id	sid	tid	token	lemma	pos
cana-3689	1	1	communications	communication	NOUN
cana-3689	1	2	on	on	ADP
cana-3689	1	3	applied	apply	VERB
cana-3689	1	4	nonlinear	nonlinear	ADJ
cana-3689	1	5	analysis	analysis	NOUN
cana-3689	1	6	issn	issn	NOUN
cana-3689	1	7	:	:	PUNCT
cana-3689	1	8	1074	1074	NUM
cana-3689	1	9	-	-	PUNCT
cana-3689	1	10	133x	133x	NUM
cana-3689	1	11	vol	vol	NOUN
cana-3689	1	12	32	32	NUM
cana-3689	1	13	no	no	NOUN
cana-3689	1	14	.	.	PUNCT
cana-3689	2	1	8s	8s	PROPN
cana-3689	2	2	(	(	PUNCT
cana-3689	2	3	2025	2025	NUM
cana-3689	2	4	)	)	PUNCT
cana-3689	2	5	https://internationalpubls.com	https://internationalpubls.com	X
cana-3689	2	6	444	444	NUM
cana-3689	2	7	comparative	comparative	ADJ
cana-3689	2	8	study	study	NOUN
cana-3689	2	9	of	of	ADP
cana-3689	2	10	machine	machine	NOUN
cana-3689	2	11	learning	learning	NOUN
cana-3689	2	12	models	model	NOUN
cana-3689	2	13	for	for	ADP
cana-3689	2	14	predicting	predict	VERB
cana-3689	2	15	cardio	cardio	NOUN
cana-3689	2	16	activities	activity	NOUN
cana-3689	2	17	based	base	VERB
cana-3689	2	18	on	on	ADP
cana-3689	2	19	diverse	diverse	ADJ
cana-3689	2	20	performance	performance	NOUN
cana-3689	2	21	metrics	metric	NOUN
cana-3689	2	22	dr	dr	PROPN
cana-3689	2	23	.	.	PROPN
cana-3689	2	24	m.	m.	PROPN
cana-3689	2	25	vijayakanth1	vijayakanth1	PROPN
cana-3689	2	26	*	*	PROPN
cana-3689	2	27	,	,	PUNCT
cana-3689	2	28	dr	dr	PROPN
cana-3689	2	29	.	.	PROPN
cana-3689	2	30	m.	m.	PROPN
cana-3689	2	31	rajendiran2	rajendiran2	PROPN
cana-3689	3	1	1*assistant	1*assistant	ADJ
cana-3689	3	2	professor	professor	NOUN
cana-3689	3	3	,	,	PUNCT
cana-3689	3	4	department	department	NOUN
cana-3689	3	5	of	of	ADP
cana-3689	3	6	computer	computer	NOUN
cana-3689	3	7	science	science	NOUN
cana-3689	3	8	,	,	PUNCT
cana-3689	3	9	thiru	thiru	PROPN
cana-3689	3	10	kolanjiappar	kolanjiappar	PROPN
cana-3689	3	11	government	government	PROPN
cana-3689	3	12	arts	arts	PROPN
cana-3689	3	13	college	college	PROPN
cana-3689	3	14	,	,	PUNCT
cana-3689	3	15	virudhachalam	virudhachalam	PROPN
cana-3689	3	16	,	,	PUNCT
cana-3689	3	17	tamil	tamil	PROPN
cana-3689	3	18	nadu	nadu	PROPN
cana-3689	3	19	,	,	PUNCT
cana-3689	3	20	india	india	PROPN
cana-3689	3	21	.	.	PUNCT
cana-3689	4	1	2assistant	2assistant	NUM
cana-3689	4	2	professor	professor	NOUN
cana-3689	4	3	,	,	PUNCT
cana-3689	4	4	department	department	NOUN
cana-3689	4	5	of	of	ADP
cana-3689	4	6	computer	computer	NOUN
cana-3689	4	7	science	science	NOUN
cana-3689	4	8	,	,	PUNCT
cana-3689	4	9	government	government	NOUN
cana-3689	4	10	arts	art	NOUN
cana-3689	4	11	and	and	CCONJ
cana-3689	4	12	science	science	PROPN
cana-3689	4	13	college	college	PROPN
cana-3689	4	14	,	,	PUNCT
cana-3689	4	15	jayankondam	jayankondam	NOUN
cana-3689	4	16	,	,	PUNCT
cana-3689	4	17	tamil	tamil	PROPN
cana-3689	4	18	nadu	nadu	PROPN
cana-3689	4	19	,	,	PUNCT
cana-3689	4	20	india	india	PROPN
cana-3689	4	21	.	.	PUNCT
cana-3689	4	22	email	email	NOUN
cana-3689	4	23	:	:	PUNCT
cana-3689	4	24	2rajendranmaha@gmail.com	2rajendranmaha@gmail.com	NUM
cana-3689	4	25	corresponding	correspond	VERB
cana-3689	4	26	email	email	NOUN
cana-3689	4	27	:	:	PUNCT
cana-3689	4	28	1*vijayakanth82@gmail.com	1*vijayakanth82@gmail.com	PROPN
cana-3689	4	29	article	article	NOUN
cana-3689	4	30	history	history	NOUN
cana-3689	4	31	:	:	PUNCT
cana-3689	4	32	received	receive	VERB
cana-3689	4	33	:	:	PUNCT
cana-3689	4	34	30	30	NUM
cana-3689	4	35	-	-	SYM
cana-3689	4	36	10	10	NUM
cana-3689	4	37	-	-	PUNCT
cana-3689	4	38	2024	2024	NUM
cana-3689	4	39	revised:05	revised:05	VERB
cana-3689	4	40	-	-	SYM
cana-3689	4	41	12	12	NUM
cana-3689	4	42	-	-	PUNCT
cana-3689	4	43	2024	2024	NUM
cana-3689	4	44	accepted:28	accepted:28	NUM
cana-3689	4	45	-	-	PUNCT
cana-3689	4	46	12	12	NUM
cana-3689	4	47	-	-	PUNCT
cana-3689	4	48	2024	2024	NUM
cana-3689	4	49	abstract	abstract	NOUN
cana-3689	4	50	:	:	PUNCT
cana-3689	4	51	the	the	DET
cana-3689	4	52	prediction	prediction	NOUN
cana-3689	4	53	of	of	ADP
cana-3689	4	54	cardio	cardio	NOUN
cana-3689	4	55	activities	activity	NOUN
cana-3689	4	56	is	be	AUX
cana-3689	4	57	vital	vital	ADJ
cana-3689	4	58	for	for	ADP
cana-3689	4	59	enhancing	enhance	VERB
cana-3689	4	60	the	the	DET
cana-3689	4	61	understanding	understanding	NOUN
cana-3689	4	62	of	of	ADP
cana-3689	4	63	physical	physical	ADJ
cana-3689	4	64	performance	performance	NOUN
cana-3689	4	65	and	and	CCONJ
cana-3689	4	66	facilitating	facilitate	VERB
cana-3689	4	67	effective	effective	ADJ
cana-3689	4	68	health	health	NOUN
cana-3689	4	69	monitoring	monitoring	NOUN
cana-3689	4	70	.	.	PUNCT
cana-3689	5	1	this	this	DET
cana-3689	5	2	research	research	NOUN
cana-3689	5	3	investigates	investigate	VERB
cana-3689	5	4	the	the	DET
cana-3689	5	5	implementation	implementation	NOUN
cana-3689	5	6	of	of	ADP
cana-3689	5	7	diverse	diverse	ADJ
cana-3689	5	8	machine	machine	NOUN
cana-3689	5	9	learning	learn	VERB
cana-3689	5	10	techniques	technique	NOUN
cana-3689	5	11	,	,	PUNCT
cana-3689	5	12	including	include	VERB
cana-3689	5	13	logistic	logistic	ADJ
cana-3689	5	14	regression	regression	NOUN
cana-3689	5	15	,	,	PUNCT
cana-3689	5	16	multilayer	multilayer	PROPN
cana-3689	5	17	perceptron	perceptron	PROPN
cana-3689	5	18	,	,	PUNCT
cana-3689	5	19	smo	smo	PROPN
cana-3689	5	20	,	,	PUNCT
cana-3689	5	21	j48	j48	PROPN
cana-3689	5	22	,	,	PUNCT
cana-3689	5	23	random	random	ADJ
cana-3689	5	24	forest	forest	NOUN
cana-3689	5	25	,	,	PUNCT
cana-3689	5	26	and	and	CCONJ
cana-3689	5	27	rep	rep	PROPN
cana-3689	5	28	tree	tree	NOUN
cana-3689	5	29	,	,	PUNCT
cana-3689	5	30	for	for	ADP
cana-3689	5	31	forecasting	forecast	VERB
cana-3689	5	32	cardio	cardio	NOUN
cana-3689	5	33	activity	activity	NOUN
cana-3689	5	34	outcomes	outcome	NOUN
cana-3689	5	35	.	.	PUNCT
cana-3689	6	1	the	the	DET
cana-3689	6	2	analysis	analysis	NOUN
cana-3689	6	3	is	be	AUX
cana-3689	6	4	conducted	conduct	VERB
cana-3689	6	5	using	use	VERB
cana-3689	6	6	an	an	DET
cana-3689	6	7	extensive	extensive	ADJ
cana-3689	6	8	set	set	NOUN
cana-3689	6	9	of	of	ADP
cana-3689	6	10	parameters	parameter	NOUN
cana-3689	6	11	,	,	PUNCT
cana-3689	6	12	such	such	ADJ
cana-3689	6	13	as	as	ADP
cana-3689	6	14	date	date	NOUN
cana-3689	6	15	,	,	PUNCT
cana-3689	6	16	type	type	NOUN
cana-3689	6	17	,	,	PUNCT
cana-3689	6	18	distance	distance	NOUN
cana-3689	6	19	(	(	PUNCT
cana-3689	6	20	km	km	NOUN
cana-3689	6	21	)	)	PUNCT
cana-3689	6	22	,	,	PUNCT
cana-3689	6	23	duration	duration	NOUN
cana-3689	6	24	,	,	PUNCT
cana-3689	6	25	average	average	ADJ
cana-3689	6	26	pace	pace	NOUN
cana-3689	6	27	,	,	PUNCT
cana-3689	6	28	average	average	ADJ
cana-3689	6	29	speed	speed	NOUN
cana-3689	6	30	(	(	PUNCT
cana-3689	6	31	km	km	NOUN
cana-3689	6	32	/	/	SYM
cana-3689	6	33	h	h	NOUN
cana-3689	6	34	)	)	PUNCT
cana-3689	6	35	,	,	PUNCT
cana-3689	6	36	calories	calorie	NOUN
cana-3689	6	37	burned	burn	VERB
cana-3689	6	38	,	,	PUNCT
cana-3689	6	39	and	and	CCONJ
cana-3689	6	40	climb	climb	VERB
cana-3689	6	41	(	(	PUNCT
cana-3689	6	42	m	m	NOUN
cana-3689	6	43	)	)	PUNCT
cana-3689	6	44	.	.	PUNCT
cana-3689	7	1	to	to	PART
cana-3689	7	2	assess	assess	VERB
cana-3689	7	3	the	the	DET
cana-3689	7	4	performance	performance	NOUN
cana-3689	7	5	and	and	CCONJ
cana-3689	7	6	reliability	reliability	NOUN
cana-3689	7	7	of	of	ADP
cana-3689	7	8	these	these	DET
cana-3689	7	9	models	model	NOUN
cana-3689	7	10	,	,	PUNCT
cana-3689	7	11	several	several	ADJ
cana-3689	7	12	metrics	metric	NOUN
cana-3689	7	13	namely	namely	ADV
cana-3689	7	14	tp	tp	NOUN
cana-3689	7	15	rate	rate	NOUN
cana-3689	7	16	,	,	PUNCT
cana-3689	7	17	fp	fp	ADJ
cana-3689	7	18	rate	rate	NOUN
cana-3689	7	19	,	,	PUNCT
cana-3689	7	20	precision	precision	NOUN
cana-3689	7	21	,	,	PUNCT
cana-3689	7	22	recall	recall	NOUN
cana-3689	7	23	,	,	PUNCT
cana-3689	7	24	f	f	X
cana-3689	7	25	-	-	PUNCT
cana-3689	7	26	measure	measure	NOUN
cana-3689	7	27	,	,	PUNCT
cana-3689	7	28	mcc	mcc	PROPN
cana-3689	7	29	,	,	PUNCT
cana-3689	7	30	roc	roc	PROPN
cana-3689	7	31	area	area	NOUN
cana-3689	7	32	,	,	PUNCT
cana-3689	7	33	and	and	CCONJ
cana-3689	7	34	prc	prc	PROPN
cana-3689	7	35	area	area	NOUN
cana-3689	7	36	are	be	AUX
cana-3689	7	37	employed	employ	VERB
cana-3689	7	38	.	.	PUNCT
cana-3689	8	1	the	the	DET
cana-3689	8	2	experimental	experimental	ADJ
cana-3689	8	3	findings	finding	NOUN
cana-3689	8	4	provide	provide	VERB
cana-3689	8	5	a	a	DET
cana-3689	8	6	comprehensive	comprehensive	ADJ
cana-3689	8	7	understanding	understanding	NOUN
cana-3689	8	8	of	of	ADP
cana-3689	8	9	the	the	DET
cana-3689	8	10	relative	relative	ADJ
cana-3689	8	11	effectiveness	effectiveness	NOUN
cana-3689	8	12	of	of	ADP
cana-3689	8	13	the	the	DET
cana-3689	8	14	models	model	NOUN
cana-3689	8	15	,	,	PUNCT
cana-3689	8	16	offering	offer	VERB
cana-3689	8	17	practical	practical	ADJ
cana-3689	8	18	insights	insight	NOUN
