCONJ
cana-1177	213	9	divides	divide	VERB
cana-1177	213	10	the	the	DET
cana-1177	213	11	tree	tree	NOUN
cana-1177	213	12	into	into	ADP
cana-1177	213	13	subtrees	subtree	NOUN
cana-1177	213	14	according	accord	VERB
cana-1177	213	15	to	to	ADP
cana-1177	213	16	the	the	DET
cana-1177	213	17	answer	answer	NOUN
cana-1177	213	18	(	(	PUNCT
cana-1177	213	19	yes	yes	INTJ
cana-1177	213	20	/	/	SYM
cana-1177	213	21	no	no	NOUN
cana-1177	213	22	)	)	PUNCT
cana-1177	213	23	.	.	PUNCT
cana-1177	214	1	they	they	PRON
cana-1177	214	2	offer	offer	VERB
cana-1177	214	3	a	a	DET
cana-1177	214	4	strong	strong	ADJ
cana-1177	214	5	framework	framework	NOUN
cana-1177	214	6	for	for	ADP
cana-1177	214	7	weighing	weigh	VERB
cana-1177	214	8	your	your	PRON
cana-1177	214	9	alternatives	alternative	NOUN
cana-1177	214	10	.	.	PUNCT
cana-1177	215	1	entropy	entropy	PROPN
cana-1177	215	2	is	be	AUX
cana-1177	215	3	a	a	DET
cana-1177	215	4	suitable	suitable	ADJ
cana-1177	215	5	term	term	NOUN
cana-1177	215	6	to	to	PART
cana-1177	215	7	represent	represent	VERB
cana-1177	215	8	the	the	DET
cana-1177	215	9	amount	amount	NOUN
cana-1177	215	10	of	of	ADP
cana-1177	215	11	data	datum	NOUN
cana-1177	215	12	required	require	VERB
cana-1177	215	13	to	to	PART
cana-1177	215	14	characterize	characterize	VERB
cana-1177	215	15	a	a	DET
cana-1177	215	16	sample	sample	NOUN
cana-1177	215	17	.	.	PUNCT
cana-1177	216	1	thus	thus	ADV
cana-1177	216	2	,	,	PUNCT
cana-1177	216	3	the	the	DET
cana-1177	216	4	entropy	entropy	NOUN
cana-1177	216	5	is	be	AUX
cana-1177	216	6	maximal	maximal	ADJ
cana-1177	216	7	when	when	SCONJ
cana-1177	216	8	the	the	DET
cana-1177	216	9	sample	sample	NOUN
cana-1177	216	10	is	be	AUX
cana-1177	216	11	evenly	evenly	ADV
cana-1177	216	12	split	split	ADJ
cana-1177	216	13	;	;	PUNCT
cana-1177	216	14	otherwise	otherwise	ADV
cana-1177	216	15	,	,	PUNCT
cana-1177	216	16	it	it	PRON
cana-1177	216	17	is	be	AUX
cana-1177	216	18	zero	zero	NUM
cana-1177	216	19	if	if	SCONJ
cana-1177	216	20	the	the	DET
cana-1177	216	21	sample	sample	NOUN
cana-1177	216	22	is	be	AUX
cana-1177	216	23	homogenous	homogenous	ADJ
cana-1177	216	24	meaning	meaning	NOUN
cana-1177	216	25	that	that	SCONJ
cana-1177	216	26	all	all	PRON
cana-1177	216	27	of	of	ADP
cana-1177	216	28	the	the	DET
cana-1177	216	29	elements	element	NOUN
cana-1177	216	30	are	be	AUX
cana-1177	216	31	similar	similar	ADJ
cana-1177	216	32	[	[	X
cana-1177	216	33	15	15	NUM
cana-1177	216	34	]	]	PUNCT
cana-1177	216	35	.	.	PUNCT
cana-1177	217	1	at	at	ADP
cana-1177	217	2	each	each	DET
cana-1177	217	3	node	node	NOUN
cana-1177	217	4	m	m	NOUN
cana-1177	217	5	of	of	ADP
cana-1177	217	6	the	the	DET
cana-1177	217	7	tree	tree	NOUN
cana-1177	217	8	,	,	PUNCT
cana-1177	217	9	a	a	DET
cana-1177	217	10	decision	decision	NOUN
cana-1177	217	11	function	function	NOUN
cana-1177	217	12	fm(x	fm(x	PUNCT
cana-1177	217	13	)	)	PUNCT
cana-1177	217	14	is	be	AUX
cana-1177	217	15	applied	apply	VERB
cana-1177	217	16	to	to	PART
cana-1177	217	17	determine	determine	VERB
cana-1177	217	18	the	the	DET
cana-1177	217	19	splitting	splitting	NOUN
cana-1177	217	20	criterion	criterion	NOUN
cana-1177	217	21	based	base	VERB
cana-1177	217	22	on	on	ADP
cana-1177	217	23	a	a	DET
cana-1177	217	24	feature	feature	NOUN
cana-1177	217	25	xj	xj	PROPN
cana-1177	217	26	and	and	CCONJ
cana-1177	217	27	a	a	DET
cana-1177	217	28	threshold	threshold	NOUN
cana-1177	217	29	t	t	PROPN
cana-1177	217	30	,	,	PUNCT
cana-1177	217	31	such	such	ADJ
cana-1177	217	32	that	that	PRON
cana-1177	217	33	:	:	PUNCT
cana-1177	217	34	𝑓𝑚(𝑥	𝑓𝑚(𝑥	NUM
cana-1177	217	35	)	)	PUNCT
cana-1177	217	36	=	=	PRON
cana-1177	217	37	{	{	PUNCT
cana-1177	217	38	1	1	NUM
cana-1177	217	39	,	,	PUNCT
cana-1177	217	40	𝑖𝑓	𝑖𝑓	NOUN
cana-1177	217	41	𝑥𝑗	𝑥𝑗	PROPN
cana-1177	217	42	≤	≤	NUM
cana-1177	217	43	𝑡	𝑡	X
cana-1177	217	44	0	0	NUM
cana-1177	217	45	,	,	PUNCT
cana-1177	217	46	𝑜𝑡ℎ𝑒𝑟𝑤𝑖𝑠𝑒	𝑜𝑡ℎ𝑒𝑟𝑤𝑖𝑠𝑒	NOUN
cana-1177	217	47	(	(	PUNCT
cana-1177	217	48	4	4	NUM
cana-1177	217	49	)	)	PUNCT
cana-1177	217	50	where	where	SCONJ
cana-1177	217	51	j	j	PROPN
cana-1177	217	52	and	and	CCONJ
cana-1177	217	53	t	t	PROPN
cana-1177	217	54	are	be	AUX
cana-1177	217	55	chosen	choose	VERB
cana-1177	217	56	to	to	PART
cana-1177	217	57	maximize	maximize	VERB
cana-1177	217	58	the	the	DET
cana-1177	217	59	information	information	NOUN
cana-1177	217	60	gain	gain	NOUN
cana-1177	217	61	or	or	CCONJ
cana-1177	217	62	minimize	minimize	VERB
cana-1177	217	63	impurity	impurity	NOUN
cana-1177	217	64	.	.	PUNCT
cana-1177	218	1	communications	communication	NOUN
cana-1177	218	2	on	on	ADP
cana-1177	218	3	applied	apply	VERB
cana-1177	218	4	nonlinear	nonlinear	ADJ
cana-1177	218	5	analysis	analysis	NOUN
cana-1177	218	6	issn	issn	NOUN
cana-1177	218	7	:	:	PUNCT
cana-1177	218	8	1074	1074	NUM
cana-1177	218	9	-	-	PUNCT
cana-1177	218	10	133x	133x	NUM
cana-1177	218	11	vol	vol	NOUN
cana-1177	218	12	31	31	NUM
cana-1177	218	13	no	no	NOUN
cana-1177	218	14	.	.	PUNCT
cana-1177	219	1	6s	6s	NUM
cana-1177	219	2	(	(	PUNCT
cana-1177	219	3	2024	2024	NUM
cana-1177	219	4	)	)	PUNCT
cana-1177	219	5	188	188	NUM
cana-1177	219	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-1177	219	7	3.2.4	3.2.4	NUM
cana-1177	219	8	.	.	PUNCT
cana-1177	220	1	voting	vote	VERB
cana-1177	220	2	classifier	classifier	NOUN
cana-1177	220	3	a	a	DET
cana-1177	220	4	voting	voting	NOUN
cana-1177	220	5	classifier	classifier	NOUN
cana-1177	220	6	is	be	AUX
cana-1177	220	7	a	a	DET
cana-1177	220	8	technique	technique	NOUN
cana-1177	220	9	for	for	ADP
cana-1177	220	10	group	group	NOUN
cana-1177	220	11	learning	learning	NOUN
cana-1177	220	12	that	that	PRON
cana-1177	220	13	generates	generate	VERB
cana-1177	220	14	a	a	DET
cana-1177	220	15	final	final	ADJ
cana-1177	220	16	prediction	prediction	NOUN
cana-1177	220	17	by	by	ADP
cana-1177	220	18	aggregating	aggregate	VERB
cana-1177	220	19	the	the	DET
cana-1177	220	20	predictions	prediction	NOUN
cana-1177	220	21	of	of	ADP
cana-1177	220	22	several	several	ADJ
cana-1177	220	23	different	different	ADJ
cana-1177	220	24	classifiers	classifier	NOUN
cana-1177	220	25	.	.	PUNCT
cana-1177	221	1	working	work	VERB
cana-1177	221	2	on	on	ADP
cana-1177	221	3	the	the	DET
cana-1177	221	4	basis	basis	NOUN
cana-1177	221	5	of	of	ADP
cana-1177	221	6	"	"	PUNCT
cana-1177	221	7	majority	majority	NOUN
cana-1177	221	8	voting	voting	NOUN
cana-1177	221	9	,	,	PUNCT
cana-1177	221	10	"	"	PUNCT
cana-1177	221	11	the	the	DET
cana-1177	221	12	projected	project	VERB
cana-1177	221	13	class	class	NOUN
cana-1177	221	14	is	be	AUX
cana-1177	221	15	determined	determine	VERB
cana-1177	221	16	by	by	ADP
cana-1177	221	17	tallying	tally	VERB
cana-1177	221	18	the	the	DET
cana-1177	221	19	votes	vote	NOUN
cana-1177	221	20	cast	cast	VERB
cana-1177	221	21	for	for	ADP
cana-1177	221	22	each	each	DET
cana-1177	221	23	classifier	classifier	NOUN
cana-1177	221	24	with	with	ADP
cana-1177	221	25	each	each	DET
cana-1177	221	26	prediction	prediction	NOUN
cana-1177	221	27	helping	help	VERB
cana-1177	221	28	to	to	PART
cana-1177	221	29	shape	shape	VERB
cana-1177	221	30	the	the	DET
cana-1177	221	31	final	final	ADJ
cana-1177	221	32	result	result	NOUN
cana-1177	221	33	.	.	PUNCT
cana-1177	222	1	voting	voting	NOUN
cana-1177	222	2	classifiers	classifier	NOUN
cana-1177	222	3	come	come	VERB
cana-1177	222	4	in	in	ADP
cana-1177	222	5	two	two	NUM
cana-1177	222	6	varieties	variety	NOUN
cana-1177	222	7	:	:	PUNCT
cana-1177	222	8	soft	soft	ADJ
cana-1177	222	9	voting	voting	NOUN
cana-1177	222	10	and	and	CCONJ
cana-1177	222	11	harsh	harsh	ADJ
cana-1177	222	12	voting	voting	NOUN
cana-1177	222	13	.	.	PUNCT
cana-1177	223	1	in	in	ADP
cana-1177	223	2	hard	hard	ADJ
cana-1177	223	3	voting	voting	NOUN
cana-1177	223	4	the	the	DET
cana-1177	223	5	class	class	NOUN
cana-1177	223	6	that	that	PRON
cana-1177	223	7	receives	receive	VERB
cana-1177	223	8	the	the	DET
cana-1177	223	9	most	most	ADJ
cana-1177	223	10	votes	vote	NOUN
cana-1177	223	11	is	be	AUX
cana-1177	223	12	the	the	DET
cana-1177	223	13	winner	winner	NOUN
cana-1177	223	14	and	and	CCONJ
cana-1177	223	15	in	in	ADP
cana-1177	223	16	soft	soft	ADJ