cana-3689	8	19	for	for	ADP
cana-3689	8	20	identifying	identify	VERB
cana-3689	8	21	optimal	optimal	ADJ
cana-3689	8	22	methodologies	methodology	NOUN
cana-3689	8	23	in	in	ADP
cana-3689	8	24	the	the	DET
cana-3689	8	25	domain	domain	NOUN
cana-3689	8	26	of	of	ADP
cana-3689	8	27	cardio	cardio	NOUN
cana-3689	8	28	activity	activity	NOUN
cana-3689	8	29	predictions	prediction	NOUN
cana-3689	8	30	.	.	PUNCT
cana-3689	9	1	keywords	keyword	NOUN
cana-3689	9	2	:	:	PUNCT
cana-3689	9	3	cardio	cardio	NOUN
cana-3689	9	4	activity	activity	NOUN
cana-3689	9	5	prediction	prediction	NOUN
cana-3689	9	6	,	,	PUNCT
cana-3689	9	7	health	health	NOUN
cana-3689	9	8	analytics	analytic	NOUN
cana-3689	9	9	,	,	PUNCT
cana-3689	9	10	data	datum	NOUN
cana-3689	9	11	mining	mining	NOUN
cana-3689	9	12	,	,	PUNCT
cana-3689	9	13	machine	machine	NOUN
cana-3689	9	14	learning	learn	VERB
cana-3689	9	15	techniques	technique	NOUN
cana-3689	9	16	,	,	PUNCT
cana-3689	9	17	and	and	CCONJ
cana-3689	9	18	performance	performance	NOUN
cana-3689	9	19	evaluation	evaluation	NOUN
cana-3689	9	20	.	.	PUNCT
cana-3689	10	1	1	1	X
cana-3689	10	2	.	.	X
cana-3689	10	3	introduction	introduction	NOUN
cana-3689	10	4	and	and	CCONJ
cana-3689	10	5	review	review	NOUN
cana-3689	10	6	of	of	ADP
cana-3689	10	7	the	the	DET
cana-3689	10	8	literature	literature	NOUN
cana-3689	10	9	the	the	DET
cana-3689	10	10	analysis	analysis	NOUN
cana-3689	10	11	and	and	CCONJ
cana-3689	10	12	forecasting	forecasting	NOUN
cana-3689	10	13	of	of	ADP
cana-3689	10	14	cardio	cardio	NOUN
cana-3689	10	15	activities	activity	NOUN
cana-3689	10	16	have	have	AUX
cana-3689	10	17	become	become	VERB
cana-3689	10	18	increasingly	increasingly	ADV
cana-3689	10	19	significant	significant	ADJ
cana-3689	10	20	in	in	ADP
cana-3689	10	21	advancing	advance	VERB
cana-3689	10	22	health	health	NOUN
cana-3689	10	23	monitoring	monitoring	NOUN
cana-3689	10	24	systems	system	NOUN
cana-3689	10	25	and	and	CCONJ
cana-3689	10	26	optimizing	optimize	VERB
cana-3689	10	27	physical	physical	ADJ
cana-3689	10	28	performance	performance	NOUN
cana-3689	10	29	.	.	PUNCT
cana-3689	11	1	the	the	DET
cana-3689	11	2	widespread	widespread	ADJ
cana-3689	11	3	adoption	adoption	NOUN
cana-3689	11	4	of	of	ADP
cana-3689	11	5	wearable	wearable	ADJ
cana-3689	11	6	fitness	fitness	NOUN
cana-3689	11	7	technologies	technology	NOUN
cana-3689	11	8	,	,	PUNCT
cana-3689	11	9	coupled	couple	VERB
cana-3689	11	10	with	with	ADP
cana-3689	11	11	the	the	DET
cana-3689	11	12	abundance	abundance	NOUN
cana-3689	11	13	of	of	ADP
cana-3689	11	14	detailed	detailed	ADJ
cana-3689	11	15	activity	activity	NOUN
cana-3689	11	16	data	datum	NOUN
cana-3689	11	17	,	,	PUNCT
cana-3689	11	18	has	have	AUX
cana-3689	11	19	spurred	spur	VERB
cana-3689	11	20	a	a	DET
cana-3689	11	21	growing	grow	VERB
cana-3689	11	22	interest	interest	NOUN
cana-3689	11	23	in	in	ADP
cana-3689	11	24	utilizing	utilize	VERB
cana-3689	11	25	machine	machine	NOUN
cana-3689	11	26	learning	learning	NOUN
cana-3689	11	27	methodologies	methodology	NOUN
cana-3689	11	28	to	to	PART
cana-3689	11	29	derive	derive	VERB
cana-3689	11	30	valuable	valuable	ADJ
cana-3689	11	31	insights	insight	NOUN
cana-3689	11	32	and	and	CCONJ
cana-3689	11	33	predict	predict	VERB
cana-3689	11	34	outcomes	outcome	NOUN
cana-3689	11	35	associated	associate	VERB
cana-3689	11	36	with	with	ADP
cana-3689	11	37	cardio	cardio	NOUN
cana-3689	11	38	activities	activity	NOUN
cana-3689	11	39	.	.	PUNCT
cana-3689	12	1	such	such	ADJ
cana-3689	12	2	predictive	predictive	ADJ
cana-3689	12	3	capabilities	capability	NOUN
cana-3689	12	4	enable	enable	VERB
cana-3689	12	5	individuals	individual	NOUN
cana-3689	12	6	to	to	PART
cana-3689	12	7	effectively	effectively	ADV
cana-3689	12	8	monitor	monitor	VERB
cana-3689	12	9	their	their	PRON
cana-3689	12	10	progress	progress	NOUN
cana-3689	12	11	,	,	PUNCT
cana-3689	12	12	detect	detect	VERB
cana-3689	12	13	potential	potential	ADJ
cana-3689	12	14	health	health	NOUN
cana-3689	12	15	concerns	concern	NOUN
cana-3689	12	16	,	,	PUNCT
cana-3689	12	17	and	and	CCONJ
cana-3689	12	18	customize	customize	VERB
cana-3689	12	19	fitness	fitness	NOUN
cana-3689	12	20	plans	plan	NOUN
cana-3689	12	21	tailored	tailor	VERB
cana-3689	12	22	to	to	ADP
cana-3689	12	23	their	their	PRON
cana-3689	12	24	unique	unique	ADJ
cana-3689	12	25	requirements	requirement	NOUN
cana-3689	12	26	.	.	PUNCT
cana-3689	13	1	this	this	DET
cana-3689	13	2	research	research	NOUN
cana-3689	13	3	centers	center	NOUN
cana-3689	13	4	on	on	ADP
cana-3689	13	5	employing	employ	VERB
cana-3689	13	6	machine	machine	NOUN
cana-3689	13	7	learning	learn	VERB
cana-3689	13	8	techniques	technique	NOUN
cana-3689	13	9	to	to	PART
cana-3689	13	10	forecast	forecast	VERB
cana-3689	13	11	cardio	cardio	NOUN
cana-3689	13	12	activity	activity	NOUN
cana-3689	13	13	outcomes	outcome	NOUN
cana-3689	13	14	based	base	VERB
cana-3689	13	15	on	on	ADP
cana-3689	13	16	a	a	DET
cana-3689	13	17	comprehensive	comprehensive	ADJ
cana-3689	13	18	range	range	NOUN
cana-3689	13	19	of	of	ADP
cana-3689	13	20	parameters	parameter	NOUN
cana-3689	13	21	,	,	PUNCT
cana-3689	13	22	including	include	VERB
cana-3689	13	23	date	date	NOUN
cana-3689	13	24	,	,	PUNCT
cana-3689	13	25	type	type	NOUN
cana-3689	13	26	,	,	PUNCT
cana-3689	13	27	distance	distance	NOUN
cana-3689	13	28	(	(	PUNCT
cana-3689	13	29	km	km	NOUN
cana-3689	13	30	)	)	PUNCT
cana-3689	13	31	,	,	PUNCT
cana-3689	13	32	duration	duration	NOUN
cana-3689	13	33	,	,	PUNCT
cana-3689	13	34	average	average	ADJ
cana-3689	13	35	pace	pace	NOUN
cana-3689	13	36	,	,	PUNCT
cana-3689	13	37	average	average	ADJ
cana-3689	13	38	speed	speed	NOUN
cana-3689	13	39	(	(	PUNCT
cana-3689	13	40	km	km	NOUN
cana-3689	13	41	/	/	SYM
cana-3689	13	42	h	h	NOUN
cana-3689	13	43	)	)	PUNCT
cana-3689	13	44	,	,	PUNCT
cana-3689	13	45	calories	calorie	NOUN
cana-3689	13	46	burned	burn	VERB
cana-3689	13	47	,	,	PUNCT
cana-3689	13	48	and	and	CCONJ
cana-3689	13	49	climb	climb	VERB
cana-3689	13	50	(	(	PUNCT
cana-3689	13	51	m	m	NOUN
cana-3689	13	52	)	)	PUNCT
cana-3689	13	53	.	.	PUNCT
cana-3689	14	1	these	these	DET
cana-3689	14	2	parameters	parameter	NOUN
cana-3689	14	3	encompass	encompass	VERB
cana-3689	14	4	essential	essential	ADJ
cana-3689	14	5	dimensions	dimension	NOUN
cana-3689	14	6	of	of	ADP
cana-3689	14	7	cardio	cardio	NOUN
cana-3689	14	8	activities	activity	NOUN
cana-3689	14	9	,	,	PUNCT
cana-3689	14	10	forming	form	VERB
cana-3689	14	11	a	a	DET
cana-3689	14	12	robust	robust	ADJ
cana-3689	14	13	foundation	foundation	NOUN
cana-3689	14	14	for	for	ADP
cana-3689	14	15	predictive	predictive	ADJ
cana-3689	14	16	modeling	modeling	NOUN
cana-3689	14	17	efforts	effort	NOUN
cana-3689	14	18	.	.	PUNCT
cana-3689	15	1	to	to	PART
cana-3689	15	2	address	address	VERB
cana-3689	15	3	this	this	DET
cana-3689	15	4	objective	objective	NOUN
cana-3689	15	5	,	,	PUNCT
cana-3689	15	6	a	a	DET
cana-3689	15	7	diverse	diverse	ADJ
cana-3689	15	8	set	set	NOUN
cana-3689	15	9	of	of	ADP
cana-3689	15	10	machine	machine	NOUN
cana-3689	15	11	learning	learn	VERB
cana-3689	15	12	algorithms	algorithm	NOUN
cana-3689	15	13	—	—	PUNCT
cana-3689	15	14	namely	namely	ADV
cana-3689	15	15	logistic	logistic	ADJ
cana-3689	15	16	regression	regression	NOUN
cana-3689	15	17	,	,	PUNCT
cana-3689	15	18	multilayer	multilayer	PROPN
cana-3689	15	19	perceptron	perceptron	PROPN
cana-3689	15	20	,	,	PUNCT
cana-3689	15	21	smo	smo	PROPN
cana-3689	15	22	,	,	PUNCT
cana-3689	15	23	j48	j48	PROPN
cana-3689	15	24	,	,	PUNCT
cana-3689	15	25	random	random	ADJ
cana-3689	15	26	forest	forest	NOUN
cana-3689	15	27	,	,	PUNCT
cana-3689	15	28	and	and	CCONJ
cana-3689	15	29	rep	rep	PROPN
cana-3689	15	30	tree	tree	NOUN
cana-3689	15	31	—	—	PUNCT
cana-3689	15	32	are	be	AUX
cana-3689	15	33	implemented	implement	VERB
cana-3689	15	34	and	and	CCONJ
cana-3689	15	35	subjected	subject	VERB
cana-3689	15	36	to	to	ADP
cana-3689	15	37	rigorous	rigorous	ADJ
cana-3689	15	38	evaluation	evaluation	NOUN
cana-3689	15	39	.	.	PUNCT
cana-3689	16	1	the	the	DET
cana-3689	16	2	performance	performance	NOUN
cana-3689	16	3	of	of	ADP
cana-3689	16	4	these	these	DET
cana-3689	16	5	models	model	NOUN
cana-3689	16	6	is	be	AUX
cana-3689	16	7	assessed	assess	VERB
cana-3689	16	8	using	use	VERB
cana-3689	16	9	various	various	ADJ
cana-3689	16	10	metrics	metric	NOUN
cana-3689	16	11	,	,	PUNCT
cana-3689	16	12	including	include	VERB
cana-3689	16	13	tp	tp	ADP
cana-3689	16	14	rate	rate	NOUN
cana-3689	16	15	,	,	PUNCT
cana-3689	16	16	fp	fp	ADJ
cana-3689	16	17	rate	rate	NOUN
cana-3689	16	18	,	,	PUNCT
cana-3689	16	19	precision	precision	NOUN
cana-3689	16	20	,	,	PUNCT
cana-3689	16	21	recall	recall	NOUN
cana-3689	16	22	,	,	PUNCT
cana-3689	16	23	f	f	X
cana-3689	16	24	-	-	PUNCT
cana-3689	16	25	measure	measure	NOUN
cana-3689	16	26	,	,	PUNCT
cana-3689	16	27	mcc	mcc	PROPN
cana-3689	16	28	,	,	PUNCT
cana-3689	16	29	roc	roc	PROPN
cana-3689	16	30	area	area	NOUN
cana-3689	16	31	,	,	PUNCT
cana-3689	16	32	and	and	CCONJ
cana-3689	16	33	prc	prc	PROPN
cana-3689	16	34	area	area	NOUN
cana-3689	16	35	,	,	PUNCT
cana-3689	16	36	to	to	PART
cana-3689	16	37	ensure	ensure	VERB
cana-3689	16	38	a	a	DET
cana-3689	16	39	comprehensive	comprehensive	ADJ
cana-3689	16	40	understanding	understanding	NOUN
cana-3689	16	41	of	of	ADP
cana-3689	16	42	their	their	PRON
cana-3689	16	43	predictive	predictive	ADJ
cana-3689	16	44	accuracy	accuracy	NOUN
cana-3689	16	45	and	and	CCONJ
cana-3689	16	46	reliability	reliability	NOUN
cana-3689	16	47	.	.	PUNCT
cana-3689	17	1	the	the	DET
cana-3689	17	2	mailto:2rajendranmaha@gmail.com	mailto:2rajendranmaha@gmail.com	NOUN
cana-3689	17	3	communications	communication	NOUN
cana-3689	17	4	on	on	ADP
cana-3689	17	5	applied	apply	VERB
cana-3689	17	6	nonlinear	nonlinear	ADJ
cana-3689	17	7	analysis	analysis	NOUN
cana-3689	17	8	issn	issn	NOUN
cana-3689	17	9	:	:	PUNCT
cana-3689	17	10	1074	1074	NUM
cana-3689	17	11	-	-	PUNCT
cana-3689	17	12	133x	133x	NUM
cana-3689	17	13	vol	vol	NOUN
cana-3689	17	14	32	32	NUM
cana-3689	17	15	no	no	NOUN
cana-3689	17	16	.	.	PUNCT
cana-3689	18	1	8s	8s	PROPN
cana-3689	18	2	(	(	PUNCT
cana-3689	18	3	2025	2025	NUM
cana-3689	18	4	)	)	PUNCT
cana-3689	18	5	https://internationalpubls.com	https://internationalpubls.com	X
cana-3689	18	6	445	445	NUM
cana-3689	18	7	overarching	overarching	ADJ
cana-3689	18	8	aim	aim	NOUN
cana-3689	18	9	of	of	ADP
cana-3689	18	10	this	this	DET
cana-3689	18	11	study	study	NOUN
cana-3689	18	12	is	be	AUX
cana-3689	18	13	to	to	PART
cana-3689	18	14	conduct	conduct	VERB
cana-3689	18	15	a	a	DET
cana-3689	18	16	detailed	detailed	ADJ
cana-3689	18	17	comparative	comparative	ADJ
cana-3689	18	18	analysis	analysis	NOUN
cana-3689	18	19	of	of	ADP
cana-3689	18	20	these	these	DET
cana-3689	18	21	machine	machine	NOUN
cana-3689	18	22	learning	learn	VERB
cana-3689	18	23	approaches	approach	NOUN
cana-3689	18	24	,	,	PUNCT
cana-3689	18	25	identifying	identify	VERB
cana-3689	18	26	their	their	PRON
cana-3689	18	27	respective	respective	ADJ
cana-3689	18	28	strengths	strength	NOUN
cana-3689	18	29	and	and	CCONJ
cana-3689	18	30	limitations	limitation	NOUN
cana-3689	18	31	in	in	ADP
cana-3689	18	32	tackling	tackle	VERB
cana-3689	18	33	cardio	cardio	NOUN
cana-3689	18	34	activity	activity	NOUN
cana-3689	18	35	prediction	prediction	NOUN
cana-3689	18	36	challenges	challenge	NOUN
cana-3689	18	37	.	.	PUNCT
cana-3689	19	1	by	by	ADP
cana-3689	19	2	examining	examine	VERB
cana-3689	19	3	the	the	DET
cana-3689	19	4	models	model	NOUN
cana-3689	19	5	'	'	PART
cana-3689	19	6	performance	performance	NOUN
cana-3689	19	7	across	across	ADP
cana-3689	19	8	multiple	multiple	ADJ
cana-3689	19	9	evaluation	evaluation	NOUN
cana-3689	19	10	criteria	criterion	NOUN
cana-3689	19	11	,	,	PUNCT
cana-3689	19	12	this	this	DET
cana-3689	19	13	work	work	NOUN
cana-3689	19	14	seeks	seek	VERB
cana-3689	19	15	to	to	PART
cana-3689	19	16	generate	generate	VERB
cana-3689	19	17	actionable	actionable	ADJ
cana-3689	19	18	insights	insight	NOUN
cana-3689	19	19	that	that	PRON
cana-3689	19	20	can	can	AUX
cana-3689	19	21	inform	inform	VERB
cana-3689	19	22	the	the	DET
cana-3689	19	23	development	development	NOUN
cana-3689	19	24	of	of	ADP
cana-3689	19	25	effective	effective	ADJ
cana-3689	19	26	predictive	predictive	ADJ
cana-3689	19	27	frameworks	framework	NOUN
cana-3689	19	28	for	for	ADP
cana-3689	19	29	health	health	NOUN
cana-3689	19	30	monitoring	monitoring	NOUN
cana-3689	19	31	and	and	CCONJ
cana-3689	19	32	fitness	fitness	NOUN
cana-3689	19	33	analysis	analysis	NOUN
cana-3689	19	34	.	.	PUNCT
cana-3689	20	1	the	the	DET
cana-3689	20	2	results	result	NOUN
cana-3689	20	3	of	of	ADP
cana-3689	20	4	this	this	DET
cana-3689	20	5	study	study	NOUN
cana-3689	20	6	have	have	VERB
cana-3689	20	7	the	the	DET
cana-3689	20	8	potential	potential	NOUN
cana-3689	20	9	to	to	PART
cana-3689	20	10	significantly	significantly	ADV
cana-3689	20	11	enhance	enhance	VERB
cana-3689	20	12	the	the	DET
cana-3689	20	13	accuracy	accuracy	NOUN
cana-3689	20	14	and	and	CCONJ
cana-3689	20	15	utility	utility	NOUN
cana-3689	20	16	of	of	ADP
cana-3689	20	17	cardio	cardio	NOUN
cana-3689	20	18	activity	activity	NOUN
cana-3689	20	19	predictions	prediction	NOUN
cana-3689	20	20	,	,	PUNCT
cana-3689	20	21	thereby	thereby	ADV
cana-3689	20	22	contributing	contribute	VERB
cana-3689	20	23	to	to	ADP
cana-3689	20	24	the	the	DET
cana-3689	20	25	evolution	evolution	NOUN
cana-3689	20	26	of	of	ADP
cana-3689	20	27	personalized	personalize	VERB
cana-3689	20	28	healthcare	healthcare	NOUN
cana-3689	20	29	solutions	solution	NOUN
cana-3689	20	30	and	and	CCONJ
cana-3689	20	31	fitness	fitness	NOUN
cana-3689	20	32	optimization	optimization	NOUN
cana-3689	20	33	strategies	strategy	NOUN
cana-3689	20	34	,	,	PUNCT
cana-3689	20	35	where	where	SCONJ
cana-3689	20	36	data	data	NOUN
cana-3689	20	37	-	-	PUNCT
cana-3689	20	38	driven	drive	VERB
cana-3689	20	39	decisionmaking	decisionmaking	NOUN
cana-3689	20	40	assumes	assume	VERB
cana-3689	20	41	a	a	DET
cana-3689	20	42	pivotal	pivotal	ADJ
cana-3689	20	43	role	role	NOUN
cana-3689	20	44	.	.	PUNCT
cana-3689	21	1	in	in	ADP
cana-3689	21	2	their	their	PRON
cana-3689	21	3	investigation	investigation	NOUN
cana-3689	21	4	,	,	PUNCT
cana-3689	21	5	smith	smith	PROPN
cana-3689	21	6	et	et	PROPN
cana-3689	21	7	al	al	PROPN
cana-3689	21	8	.	.	PROPN
cana-3689	22	1	(	(	PUNCT
cana-3689	22	2	2019	2019	NUM
cana-3689	22	3	)	)	PUNCT
cana-3689	22	4	analyzed	analyze	VERB
cana-3689	22	5	the	the	DET
cana-3689	22	6	predictive	predictive	ADJ
cana-3689	22	7	capabilities	capability	NOUN
cana-3689	22	8	of	of	ADP
cana-3689	22	9	random	random	ADJ
cana-3689	22	10	forest	forest	NOUN
cana-3689	22	11	and	and	CCONJ
cana-3689	22	12	multilayer	multilayer	ADJ
cana-3689	22	13	perceptron	perceptron	PROPN
cana-3689	22	14	models	model	NOUN
cana-3689	22	15	for	for	ADP
cana-3689	22	16	cardio	cardio	NOUN
cana-3689	22	17	activities	activity	NOUN
cana-3689	22	18	,	,	PUNCT
cana-3689	22	19	using	use	VERB
cana-3689	22	20	datasets	dataset	NOUN
cana-3689	22	21	derived	derive	VERB
cana-3689	22	22	from	from	ADP
cana-3689	22	23	wearable	wearable	ADJ
cana-3689	22	24	devices	device	NOUN
cana-3689	22	25	.	.	PUNCT
cana-3689	23	1	their	their	PRON
cana-3689	23	2	study	study	NOUN
cana-3689	23	3	integrated	integrate	VERB
cana-3689	23	4	parameters	parameter	NOUN
cana-3689	23	5	such	such	ADJ
cana-3689	23	6	as	as	ADP
cana-3689	23	7	duration	duration	NOUN
cana-3689	23	8	,	,	PUNCT
cana-3689	23	9	distance	distance	NOUN
cana-3689	23	10	(	(	PUNCT
cana-3689	23	11	km	km	NOUN
cana-3689	23	12	)	)	PUNCT
cana-3689	23	13	,	,	PUNCT
cana-3689	23	14	calories	calorie	NOUN
cana-3689	23	15	burned	burn	VERB
cana-3689	23	16	,	,	PUNCT
cana-3689	23	17	and	and	CCONJ
cana-3689	23	18	average	average	ADJ
cana-3689	23	19	speed	speed	NOUN
cana-3689	23	20	(	(	PUNCT
cana-3689	23	21	km	km	NOUN
cana-3689	23	22	/	/	SYM
cana-3689	23	23	h	h	NOUN
cana-3689	23	24	)	)	PUNCT
cana-3689	23	25	,	,	PUNCT
cana-3689	23	26	employing	employ	VERB
cana-3689	23	27	metrics	metric	NOUN
cana-3689	23	28	like	like	ADP
cana-3689	23	29	precision	precision	NOUN
cana-3689	23	30	,	,	PUNCT
cana-3689	23	31	recall	recall	NOUN
cana-3689	23	32	,	,	PUNCT
cana-3689	23	33	and	and	CCONJ
cana-3689	23	34	f	f	X
cana-3689	23	35	-	-	PUNCT
cana-3689	23	36	measure	measure	NOUN
cana-3689	23	37	to	to	PART
cana-3689	23	38	evaluate	evaluate	VERB
cana-3689	23	39	model	model	NOUN
cana-3689	23	40	performance	performance	NOUN
cana-3689	23	41	.	.	PUNCT
cana-3689	24	1	their	their	PRON
cana-3689	24	2	findings	finding	NOUN
cana-3689	24	3	indicated	indicate	VERB
cana-3689	24	4	that	that	SCONJ
cana-3689	24	5	random	random	ADJ
cana-3689	24	6	forest	forest	NOUN
cana-3689	24	7	surpassed	surpass	VERB
cana-3689	24	8	other	other	ADJ
cana-3689	24	9	approaches	approach	NOUN
cana-3689	24	10	,	,	PUNCT
cana-3689	24	11	achieving	achieve	VERB
cana-3689	24	12	an	an	DET
cana-3689	24	13	average	average	ADJ
cana-3689	24	14	precision	precision	NOUN
cana-3689	24	15	of	of	ADP
cana-3689	24	16	92	92	NUM
cana-3689	24	17	%	%	NOUN
cana-3689	24	18	and	and	CCONJ
cana-3689	24	19	an	an	DET
cana-3689	24	20	f	f	NOUN
cana-3689	24	21	-	-	PUNCT
cana-3689	24	22	measure	measure	NOUN
cana-3689	24	23	of	of	ADP
cana-3689	24	24	90	90	NUM
cana-3689	24	25	%	%	NOUN
cana-3689	24	26	.	.	PUNCT
cana-3689	25	1	this	this	DET
cana-3689	25	2	research	research	NOUN
cana-3689	25	3	underscores	underscore	VERB
cana-3689	25	4	the	the	DET
cana-3689	25	5	reliability	reliability	NOUN
cana-3689	25	6	of	of	ADP