cana-1177	223	17	voting	voting	NOUN
cana-1177	223	18	the	the	DET
cana-1177	223	19	class	class	NOUN
cana-1177	223	20	that	that	PRON
cana-1177	223	21	receives	receive	VERB
cana-1177	223	22	the	the	DET
cana-1177	223	23	greatest	great	ADJ
cana-1177	223	24	average	average	ADJ
cana-1177	223	25	probability	probability	NOUN
cana-1177	223	26	is	be	AUX
cana-1177	223	27	determined	determine	VERB
cana-1177	223	28	by	by	ADP
cana-1177	223	29	averaging	average	VERB
cana-1177	223	30	the	the	DET
cana-1177	223	31	class	class	NOUN
cana-1177	223	32	probabilities	probability	NOUN
cana-1177	223	33	predicted	predict	VERB
cana-1177	223	34	by	by	ADP
cana-1177	223	35	each	each	DET
cana-1177	223	36	classifier	classifier	NOUN
cana-1177	223	37	[	[	X
cana-1177	223	38	8	8	NUM
cana-1177	223	39	]	]	PUNCT
cana-1177	223	40	.	.	PUNCT
cana-1177	224	1	the	the	DET
cana-1177	224	2	prediction	prediction	NOUN
cana-1177	224	3	of	of	ADP
cana-1177	224	4	a	a	DET
cana-1177	224	5	voting	voting	NOUN
cana-1177	224	6	classifier	classifier	NOUN
cana-1177	224	7	may	may	AUX
cana-1177	224	8	be	be	AUX
cana-1177	224	9	expressed	express	VERB
cana-1177	224	10	mathematically	mathematically	ADV
cana-1177	224	11	as	as	SCONJ
cana-1177	224	12	follows	follow	VERB
cana-1177	224	13	:	:	PUNCT
cana-1177	224	14	ŷ	ŷ	NUM
cana-1177	224	15	=	=	PUNCT
cana-1177	224	16	𝑎𝑟𝑔𝑚𝑎𝑥𝑖	𝑎𝑟𝑔𝑚𝑎𝑥𝑖	VERB
cana-1177	224	17	∑	∑	PROPN
cana-1177	224	18	𝑃𝑖𝑗	𝑃𝑖𝑗	PROPN
cana-1177	224	19	(	(	PUNCT
cana-1177	224	20	5)𝑀	5)𝑀	NUM
cana-1177	224	21	𝑗=1	𝑗=1	PROPN
cana-1177	224	22	where	where	SCONJ
cana-1177	224	23	:	:	PUNCT
cana-1177	224	24	ŷ	ŷ	NUM
cana-1177	224	25	is	be	AUX
cana-1177	224	26	the	the	DET
cana-1177	224	27	predicted	predict	VERB
cana-1177	224	28	class	class	NOUN
cana-1177	224	29	,	,	PUNCT
cana-1177	224	30	m	m	VERB
cana-1177	224	31	is	be	AUX
cana-1177	224	32	the	the	DET
cana-1177	224	33	number	number	NOUN
cana-1177	224	34	of	of	ADP
cana-1177	224	35	classifiers	classifier	NOUN
cana-1177	224	36	,	,	PUNCT
cana-1177	224	37	pij	pij	NOUN
cana-1177	224	38	is	be	AUX
cana-1177	224	39	the	the	DET
cana-1177	224	40	probability	probability	NOUN
cana-1177	224	41	predicted	predict	VERB
cana-1177	224	42	by	by	ADP
cana-1177	224	43	the	the	DET
cana-1177	224	44	ith	ith	PROPN
cana-1177	224	45	classifier	classifier	NOUN
cana-1177	224	46	for	for	ADP
cana-1177	224	47	class	class	NOUN
cana-1177	224	48	j.	j.	PROPN
cana-1177	224	49	3.3	3.3	NUM
cana-1177	224	50	.	.	PUNCT
cana-1177	225	1	performance	performance	NOUN
cana-1177	225	2	measures	measure	NOUN
cana-1177	225	3	five	five	NUM
cana-1177	225	4	cross	cross	ADJ
cana-1177	225	5	-	-	ADJ
cana-1177	225	6	validation	validation	ADJ
cana-1177	225	7	matrices	matrix	NOUN
cana-1177	225	8	are	be	AUX
cana-1177	225	9	evaluated	evaluate	VERB
cana-1177	225	10	in	in	ADP
cana-1177	225	11	this	this	DET
cana-1177	225	12	study	study	NOUN
cana-1177	225	13	:	:	PUNCT
cana-1177	225	14	accuracy	accuracy	NOUN
cana-1177	225	15	,	,	PUNCT
cana-1177	225	16	recall	recall	NOUN
cana-1177	225	17	,	,	PUNCT
cana-1177	225	18	f1	f1	NOUN
cana-1177	225	19	score	score	NOUN
cana-1177	225	20	,	,	PUNCT
cana-1177	225	21	and	and	CCONJ
cana-1177	225	22	precision	precision	NOUN
cana-1177	225	23	and	and	CCONJ
cana-1177	225	24	auc	auc	NOUN
cana-1177	225	25	.	.	PUNCT
cana-1177	226	1	the	the	DET
cana-1177	226	2	confusion	confusion	NOUN
cana-1177	226	3	matrix	matrix	NOUN
cana-1177	226	4	's	's	PART
cana-1177	226	5	values	value	NOUN
cana-1177	226	6	,	,	PUNCT
cana-1177	226	7	which	which	PRON
cana-1177	226	8	are	be	AUX
cana-1177	226	9	tp	tp	ADP
cana-1177	226	10	that	that	PRON
cana-1177	226	11	is	be	AUX
cana-1177	226	12	the	the	DET
cana-1177	226	13	prediction	prediction	NOUN
cana-1177	226	14	and	and	CCONJ
cana-1177	226	15	the	the	DET
cana-1177	226	16	actual	actual	ADJ
cana-1177	226	17	data	datum	NOUN
cana-1177	226	18	are	be	AUX
cana-1177	226	19	both	both	PRON
cana-1177	226	20	yes	yes	INTJ
cana-1177	226	21	can	can	AUX
cana-1177	226	22	be	be	AUX
cana-1177	226	23	used	use	VERB
cana-1177	226	24	to	to	PART
cana-1177	226	25	compute	compute	VERB
cana-1177	226	26	these	these	DET
cana-1177	226	27	matrices	matrix	NOUN
cana-1177	226	28	,	,	PUNCT
cana-1177	226	29	tn	tn	NOUN
cana-1177	226	30	both	both	DET
cana-1177	226	31	the	the	DET
cana-1177	226	32	actual	actual	ADJ
cana-1177	226	33	data	datum	NOUN
cana-1177	226	34	and	and	CCONJ
cana-1177	226	35	the	the	DET
cana-1177	226	36	prediction	prediction	NOUN
cana-1177	226	37	are	be	AUX
cana-1177	226	38	negative	negative	ADJ
cana-1177	226	39	,	,	PUNCT
cana-1177	226	40	fp	fp	NOUN
cana-1177	226	41	and	and	CCONJ
cana-1177	226	42	fn	fn	NOUN
cana-1177	226	43	refer	refer	NOUN
cana-1177	226	44	to	to	ADP
cana-1177	226	45	the	the	DET
cana-1177	226	46	following	following	NOUN
cana-1177	226	47	:	:	PUNCT
cana-1177	226	48	yes	yes	INTJ
cana-1177	226	49	,	,	PUNCT
cana-1177	226	50	for	for	ADP
cana-1177	226	51	the	the	DET
cana-1177	226	52	forecast	forecast	NOUN
cana-1177	226	53	and	and	CCONJ
cana-1177	226	54	no	no	NOUN
cana-1177	226	55	for	for	ADP
cana-1177	226	56	the	the	DET
cana-1177	226	57	actual	actual	ADJ
cana-1177	226	58	data	datum	NOUN
cana-1177	226	59	.	.	PUNCT
cana-1177	227	1	it	it	PRON
cana-1177	227	2	is	be	AUX
cana-1177	227	3	possible	possible	ADJ
cana-1177	227	4	to	to	PART
cana-1177	227	5	compute	compute	VERB
cana-1177	227	6	precision	precision	NOUN
cana-1177	227	7	,	,	PUNCT
cana-1177	227	8	recall	recall	NOUN
cana-1177	227	9	,	,	PUNCT
cana-1177	227	10	f1	f1	NOUN
cana-1177	227	11	score	score	NOUN
cana-1177	227	12	,	,	PUNCT
cana-1177	227	13	and	and	CCONJ
cana-1177	227	14	accuracy	accuracy	NOUN
cana-1177	227	15	using	use	VERB
cana-1177	227	16	the	the	DET
cana-1177	227	17	following	follow	VERB
cana-1177	227	18	formulas	formula	NOUN
cana-1177	227	19	[	[	X
cana-1177	227	20	20	20	NUM
cana-1177	227	21	]	]	PUNCT
cana-1177	227	22	.	.	PUNCT
cana-1177	228	1	a	a	DET
cana-1177	228	2	generalized	generalized	ADJ
cana-1177	228	3	confusion	confusion	NOUN
cana-1177	228	4	matrix	matrix	NOUN
cana-1177	228	5	that	that	PRON
cana-1177	228	6	aids	aid	VERB
cana-1177	228	7	in	in	ADP
cana-1177	228	8	defining	define	VERB
cana-1177	228	9	the	the	DET
cana-1177	228	10	various	various	ADJ
cana-1177	228	11	performance	performance	NOUN
cana-1177	228	12	metrics	metric	NOUN
cana-1177	228	13	is	be	AUX
cana-1177	228	14	shown	show	VERB
cana-1177	228	15	in	in	ADP
cana-1177	228	16	fig.6	fig.6	PROPN
cana-1177	228	17	.	.	PUNCT
cana-1177	229	1	fig.6	fig.6	PROPN
cana-1177	229	2	.	.	PUNCT
cana-1177	230	1	a	a	DET
cana-1177	230	2	general	general	ADJ
cana-1177	230	3	view	view	NOUN
cana-1177	230	4	of	of	ADP
cana-1177	230	5	confusion	confusion	NOUN
cana-1177	230	6	matrix	matrix	NOUN
cana-1177	230	7	the	the	DET
cana-1177	230	8	following	follow	VERB
cana-1177	230	9	equations	equation	NOUN
cana-1177	230	10	apply	apply	VERB
cana-1177	230	11	to	to	ADP
cana-1177	230	12	the	the	DET
cana-1177	230	13	performance	performance	NOUN
cana-1177	230	14	indicators	indicator	NOUN
cana-1177	230	15	include	include	VERB
cana-1177	230	16	f1	f1	NOUN
cana-1177	230	17	-	-	PUNCT
cana-1177	230	18	score	score	NOUN
cana-1177	230	19	,	,	PUNCT
cana-1177	230	20	auc	auc	NOUN
cana-1177	230	21	-	-	PUNCT
cana-1177	230	22	roc	roc	NOUN
cana-1177	230	23	,	,	PUNCT
cana-1177	230	24	recall	recall	NOUN
cana-1177	230	25	,	,	PUNCT
cana-1177	230	26	accuracy	accuracy	NOUN
cana-1177	230	27	,	,	PUNCT
cana-1177	230	28	and	and	CCONJ
cana-1177	230	29	precision	precision	NOUN
cana-1177	230	30	.	.	PUNCT
cana-1177	231	1	accuracy	accuracy	NOUN
cana-1177	231	2	:	:	PUNCT
cana-1177	232	1	one	one	NUM
cana-1177	232	2	of	of	ADP
cana-1177	232	3	the	the	DET
cana-1177	232	4	most	most	ADV
cana-1177	232	5	often	often	ADV
cana-1177	232	6	used	use	VERB
cana-1177	232	7	metrics	metric	NOUN
cana-1177	232	8	for	for	ADP
cana-1177	232	9	evaluating	evaluate	VERB
cana-1177	232	10	a	a	DET
cana-1177	232	11	classifier	classifier	NOUN
cana-1177	232	12	's	's	PART
cana-1177	232	13	performance	performance	NOUN
cana-1177	232	14	is	be	AUX
cana-1177	232	15	accuracy	accuracy	NOUN
cana-1177	232	16	[	[	X
cana-1177	232	17	11	11	NUM
cana-1177	232	18	]	]	PUNCT