cana-3689	25	7	ensemble	ensemble	ADJ
cana-3689	25	8	-	-	PUNCT
cana-3689	25	9	based	base	VERB
cana-3689	25	10	methods	method	NOUN
cana-3689	25	11	in	in	ADP
cana-3689	25	12	addressing	address	VERB
cana-3689	25	13	the	the	DET
cana-3689	25	14	challenges	challenge	NOUN
cana-3689	25	15	posed	pose	VERB
cana-3689	25	16	by	by	ADP
cana-3689	25	17	highdimensional	highdimensional	ADJ
cana-3689	25	18	datasets	dataset	NOUN
cana-3689	25	19	in	in	ADP
cana-3689	25	20	cardio	cardio	NOUN
cana-3689	25	21	activity	activity	NOUN
cana-3689	25	22	prediction	prediction	NOUN
cana-3689	25	23	tasks	task	NOUN
cana-3689	25	24	.	.	PUNCT
cana-3689	26	1	brown	brown	PROPN
cana-3689	26	2	and	and	CCONJ
cana-3689	26	3	lee	lee	PROPN
cana-3689	26	4	(	(	PUNCT
cana-3689	26	5	2020	2020	NUM
cana-3689	26	6	)	)	PUNCT
cana-3689	26	7	conducted	conduct	VERB
cana-3689	26	8	a	a	DET
cana-3689	26	9	detailed	detailed	ADJ
cana-3689	26	10	assessment	assessment	NOUN
cana-3689	26	11	of	of	ADP
cana-3689	26	12	logistic	logistic	ADJ
cana-3689	26	13	regression	regression	NOUN
cana-3689	26	14	and	and	CCONJ
cana-3689	26	15	smo	smo	NOUN
cana-3689	26	16	models	model	NOUN
cana-3689	26	17	for	for	ADP
cana-3689	26	18	predicting	predict	VERB
cana-3689	26	19	cardio	cardio	NOUN
cana-3689	26	20	activities	activity	NOUN
cana-3689	26	21	using	use	VERB
cana-3689	26	22	a	a	DET
cana-3689	26	23	dataset	dataset	NOUN
cana-3689	26	24	containing	contain	VERB
cana-3689	26	25	parameters	parameter	NOUN
cana-3689	26	26	such	such	ADJ
cana-3689	26	27	as	as	ADP
cana-3689	26	28	type	type	NOUN
cana-3689	26	29	,	,	PUNCT
cana-3689	26	30	average	average	ADJ
cana-3689	26	31	pace	pace	NOUN
cana-3689	26	32	,	,	PUNCT
cana-3689	26	33	and	and	CCONJ
cana-3689	26	34	climb	climb	VERB
cana-3689	26	35	(	(	PUNCT
cana-3689	26	36	m	m	NOUN
cana-3689	26	37	)	)	PUNCT
cana-3689	26	38	.	.	PUNCT
cana-3689	27	1	they	they	PRON
cana-3689	27	2	observed	observe	VERB
cana-3689	27	3	that	that	SCONJ
cana-3689	27	4	while	while	SCONJ
cana-3689	27	5	logistic	logistic	ADJ
cana-3689	27	6	regression	regression	NOUN
cana-3689	27	7	performed	perform	VERB
cana-3689	27	8	better	well	ADV
cana-3689	27	9	on	on	ADP
cana-3689	27	10	linearly	linearly	ADV
cana-3689	27	11	separable	separable	ADJ
cana-3689	27	12	datasets	dataset	NOUN
cana-3689	27	13	,	,	PUNCT
cana-3689	27	14	smo	smo	PROPN
cana-3689	27	15	excelled	excel	VERB
cana-3689	27	16	in	in	ADP
cana-3689	27	17	identifying	identify	VERB
cana-3689	27	18	patterns	pattern	NOUN
cana-3689	27	19	within	within	ADP
cana-3689	27	20	non	non	ADJ
cana-3689	27	21	-	-	ADJ
cana-3689	27	22	linear	linear	ADJ
cana-3689	27	23	datasets	dataset	NOUN
cana-3689	27	24	.	.	PUNCT
cana-3689	28	1	with	with	ADP
cana-3689	28	2	a	a	DET
cana-3689	28	3	focus	focus	NOUN
cana-3689	28	4	on	on	ADP
cana-3689	28	5	performance	performance	NOUN
cana-3689	28	6	metrics	metric	NOUN
cana-3689	28	7	like	like	ADP
cana-3689	28	8	mcc	mcc	NOUN
cana-3689	28	9	and	and	CCONJ
cana-3689	28	10	roc	roc	PROPN
cana-3689	28	11	area	area	NOUN
cana-3689	28	12	,	,	PUNCT
cana-3689	28	13	their	their	PRON
cana-3689	28	14	results	result	NOUN
cana-3689	28	15	showcased	showcase	VERB
cana-3689	28	16	smo	smo	PROPN
cana-3689	28	17	’s	’s	PART
cana-3689	28	18	superiority	superiority	NOUN
cana-3689	28	19	,	,	PUNCT
cana-3689	28	20	achieving	achieve	VERB
cana-3689	28	21	an	an	DET
cana-3689	28	22	mcc	mcc	NOUN
cana-3689	28	23	of	of	ADP
cana-3689	28	24	0.85	0.85	NUM
cana-3689	28	25	and	and	CCONJ
cana-3689	28	26	a	a	DET
cana-3689	28	27	roc	roc	PROPN
cana-3689	28	28	area	area	NOUN
cana-3689	28	29	of	of	ADP
cana-3689	28	30	0.91	0.91	NUM
cana-3689	28	31	,	,	PUNCT
cana-3689	28	32	particularly	particularly	ADV
cana-3689	28	33	in	in	ADP
cana-3689	28	34	climbing	climbing	NOUN
cana-3689	28	35	activities	activity	NOUN
cana-3689	28	36	,	,	PUNCT
cana-3689	28	37	thereby	thereby	ADV
cana-3689	28	38	emphasizing	emphasize	VERB
cana-3689	28	39	its	its	PRON
cana-3689	28	40	utility	utility	NOUN
cana-3689	28	41	in	in	ADP
cana-3689	28	42	scenarios	scenario	NOUN
cana-3689	28	43	with	with	ADP
cana-3689	28	44	complex	complex	ADJ
cana-3689	28	45	data	datum	NOUN
cana-3689	28	46	relationships	relationship	NOUN
cana-3689	28	47	.	.	PUNCT
cana-3689	29	1	johnson	johnson	PROPN
cana-3689	29	2	et	et	PROPN
cana-3689	29	3	al	al	PROPN
cana-3689	29	4	.	.	PROPN
cana-3689	30	1	(	(	PUNCT
cana-3689	30	2	2018	2018	NUM
cana-3689	30	3	)	)	PUNCT
cana-3689	30	4	conducted	conduct	VERB
cana-3689	30	5	a	a	DET
cana-3689	30	6	comparative	comparative	ADJ
cana-3689	30	7	study	study	NOUN
cana-3689	30	8	of	of	ADP
cana-3689	30	9	decision	decision	NOUN
cana-3689	30	10	tree	tree	NOUN
cana-3689	30	11	algorithms	algorithm	NOUN
cana-3689	30	12	,	,	PUNCT
cana-3689	30	13	namely	namely	ADV
cana-3689	30	14	j48	j48	ADJ
cana-3689	30	15	and	and	CCONJ
cana-3689	30	16	rep	rep	NOUN
cana-3689	30	17	tree	tree	NOUN
cana-3689	30	18	,	,	PUNCT
cana-3689	30	19	for	for	ADP
cana-3689	30	20	predicting	predict	VERB
cana-3689	30	21	cardio	cardio	NOUN
cana-3689	30	22	activity	activity	NOUN
cana-3689	30	23	outcomes	outcome	NOUN
cana-3689	30	24	.	.	PUNCT
cana-3689	31	1	their	their	PRON
cana-3689	31	2	work	work	NOUN
cana-3689	31	3	employed	employ	VERB
cana-3689	31	4	a	a	DET
cana-3689	31	5	dataset	dataset	NOUN
cana-3689	31	6	enriched	enrich	VERB
cana-3689	31	7	with	with	ADP
cana-3689	31	8	parameters	parameter	NOUN
cana-3689	31	9	like	like	ADP
cana-3689	31	10	date	date	NOUN
cana-3689	31	11	,	,	PUNCT
cana-3689	31	12	type	type	NOUN
cana-3689	31	13	,	,	PUNCT
cana-3689	31	14	and	and	CCONJ
cana-3689	31	15	distance	distance	NOUN
cana-3689	31	16	(	(	PUNCT
cana-3689	31	17	km	km	NOUN
cana-3689	31	18	)	)	PUNCT
cana-3689	31	19	to	to	PART
cana-3689	31	20	evaluate	evaluate	VERB
cana-3689	31	21	the	the	DET
cana-3689	31	22	influence	influence	NOUN
cana-3689	31	23	of	of	ADP
cana-3689	31	24	tree	tree	NOUN
cana-3689	31	25	structures	structure	NOUN
cana-3689	31	26	on	on	ADP
cana-3689	31	27	predictive	predictive	ADJ
cana-3689	31	28	accuracy	accuracy	NOUN
cana-3689	31	29	.	.	PUNCT
cana-3689	32	1	the	the	DET
cana-3689	32	2	research	research	NOUN
cana-3689	32	3	demonstrated	demonstrate	VERB
cana-3689	32	4	that	that	SCONJ
cana-3689	32	5	rep	rep	NOUN
cana-3689	32	6	tree	tree	NOUN
cana-3689	32	7	achieved	achieve	VERB
cana-3689	32	8	greater	great	ADJ
cana-3689	32	9	accuracy	accuracy	NOUN
cana-3689	32	10	and	and	CCONJ
cana-3689	32	11	reduced	reduce	VERB
cana-3689	32	12	computational	computational	ADJ
cana-3689	32	13	time	time	NOUN
cana-3689	32	14	,	,	PUNCT
cana-3689	32	15	with	with	ADP
cana-3689	32	16	an	an	DET
cana-3689	32	17	average	average	ADJ
cana-3689	32	18	tp	tp	NOUN
cana-3689	32	19	rate	rate	NOUN
cana-3689	32	20	of	of	ADP
cana-3689	32	21	0.89	0.89	NUM
cana-3689	32	22	compared	compare	VERB
cana-3689	32	23	to	to	ADP
cana-3689	32	24	j48	j48	PROPN
cana-3689	32	25	's	's	PART
cana-3689	32	26	0.84	0.84	NUM
cana-3689	32	27	.	.	PUNCT
cana-3689	33	1	these	these	DET
cana-3689	33	2	results	result	NOUN
cana-3689	33	3	highlight	highlight	VERB
cana-3689	33	4	the	the	DET
cana-3689	33	5	efficiency	efficiency	NOUN
cana-3689	33	6	of	of	ADP
cana-3689	33	7	lightweight	lightweight	ADJ
cana-3689	33	8	decision	decision	NOUN
cana-3689	33	9	tree	tree	NOUN
cana-3689	33	10	models	model	NOUN
cana-3689	33	11	,	,	PUNCT
cana-3689	33	12	particularly	particularly	ADV
cana-3689	33	13	for	for	ADP
cana-3689	33	14	real	real	ADJ
cana-3689	33	15	-	-	PUNCT
cana-3689	33	16	time	time	NOUN
cana-3689	33	17	predictive	predictive	ADJ
cana-3689	33	18	applications	application	NOUN
cana-3689	33	19	.	.	PUNCT
cana-3689	34	1	martinez	martinez	PROPN
cana-3689	34	2	et	et	PROPN
cana-3689	34	3	al	al	PROPN
cana-3689	34	4	.	.	PROPN
cana-3689	35	1	(	(	PUNCT
cana-3689	35	2	2021	2021	NUM
cana-3689	35	3	)	)	PUNCT
cana-3689	35	4	proposed	propose	VERB
cana-3689	35	5	a	a	DET
cana-3689	35	6	hybrid	hybrid	ADJ
cana-3689	35	7	model	model	NOUN
cana-3689	35	8	combining	combine	VERB
cana-3689	35	9	random	random	ADJ
cana-3689	35	10	forest	forest	NOUN
cana-3689	35	11	and	and	CCONJ
cana-3689	35	12	multilayer	multilayer	PROPN
cana-3689	35	13	perceptron	perceptron	PROPN
cana-3689	35	14	to	to	PART
cana-3689	35	15	improve	improve	VERB
cana-3689	35	16	cardio	cardio	NOUN
cana-3689	35	17	activity	activity	NOUN
cana-3689	35	18	predictions	prediction	NOUN
cana-3689	35	19	.	.	PUNCT
cana-3689	36	1	their	their	PRON
cana-3689	36	2	dataset	dataset	NOUN
cana-3689	36	3	incorporated	incorporate	VERB
cana-3689	36	4	parameters	parameter	NOUN
cana-3689	36	5	such	such	ADJ
cana-3689	36	6	as	as	ADP
cana-3689	36	7	duration	duration	NOUN
cana-3689	36	8	,	,	PUNCT
cana-3689	36	9	calories	calorie	NOUN
cana-3689	36	10	burned	burn	VERB
cana-3689	36	11	,	,	PUNCT
cana-3689	36	12	and	and	CCONJ
cana-3689	36	13	average	average	ADJ
cana-3689	36	14	speed	speed	NOUN
cana-3689	36	15	(	(	PUNCT
cana-3689	36	16	km	km	NOUN
cana-3689	36	17	/	/	SYM
cana-3689	36	18	h	h	NOUN
cana-3689	36	19	)	)	PUNCT
cana-3689	36	20	.	.	PUNCT
cana-3689	37	1	by	by	ADP
cana-3689	37	2	leveraging	leverage	VERB
cana-3689	37	3	ensemble	ensemble	ADJ
cana-3689	37	4	methods	method	NOUN
cana-3689	37	5	,	,	PUNCT
cana-3689	37	6	the	the	DET
cana-3689	37	7	hybrid	hybrid	ADJ
cana-3689	37	8	approach	approach	NOUN
cana-3689	37	9	significantly	significantly	ADV
cana-3689	37	10	enhanced	enhance	VERB
cana-3689	37	11	precision	precision	NOUN
cana-3689	37	12	and	and	CCONJ
cana-3689	37	13	recall	recall	NOUN
cana-3689	37	14	,	,	PUNCT
cana-3689	37	15	especially	especially	ADV
cana-3689	37	16	for	for	ADP
cana-3689	37	17	high	high	ADJ
cana-3689	37	18	-	-	PUNCT
cana-3689	37	19	intensity	intensity	NOUN
cana-3689	37	20	activities	activity	NOUN
cana-3689	37	21	,	,	PUNCT
cana-3689	37	22	achieving	achieve	VERB
cana-3689	37	23	a	a	DET
cana-3689	37	24	precision	precision	NOUN
cana-3689	37	25	of	of	ADP
cana-3689	37	26	94	94	NUM
cana-3689	37	27	%	%	NOUN
cana-3689	37	28	and	and	CCONJ
cana-3689	37	29	recall	recall	NOUN
cana-3689	37	30	of	of	ADP
cana-3689	37	31	92	92	NUM
cana-3689	37	32	%	%	NOUN
cana-3689	37	33	.	.	PUNCT
cana-3689	38	1	this	this	DET
cana-3689	38	2	study	study	NOUN
cana-3689	38	3	underscores	underscore	VERB
cana-3689	38	4	the	the	DET
cana-3689	38	5	potential	potential	NOUN
cana-3689	38	6	of	of	ADP
cana-3689	38	7	hybrid	hybrid	ADJ
cana-3689	38	8	models	model	NOUN
cana-3689	38	9	in	in	ADP
cana-3689	38	10	achieving	achieve	VERB
cana-3689	38	11	superior	superior	ADJ
cana-3689	38	12	predictive	predictive	ADJ
cana-3689	38	13	performance	performance	NOUN
cana-3689	38	14	for	for	ADP
cana-3689	38	15	complex	complex	ADJ
cana-3689	38	16	activity	activity	NOUN
cana-3689	38	17	patterns	pattern	NOUN
cana-3689	38	18	.	.	PUNCT
cana-3689	39	1	gupta	gupta	PROPN
cana-3689	39	2	et	et	PROPN
cana-3689	39	3	al	al	PROPN
cana-3689	39	4	.	.	PROPN
cana-3689	40	1	(	(	PUNCT
cana-3689	40	2	2020	2020	NUM
cana-3689	40	3	)	)	PUNCT
cana-3689	40	4	examined	examine	VERB
cana-3689	40	5	the	the	DET
cana-3689	40	6	role	role	NOUN
cana-3689	40	7	of	of	ADP
cana-3689	40	8	feature	feature	NOUN
cana-3689	40	9	selection	selection	NOUN
cana-3689	40	10	in	in	ADP
cana-3689	40	11	improving	improve	VERB
cana-3689	40	12	the	the	DET
cana-3689	40	13	performance	performance	NOUN
cana-3689	40	14	of	of	ADP
cana-3689	40	15	logistic	logistic	ADJ
cana-3689	40	16	regression	regression	NOUN
cana-3689	40	17	and	and	CCONJ
cana-3689	40	18	random	random	ADJ
cana-3689	40	19	forest	forest	NOUN
cana-3689	40	20	models	model	NOUN
cana-3689	40	21	for	for	ADP
cana-3689	40	22	cardio	cardio	NOUN
cana-3689	40	23	activity	activity	NOUN
cana-3689	40	24	prediction	prediction	NOUN
cana-3689	40	25	.	.	PUNCT
cana-3689	41	1	their	their	PRON
cana-3689	41	2	analysis	analysis	NOUN
cana-3689	41	3	considered	consider	VERB
cana-3689	41	4	parameters	parameter	NOUN
cana-3689	41	5	like	like	ADP
cana-3689	41	6	type	type	NOUN
cana-3689	41	7	,	,	PUNCT
cana-3689	41	8	distance	distance	NOUN
cana-3689	41	9	(	(	PUNCT
cana-3689	41	10	km	km	NOUN
cana-3689	41	11	)	)	PUNCT
cana-3689	41	12	,	,	PUNCT
cana-3689	41	13	and	and	CCONJ
cana-3689	41	14	climb	climb	VERB
cana-3689	41	15	(	(	PUNCT
cana-3689	41	16	m	m	NOUN
cana-3689	41	17	)	)	PUNCT
cana-3689	41	18	,	,	PUNCT
cana-3689	41	19	demonstrating	demonstrate	VERB
cana-3689	41	20	that	that	SCONJ
cana-3689	41	21	optimal	optimal	ADJ
cana-3689	41	22	feature	feature	NOUN
cana-3689	41	23	selection	selection	NOUN
cana-3689	41	24	substantially	substantially	ADV
cana-3689	41	25	enhanced	enhance	VERB
cana-3689	41	26	precision	precision	NOUN
cana-3689	41	27	and	and	CCONJ
cana-3689	41	28	roc	roc	PROPN
cana-3689	41	29	area	area	NOUN
cana-3689	41	30	.	.	PUNCT
cana-3689	42	1	logistic	logistic	ADJ
cana-3689	42	2	regression	regression	NOUN
cana-3689	42	3	attained	attain	VERB
cana-3689	42	4	a	a	DET
cana-3689	42	5	precision	precision	NOUN
cana-3689	42	6	of	of	ADP
cana-3689	42	7	85	85	NUM
cana-3689	42	8	%	%	NOUN
cana-3689	42	9	with	with	ADP
cana-3689	42	10	selected	select	VERB
cana-3689	42	11	features	feature	NOUN
cana-3689	42	12	,	,	PUNCT
cana-3689	42	13	while	while	SCONJ
cana-3689	42	14	random	random	ADJ
cana-3689	42	15	forest	forest	NOUN
cana-3689	42	16	achieved	achieve	VERB
cana-3689	42	17	a	a	DET
cana-3689	42	18	roc	roc	PROPN
cana-3689	42	19	area	area	NOUN
cana-3689	42	20	of	of	ADP
cana-3689	42	21	0.93	0.93	NUM
cana-3689	42	22	,	,	PUNCT
cana-3689	42	23	emphasizing	emphasize	VERB
cana-3689	42	24	the	the	DET
cana-3689	42	25	importance	importance	NOUN
cana-3689	42	26	of	of	ADP
cana-3689	42	27	dimensionality	dimensionality	NOUN
cana-3689	42	28	reduction	reduction	NOUN
cana-3689	42	29	in	in	ADP
cana-3689	42	30	improving	improve	VERB
cana-3689	42	31	computational	computational	ADJ
cana-3689	42	32	efficiency	efficiency	NOUN
cana-3689	42	33	and	and	CCONJ
cana-3689	42	34	model	model	NOUN
cana-3689	42	35	accuracy	accuracy	NOUN
cana-3689	42	36	.	.	PUNCT
cana-3689	43	1	wang	wang	PROPN
cana-3689	43	2	and	and	CCONJ
cana-3689	43	3	zhang	zhang	PROPN
cana-3689	43	4	(	(	PUNCT
cana-3689	43	5	2017	2017	NUM
cana-3689	43	6	)	)	PUNCT
cana-3689	43	7	delved	delve	VERB
cana-3689	43	8	into	into	ADP
cana-3689	43	9	the	the	DET
cana-3689	43	10	predictive	predictive	ADJ
cana-3689	43	11	potential	potential	NOUN
cana-3689	43	12	of	of	ADP
cana-3689	43	13	multilayer	multilayer	ADJ
cana-3689	43	14	perceptron	perceptron	PROPN
cana-3689	43	15	models	model	NOUN
cana-3689	43	16	for	for	ADP
cana-3689	43	17	identifying	identify	VERB
cana-3689	43	18	cardio	cardio	NOUN
cana-3689	43	19	activity	activity	NOUN
cana-3689	43	20	types	type	NOUN
cana-3689	43	21	using	use	VERB
cana-3689	43	22	parameters	parameter	NOUN
cana-3689	43	23	such	such	ADJ
cana-3689	43	24	as	as	ADP
cana-3689	43	25	average	average	ADJ
cana-3689	43	26	pace	pace	NOUN
cana-3689	43	27	,	,	PUNCT
cana-3689	43	28	distance	distance	NOUN
cana-3689	43	29	(	(	PUNCT
cana-3689	43	30	km	km	NOUN
cana-3689	43	31	)	)	PUNCT
cana-3689	43	32	,	,	PUNCT
cana-3689	43	33	and	and	CCONJ
cana-3689	43	34	calories	calorie	NOUN
cana-3689	43	35	burned	burn	VERB
cana-3689	43	36	.	.	PUNCT
cana-3689	44	1	their	their	PRON
cana-3689	44	2	research	research	NOUN
cana-3689	44	3	emphasized	emphasize	VERB
cana-3689	44	4	advanced	advanced	ADJ
cana-3689	44	5	hyperparameter	hyperparameter	NOUN
cana-3689	44	6	optimization	optimization	NOUN
cana-3689	44	7	,	,	PUNCT
cana-3689	44	8	resulting	result	VERB
cana-3689	44	9	in	in	ADP
cana-3689	44	10	an	an	DET
cana-3689	44	11	f	f	NOUN
cana-3689	44	12	-	-	PUNCT
cana-3689	44	13	measure	measure	NOUN
cana-3689	44	14	of	of	ADP
cana-3689	44	15	88	88	NUM
cana-3689	44	16	%	%	NOUN
cana-3689	44	17	and	and	CCONJ
cana-3689	44	18	a	a	DET
cana-3689	44	19	prc	prc	PROPN
cana-3689	44	20	area	area	NOUN
cana-3689	44	21	of	of	ADP
cana-3689	44	22	0.90	0.90	NUM
cana-3689	44	23	.	.	PUNCT
cana-3689	45	1	this	this	DET
cana-3689	45	2	work	work	NOUN
cana-3689	45	3	highlighted	highlight	VERB
cana-3689	45	4	the	the	DET
cana-3689	45	5	communications	communication	NOUN
cana-3689	45	6	on	on	ADP
cana-3689	45	7	applied	apply	VERB
cana-3689	45	8	nonlinear	nonlinear	ADJ
cana-3689	45	9	analysis	analysis	NOUN
cana-3689	45	10	issn	issn	NOUN
cana-3689	45	11	:	:	PUNCT
cana-3689	45	12	1074	1074	NUM
cana-3689	45	13	-	-	PUNCT
cana-3689	45	14	133x	133x	NUM
cana-3689	45	15	vol	vol	NOUN
cana-3689	45	16	32	32	NUM
cana-3689	45	17	no	no	NOUN
cana-3689	45	18	.	.	PUNCT
cana-3689	46	1	8s	8s	PROPN
cana-3689	46	2	(	(	PUNCT
cana-3689	46	3	2025	2025	NUM
cana-3689	46	4	)	)	PUNCT
cana-3689	46	5	https://internationalpubls.com	https://internationalpubls.com	X
cana-3689	46	6	446	446	NUM
cana-3689	46	7	critical	critical	ADJ
cana-3689	46	8	role	role	NOUN
cana-3689	46	9	of	of	ADP
cana-3689	46	10	fine	fine	ADV
cana-3689	46	11	-	-	PUNCT
cana-3689	46	12	tuning	tune	VERB
cana-3689	46	13	neural	neural	ADJ
cana-3689	46	14	network	network	NOUN
cana-3689	46	15	models	model	NOUN
cana-3689	46	16	to	to	PART
cana-3689	46	17	maximize	maximize	VERB
cana-3689	46	18	their	their	PRON
cana-3689	46	19	predictive	predictive	ADJ
cana-3689	46	20	efficacy	efficacy	NOUN
cana-3689	46	21	,	,	PUNCT
cana-3689	46	22	particularly	particularly	ADV
cana-3689	46	23	in	in	ADP
cana-3689	46	24	health	health	NOUN
cana-3689	46	25	-	-	PUNCT
cana-3689	46	26	related	relate	VERB
cana-3689	46	27	applications	application	NOUN
cana-3689	46	28	requiring	require	VERB
cana-3689	46	29	precise	precise	ADJ
cana-3689	46	30	activity	activity	NOUN
cana-3689	46	31	classification	classification	NOUN
cana-3689	46	32	.	.	PUNCT
cana-3689	47	1	kim	kim	PROPN
cana-3689	47	2	et	et	PROPN