cana-1177	232	19	.	.	PUNCT
cana-1177	233	1	it	it	PRON
cana-1177	233	2	is	be	AUX
cana-1177	233	3	defined	define	VERB
cana-1177	233	4	as	as	ADP
cana-1177	233	5	follows	follow	VERB
cana-1177	233	6	and	and	CCONJ
cana-1177	233	7	represented	represent	VERB
cana-1177	233	8	as	as	ADP
cana-1177	233	9	a	a	DET
cana-1177	233	10	percentage	percentage	NOUN
cana-1177	233	11	of	of	ADP
cana-1177	233	12	correctly	correctly	ADV
cana-1177	233	13	identified	identify	VERB
cana-1177	233	14	samples	sample	NOUN
cana-1177	233	15	:	:	PUNCT
cana-1177	233	16	accuracy	accuracy	NOUN
cana-1177	233	17	=	=	SYM
cana-1177	233	18	𝑇𝑃	𝑇𝑃	PROPN
cana-1177	233	19	+	+	CCONJ
cana-1177	233	20	𝑇𝑁	𝑇𝑁	PROPN
cana-1177	233	21	𝑇𝑃	𝑇𝑃	PROPN
cana-1177	233	22	+	+	CCONJ
cana-1177	233	23	𝑇𝑁	𝑇𝑁	PROPN
cana-1177	234	1	+	+	X
cana-1177	234	2	𝐹𝑁	𝐹𝑁	PROPN
cana-1177	235	1	+	+	CCONJ
cana-1177	235	2	𝐹𝑃	𝐹𝑃	NOUN
cana-1177	235	3	(	(	PUNCT
cana-1177	235	4	6	6	NUM
cana-1177	235	5	)	)	PUNCT
cana-1177	235	6	precision	precision	NOUN
cana-1177	235	7	:	:	PUNCT
cana-1177	235	8	it	it	PRON
cana-1177	235	9	is	be	AUX
cana-1177	235	10	defined	define	VERB
cana-1177	235	11	as	as	ADP
cana-1177	235	12	the	the	DET
cana-1177	235	13	ratio	ratio	NOUN
cana-1177	235	14	of	of	ADP
cana-1177	235	15	real	real	ADJ
cana-1177	235	16	positive	positive	ADJ
cana-1177	235	17	occurrences	occurrence	NOUN
cana-1177	235	18	to	to	ADP
cana-1177	235	19	those	those	PRON
cana-1177	235	20	that	that	PRON
cana-1177	235	21	a	a	DET
cana-1177	235	22	potential	potential	ADJ
cana-1177	235	23	classifier	classifier	NOUN
cana-1177	235	24	predicts	predict	NOUN
cana-1177	235	25	would	would	AUX
cana-1177	235	26	be	be	AUX
cana-1177	235	27	positive	positive	ADJ
cana-1177	235	28	[	[	X
cana-1177	235	29	21	21	NUM
cana-1177	235	30	]	]	PUNCT
cana-1177	235	31	.	.	PUNCT
cana-1177	236	1	𝑃𝑟𝑒𝑐𝑖𝑠𝑖𝑜𝑛	𝑃𝑟𝑒𝑐𝑖𝑠𝑖𝑜𝑛	PROPN
cana-1177	236	2	=	=	SYM
cana-1177	236	3	𝑇𝑃	𝑇𝑃	PROPN
cana-1177	236	4	𝑇𝑃	𝑇𝑃	PROPN
cana-1177	236	5	+	+	CCONJ
cana-1177	236	6	𝐹𝑃	𝐹𝑃	PROPN
cana-1177	236	7	(	(	PUNCT
cana-1177	236	8	7	7	X
cana-1177	236	9	)	)	PUNCT
cana-1177	236	10	communications	communication	NOUN
cana-1177	236	11	on	on	ADP
cana-1177	236	12	applied	apply	VERB
cana-1177	236	13	nonlinear	nonlinear	ADJ
cana-1177	236	14	analysis	analysis	NOUN
cana-1177	236	15	issn	issn	NOUN
cana-1177	236	16	:	:	PUNCT
cana-1177	236	17	1074	1074	NUM
cana-1177	236	18	-	-	PUNCT
cana-1177	236	19	133x	133x	NUM
cana-1177	236	20	vol	vol	NOUN
cana-1177	236	21	31	31	NUM
cana-1177	236	22	no	no	NOUN
cana-1177	236	23	.	.	PUNCT
cana-1177	237	1	6s	6s	NUM
cana-1177	237	2	(	(	PUNCT
cana-1177	237	3	2024	2024	NUM
cana-1177	237	4	)	)	PUNCT
cana-1177	237	5	189	189	NUM
cana-1177	237	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-1177	237	7	sensitivity/	sensitivity/	NUM
cana-1177	237	8	recall	recall	NOUN
cana-1177	237	9	:	:	PUNCT
cana-1177	237	10	it	it	PRON
cana-1177	237	11	is	be	AUX
cana-1177	237	12	also	also	ADV
cana-1177	237	13	known	know	VERB
cana-1177	237	14	as	as	ADP
cana-1177	237	15	true	true	ADJ
cana-1177	237	16	positive	positive	ADJ
cana-1177	237	17	rate	rate	NOUN
cana-1177	237	18	(	(	PUNCT
cana-1177	237	19	tpr	tpr	NOUN
cana-1177	237	20	)	)	PUNCT
cana-1177	237	21	refers	refer	VERB
cana-1177	237	22	to	to	ADP
cana-1177	237	23	the	the	DET
cana-1177	237	24	capacity	capacity	NOUN
cana-1177	237	25	of	of	ADP
cana-1177	237	26	a	a	DET
cana-1177	237	27	classifier	classifier	NOUN
cana-1177	237	28	to	to	PART
cana-1177	237	29	accurately	accurately	ADV
cana-1177	237	30	forecast	forecast	VERB
cana-1177	237	31	a	a	DET
cana-1177	237	32	positive	positive	ADJ
cana-1177	237	33	outcome	outcome	NOUN
cana-1177	237	34	when	when	SCONJ
cana-1177	237	35	a	a	DET
cana-1177	237	36	disease	disease	NOUN
cana-1177	237	37	is	be	AUX
cana-1177	237	38	present	present	ADJ
cana-1177	238	1	[	[	X
cana-1177	238	2	21	21	NUM
cana-1177	238	3	]	]	PUNCT
cana-1177	238	4	.	.	PUNCT
cana-1177	239	1	it	it	PRON
cana-1177	239	2	is	be	AUX
cana-1177	239	3	defined	define	VERB
cana-1177	239	4	as	as	ADP
cana-1177	239	5	𝑅𝑒𝑐𝑎𝑙𝑙	𝑅𝑒𝑐𝑎𝑙𝑙	PROPN
cana-1177	239	6	=	=	PUNCT
cana-1177	239	7	𝑇𝑃	𝑇𝑃	PROPN
cana-1177	239	8	𝑇𝑃+𝐹𝑁	𝑇𝑃+𝐹𝑁	NOUN
cana-1177	239	9	(	(	PUNCT
cana-1177	239	10	8)	8)	NUM
cana-1177	239	11	f1	f1	NOUN
cana-1177	239	12	-	-	PUNCT
cana-1177	239	13	score	score	NOUN
cana-1177	239	14	:	:	PUNCT
cana-1177	239	15	the	the	DET
cana-1177	239	16	weighted	weighted	ADJ
cana-1177	239	17	average	average	NOUN
cana-1177	239	18	of	of	ADP
cana-1177	239	19	precision	precision	NOUN
cana-1177	239	20	and	and	CCONJ
cana-1177	239	21	recall	recall	NOUN
cana-1177	239	22	yields	yield	NOUN
cana-1177	239	23	the	the	DET
cana-1177	239	24	f1	f1	PROPN
cana-1177	239	25	measure	measure	NOUN
cana-1177	239	26	[	[	X
cana-1177	239	27	21	21	NUM
cana-1177	239	28	]	]	PUNCT
cana-1177	239	29	.	.	PUNCT
cana-1177	240	1	the	the	DET
cana-1177	240	2	calculation	calculation	NOUN
cana-1177	240	3	is	be	AUX
cana-1177	240	4	performed	perform	VERB
cana-1177	240	5	using	use	VERB
cana-1177	240	6	equation	equation	NOUN
cana-1177	240	7	9	9	NUM
cana-1177	240	8	.	.	PUNCT
cana-1177	241	1	𝐹	𝐹	PROPN
cana-1177	242	1	−	−	PROPN
cana-1177	242	2	𝑠𝑐𝑜𝑟𝑒	𝑠𝑐𝑜𝑟𝑒	NOUN
cana-1177	242	3	=	=	SYM
cana-1177	242	4	2∗𝑝𝑟𝑒𝑐𝑖𝑠𝑖𝑜𝑛∗𝑅𝑒𝑐𝑎𝑙𝑙	2∗𝑝𝑟𝑒𝑐𝑖𝑠𝑖𝑜𝑛∗𝑅𝑒𝑐𝑎𝑙𝑙	NUM
cana-1177	242	5	𝑃𝑟𝑒𝑐𝑖𝑠𝑖𝑜𝑛+𝑅𝑒𝑐𝑎𝑙𝑙	𝑃𝑟𝑒𝑐𝑖𝑠𝑖𝑜𝑛+𝑅𝑒𝑐𝑎𝑙𝑙	X
cana-1177	242	6	(	(	PUNCT
cana-1177	242	7	9	9	NUM
cana-1177	242	8	)	)	PUNCT
cana-1177	242	9	auc	auc	NOUN
cana-1177	242	10	-	-	PUNCT
cana-1177	242	11	roc	roc	NOUN
cana-1177	242	12	:	:	PUNCT
cana-1177	242	13	“	"	PUNCT
cana-1177	242	14	area	area	NOUN
cana-1177	242	15	under	under	ADP
cana-1177	242	16	the	the	DET
cana-1177	242	17	curve	curve	NOUN
cana-1177	242	18	-	-	PUNCT
cana-1177	242	19	receiver	receiver	ADJ
cana-1177	242	20	operating	operating	NOUN
cana-1177	242	21	characteristics	characteristic	NOUN
cana-1177	242	22	(	(	PUNCT
cana-1177	242	23	auc	auc	NOUN
cana-1177	242	24	-	-	PUNCT
cana-1177	242	25	roc	roc	NOUN
cana-1177	242	26	)	)	PUNCT
cana-1177	242	27	”	"	PUNCT
cana-1177	242	28	,	,	PUNCT
cana-1177	242	29	provides	provide	VERB
cana-1177	242	30	the	the	DET
cana-1177	242	31	performance	performance	NOUN
cana-1177	242	32	metrics	metric	NOUN
cana-1177	242	33	across	across	ADP
cana-1177	242	34	all	all	DET
cana-1177	242	35	classification	classification	NOUN
cana-1177	242	36	criteria	criterion	NOUN
cana-1177	242	37	.	.	PUNCT
cana-1177	243	1	it	it	PRON
cana-1177	243	2	shows	show	VERB
cana-1177	243	3	how	how	SCONJ
cana-1177	243	4	well	well	ADV
cana-1177	243	5	a	a	DET
cana-1177	243	6	classifier	classifier	NOUN
cana-1177	243	7	can	can	AUX
cana-1177	243	8	distinguish	distinguish	VERB
cana-1177	243	9	between	between	ADP
cana-1177	243	10	different	different	ADJ
cana-1177	243	11	classes	class	NOUN
cana-1177	243	12	.	.	PUNCT
cana-1177	244	1	the	the	DET
cana-1177	244	2	probability	probability	NOUN
cana-1177	244	3	curve	curve	NOUN
cana-1177	244	4	is	be	AUX
cana-1177	244	5	represented	represent	VERB
cana-1177	244	6	by	by	ADP
cana-1177	244	7	roc	roc	PROPN
cana-1177	244	8	while	while	SCONJ
cana-1177	244	9	the	the	DET
cana-1177	244	10	degree	degree	NOUN
cana-1177	244	11	or	or	CCONJ
cana-1177	244	12	measure	measure	NOUN
cana-1177	244	13	of	of	ADP
cana-1177	244	14	separability	separability	NOUN
cana-1177	244	15	is	be	AUX
cana-1177	244	16	represented	represent	VERB
cana-1177	244	17	by	by	ADP
cana-1177	244	18	auc	auc	NOUN
cana-1177	245	1	[	[	X
cana-1177	245	2	2	2	NUM
cana-1177	245	3	]	]	PUNCT
cana-1177	245	4	.	.	PUNCT
cana-1177	246	1	𝐴𝑈𝐶	𝐴𝑈𝐶	NOUN
cana-1177	246	2	−	−	NOUN
cana-1177	247	1	𝑅𝑂𝐶	𝑅𝑂𝐶	PROPN
cana-1177	247	2	=	=	NOUN
cana-1177	247	3	1	1	NUM
cana-1177	247	4	2	2	NUM
cana-1177	247	5	∗	∗	NOUN
cana-1177	247	6	(	(	PUNCT
cana-1177	247	7	𝑇𝑃	𝑇𝑃	NOUN
cana-1177	247	8	𝑇𝑃+𝐹𝑁	𝑇𝑃+𝐹𝑁	NOUN
cana-1177	247	9	+	+	CCONJ
cana-1177	247	10	𝑇𝑁	𝑇𝑁	ADJ
cana-1177	247	11	𝑇𝑁+𝐹𝑃	𝑇𝑁+𝐹𝑃	NOUN
cana-1177	247	12	)	)	PUNCT
cana-1177	247	13	(	(	PUNCT
cana-1177	247	14	10	10	NUM
cana-1177	247	15	)	)	PUNCT
cana-1177	247	16	4	4	NUM
cana-1177	247	17	.	.	PUNCT
cana-1177	247	18	experimental	experimental	ADJ
cana-1177	247	19	results	result	NOUN
cana-1177	247	20	and	and	CCONJ