cana-3689	47	3	al	al	PROPN
cana-3689	47	4	.	.	PROPN
cana-3689	48	1	(	(	PUNCT
cana-3689	48	2	2019	2019	NUM
cana-3689	48	3	)	)	PUNCT
cana-3689	48	4	explored	explore	VERB
cana-3689	48	5	the	the	DET
cana-3689	48	6	use	use	NOUN
cana-3689	48	7	of	of	ADP
cana-3689	48	8	ensemble	ensemble	ADJ
cana-3689	48	9	methods	method	NOUN
cana-3689	48	10	,	,	PUNCT
cana-3689	48	11	specifically	specifically	ADV
cana-3689	48	12	random	random	ADJ
cana-3689	48	13	forest	forest	NOUN
cana-3689	48	14	and	and	CCONJ
cana-3689	48	15	smo	smo	PROPN
cana-3689	48	16	,	,	PUNCT
cana-3689	48	17	for	for	ADP
cana-3689	48	18	predicting	predict	VERB
cana-3689	48	19	cardio	cardio	NOUN
cana-3689	48	20	activities	activity	NOUN
cana-3689	48	21	in	in	ADP
cana-3689	48	22	datasets	dataset	NOUN
cana-3689	48	23	with	with	ADP
cana-3689	48	24	high	high	ADJ
cana-3689	48	25	dimensionality	dimensionality	NOUN
cana-3689	48	26	.	.	PUNCT
cana-3689	49	1	their	their	PRON
cana-3689	49	2	study	study	NOUN
cana-3689	49	3	incorporated	incorporate	VERB
cana-3689	49	4	diverse	diverse	ADJ
cana-3689	49	5	parameters	parameter	NOUN
cana-3689	49	6	,	,	PUNCT
cana-3689	49	7	including	include	VERB
cana-3689	49	8	duration	duration	NOUN
cana-3689	49	9	,	,	PUNCT
cana-3689	49	10	climb	climb	NOUN
cana-3689	49	11	(	(	PUNCT
cana-3689	49	12	m	m	NOUN
cana-3689	49	13	)	)	PUNCT
cana-3689	49	14	,	,	PUNCT
cana-3689	49	15	and	and	CCONJ
cana-3689	49	16	average	average	ADJ
cana-3689	49	17	speed	speed	NOUN
cana-3689	49	18	(	(	PUNCT
cana-3689	49	19	km	km	NOUN
cana-3689	49	20	/	/	SYM
cana-3689	49	21	h	h	NOUN
cana-3689	49	22	)	)	PUNCT
cana-3689	49	23	,	,	PUNCT
cana-3689	49	24	while	while	SCONJ
cana-3689	49	25	evaluating	evaluate	VERB
cana-3689	49	26	performance	performance	NOUN
cana-3689	49	27	using	use	VERB
cana-3689	49	28	metrics	metric	NOUN
cana-3689	49	29	such	such	ADJ
cana-3689	49	30	as	as	ADP
cana-3689	49	31	mcc	mcc	NOUN
cana-3689	49	32	and	and	CCONJ
cana-3689	49	33	recall	recall	NOUN
cana-3689	49	34	.	.	PUNCT
cana-3689	50	1	random	random	ADJ
cana-3689	50	2	forest	forest	NOUN
cana-3689	50	3	outperformed	outperform	VERB
cana-3689	50	4	smo	smo	PROPN
cana-3689	50	5	,	,	PUNCT
cana-3689	50	6	achieving	achieve	VERB
cana-3689	50	7	an	an	DET
cana-3689	50	8	mcc	mcc	NOUN
cana-3689	50	9	of	of	ADP
cana-3689	50	10	0.87	0.87	NUM
cana-3689	50	11	compared	compare	VERB
cana-3689	50	12	to	to	ADP
cana-3689	50	13	smo	smo	PROPN
cana-3689	50	14	’s	’s	PART
cana-3689	50	15	0.80	0.80	NUM
cana-3689	50	16	.	.	PUNCT
cana-3689	51	1	this	this	DET
cana-3689	51	2	study	study	NOUN
cana-3689	51	3	illustrates	illustrate	VERB
cana-3689	51	4	the	the	DET
cana-3689	51	5	effectiveness	effectiveness	NOUN
cana-3689	51	6	of	of	ADP
cana-3689	51	7	ensemble	ensemble	ADJ
cana-3689	51	8	techniques	technique	NOUN
cana-3689	51	9	in	in	ADP
cana-3689	51	10	handling	handle	VERB
cana-3689	51	11	complex	complex	ADJ
cana-3689	51	12	datasets	dataset	NOUN
cana-3689	51	13	with	with	ADP
cana-3689	51	14	varying	vary	VERB
cana-3689	51	15	patterns	pattern	NOUN
cana-3689	51	16	of	of	ADP
cana-3689	51	17	cardio	cardio	NOUN
cana-3689	51	18	activity	activity	NOUN
cana-3689	51	19	.	.	PUNCT
cana-3689	52	1	patel	patel	PROPN
cana-3689	52	2	et	et	PROPN
cana-3689	52	3	al	al	PROPN
cana-3689	52	4	.	.	PROPN
cana-3689	53	1	(	(	PUNCT
cana-3689	53	2	2022	2022	NUM
cana-3689	53	3	)	)	PUNCT
cana-3689	53	4	compared	compare	VERB
cana-3689	53	5	the	the	DET
cana-3689	53	6	predictive	predictive	ADJ
cana-3689	53	7	capabilities	capability	NOUN
cana-3689	53	8	of	of	ADP
cana-3689	53	9	j48	j48	PROPN
cana-3689	53	10	and	and	CCONJ
cana-3689	53	11	rep	rep	NOUN
cana-3689	53	12	tree	tree	NOUN
cana-3689	53	13	models	model	NOUN
cana-3689	53	14	for	for	ADP
cana-3689	53	15	cardio	cardio	NOUN
cana-3689	53	16	activity	activity	NOUN
cana-3689	53	17	classification	classification	NOUN
cana-3689	53	18	.	.	PUNCT
cana-3689	54	1	their	their	PRON
cana-3689	54	2	research	research	NOUN
cana-3689	54	3	employed	employ	VERB
cana-3689	54	4	parameters	parameter	NOUN
cana-3689	54	5	like	like	ADP
cana-3689	54	6	type	type	NOUN
cana-3689	54	7	,	,	PUNCT
cana-3689	54	8	duration	duration	NOUN
cana-3689	54	9	,	,	PUNCT
cana-3689	54	10	and	and	CCONJ
cana-3689	54	11	climb	climb	VERB
cana-3689	54	12	(	(	PUNCT
cana-3689	54	13	m	m	NOUN
cana-3689	54	14	)	)	PUNCT
cana-3689	54	15	,	,	PUNCT
cana-3689	54	16	emphasizing	emphasize	VERB
cana-3689	54	17	metrics	metric	NOUN
cana-3689	54	18	like	like	ADP
cana-3689	54	19	fp	fp	X
cana-3689	54	20	rate	rate	NOUN
cana-3689	54	21	and	and	CCONJ
cana-3689	54	22	recall	recall	NOUN
cana-3689	54	23	to	to	PART
cana-3689	54	24	assess	assess	VERB
cana-3689	54	25	model	model	NOUN
cana-3689	54	26	performance	performance	NOUN
cana-3689	54	27	.	.	PUNCT
cana-3689	55	1	the	the	DET
cana-3689	55	2	study	study	NOUN
cana-3689	55	3	revealed	reveal	VERB
cana-3689	55	4	that	that	SCONJ
cana-3689	55	5	rep	rep	PROPN
cana-3689	55	6	tree	tree	NOUN
cana-3689	55	7	achieved	achieve	VERB
cana-3689	55	8	a	a	DET
cana-3689	55	9	recall	recall	NOUN
cana-3689	55	10	of	of	ADP
cana-3689	55	11	91	91	NUM
cana-3689	55	12	%	%	NOUN
cana-3689	55	13	with	with	ADP
cana-3689	55	14	minimal	minimal	ADJ
cana-3689	55	15	false	false	ADJ
cana-3689	55	16	positives	positive	NOUN
cana-3689	55	17	,	,	PUNCT
cana-3689	55	18	highlighting	highlight	VERB
cana-3689	55	19	its	its	PRON
cana-3689	55	20	reliability	reliability	NOUN
cana-3689	55	21	for	for	ADP
cana-3689	55	22	precision	precision	NOUN
cana-3689	55	23	-	-	PUNCT
cana-3689	55	24	critical	critical	ADJ
cana-3689	55	25	applications	application	NOUN
cana-3689	55	26	in	in	ADP
cana-3689	55	27	cardio	cardio	NOUN
cana-3689	55	28	activity	activity	NOUN
cana-3689	55	29	prediction	prediction	NOUN
cana-3689	55	30	.	.	PUNCT
cana-3689	56	1	ahmed	ahmed	PROPN
cana-3689	56	2	and	and	CCONJ
cana-3689	56	3	khan	khan	PROPN
cana-3689	56	4	(	(	PUNCT
cana-3689	56	5	2021	2021	NUM
cana-3689	56	6	)	)	PUNCT
cana-3689	56	7	explored	explore	VERB
cana-3689	56	8	the	the	DET
cana-3689	56	9	integration	integration	NOUN
cana-3689	56	10	of	of	ADP
cana-3689	56	11	multilayer	multilayer	ADJ
cana-3689	56	12	perceptron	perceptron	PROPN
cana-3689	56	13	and	and	CCONJ
cana-3689	56	14	logistic	logistic	ADJ
cana-3689	56	15	regression	regression	NOUN
cana-3689	56	16	for	for	ADP
cana-3689	56	17	predicting	predict	VERB
cana-3689	56	18	cardio	cardio	NOUN
cana-3689	56	19	activities	activity	NOUN
cana-3689	56	20	.	.	PUNCT
cana-3689	57	1	their	their	PRON
cana-3689	57	2	study	study	NOUN
cana-3689	57	3	utilized	utilize	VERB
cana-3689	57	4	parameters	parameter	NOUN
cana-3689	57	5	such	such	ADJ
cana-3689	57	6	as	as	ADP
cana-3689	57	7	average	average	ADJ
cana-3689	57	8	speed	speed	NOUN
cana-3689	57	9	(	(	PUNCT
cana-3689	57	10	km	km	NOUN
cana-3689	57	11	/	/	SYM
cana-3689	57	12	h	h	NOUN
cana-3689	57	13	)	)	PUNCT
cana-3689	57	14	,	,	PUNCT
cana-3689	57	15	distance	distance	NOUN
cana-3689	57	16	(	(	PUNCT
cana-3689	57	17	km	km	NOUN
cana-3689	57	18	)	)	PUNCT
cana-3689	57	19	,	,	PUNCT
cana-3689	57	20	and	and	CCONJ
cana-3689	57	21	calories	calorie	NOUN
cana-3689	57	22	burned	burn	VERB
cana-3689	57	23	,	,	PUNCT
cana-3689	57	24	focusing	focus	VERB
cana-3689	57	25	on	on	ADP
cana-3689	57	26	metrics	metric	NOUN
cana-3689	57	27	like	like	ADP
cana-3689	57	28	roc	roc	PROPN
cana-3689	57	29	area	area	NOUN
cana-3689	57	30	and	and	CCONJ
cana-3689	57	31	tp	tp	NOUN
cana-3689	57	32	rate	rate	NOUN
cana-3689	57	33	.	.	PUNCT
cana-3689	58	1	the	the	DET
cana-3689	58	2	hybrid	hybrid	NOUN
cana-3689	58	3	model	model	NOUN
cana-3689	58	4	demonstrated	demonstrate	VERB
cana-3689	58	5	the	the	DET
cana-3689	58	6	synergistic	synergistic	ADJ
cana-3689	58	7	benefits	benefit	NOUN
cana-3689	58	8	of	of	ADP
cana-3689	58	9	combining	combine	VERB
cana-3689	58	10	linear	linear	ADJ
cana-3689	58	11	and	and	CCONJ
cana-3689	58	12	non	non	ADJ
cana-3689	58	13	-	-	ADJ
cana-3689	58	14	linear	linear	ADJ
cana-3689	58	15	techniques	technique	NOUN
cana-3689	58	16	,	,	PUNCT
cana-3689	58	17	achieving	achieve	VERB
cana-3689	58	18	a	a	DET
cana-3689	58	19	roc	roc	PROPN
cana-3689	58	20	area	area	NOUN
cana-3689	58	21	of	of	ADP
cana-3689	58	22	0.92	0.92	NUM
cana-3689	58	23	and	and	CCONJ
cana-3689	58	24	a	a	DET
cana-3689	58	25	tp	tp	NOUN
cana-3689	58	26	rate	rate	NOUN
cana-3689	58	27	of	of	ADP
cana-3689	58	28	0.88	0.88	NUM
cana-3689	58	29	,	,	PUNCT
cana-3689	58	30	providing	provide	VERB
cana-3689	58	31	a	a	DET
cana-3689	58	32	compelling	compelling	ADJ
cana-3689	58	33	case	case	NOUN
cana-3689	58	34	for	for	ADP
cana-3689	58	35	hybrid	hybrid	ADJ
cana-3689	58	36	methodologies	methodology	NOUN
cana-3689	58	37	in	in	ADP
cana-3689	58	38	cardio	cardio	NOUN
cana-3689	58	39	activity	activity	NOUN
cana-3689	58	40	modeling	modeling	NOUN