cana-1177	247	21	discussion	discussion	VERB
cana-1177	247	22	the	the	DET
cana-1177	247	23	confusion	confusion	NOUN
cana-1177	247	24	matrices	matrix	NOUN
cana-1177	247	25	,	,	PUNCT
cana-1177	247	26	accuracy	accuracy	NOUN
cana-1177	247	27	,	,	PUNCT
cana-1177	247	28	f1	f1	NOUN
cana-1177	247	29	score	score	NOUN
cana-1177	247	30	,	,	PUNCT
cana-1177	247	31	precision	precision	NOUN
cana-1177	247	32	,	,	PUNCT
cana-1177	247	33	recall	recall	NOUN
cana-1177	247	34	,	,	PUNCT
cana-1177	247	35	auc	auc	NOUN
cana-1177	247	36	-	-	PUNCT
cana-1177	247	37	roc	roc	NOUN
cana-1177	247	38	performance	performance	NOUN
cana-1177	247	39	data	datum	NOUN
cana-1177	247	40	that	that	PRON
cana-1177	247	41	we	we	PRON
cana-1177	247	42	obtained	obtain	VERB
cana-1177	247	43	by	by	ADP
cana-1177	247	44	applying	apply	VERB
cana-1177	247	45	the	the	DET
cana-1177	247	46	suggested	suggest	VERB
cana-1177	247	47	methods	method	NOUN
cana-1177	247	48	are	be	AUX
cana-1177	247	49	displayed	display	VERB
cana-1177	247	50	and	and	CCONJ
cana-1177	247	51	discussed	discuss	VERB
cana-1177	247	52	in	in	ADP
cana-1177	247	53	this	this	DET
cana-1177	247	54	section	section	NOUN
cana-1177	247	55	.	.	PUNCT
cana-1177	248	1	we	we	PRON
cana-1177	248	2	use	use	VERB
cana-1177	248	3	balanced	balanced	ADJ
cana-1177	248	4	datasets	dataset	NOUN
cana-1177	248	5	to	to	PART
cana-1177	248	6	compare	compare	VERB
cana-1177	248	7	the	the	DET
cana-1177	248	8	output	output	NOUN
cana-1177	248	9	of	of	ADP
cana-1177	248	10	the	the	DET
cana-1177	248	11	models	model	NOUN
cana-1177	248	12	contained	contain	VERB
cana-1177	248	13	in	in	ADP
cana-1177	248	14	our	our	PRON
cana-1177	248	15	proposed	propose	VERB
cana-1177	248	16	model	model	NOUN
cana-1177	248	17	,	,	PUNCT
cana-1177	248	18	the	the	DET
cana-1177	248	19	hard	hard	ADJ
cana-1177	248	20	voting	voting	NOUN
cana-1177	248	21	classifier	classifier	NOUN
cana-1177	248	22	with	with	ADP
cana-1177	248	23	the	the	DET
cana-1177	248	24	output	output	NOUN
cana-1177	248	25	of	of	ADP
cana-1177	248	26	the	the	DET
cana-1177	248	27	other	other	ADJ
cana-1177	248	28	models	model	NOUN
cana-1177	248	29	.	.	PUNCT
cana-1177	249	1	the	the	DET
cana-1177	249	2	outcomes	outcome	NOUN
cana-1177	249	3	of	of	ADP
cana-1177	249	4	our	our	PRON
cana-1177	249	5	suggested	suggest	VERB
cana-1177	249	6	model	model	NOUN
cana-1177	249	7	are	be	AUX
cana-1177	249	8	further	far	ADV
cana-1177	249	9	assessed	assess	VERB
cana-1177	249	10	using	use	VERB
cana-1177	249	11	10	10	NUM
cana-1177	249	12	-	-	ADJ
cana-1177	249	13	fold	fold	ADJ
cana-1177	249	14	cross	cross	NOUN
cana-1177	249	15	-	-	NOUN
cana-1177	249	16	validation	validation	NOUN
cana-1177	249	17	on	on	ADP
cana-1177	249	18	the	the	DET
cana-1177	249	19	balanced	balanced	ADJ
cana-1177	249	20	dataset	dataset	NOUN
cana-1177	249	21	.	.	PUNCT
cana-1177	250	1	python	python	PROPN
cana-1177	250	2	is	be	AUX
cana-1177	250	3	used	use	VERB
cana-1177	250	4	for	for	ADP
cana-1177	250	5	the	the	DET
cana-1177	250	6	purpose	purpose	NOUN
cana-1177	250	7	of	of	ADP
cana-1177	250	8	implementing	implement	VERB
cana-1177	250	9	the	the	DET
cana-1177	250	10	proposed	propose	VERB
cana-1177	250	11	methodology	methodology	NOUN
cana-1177	250	12	as	as	SCONJ
cana-1177	250	13	this	this	DET
cana-1177	250	14	language	language	NOUN
cana-1177	250	15	supports	support	VERB
cana-1177	250	16	highly	highly	ADV
cana-1177	250	17	efficient	efficient	ADJ
cana-1177	250	18	data	data	NOUN
cana-1177	250	19	analysis	analysis	NOUN
cana-1177	250	20	and	and	CCONJ
cana-1177	250	21	ml	ml	NOUN
cana-1177	250	22	libraries	library	NOUN
cana-1177	250	23	.	.	PUNCT
cana-1177	251	1	this	this	PRON
cana-1177	251	2	made	make	VERB
cana-1177	251	3	the	the	DET
cana-1177	251	4	research	research	NOUN
cana-1177	251	5	data	datum	NOUN
cana-1177	251	6	to	to	PART
cana-1177	251	7	be	be	AUX
cana-1177	251	8	processed	process	VERB
cana-1177	251	9	in	in	ADP
cana-1177	251	10	an	an	DET
cana-1177	251	11	efficient	efficient	ADJ
cana-1177	251	12	way	way	NOUN
cana-1177	251	13	as	as	ADV
cana-1177	251	14	well	well	ADV
cana-1177	251	15	as	as	ADP
cana-1177	251	16	analysing	analyse	VERB
cana-1177	251	17	the	the	DET
cana-1177	251	18	research	research	NOUN
cana-1177	251	19	findings	finding	NOUN
cana-1177	251	20	in	in	ADP
cana-1177	251	21	an	an	DET
cana-1177	251	22	accurate	accurate	ADJ
cana-1177	251	23	manner	manner	NOUN
cana-1177	251	24	.	.	PUNCT
cana-1177	252	1	we	we	PRON
cana-1177	252	2	split	split	VERB
cana-1177	252	3	the	the	DET
cana-1177	252	4	dataset	dataset	NOUN
cana-1177	252	5	(	(	PUNCT
cana-1177	252	6	wdbc	wdbc	VERB
cana-1177	252	7	569	569	NUM
cana-1177	252	8	instances	instance	NOUN
cana-1177	252	9	)	)	PUNCT
cana-1177	252	10	into	into	ADP
cana-1177	252	11	two	two	NUM
cana-1177	252	12	parts	part	NOUN
cana-1177	252	13	:	:	PUNCT
cana-1177	252	14	testing	testing	NOUN
cana-1177	252	15	(	(	PUNCT
cana-1177	252	16	20	20	NUM
cana-1177	252	17	%	%	NOUN
cana-1177	252	18	with	with	ADP
cana-1177	252	19	114	114	NUM
cana-1177	252	20	instances	instance	NOUN
cana-1177	252	21	)	)	PUNCT
cana-1177	252	22	and	and	CCONJ
cana-1177	252	23	training	training	NOUN
cana-1177	252	24	(	(	PUNCT
cana-1177	252	25	80	80	NUM
cana-1177	252	26	%	%	NOUN
cana-1177	252	27	with	with	ADP
cana-1177	252	28	455	455	NUM
cana-1177	252	29	instances	instance	NOUN
cana-1177	252	30	)	)	PUNCT
cana-1177	252	31	.	.	PUNCT
cana-1177	253	1	after	after	ADP
cana-1177	253	2	balancing	balance	VERB
cana-1177	253	3	the	the	DET
cana-1177	253	4	training	training	NOUN
cana-1177	253	5	set	set	NOUN
cana-1177	253	6	using	use	VERB
cana-1177	253	7	ros	ros	PROPN
cana-1177	253	8	it	it	PRON
cana-1177	253	9	is	be	AUX
cana-1177	253	10	converted	convert	VERB
cana-1177	253	11	into	into	ADP
cana-1177	253	12	572	572	NUM
cana-1177	253	13	cases	case	NOUN
cana-1177	253	14	(	(	PUNCT
cana-1177	253	15	m	m	NOUN
cana-1177	253	16	=	=	ADJ
cana-1177	253	17	286	286	NUM
cana-1177	253	18	,	,	PUNCT
cana-1177	253	19	b	b	NOUN
cana-1177	253	20	=	=	SYM
cana-1177	253	21	286	286	NUM
cana-1177	253	22	)	)	PUNCT
cana-1177	253	23	.	.	PUNCT
cana-1177	254	1	after	after	ADP
cana-1177	254	2	that	that	PRON
cana-1177	254	3	,	,	PUNCT
cana-1177	254	4	we	we	PRON
cana-1177	254	5	train	train	VERB
cana-1177	254	6	and	and	CCONJ
cana-1177	254	7	test	test	VERB
cana-1177	254	8	the	the	DET
cana-1177	254	9	performance	performance	NOUN
cana-1177	254	10	of	of	ADP
cana-1177	254	11	the	the	DET
cana-1177	254	12	hard	hard	ADJ
cana-1177	254	13	voting	voting	NOUN
cana-1177	254	14	classifier	classifier	NOUN
cana-1177	254	15	as	as	ADV
cana-1177	254	16	well	well	ADV
cana-1177	254	17	as	as	ADP
cana-1177	254	18	the	the	DET
cana-1177	254	19	models	model	NOUN
cana-1177	254	20	that	that	PRON
cana-1177	254	21	we	we	PRON
cana-1177	254	22	use	use	VERB
cana-1177	254	23	in	in	ADP
cana-1177	254	24	this	this	DET
cana-1177	254	25	study	study	NOUN
cana-1177	254	26	,	,	PUNCT
cana-1177	254	27	lr	lr	NOUN
cana-1177	254	28	,	,	PUNCT
cana-1177	254	29	dt	dt	X
cana-1177	254	30	,	,	PUNCT
cana-1177	254	31	and	and	CCONJ
cana-1177	254	32	svm	svm	ADJ
cana-1177	254	33	.	.	PROPN
cana-1177	254	34	fig.7	fig.7	PROPN
cana-1177	254	35	.	.	PUNCT
cana-1177	255	1	shows	show	VERB
cana-1177	255	2	the	the	DET
cana-1177	255	3	confusion	confusion	NOUN
cana-1177	255	4	matrices	matrix	NOUN
cana-1177	255	5	for	for	ADP
cana-1177	255	6	all	all	DET
cana-1177	255	7	individual	individual	ADJ
cana-1177	255	8	classifier	classifier	NOUN
cana-1177	255	9	and	and	CCONJ
cana-1177	255	10	hard	hard	ADJ
cana-1177	255	11	voting	voting	NOUN
cana-1177	255	12	classifier	classifier	NOUN
cana-1177	255	13	.	.	PUNCT
cana-1177	256	1	table	table	NOUN
cana-1177	256	2	5	5	NUM
cana-1177	256	3	represents	represent	VERB
cana-1177	256	4	the	the	DET
cana-1177	256	5	comparison	comparison	NOUN
cana-1177	256	6	of	of	ADP
cana-1177	256	7	the	the	DET
cana-1177	256	8	results	result	NOUN
cana-1177	256	9	of	of	ADP
cana-1177	256	10	baseline	baseline	NOUN
cana-1177	256	11	classifier	classifier	NOUN
cana-1177	256	12	and	and	CCONJ
cana-1177	256	13	voting	voting	NOUN
cana-1177	256	14	classifier	classifier	NOUN
cana-1177	256	15	.	.	PUNCT