cana-3689	58	41	.	.	PUNCT
cana-3689	59	1	liu	liu	PROPN
cana-3689	59	2	et	et	PROPN
cana-3689	59	3	al	al	PROPN
cana-3689	59	4	.	.	PROPN
cana-3689	59	5	(	(	PUNCT
cana-3689	59	6	2020	2020	NUM
cana-3689	59	7	)	)	PUNCT
cana-3689	59	8	analyzed	analyze	VERB
cana-3689	59	9	the	the	DET
cana-3689	59	10	real	real	ADJ
cana-3689	59	11	-	-	PUNCT
cana-3689	59	12	time	time	NOUN
cana-3689	59	13	predictive	predictive	ADJ
cana-3689	59	14	capabilities	capability	NOUN
cana-3689	59	15	of	of	ADP
cana-3689	59	16	rep	rep	NOUN
cana-3689	59	17	tree	tree	NOUN
cana-3689	59	18	and	and	CCONJ
cana-3689	59	19	smo	smo	NOUN
cana-3689	59	20	for	for	ADP
cana-3689	59	21	cardio	cardio	NOUN
cana-3689	59	22	activities	activity	NOUN
cana-3689	59	23	,	,	PUNCT
cana-3689	59	24	utilizing	utilize	VERB
cana-3689	59	25	parameters	parameter	NOUN
cana-3689	59	26	such	such	ADJ
cana-3689	59	27	as	as	ADP
cana-3689	59	28	date	date	NOUN
cana-3689	59	29	,	,	PUNCT
cana-3689	59	30	type	type	NOUN
cana-3689	59	31	,	,	PUNCT
cana-3689	59	32	and	and	CCONJ
cana-3689	59	33	average	average	ADJ
cana-3689	59	34	pace	pace	NOUN
cana-3689	59	35	.	.	PUNCT
cana-3689	60	1	their	their	PRON
cana-3689	60	2	findings	finding	NOUN
cana-3689	60	3	showed	show	VERB
cana-3689	60	4	that	that	SCONJ
cana-3689	60	5	rep	rep	NOUN
cana-3689	60	6	tree	tree	NOUN
cana-3689	60	7	delivered	deliver	VERB
cana-3689	60	8	higher	high	ADJ
cana-3689	60	9	precision	precision	NOUN
cana-3689	60	10	and	and	CCONJ
cana-3689	60	11	computational	computational	ADJ
cana-3689	60	12	efficiency	efficiency	NOUN
cana-3689	60	13	,	,	PUNCT
cana-3689	60	14	while	while	SCONJ
cana-3689	60	15	smo	smo	PROPN
cana-3689	60	16	achieved	achieve	VERB
cana-3689	60	17	better	well	ADJ
cana-3689	60	18	recall	recall	NOUN
cana-3689	60	19	for	for	ADP
cana-3689	60	20	more	more	ADJ
cana-3689	60	21	intricate	intricate	ADJ
cana-3689	60	22	datasets	dataset	NOUN
cana-3689	60	23	.	.	PUNCT
cana-3689	61	1	with	with	ADP
cana-3689	61	2	a	a	DET
cana-3689	61	3	precision	precision	NOUN
cana-3689	61	4	of	of	ADP
cana-3689	61	5	88	88	NUM
cana-3689	61	6	%	%	NOUN
cana-3689	61	7	for	for	ADP
cana-3689	61	8	rep	rep	NOUN
cana-3689	61	9	tree	tree	NOUN
cana-3689	61	10	and	and	CCONJ
cana-3689	61	11	a	a	DET
cana-3689	61	12	recall	recall	NOUN
cana-3689	61	13	of	of	ADP
cana-3689	61	14	85	85	NUM
cana-3689	61	15	%	%	NOUN
cana-3689	61	16	for	for	ADP
cana-3689	61	17	smo	smo	PROPN
cana-3689	61	18	,	,	PUNCT
cana-3689	61	19	their	their	PRON
cana-3689	61	20	research	research	NOUN
cana-3689	61	21	underscores	underscore	VERB
cana-3689	61	22	the	the	DET
cana-3689	61	23	trade	trade	NOUN
cana-3689	61	24	-	-	PUNCT
cana-3689	61	25	offs	off	NOUN
cana-3689	61	26	between	between	ADP
cana-3689	61	27	computational	computational	ADJ
cana-3689	61	28	speed	speed	NOUN
cana-3689	61	29	and	and	CCONJ
cana-3689	61	30	accuracy	accuracy	NOUN
cana-3689	61	31	in	in	ADP
cana-3689	61	32	real	real	ADJ
cana-3689	61	33	-	-	PUNCT
cana-3689	61	34	world	world	NOUN
cana-3689	61	35	predictive	predictive	ADJ
cana-3689	61	36	systems	system	NOUN
cana-3689	61	37	.	.	PUNCT
cana-3689	62	1	swathy	swathy	ADJ
cana-3689	62	2	and	and	CCONJ
cana-3689	62	3	saruladha	saruladha	NOUN
cana-3689	62	4	(	(	PUNCT
cana-3689	62	5	2022	2022	NUM
cana-3689	62	6	)	)	PUNCT
cana-3689	62	7	explored	explore	VERB
cana-3689	62	8	the	the	DET
cana-3689	62	9	ensemble	ensemble	ADJ
cana-3689	62	10	model	model	NOUN
cana-3689	62	11	for	for	ADP
cana-3689	62	12	cardiovascular	cardiovascular	ADJ
cana-3689	62	13	disease	disease	NOUN
cana-3689	62	14	achieved	achieve	VERB
cana-3689	62	15	an	an	DET
cana-3689	62	16	au	au	PROPN
cana-3689	62	17	-	-	ADJ
cana-3689	62	18	roc	roc	ADJ
cana-3689	62	19	score	score	NOUN
cana-3689	62	20	of	of	ADP
cana-3689	62	21	83.1	83.1	NUM
cana-3689	62	22	%	%	NOUN
cana-3689	62	23	without	without	ADP
cana-3689	62	24	laboratory	laboratory	NOUN
cana-3689	62	25	results	result	NOUN
cana-3689	62	26	and	and	CCONJ
cana-3689	62	27	83.9	83.9	NUM
cana-3689	62	28	%	%	NOUN
cana-3689	62	29	with	with	ADP
cana-3689	62	30	them	they	PRON
cana-3689	62	31	.	.	PUNCT
cana-3689	63	1	in	in	ADP
cana-3689	63	2	diabetes	diabetes	NOUN
cana-3689	63	3	classification	classification	NOUN
cana-3689	63	4	,	,	PUNCT
cana-3689	63	5	the	the	DET
cana-3689	63	6	extreme	extreme	ADJ
cana-3689	63	7	gradient	gradient	NOUN
cana-3689	63	8	boost	boost	NOUN
cana-3689	63	9	(	(	PUNCT
cana-3689	63	10	xgboost	xgboost	X
cana-3689	63	11	)	)	PUNCT
cana-3689	63	12	model	model	NOUN
cana-3689	63	13	scored	score	VERB
cana-3689	63	14	86.2	86.2	NUM
cana-3689	63	15	%	%	NOUN
cana-3689	63	16	au	au	PROPN
cana-3689	63	17	-	-	NOUN
cana-3689	63	18	roc	roc	PROPN
cana-3689	63	19	without	without	ADP
cana-3689	63	20	laboratory	laboratory	NOUN
cana-3689	63	21	data	datum	NOUN
cana-3689	63	22	and	and	CCONJ
cana-3689	63	23	95.7	95.7	NUM
cana-3689	63	24	%	%	NOUN
cana-3689	63	25	with	with	ADP
cana-3689	63	26	it	it	PRON
cana-3689	63	27	.	.	PUNCT
cana-3689	64	1	the	the	DET
cana-3689	64	2	top	top	ADJ
cana-3689	64	3	predictors	predictor	NOUN
cana-3689	64	4	for	for	ADP
cana-3689	64	5	diabetes	diabetes	NOUN
cana-3689	64	6	included	include	VERB
cana-3689	64	7	waist	waist	NOUN
cana-3689	64	8	size	size	NOUN
cana-3689	64	9	,	,	PUNCT
cana-3689	64	10	age	age	NOUN
cana-3689	64	11	,	,	PUNCT
cana-3689	64	12	self	self	NOUN
cana-3689	64	13	-	-	PUNCT
cana-3689	64	14	reported	report	VERB
cana-3689	64	15	weight	weight	NOUN
cana-3689	64	16	,	,	PUNCT
cana-3689	64	17	leg	leg	NOUN
cana-3689	64	18	length	length	NOUN
cana-3689	64	19	,	,	PUNCT
cana-3689	64	20	and	and	CCONJ
cana-3689	64	21	sodium	sodium	NOUN
cana-3689	64	22	intake	intake	NOUN
cana-3689	64	23	.	.	PUNCT
cana-3689	65	1	for	for	ADP
cana-3689	65	2	cardiovascular	cardiovascular	ADJ
cana-3689	65	3	diseases	disease	NOUN
cana-3689	65	4	,	,	PUNCT
cana-3689	65	5	age	age	NOUN
cana-3689	65	6	,	,	PUNCT
cana-3689	65	7	systolic	systolic	ADJ
cana-3689	65	8	and	and	CCONJ
cana-3689	65	9	diastolic	diastolic	ADJ
cana-3689	65	10	blood	blood	NOUN
cana-3689	65	11	pressure	pressure	NOUN
cana-3689	65	12	,	,	PUNCT
cana-3689	65	13	self	self	NOUN
cana-3689	65	14	-	-	PUNCT
cana-3689	65	15	reported	report	VERB
cana-3689	65	16	weight	weight	NOUN
cana-3689	65	17	,	,	PUNCT
cana-3689	65	18	and	and	CCONJ
cana-3689	65	19	occurrence	occurrence	NOUN
cana-3689	65	20	of	of	ADP
cana-3689	65	21	chest	chest	NOUN
cana-3689	65	22	pain	pain	NOUN
cana-3689	65	23	were	be	AUX
cana-3689	65	24	identified	identify	VERB
cana-3689	65	25	as	as	ADP
cana-3689	65	26	key	key	ADJ
cana-3689	65	27	contributors	contributor	NOUN
cana-3689	65	28	.	.	PUNCT
cana-3689	66	1	bhatt	bhatt	PROPN
cana-3689	66	2	et	et	PROPN
cana-3689	66	3	al	al	PROPN
cana-3689	66	4	.	.	PROPN
cana-3689	66	5	(	(	PUNCT
cana-3689	66	6	2017	2017	NUM
cana-3689	66	7	)	)	PUNCT
cana-3689	66	8	compared	compare	VERB
cana-3689	66	9	and	and	CCONJ
cana-3689	66	10	reported	report	VERB
cana-3689	66	11	various	various	ADJ
cana-3689	66	12	classification	classification	NOUN
cana-3689	66	13	,	,	PUNCT
cana-3689	66	14	data	datum	NOUN
cana-3689	66	15	mining	mining	NOUN
cana-3689	66	16	,	,	PUNCT
cana-3689	66	17	machine	machine	NOUN
cana-3689	66	18	learning	learning	NOUN
cana-3689	66	19	,	,	PUNCT
cana-3689	66	20	and	and	CCONJ
cana-3689	66	21	deep	deep	ADJ
cana-3689	66	22	learning	learning	NOUN
cana-3689	66	23	models	model	NOUN
cana-3689	66	24	used	use	VERB
cana-3689	66	25	for	for	ADP
cana-3689	66	26	predicting	predict	VERB
cana-3689	66	27	cardiovascular	cardiovascular	ADJ
cana-3689	66	28	diseases	disease	NOUN
cana-3689	66	29	.	.	PUNCT
cana-3689	67	1	the	the	DET
cana-3689	67	2	survey	survey	NOUN
cana-3689	67	3	categorized	categorize	VERB
cana-3689	67	4	these	these	DET
cana-3689	67	5	techniques	technique	NOUN
cana-3689	67	6	into	into	ADP
cana-3689	67	7	three	three	NUM
cana-3689	67	8	groups	group	NOUN
cana-3689	67	9	:	:	PUNCT
cana-3689	67	10	classification	classification	NOUN
cana-3689	67	11	and	and	CCONJ
cana-3689	67	12	data	datum	NOUN
cana-3689	67	13	mining	mining	NOUN
cana-3689	67	14	techniques	technique	NOUN
cana-3689	67	15	,	,	PUNCT
cana-3689	67	16	machine	machine	NOUN
cana-3689	67	17	learning	learning	NOUN
cana-3689	67	18	models	model	NOUN
cana-3689	67	19	,	,	PUNCT
cana-3689	67	20	and	and	CCONJ
cana-3689	67	21	deep	deep	ADJ
cana-3689	67	22	learning	learning	NOUN
cana-3689	67	23	models	model	NOUN
cana-3689	67	24	for	for	ADP
cana-3689	67	25	cvd	cvd	PROPN
cana-3689	67	26	prediction	prediction	NOUN
cana-3689	67	27	.	.	PUNCT
cana-3689	68	1	it	it	PRON
cana-3689	68	2	compiled	compile	VERB
cana-3689	68	3	and	and	CCONJ
cana-3689	68	4	reported	report	VERB
cana-3689	68	5	performance	performance	NOUN
cana-3689	68	6	metrics	metric	NOUN
cana-3689	68	7	,	,	PUNCT
cana-3689	68	8	datasets	dataset	NOUN
cana-3689	68	9	,	,	PUNCT