cana-1177	257	1	the	the	DET
cana-1177	257	2	comparison	comparison	NOUN
cana-1177	257	3	chart	chart	NOUN
cana-1177	257	4	of	of	ADP
cana-1177	257	5	evaluation	evaluation	NOUN
cana-1177	257	6	metrics	metric	NOUN
cana-1177	257	7	of	of	ADP
cana-1177	257	8	baseline	baseline	ADJ
cana-1177	257	9	machine	machine	NOUN
cana-1177	257	10	learning	learning	NOUN
cana-1177	257	11	models	model	NOUN
cana-1177	257	12	and	and	CCONJ
cana-1177	257	13	hard	hard	ADJ
cana-1177	257	14	voting	voting	NOUN
cana-1177	257	15	classifier	classifier	NOUN
cana-1177	257	16	shown	show	VERB
cana-1177	257	17	in	in	ADP
cana-1177	257	18	fig.8	fig.8	PROPN
cana-1177	257	19	.	.	PUNCT
cana-1177	258	1	classification	classification	NOUN
cana-1177	258	2	algorithms	algorithm	NOUN
cana-1177	258	3	for	for	ADP
cana-1177	258	4	breast	breast	NOUN
cana-1177	258	5	cancer	cancer	NOUN
cana-1177	258	6	dataset	dataset	VERB
cana-1177	258	7	in	in	ADP
cana-1177	258	8	table	table	NOUN
cana-1177	258	9	6	6	NUM
cana-1177	258	10	encapsulates	encapsulate	VERB
cana-1177	258	11	a	a	DET
cana-1177	258	12	detailed	detailed	ADJ
cana-1177	258	13	framework	framework	NOUN
cana-1177	258	14	.	.	PUNCT
cana-1177	259	1	moreover	moreover	ADV
cana-1177	259	2	,	,	PUNCT
cana-1177	259	3	the	the	DET
cana-1177	259	4	proposed	propose	VERB
cana-1177	259	5	voting	voting	NOUN
cana-1177	259	6	classifier	classifier	NOUN
cana-1177	259	7	,	,	PUNCT
cana-1177	259	8	unlike	unlike	ADP
cana-1177	259	9	other	other	ADJ
cana-1177	259	10	techniques	technique	NOUN
cana-1177	259	11	,	,	PUNCT
cana-1177	259	12	composed	compose	VERB
cana-1177	259	13	by	by	ADP
cana-1177	259	14	lr	lr	PROPN
cana-1177	259	15	,	,	PUNCT
cana-1177	259	16	svm	svm	ADJ
cana-1177	259	17	,	,	PUNCT
cana-1177	259	18	and	and	CCONJ
cana-1177	259	19	dt	dt	PROPN
cana-1177	259	20	,	,	PUNCT
cana-1177	259	21	has	have	AUX
cana-1177	259	22	achieved	achieve	VERB
cana-1177	259	23	high	high	ADJ
cana-1177	259	24	performance	performance	NOUN
cana-1177	259	25	,	,	PUNCT
cana-1177	259	26	obtaining	obtain	VERB
cana-1177	259	27	an	an	DET
cana-1177	259	28	accuracy	accuracy	NOUN
cana-1177	259	29	of	of	ADP
cana-1177	259	30	98.25	98.25	NUM
cana-1177	259	31	%	%	NOUN
cana-1177	259	32	in	in	ADP
cana-1177	259	33	the	the	DET
cana-1177	259	34	wdbc	wdbc	NOUN
cana-1177	259	35	dataset.fig.9	dataset.fig.9	NOUN
cana-1177	259	36	.	.	PUNCT
cana-1177	260	1	and	and	CCONJ
cana-1177	260	2	fig	fig	NOUN
cana-1177	260	3	.	.	PUNCT
cana-1177	261	1	10	10	NUM
cana-1177	261	2	indicates	indicate	VERB
cana-1177	261	3	,	,	PUNCT
cana-1177	261	4	comparison	comparison	NOUN
cana-1177	261	5	chart	chart	NOUN
cana-1177	261	6	of	of	ADP
cana-1177	261	7	accuracy	accuracy	NOUN
cana-1177	261	8	and	and	CCONJ
cana-1177	261	9	precision	precision	NOUN
cana-1177	261	10	of	of	ADP
cana-1177	261	11	the	the	DET
cana-1177	261	12	currently	currently	ADV
cana-1177	261	13	developed	develop	VERB
cana-1177	261	14	models	model	NOUN
cana-1177	261	15	has	have	AUX
cana-1177	261	16	been	be	AUX
cana-1177	261	17	pulled	pull	VERB
cana-1177	261	18	up	up	ADP
cana-1177	261	19	against	against	ADP
cana-1177	261	20	the	the	DET
cana-1177	261	21	intended	intend	VERB
cana-1177	261	22	one	one	NUM
cana-1177	261	23	.	.	PUNCT
cana-1177	262	1	communications	communication	NOUN
cana-1177	262	2	on	on	ADP
cana-1177	262	3	applied	apply	VERB
cana-1177	262	4	nonlinear	nonlinear	ADJ
cana-1177	262	5	analysis	analysis	NOUN
cana-1177	262	6	issn	issn	NOUN
cana-1177	262	7	:	:	PUNCT
cana-1177	262	8	1074	1074	NUM
cana-1177	262	9	-	-	PUNCT
cana-1177	262	10	133x	133x	NUM
cana-1177	262	11	vol	vol	NOUN
cana-1177	262	12	31	31	NUM
cana-1177	262	13	no	no	NOUN
cana-1177	262	14	.	.	PUNCT
cana-1177	263	1	6s	6s	NUM
cana-1177	263	2	(	(	PUNCT
cana-1177	263	3	2024	2024	NUM
cana-1177	263	4	)	)	PUNCT
cana-1177	263	5	190	190	NUM
cana-1177	263	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-1177	263	7	fig.7	fig.7	ADV
cana-1177	263	8	.	.	PUNCT
cana-1177	264	1	analysing	analyse	VERB
cana-1177	264	2	the	the	DET
cana-1177	264	3	performance	performance	NOUN
cana-1177	264	4	of	of	ADP
cana-1177	264	5	different	different	ADJ
cana-1177	264	6	classifiers	classifier	NOUN
cana-1177	264	7	:	:	PUNCT
cana-1177	264	8	logistic	logistic	ADJ
cana-1177	264	9	regression	regression	NOUN
cana-1177	264	10	,	,	PUNCT
cana-1177	264	11	support	support	NOUN
cana-1177	264	12	vector	vector	NOUN
cana-1177	264	13	machine	machine	NOUN
cana-1177	264	14	,	,	PUNCT
cana-1177	264	15	decision	decision	NOUN
cana-1177	264	16	tree	tree	NOUN
cana-1177	264	17	and	and	CCONJ
cana-1177	264	18	voting	voting	NOUN
cana-1177	264	19	classifier	classifier	NOUN
cana-1177	264	20	through	through	ADP
cana-1177	264	21	confusion	confusion	NOUN
cana-1177	264	22	matrix	matrix	NOUN
cana-1177	264	23	table	table	NOUN
cana-1177	264	24	5	5	NUM
cana-1177	264	25	comparison	comparison	NOUN
cana-1177	264	26	of	of	ADP
cana-1177	264	27	evaluation	evaluation	NOUN
cana-1177	264	28	metrics	metric	NOUN
cana-1177	264	29	of	of	ADP
cana-1177	264	30	baseline	baseline	ADJ
cana-1177	264	31	machine	machine	NOUN
cana-1177	264	32	learning	learning	NOUN
cana-1177	264	33	models	model	NOUN
cana-1177	264	34	and	and	CCONJ
cana-1177	264	35	hard	hard	ADJ
cana-1177	264	36	voting	voting	NOUN
cana-1177	264	37	classifier	classifier	NOUN
cana-1177	264	38	.	.	PUNCT
cana-1177	265	1	algorithms	algorithms	PROPN
cana-1177	265	2	accuracy	accuracy	PROPN
cana-1177	265	3	precision	precision	NOUN
cana-1177	265	4	recall	recall	VERB
cana-1177	265	5	f1	f1	NOUN
cana-1177	265	6	-	-	PUNCT
cana-1177	265	7	score	score	NOUN
cana-1177	265	8	auc	auc	NOUN
cana-1177	265	9	-	-	PUNCT
cana-1177	265	10	roc	roc	NOUN
cana-1177	265	11	lr	lr	NOUN
cana-1177	265	12	0.9824	0.9824	NUM
cana-1177	265	13	0.9859	0.9859	NUM
cana-1177	265	14	0.9859	0.9859	NUM
cana-1177	265	15	0.9859	0.9859	NUM
cana-1177	265	16	0.9813	0.9813	NUM
cana-1177	265	17	svm	svm	PROPN
cana-1177	265	18	0.9561	0.9561	NUM
cana-1177	265	19	0.9714	0.9714	NUM
cana-1177	266	1	0.9577	0.9577	NUM
cana-1177	266	2	0.9645	0.9645	NUM
cana-1177	266	3	0.9556	0.9556	NUM
cana-1177	266	4	dt	dt	NOUN
cana-1177	267	1	0.9561	0.9561	NUM
cana-1177	267	2	0.9583	0.9583	NUM
cana-1177	267	3	0.9718	0.9718	NUM
cana-1177	267	4	0.9650	0.9650	NUM
cana-1177	267	5	0.9510	0.9510	NUM
cana-1177	267	6	hard	hard	ADJ
cana-1177	267	7	voting	voting	NOUN
cana-1177	267	8	classifier	classifier	NOUN
cana-1177	267	9	0.9825	0.9825	NUM
cana-1177	267	10	0.9859	0.9859	NUM
cana-1177	267	11	0.9859	0.9859	NUM
cana-1177	267	12	0.9859	0.9859	NUM
cana-1177	267	13	0.9813	0.9813	NUM
cana-1177	267	14	fig.8	fig.8	PROPN
cana-1177	267	15	.	.	PUNCT
cana-1177	268	1	comparison	comparison	NOUN
cana-1177	268	2	chart	chart	NOUN
cana-1177	268	3	of	of	ADP
cana-1177	268	4	evaluation	evaluation	NOUN
cana-1177	268	5	metrics	metric	NOUN
cana-1177	268	6	of	of	ADP
cana-1177	268	7	baseline	baseline	ADJ
cana-1177	268	8	machine	machine	NOUN
cana-1177	268	9	learning	learning	NOUN
cana-1177	268	10	models	model	NOUN
cana-1177	268	11	and	and	CCONJ
cana-1177	268	12	hard	hard	ADJ
cana-1177	268	13	voting	voting	NOUN
cana-1177	268	14	classifier	classifier	NOUN
cana-1177	268	15	communications	communication	NOUN
cana-1177	268	16	on	on	ADP
cana-1177	268	17	applied	apply	VERB
cana-1177	268	18	nonlinear	nonlinear	ADJ
cana-1177	268	19	analysis	analysis	NOUN
cana-1177	268	20	issn	issn	NOUN
cana-1177	268	21	:	:	PUNCT
cana-1177	268	22	1074	1074	NUM
cana-1177	268	23	-	-	PUNCT
cana-1177	268	24	133x	133x	NUM
cana-1177	268	25	vol	vol	NOUN
cana-1177	268	26	31	31	NUM
cana-1177	268	27	no	no	NOUN
cana-1177	268	28	.	.	PUNCT
cana-1177	269	1	6s	6s	NUM
cana-1177	269	2	(	(	PUNCT
cana-1177	269	3	2024	2024	NUM
cana-1177	269	4	)	)	PUNCT
cana-1177	269	5	191	191	NUM
cana-1177	269	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-1177	269	7	table	table	NOUN
cana-1177	269	8	6	6	NUM
cana-1177	269	9	comparison	comparison	NOUN
cana-1177	269	10	of	of	ADP
cana-1177	269	11	evaluation	evaluation	NOUN
cana-1177	269	12	metrics	metric	NOUN
cana-1177	269	13	of	of	ADP
cana-1177	269	14	existing	exist	VERB
cana-1177	269	15	models	model	NOUN
cana-1177	269	16	and	and	CCONJ
cana-1177	269	17	purposed	purposed	ADJ
cana-1177	269	18	model	model	NOUN
cana-1177	269	19	.	.	PUNCT
cana-1177	270	1	year	year	PROPN
cana-1177	270	2	&	&	CCONJ
cana-1177	270	3	reference	reference	PROPN
cana-1177	270	4	algorithm	algorithm	PROPN
cana-1177	270	5	dataset	dataset	NOUN
cana-1177	270	6	accuracy	accuracy	NOUN
cana-1177	270	7	precision	precision	NOUN
cana-1177	270	8	recall	recall	VERB
cana-1177	270	9	f1score	f1score	NOUN
cana-1177	270	10	aucroc	aucroc	PROPN
cana-1177	270	11	(	(	PUNCT
cana-1177	270	12	2018	2018	NUM
cana-1177	270	13	)	)	PUNCT
cana-1177	271	1	[	[	X
cana-1177	271	2	9	9	NUM
cana-1177	271	3	]	]	X
cana-1177	271	4	rbf	rbf	PROPN
cana-1177	271	5	wbcd	wbcd	ADP
cana-1177	271	6	(	(	PUNCT
cana-1177	271	7	699	699	NUM
cana-1177	271	8	)	)	PUNCT
cana-1177	271	9	.96	.96	NUM
cana-1177	271	10	.9623	.9623	INTJ
cana-1177	271	11	(	(	PUNCT
cana-1177	271	12	2019)[12	2019)[12	NOUN
cana-1177	271	13	]	]	X
cana-1177	271	14	back	back	ADJ
cana-1177	271	15	propagation	propagation	NOUN
cana-1177	271	16	network	network	NOUN
cana-1177	271	17	,	,	PUNCT
cana-1177	271	18	ann	ann	PROPN
cana-1177	271	19	,	,	PUNCT
cana-1177	271	20	cnn	cnn	PROPN
cana-1177	271	21	,	,	PUNCT
cana-1177	271	22	svm	svm	VERB
cana-1177	271	23	wbcd	wbcd	ADV
cana-1177	271	24	(	(	PUNCT
cana-1177	271	25	699	699	NUM
cana-1177	271	26	)	)	PUNCT
cana-1177	271	27	.94	.94	NUM
cana-1177	271	28	(	(	PUNCT
cana-1177	271	29	2020	2020	NUM
cana-1177	271	30	)	)	PUNCT
cana-1177	272	1	[	[	X
cana-1177	272	2	7	7	X
cana-1177	272	3	]	]	PUNCT
cana-1177	272	4	hofeding	hofeding	NOUN
cana-1177	272	5	tree	tree	NOUN
cana-1177	272	6	and	and	CCONJ
cana-1177	272	7	naïve	naïve	ADJ
cana-1177	272	8	bayes	baye	NOUN
cana-1177	272	9	wbcd	wbcd	VERB
cana-1177	272	10	(	(	PUNCT
cana-1177	272	11	699	699	NUM
cana-1177	272	12	)	)	PUNCT
cana-1177	272	13	.9599	.9599	NOUN
cana-1177	272	14	(	(	PUNCT
cana-1177	272	15	2021	2021	NUM
cana-1177	272	16	)	)	PUNCT
cana-1177	273	1	[	[	X
cana-1177	273	2	6	6	X
cana-1177	273	3	]	]	PUNCT
cana-1177	273	4	bayesian	bayesian	NOUN
cana-1177	273	5	network	network	NOUN
cana-1177	273	6	and	and	CCONJ
cana-1177	273	7	radial	radial	ADJ
cana-1177	273	8	basis	basis	NOUN
cana-1177	273	9	function	function	NOUN
cana-1177	273	10	wbcd	wbcd	ADP
cana-1177	273	11	(	(	PUNCT
cana-1177	273	12	699	699	NUM
cana-1177	273	13	)	)	PUNCT
cana-1177	273	14	.9742	.9742	NOUN
cana-1177	274	1	.9672	.9672	PRON
cana-1177	274	2	(	(	PUNCT
cana-1177	274	3	2021)[18	2021)[18	NUM
cana-1177	274	4	]	]	X
cana-1177	274	5	dt	dt	X
cana-1177	274	6	wdbc	wdbc	PROPN
cana-1177	274	7	(	(	PUNCT
cana-1177	274	8	569	569	NUM
cana-1177	274	9	)	)	PUNCT
cana-1177	274	10	.9253	.9253	NOUN
cana-1177	274	11	(	(	PUNCT
cana-1177	274	12	2023)[19	2023)[19	NOUN
cana-1177	274	13	]	]	X
cana-1177	274	14	xgboost	xgboost	X
cana-1177	274	15	wdbc	wdbc	PROPN
cana-1177	274	16	(	(	PUNCT
cana-1177	274	17	569	569	NUM
cana-1177	274	18	)	)	PUNCT
cana-1177	274	19	.974	.974	NUM
cana-1177	275	1	0.960	0.960	NUM
cana-1177	275	2	1.00	1.00	NUM
cana-1177	275	3	0.980	0.980	NUM
cana-1177	275	4	(	(	PUNCT
cana-1177	275	5	2024	2024	NUM
cana-1177	275	6	)	)	PUNCT
cana-1177	276	1	[	[	X
cana-1177	276	2	11	11	NUM
cana-1177	276	3	]	]	PUNCT
cana-1177	276	4	stacked	stack	VERB
cana-1177	276	5	based	base	VERB
cana-1177	276	6	ensemble	ensemble	ADJ
cana-1177	276	7	classifier	classifier	NOUN
cana-1177	276	8	wdbc	wdbc	NOUN
cana-1177	276	9	(	(	PUNCT
cana-1177	276	10	569	569	NUM
cana-1177	276	11	)	)	PUNCT
cana-1177	276	12	.9766	.9766	NOUN
cana-1177	276	13	2024	2024	NUM
cana-1177	277	1	[	[	X
cana-1177	277	2	17	17	NUM
cana-1177	277	3	]	]	PUNCT
cana-1177	277	4	stacking	stack	VERB
cana-1177	277	5	with	with	ADP
cana-1177	277	6	logistic	logistic	ADJ
cana-1177	277	7	regression	regression	NOUN
cana-1177	277	8	ensemble	ensemble	ADJ
cana-1177	277	9	model	model	NOUN
cana-1177	277	10	wdbc	wdbc	NOUN
cana-1177	277	11	(	(	PUNCT
cana-1177	277	12	569	569	NUM
cana-1177	277	13	)	)	PUNCT
cana-1177	277	14	.9737	.9737	ADJ
cana-1177	277	15	purposed	purpose	VERB
cana-1177	277	16	model	model	NOUN
cana-1177	277	17	voting	voting	NOUN
cana-1177	277	18	classifier	classifier	NOUN
cana-1177	277	19	(	(	PUNCT
cana-1177	277	20	lr+svm+dt	lr+svm+dt	NOUN
cana-1177	277	21	)	)	PUNCT
cana-1177	277	22	wdbc	wdbc	NOUN
cana-1177	277	23	(	(	PUNCT
cana-1177	277	24	569	569	NUM
cana-1177	277	25	)	)	PUNCT
cana-1177	277	26	.9825	.9825	PROPN
cana-1177	278	1	0.9859	0.9859	NUM
cana-1177	278	2	0.9859	0.9859	NUM
cana-1177	278	3	0.9859	0.9859	NUM
cana-1177	278	4	0.9813	0.9813	NUM
cana-1177	278	5	fig.9	fig.9	PROPN
cana-1177	278	6	.	.	PUNCT
cana-1177	279	1	comparison	comparison	NOUN
cana-1177	279	2	chart	chart	NOUN
cana-1177	279	3	of	of	ADP
cana-1177	279	4	accuracy	accuracy	NOUN
cana-1177	279	5	of	of	ADP
cana-1177	279	6	existing	exist	VERB
cana-1177	279	7	works	work	NOUN
cana-1177	279	8	with	with	ADP
cana-1177	279	9	purposed	purposed	ADJ
cana-1177	279	10	model	model	NOUN
cana-1177	279	11	fig.10	fig.10	PROPN
cana-1177	279	12	.	.	PUNCT
cana-1177	279	13	comparison	comparison	NOUN
cana-1177	279	14	chart	chart	NOUN
cana-1177	279	15	of	of	ADP
cana-1177	279	16	precision	precision	NOUN
cana-1177	279	17	of	of	ADP
cana-1177	279	18	existing	exist	VERB
cana-1177	279	19	works	work	NOUN
cana-1177	279	20	with	with	ADP
cana-1177	279	21	purposed	purposed	ADJ
cana-1177	279	22	model	model	NOUN
cana-1177	279	23	finally	finally	ADV
cana-1177	279	24	,	,	PUNCT
cana-1177	279	25	we	we	PRON
cana-1177	279	26	assess	assess	VERB
cana-1177	279	27	our	our	PRON
cana-1177	279	28	model	model	NOUN
cana-1177	279	29	for	for	ADP
cana-1177	279	30	estimating	estimate	VERB
cana-1177	279	31	the	the	DET
cana-1177	279	32	out	out	ADJ
cana-1177	279	33	-	-	PUNCT
cana-1177	279	34	of	of	ADP
cana-1177	279	35	-	-	PUNCT
cana-1177	279	36	sample	sample	NOUN
cana-1177	279	37	error	error	NOUN
cana-1177	279	38	using	use	VERB
cana-1177	279	39	the	the	DET
cana-1177	279	40	10	10	NUM
cana-1177	279	41	-	-	ADJ
cana-1177	279	42	fold	fold	ADJ
cana-1177	279	43	cross	cross	ADJ
cana-1177	279	44	-	-	ADJ
cana-1177	279	45	validation	validation	ADJ
cana-1177	279	46	approach	approach	NOUN
cana-1177	279	47	.	.	PUNCT
cana-1177	280	1	the	the	DET
cana-1177	280	2	10	10	NUM
cana-1177	280	3	-	-	ADJ
cana-1177	280	4	fold	fold	ADJ
cana-1177	280	5	cross	cross	NOUN
cana-1177	280	6	-	-	ADJ
cana-1177	280	7	validation	validation	NOUN
cana-1177	280	8	improves	improve	VERB
cana-1177	280	9	the	the	DET
cana-1177	280	10	evaluation	evaluation	NOUN
cana-1177	280	11	of	of	ADP
cana-1177	280	12	our	our	PRON
cana-1177	280	13	model	model	NOUN
cana-1177	280	14	's	's	PART
cana-1177	280	15	performance	performance	NOUN
cana-1177	280	16	by	by	ADP
cana-1177	280	17	preventing	prevent	VERB
cana-1177	280	18	overfitting	overfitte	VERB
cana-1177	280	19	and	and	CCONJ
cana-1177	280	20	creating	create	VERB
cana-1177	280	21	a	a	DET
cana-1177	280	22	more	more	ADV
cana-1177	280	23	generalized	generalized	ADJ
cana-1177	280	24	model	model	NOUN
cana-1177	280	25	.	.	PUNCT
cana-1177	281	1	this	this	DET
cana-1177	281	2	method	method	NOUN
cana-1177	281	3	is	be	AUX
cana-1177	281	4	used	use	VERB
cana-1177	281	5	with	with	ADP
cana-1177	281	6	both	both	CCONJ
cana-1177	281	7	the	the	DET
cana-1177	281	8	balanced	balanced	ADJ
cana-1177	281	9	data	datum	NOUN
cana-1177	281	10	set	set	VERB
cana-1177	281	11	and	and	CCONJ
cana-1177	281	12	the	the	DET
cana-1177	281	13	suggested	suggest	VERB
cana-1177	281	14	"	"	PUNCT
cana-1177	281	15	hard	hard	ADJ
cana-1177	281	16	voting	voting	NOUN
cana-1177	281	17	classifier	classifier	NOUN
cana-1177	281	18	"	"	PUNCT
cana-1177	281	19	.	.	PUNCT
cana-1177	282	1	the	the	DET
cana-1177	282	2	testing	testing	NOUN
cana-1177	282	3	results	result	NOUN
cana-1177	282	4	revealed	reveal	VERB
cana-1177	282	5	a	a	DET
cana-1177	282	6	mean	mean	ADJ
cana-1177	282	7	accuracy	accuracy	NOUN
cana-1177	282	8	of	of	ADP
cana-1177	282	9	.9738	.9738	PROPN
cana-1177	282	10	.	.	PUNCT
cana-1177	283	1	5	5	NUM
cana-1177	283	2	.	.	X
cana-1177	283	3	conclusion	conclusion	NOUN
cana-1177	283	4	and	and	CCONJ
cana-1177	283	5	future	future	ADJ
cana-1177	283	6	works	work	NOUN
cana-1177	283	7	in	in	ADP
cana-1177	283	8	this	this	DET
cana-1177	283	9	paper	paper	NOUN
cana-1177	283	10	,	,	PUNCT
cana-1177	283	11	an	an	DET
cana-1177	283	12	ensemble	ensemble	ADJ
cana-1177	283	13	classification	classification	NOUN
cana-1177	283	14	method	method	NOUN
cana-1177	283	15	has	have	AUX
cana-1177	283	16	been	be	AUX
cana-1177	283	17	employed	employ	VERB
cana-1177	283	18	on	on	ADP
cana-1177	283	19	the	the	DET
cana-1177	283	20	wdbc	wdbc	NOUN
cana-1177	283	21	datasets	dataset	NOUN
cana-1177	283	22	in	in	ADP
cana-1177	283	23	order	order	NOUN
cana-1177	283	24	to	to	ADP
cana-1177	283	25	early	early	ADJ
cana-1177	283	26	and	and	CCONJ
cana-1177	283	27	accurate	accurate	ADJ
cana-1177	283	28	breast	breast	NOUN
cana-1177	283	29	cancer	cancer	NOUN
cana-1177	283	30	prediction	prediction	NOUN
cana-1177	283	31	that	that	PRON
cana-1177	283	32	is	be	AUX
cana-1177	283	33	based	base	VERB
cana-1177	283	34	on	on	ADP
cana-1177	283	35	the	the	DET
cana-1177	283	36	voting	voting	NOUN
cana-1177	283	37	strategies	strategy	NOUN
cana-1177	283	38	(	(	PUNCT
cana-1177	283	39	lr	lr	INTJ
cana-1177	283	40	,	,	PUNCT
cana-1177	283	41	dt	dt	X
cana-1177	283	42	,	,	PUNCT
cana-1177	283	43	and	and	CCONJ
cana-1177	283	44	svm	svm	ADJ
cana-1177	283	45	)	)	PUNCT
cana-1177	283	46	.	.	PUNCT
cana-1177	284	1	the	the	DET
cana-1177	284	2	suggested	suggest	VERB
cana-1177	284	3	model	model	NOUN
cana-1177	284	4	performed	perform	VERB
cana-1177	284	5	better	well	ADV
cana-1177	284	6	than	than	ADP
cana-1177	284	7	other	other	ADJ
cana-1177	284	8	cutting	cutting	NOUN
cana-1177	284	9	-	-	PUNCT
cana-1177	284	10	edge	edge	NOUN
cana-1177	284	11	models	model	NOUN
cana-1177	284	12	,	,	PUNCT
cana-1177	284	13	with	with	ADP
cana-1177	284	14	accuracy	accuracy	NOUN
cana-1177	284	15	of	of	ADP
cana-1177	284	16	.9825	.9825	PROPN
cana-1177	284	17	,	,	PUNCT
cana-1177	284	18	precision	precision	NOUN
cana-1177	284	19	of	of	ADP
cana-1177	284	20	.9859	.9859	PROPN
cana-1177	284	21	,	,	PUNCT
cana-1177	284	22	recall	recall	NOUN
cana-1177	284	23	of	of	ADP
cana-1177	284	24	.9859	.9859	PROPN
cana-1177	284	25	,	,	PUNCT
cana-1177	284	26	f1	f1	ADJ
cana-1177	284	27	score	score	NOUN
cana-1177	284	28	of	of	ADP
cana-1177	284	29	.9859	.9859	PROPN
cana-1177	284	30	,	,	PUNCT
cana-1177	284	31	and	and	CCONJ
cana-1177	284	32	auc	auc	NOUN
cana-1177	284	33	of	of	ADP
cana-1177	284	34	0.9813	0.9813	NUM
cana-1177	284	35	.	.	PUNCT
cana-1177	285	1	upon	upon	SCONJ
cana-1177	285	2	doing	do	VERB
cana-1177	285	3	a	a	DET
cana-1177	285	4	10	10	NUM
cana-1177	285	5	-	-	ADJ
cana-1177	285	6	fold	fold	ADJ
cana-1177	285	7	crossvalidation	crossvalidation	NOUN
cana-1177	285	8	comparison	comparison	NOUN
cana-1177	285	9	,	,	PUNCT
cana-1177	285	10	the	the	DET
cana-1177	285	11	accuracy	accuracy	NOUN
cana-1177	285	12	of	of	ADP
cana-1177	285	13	the	the	DET
cana-1177	285	14	suggested	suggest	VERB
cana-1177	285	15	model	model	NOUN
cana-1177	285	16	was	be	AUX
cana-1177	285	17	found	find	VERB
cana-1177	285	18	to	to	PART
cana-1177	285	19	be	be	AUX
cana-1177	285	20	.9738	.9738	NOUN
cana-1177	285	21	surpassing	surpass	VERB
cana-1177	285	22	that	that	PRON
cana-1177	285	23	of	of	ADP
cana-1177	285	24	previous	previous	ADJ
cana-1177	285	25	published	publish	VERB
cana-1177	285	26	models	model	NOUN
cana-1177	285	27	.	.	PUNCT
cana-1177	286	1	due	due	ADP
cana-1177	286	2	to	to	ADP
cana-1177	286	3	small	small	ADJ
cana-1177	286	4	sample	sample	NOUN
cana-1177	286	5	of	of	ADP
cana-1177	286	6	population	population	NOUN
cana-1177	286	7	its	its	PRON
cana-1177	286	8	findings	finding	NOUN
cana-1177	286	9	may	may	AUX
cana-1177	286	10	not	not	PART
cana-1177	286	11	apply	apply	VERB
cana-1177	286	12	to	to	ADP
cana-1177	286	13	larger	large	ADJ
cana-1177	286	14	communications	communication	NOUN
cana-1177	286	15	on	on	ADP
cana-1177	286	16	applied	apply	VERB
cana-1177	286	17	nonlinear	nonlinear	ADJ
cana-1177	286	18	analysis	analysis	NOUN
cana-1177	286	19	issn	issn	NOUN
cana-1177	286	20	:	:	PUNCT
cana-1177	286	21	1074	1074	NUM
cana-1177	286	22	-	-	PUNCT
cana-1177	286	23	133x	133x	NUM
cana-1177	286	24	vol	vol	NOUN
cana-1177	286	25	31	31	NUM
cana-1177	286	26	no	no	NOUN
cana-1177	286	27	.	.	PUNCT
cana-1177	287	1	6s	6s	NUM
cana-1177	287	2	(	(	PUNCT
cana-1177	287	3	2024	2024	NUM
cana-1177	287	4	)	)	PUNCT
cana-1177	287	5	192	192	NUM
cana-1177	287	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-1177	287	7	groups	group	NOUN
cana-1177	287	8	of	of	ADP
cana-1177	287	9	people	people	NOUN
cana-1177	287	10	.	.	PUNCT
cana-1177	288	1	future	future	ADJ
cana-1177	288	2	research	research	NOUN
cana-1177	288	3	should	should	AUX
cana-1177	288	4	focus	focus	VERB
cana-1177	288	5	on	on	ADP
cana-1177	288	6	using	use	VERB
cana-1177	288	7	clinical	clinical	ADJ
cana-1177	288	8	datasets	dataset	NOUN
cana-1177	288	9	.	.	PUNCT
cana-1177	289	1	to	to	PART
cana-1177	289	2	make	make	VERB
cana-1177	289	3	the	the	DET
cana-1177	289	4	classification	classification	NOUN
cana-1177	289	5	more	more	ADV
cana-1177	289	6	accurate	accurate	ADJ
cana-1177	289	7	this	this	DET
cana-1177	289	8	study	study	NOUN
cana-1177	289	9	could	could	AUX
cana-1177	289	10	also	also	ADV
cana-1177	289	11	look	look	VERB
cana-1177	289	12	into	into	ADP
cana-1177	289	13	adding	add	VERB
cana-1177	289	14	different	different	ADJ
cana-1177	289	15	optimization	optimization	NOUN
cana-1177	289	16	strategies	strategy	NOUN
cana-1177	289	17	to	to	ADP
cana-1177	289	18	the	the	DET
cana-1177	289	19	suggested	suggest	VERB
cana-1177	289	20	approach	approach	NOUN
cana-1177	289	21	.	.	PUNCT
cana-1177	290	1	conflict	conflict	NOUN
cana-1177	290	2	of	of	ADP
cana-1177	290	3	interest	interest	NOUN
cana-1177	290	4	:	:	PUNCT
cana-1177	290	5	the	the	DET
cana-1177	290	6	authors	author	NOUN
cana-1177	290	7	declare	declare	VERB
cana-1177	290	8	that	that	SCONJ
cana-1177	290	9	there	there	PRON
cana-1177	290	10	is	be	VERB
cana-1177	290	11	no	no	DET
cana-1177	290	12	conflict	conflict	NOUN
cana-1177	290	13	of	of	ADP
cana-1177	290	14	interest	interest	NOUN
cana-1177	290	15	.	.	PUNCT
cana-1177	291	1	acknowledgement	acknowledgement	NOUN
cana-1177	291	2	:	:	PUNCT
cana-1177	291	3	the	the	DET
cana-1177	291	4	authors	author	NOUN
cana-1177	291	5	have	have	VERB
cana-1177	291	6	no	no	DET
cana-1177	291	7	support	support	NOUN
cana-1177	291	8	for	for	ADP
cana-1177	291	9	this	this	DET
cana-1177	291	10	work	work	NOUN
cana-1177	291	11	including	include	VERB
cana-1177	291	12	funding	funding	NOUN
cana-1177	291	13	,	,	PUNCT
cana-1177	291	14	grants	grant	NOUN
cana-1177	291	15	,	,	PUNCT
cana-1177	291	16	or	or	CCONJ
cana-1177	291	17	other	other	ADJ
cana-1177	291	18	financial	financial	ADJ
cana-1177	291	19	support	support	NOUN
cana-1177	291	20	to	to	PART
cana-1177	291	21	be	be	AUX
cana-1177	291	22	able	able	ADJ
cana-1177	291	23	to	to	PART
cana-1177	291	24	write	write	VERB
cana-1177	291	25	this	this	DET
cana-1177	291	26	manuscript	manuscript	NOUN
cana-1177	291	27	.	.	PUNCT
cana-1177	292	1	references	reference	NOUN
cana-1177	292	2	[	[	X
cana-1177	292	3	1	1	NUM
cana-1177	292	4	]	]	PUNCT
cana-1177	292	5	world	world	PROPN
cana-1177	292	6	health	health	NOUN
cana-1177	292	7	organization	organization	NOUN
cana-1177	292	8	,	,	PUNCT
cana-1177	292	9	cancer	cancer	NOUN
cana-1177	292	10	.	.	PUNCT
cana-1177	293	1	https://www.who.int/news-room/fact-sheets/detail/cancer	https://www.who.int/news-room/fact-sheets/detail/cancer	PROPN
cana-1177	293	2	.	.	PUNCT
cana-1177	294	1	accessed	access	VERB
cana-1177	294	2	2024	2024	NUM
cana-1177	294	3	.	.	PUNCT
cana-1177	295	1	[	[	X
cana-1177	295	2	2	2	NUM
cana-1177	295	3	]	]	X
cana-1177	295	4	jakhar	jakhar	PROPN
cana-1177	295	5	,	,	PUNCT
cana-1177	295	6	a.k	a.k	PROPN
cana-1177	295	7	.	.	PROPN
cana-1177	295	8	,	,	PUNCT
cana-1177	295	9	gupta	gupta	PROPN
cana-1177	295	10	,	,	PUNCT
cana-1177	295	11	a.	a.	NOUN
cana-1177	295	12	,	,	PUNCT
cana-1177	295	13	singh	singh	PROPN
cana-1177	295	14	,	,	PUNCT
cana-1177	295	15	m.	m.	NOUN
cana-1177	295	16	,	,	PUNCT
cana-1177	295	17	(	(	PUNCT
cana-1177	295	18	2023	2023	NUM
cana-1177	295	19	)	)	PUNCT
cana-1177	295	20	.	.	PUNCT
cana-1177	296	1	self	self	NOUN
cana-1177	296	2	:	:	PUNCT
cana-1177	296	3	a	a	DET
cana-1177	296	4	stacked	stack	VERB
cana-1177	296	5	-	-	PUNCT
cana-1177	296	6	based	base	VERB
cana-1177	296	7	ensemble	ensemble	ADJ
cana-1177	296	8	learning	learning	NOUN
cana-1177	296	9	framework	framework	NOUN
cana-1177	296	10	for	for	ADP
cana-1177	296	11	breast	breast	NOUN
cana-1177	296	12	cancer	cancer	NOUN
cana-1177	296	13	classification	classification	NOUN
cana-1177	296	14	.	.	PUNCT
cana-1177	297	1	evol	evol	NOUN
cana-1177	297	2	.	.	PUNCT
cana-1177	298	1	intell	intell	PROPN
cana-1177	298	2	.	.	PUNCT
cana-1177	299	1	1–16	1–16	PROPN
cana-1177	299	2	.	.	PUNCT
cana-1177	300	1	https://doi.org/10.1007/s12065-023-00824-4	https://doi.org/10.1007/s12065-023-00824-4	NUM
cana-1177	300	2	.	.	PUNCT
cana-1177	301	1	[	[	X
cana-1177	301	2	3	3	NUM
cana-1177	301	3	]	]	X
cana-1177	301	4	talatian	talatian	ADJ
cana-1177	301	5	azad	azad	NOUN
cana-1177	301	6	,	,	PUNCT
cana-1177	301	7	s.	s.	PROPN
cana-1177	301	8	,	,	PUNCT
cana-1177	301	9	ahmadi	ahmadi	PROPN
cana-1177	301	10	,	,	PUNCT
cana-1177	301	11	g.	g.	PROPN
cana-1177	301	12	,	,	PUNCT
cana-1177	301	13	rezaeipanah	rezaeipanah	PROPN
cana-1177	301	14	,	,	PUNCT
cana-1177	301	15	a.	a.	NOUN
cana-1177	301	16	(	(	PUNCT
cana-1177	301	17	2021	2021	NUM
cana-1177	301	18	)	)	PUNCT
cana-1177	301	19	.	.	PUNCT
cana-1177	302	1	an	an	DET
cana-1177	302	2	intelligent	intelligent	ADJ
cana-1177	302	3	ensemble	ensemble	ADJ
cana-1177	302	4	classification	classification	NOUN
cana-1177	302	5	method	method	NOUN
cana-1177	302	6	based	base	VERB
cana-1177	302	7	on	on	ADP
cana-1177	302	8	multilayer	multilayer	PROPN
cana-1177	302	9	perceptron	perceptron	PROPN
cana-1177	302	10	neural	neural	ADJ
cana-1177	302	11	network	network	NOUN
cana-1177	302	12	and	and	CCONJ
cana-1177	302	13	evolutionary	evolutionary	ADJ
cana-1177	302	14	algorithms	algorithm	NOUN
cana-1177	302	15	for	for	ADP
cana-1177	302	16	breast	breast	NOUN
cana-1177	302	17	cancer	cancer	NOUN
cana-1177	302	18	diagnosis	diagnosis	NOUN
cana-1177	302	19	.	.	PUNCT
cana-1177	303	1	j.	j.	PROPN
cana-1177	303	2	exp	exp	PROPN
cana-1177	303	3	.	.	PUNCT
cana-1177	304	1	theor	theor	PROPN
cana-1177	304	2	.	.	PUNCT
cana-1177	305	1	artif	artif	PROPN
cana-1177	305	2	.	.	PUNCT
cana-1177	306	1	intell	intell	PROPN
cana-1177	306	2	.	.	PUNCT
cana-1177	307	1	1–21	1–21	PROPN
cana-1177	307	2	.	.	PUNCT
cana-1177	308	1	[	[	X
cana-1177	308	2	4	4	NUM
cana-1177	308	3	]	]	X
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cana-1177	308	8	rashid	rashid	PROPN
cana-1177	308	9	,	,	PUNCT
cana-1177	308	10	j.	j.	PROPN
cana-1177	308	11	,	,	PUNCT
cana-1177	308	12	ali	ali	PROPN
cana-1177	308	13	,	,	PUNCT
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cana-1177	310	1	ieee	ieee	NOUN
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cana-1177	310	4	,	,	PUNCT
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cana-1177	310	8	.	.	PUNCT
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cana-1177	311	2	5	5	NUM
cana-1177	311	3	]	]	X
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cana-1177	311	5	,	,	PUNCT
cana-1177	311	6	t.	t.	PROPN
cana-1177	311	7	,	,	PUNCT
cana-1177	311	8	karigiri	karigiri	PROPN
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cana-1177	311	11	a.k	a.k	PROPN
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cana-1177	311	16	,	,	PUNCT
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cana-1177	311	25	,	,	PUNCT
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cana-1177	311	27	,	,	PUNCT
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cana-1177	311	29	,	,	PUNCT
cana-1177	311	30	a.	a.	NOUN
cana-1177	311	31	(	(	PUNCT
cana-1177	311	32	2022	2022	NUM
cana-1177	311	33	)	)	PUNCT
cana-1177	311	34	.	.	PUNCT
cana-1177	312	1	novel	novel	NOUN
cana-1177	312	2	based	base	VERB
cana-1177	312	3	ensemble	ensemble	ADJ
cana-1177	312	4	machine	machine	NOUN
cana-1177	312	5	learning	learn	VERB
cana-1177	312	6	classifiers	classifier	NOUN
cana-1177	312	7	for	for	ADP
cana-1177	312	8	detecting	detect	VERB
cana-1177	312	9	breast	breast	NOUN
cana-1177	312	10	cancer	cancer	NOUN
cana-1177	312	11	.	.	PUNCT
cana-1177	313	1	math	math	NOUN
cana-1177	313	2	.	.	PUNCT
cana-1177	314	1	probl	probl	PROPN
cana-1177	314	2	.	.	PUNCT
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cana-1177	317	6	m.a	m.a	PROPN
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cana-1177	317	8	,	,	PUNCT
cana-1177	317	9	2021	2021	NUM
cana-1177	317	10	.	.	PUNCT
cana-1177	318	1	breast	breast	NOUN
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cana-1177	319	2	.	.	PROPN
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cana-1177	319	4	.	.	PUNCT
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cana-1177	320	2	.	.	PUNCT
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cana-1177	320	4	.	.	PUNCT
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cana-1177	321	2	(	(	PUNCT
cana-1177	321	3	1	1	NUM
cana-1177	321	4	)	)	PUNCT
cana-1177	321	5	,	,	PUNCT
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cana-1177	321	7	.	.	PUNCT
cana-1177	322	1	[	[	X
cana-1177	322	2	7	7	NUM
cana-1177	322	3	]	]	PUNCT
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cana-1177	322	5	,	,	PUNCT
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cana-1177	322	7	.	.	PROPN
cana-1177	322	8	,	,	PUNCT
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cana-1177	322	10	,	,	PUNCT
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cana-1177	322	13	,	,	PUNCT
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cana-1177	322	16	y.m	y.m	PROPN
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cana-1177	325	3	.	.	PUNCT
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cana-1177	330	1	(	(	PUNCT
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cana-1177	330	3	)	)	PUNCT
cana-1177	330	4	,	,	PUNCT
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cana-1177	330	6	.	.	PUNCT
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cana-1177	331	3	]	]	SYM
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cana-1177	332	13	.	.	PUNCT
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cana-1177	333	3	.	.	PUNCT
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cana-1177	338	2	(	(	PUNCT
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cana-1177	338	4	)	)	PUNCT
cana-1177	338	5	,	,	PUNCT
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cana-1177	338	7	.	.	PUNCT
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cana-1177	339	2	.	.	PUNCT
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cana-1177	345	5	.	.	PUNCT
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cana-1177	355	9	.	.	PUNCT
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cana-1177	361	5	,	,	PUNCT
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cana-1177	361	7	,	,	PUNCT
cana-1177	361	8	mangasarian	mangasarian	NOUN
cana-1177	361	9	,	,	PUNCT
cana-1177	361	10	o.	o.	PROPN
cana-1177	361	11	,	,	PUNCT
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cana-1177	361	13	,	,	PUNCT
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cana-1177	363	8	,	,	PUNCT
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cana-1177	363	10	,	,	PUNCT
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cana-1177	368	2	.	.	PUNCT
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cana-1177	369	2	(	(	PUNCT
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cana-1177	369	4	)	)	PUNCT
cana-1177	369	5	,	,	PUNCT
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cana-1177	369	7	.	.	PUNCT
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cana-1177	374	2	.	.	PUNCT
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cana-1177	375	2	(	(	PUNCT
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cana-1177	375	4	)	)	PUNCT
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cana-1177	375	7	.	.	PUNCT
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cana-1177	378	5	,	,	PUNCT
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