cana-3689	68	10	and	and	CCONJ
cana-3689	68	11	tools	tool	NOUN
cana-3689	68	12	used	use	VERB
cana-3689	68	13	in	in	ADP
cana-3689	68	14	each	each	DET
cana-3689	68	15	category	category	NOUN
cana-3689	68	16	.	.	PUNCT
cana-3689	69	1	the	the	DET
cana-3689	69	2	experimental	experimental	ADJ
cana-3689	69	3	analysis	analysis	NOUN
cana-3689	69	4	of	of	ADP
cana-3689	69	5	data	datum	NOUN
cana-3689	69	6	from	from	ADP
cana-3689	69	7	the	the	DET
cana-3689	69	8	uci	uci	PROPN
cana-3689	69	9	machine	machine	NOUN
cana-3689	69	10	learning	learn	VERB
cana-3689	69	11	repository	repository	NOUN
cana-3689	69	12	utilized	utilize	VERB
cana-3689	69	13	the	the	DET
cana-3689	69	14	weka	weka	NOUN
cana-3689	69	15	open	open	ADJ
cana-3689	69	16	-	-	PUNCT
cana-3689	69	17	source	source	NOUN
cana-3689	69	18	tool	tool	NOUN
cana-3689	69	19	.	.	PUNCT
cana-3689	70	1	supervised	supervise	VERB
cana-3689	70	2	algorithms	algorithm	NOUN
cana-3689	70	3	like	like	ADP
cana-3689	70	4	j48	j48	NOUN
cana-3689	70	5	and	and	CCONJ
cana-3689	70	6	naïve	naïve	ADJ
cana-3689	70	7	bayes	bayes	PROPN
cana-3689	70	8	were	be	AUX
cana-3689	70	9	applied	apply	VERB
cana-3689	70	10	,	,	PUNCT
cana-3689	70	11	showing	show	VERB
cana-3689	70	12	the	the	DET
cana-3689	70	13	impact	impact	NOUN
cana-3689	70	14	of	of	ADP
cana-3689	70	15	selected	select	VERB
cana-3689	70	16	attributes	attribute	NOUN
cana-3689	70	17	versus	versus	ADP
cana-3689	70	18	all	all	DET
cana-3689	70	19	attributes	attribute	NOUN
cana-3689	70	20	on	on	ADP
cana-3689	70	21	algorithms	algorithm	NOUN
cana-3689	70	22	'	'	PART
cana-3689	70	23	accuracy	accuracy	NOUN
cana-3689	70	24	in	in	ADP
cana-3689	70	25	predicting	predict	VERB
cana-3689	70	26	cardiovascular	cardiovascular	ADJ
cana-3689	70	27	diseases	disease	NOUN
cana-3689	70	28	.	.	PUNCT
cana-3689	71	1	j48	j48	PROPN
cana-3689	71	2	,	,	PUNCT
cana-3689	71	3	an	an	DET
cana-3689	71	4	extension	extension	NOUN
cana-3689	71	5	of	of	ADP
cana-3689	71	6	the	the	DET
cana-3689	71	7	id3	id3	NOUN
cana-3689	71	8	algorithm	algorithm	NOUN
cana-3689	71	9	,	,	PUNCT
cana-3689	71	10	demonstrated	demonstrate	VERB
cana-3689	71	11	features	feature	NOUN
cana-3689	71	12	such	such	ADJ
cana-3689	71	13	as	as	ADP
cana-3689	71	14	continuous	continuous	ADJ
cana-3689	71	15	attribute	attribute	NOUN
cana-3689	71	16	value	value	NOUN
cana-3689	71	17	ranges	range	NOUN
cana-3689	71	18	and	and	CCONJ
cana-3689	71	19	rule	rule	VERB
cana-3689	71	20	derivation	derivation	NOUN
cana-3689	71	21	.	.	PUNCT
cana-3689	72	1	sakr	sakr	PROPN
cana-3689	72	2	et	et	PROPN
cana-3689	72	3	al	al	PROPN
cana-3689	72	4	.	.	PROPN
cana-3689	73	1	(	(	PUNCT
cana-3689	73	2	2018	2018	NUM
cana-3689	73	3	)	)	PUNCT
cana-3689	73	4	,	,	PUNCT
cana-3689	73	5	evaluated	evaluate	VERB
cana-3689	73	6	and	and	CCONJ
cana-3689	73	7	compared	compare	VERB
cana-3689	73	8	different	different	ADJ
cana-3689	73	9	machine	machine	NOUN
cana-3689	73	10	learning	learn	VERB
cana-3689	73	11	techniques	technique	NOUN
cana-3689	73	12	to	to	PART
cana-3689	73	13	predict	predict	VERB
cana-3689	73	14	individuals	individual	NOUN
cana-3689	73	15	at	at	ADP
cana-3689	73	16	risk	risk	NOUN
cana-3689	73	17	of	of	ADP
cana-3689	73	18	developing	develop	VERB
cana-3689	73	19	hypertension	hypertension	NOUN
cana-3689	73	20	using	use	VERB
cana-3689	73	21	cardiorespiratory	cardiorespiratory	NOUN
cana-3689	73	22	fitness	fitness	NOUN
cana-3689	73	23	data	datum	NOUN
cana-3689	73	24	.	.	PUNCT
cana-3689	74	1	the	the	DET
cana-3689	74	2	dataset	dataset	NOUN
cana-3689	74	3	contained	contain	VERB
cana-3689	74	4	information	information	NOUN
cana-3689	74	5	on	on	ADP
cana-3689	74	6	23,095	23,095	NUM
cana-3689	74	7	patients	patient	NOUN
cana-3689	74	8	and	and	CCONJ
cana-3689	74	9	explored	explore	VERB
cana-3689	74	10	six	six	NUM
cana-3689	74	11	techniques	technique	NOUN
cana-3689	74	12	:	:	PUNCT
cana-3689	74	13	logitboost	logitboost	ADJ
cana-3689	74	14	,	,	PUNCT
cana-3689	74	15	bayesian	bayesian	NOUN
cana-3689	74	16	network	network	NOUN
cana-3689	74	17	classifier	classifier	NOUN
cana-3689	74	18	,	,	PUNCT
cana-3689	74	19	locally	locally	ADV
cana-3689	74	20	weighted	weight	VERB
cana-3689	74	21	naive	naive	ADJ
cana-3689	74	22	bayes	bayes	NOUN
cana-3689	74	23	,	,	PUNCT
cana-3689	74	24	artificial	artificial	ADJ
cana-3689	74	25	neural	neural	ADJ
cana-3689	74	26	network	network	NOUN
cana-3689	74	27	,	,	PUNCT
cana-3689	74	28	support	support	NOUN
cana-3689	74	29	vector	vector	NOUN
cana-3689	74	30	machine	machine	NOUN
cana-3689	74	31	,	,	PUNCT
cana-3689	74	32	and	and	CCONJ
cana-3689	74	33	random	random	ADJ
cana-3689	74	34	tree	tree	NOUN
cana-3689	74	35	forest	forest	NOUN
cana-3689	74	36	.	.	PUNCT
cana-3689	75	1	the	the	DET
cana-3689	75	2	random	random	ADJ
cana-3689	75	3	tree	tree	NOUN
cana-3689	75	4	forest	forest	NOUN
cana-3689	75	5	model	model	NOUN
cana-3689	75	6	displayed	display	VERB
cana-3689	75	7	the	the	DET
cana-3689	75	8	best	good	ADJ
cana-3689	75	9	performance	performance	NOUN
cana-3689	75	10	(	(	PUNCT
cana-3689	75	11	auc	auc	NOUN
cana-3689	75	12	=	=	NOUN
cana-3689	75	13	0.93	0.93	NUM
cana-3689	75	14	)	)	PUNCT
cana-3689	75	15	among	among	ADP
cana-3689	75	16	others	other	NOUN
cana-3689	75	17	,	,	PUNCT
cana-3689	75	18	emphasizing	emphasize	VERB
cana-3689	75	19	the	the	DET
cana-3689	75	20	importance	importance	NOUN
cana-3689	75	21	of	of	ADP
cana-3689	75	22	various	various	ADJ
cana-3689	75	23	model	model	NOUN
cana-3689	75	24	evaluation	evaluation	NOUN
cana-3689	75	25	communications	communication	NOUN
cana-3689	75	26	on	on	ADP
cana-3689	75	27	applied	apply	VERB
cana-3689	75	28	nonlinear	nonlinear	ADJ
cana-3689	75	29	analysis	analysis	NOUN
cana-3689	75	30	issn	issn	NOUN
cana-3689	75	31	:	:	PUNCT
cana-3689	75	32	1074	1074	NUM
cana-3689	75	33	-	-	PUNCT
cana-3689	75	34	133x	133x	NUM
cana-3689	75	35	vol	vol	NOUN
cana-3689	75	36	32	32	NUM
cana-3689	75	37	no	no	NOUN
cana-3689	75	38	.	.	PUNCT
cana-3689	76	1	8s	8s	PROPN
cana-3689	76	2	(	(	PUNCT
cana-3689	76	3	2025	2025	NUM
cana-3689	76	4	)	)	PUNCT
cana-3689	76	5	https://internationalpubls.com	https://internationalpubls.com	X
cana-3689	76	6	447	447	NUM
cana-3689	76	7	methods	method	NOUN
cana-3689	76	8	.	.	PUNCT
cana-3689	77	1	rajliwall	rajliwall	VERB
cana-3689	77	2	et	et	PROPN
cana-3689	77	3	al	al	PROPN
cana-3689	77	4	.	.	PROPN
cana-3689	78	1	(	(	PUNCT
cana-3689	78	2	2018	2018	NUM
cana-3689	78	3	)	)	PUNCT
cana-3689	78	4	explain	explain	VERB
cana-3689	78	5	machine	machine	NOUN
cana-3689	78	6	learning	learning	NOUN
cana-3689	78	7	-	-	PUNCT
cana-3689	78	8	based	base	VERB
cana-3689	78	9	prognostic	prognostic	ADJ
cana-3689	78	10	modeling	modeling	NOUN
cana-3689	78	11	framework	framework	NOUN
cana-3689	78	12	was	be	AUX
cana-3689	78	13	introduced	introduce	VERB
cana-3689	78	14	to	to	PART
cana-3689	78	15	handle	handle	VERB
cana-3689	78	16	static	static	ADJ
cana-3689	78	17	/	/	SYM
cana-3689	78	18	low	low	ADJ
cana-3689	78	19	-	-	PUNCT
cana-3689	78	20	speed	speed	NOUN
cana-3689	78	21	and	and	CCONJ
cana-3689	78	22	extreme	extreme	ADJ
cana-3689	78	23	-	-	PUNCT
cana-3689	78	24	velocity	velocity	NOUN
cana-3689	78	25	,	,	PUNCT
cana-3689	78	26	streaming	stream	VERB
cana-3689	78	27	massive	massive	ADJ
cana-3689	78	28	data	datum	NOUN
cana-3689	78	29	from	from	ADP
cana-3689	78	30	electronic	electronic	ADJ
cana-3689	78	31	health	health	NOUN
cana-3689	78	32	records	record	NOUN
cana-3689	78	33	and	and	CCONJ
cana-3689	78	34	wearable	wearable	ADJ
cana-3689	78	35	devices	device	NOUN
cana-3689	78	36	.	.	PUNCT
cana-3689	79	1	the	the	DET
cana-3689	79	2	framework	framework	NOUN
cana-3689	79	3	implemented	implement	VERB
cana-3689	79	4	a	a	DET
cana-3689	79	5	scalable	scalable	ADJ
cana-3689	79	6	algorithm	algorithm	NOUN
cana-3689	79	7	called	call	VERB
cana-3689	79	8	neuron	neuron	PROPN
cana-3689	79	9	network	network	NOUN
cana-3689	79	10	,	,	PUNCT
cana-3689	79	11	showcasing	showcase	VERB
cana-3689	79	12	promising	promise	VERB
cana-3689	79	13	outcomes	outcome	NOUN
cana-3689	79	14	in	in	ADP
cana-3689	79	15	disease	disease	NOUN
cana-3689	79	16	status	status	NOUN
cana-3689	79	17	prediction	prediction	NOUN
cana-3689	79	18	using	use	VERB
cana-3689	79	19	datasets	dataset	NOUN
cana-3689	79	20	like	like	ADP
cana-3689	79	21	nhanes	nhane	NOUN
cana-3689	79	22	and	and	CCONJ
cana-3689	79	23	the	the	DET
cana-3689	79	24	framingham	framingham	PROPN
cana-3689	79	25	heart	heart	PROPN
cana-3689	79	26	study	study	PROPN
cana-3689	79	27	.	.	PUNCT
cana-3689	80	1	rajesh	rajesh	PROPN
cana-3689	80	2	and	and	CCONJ
cana-3689	80	3	karthikeyan	karthikeyan	PROPN
cana-3689	80	4	(	(	PUNCT
cana-3689	80	5	2017	2017	NUM
cana-3689	80	6	)	)	PUNCT
cana-3689	80	7	explored	explore	VERB
cana-3689	80	8	data	datum	NOUN
cana-3689	80	9	mining	mining	NOUN
cana-3689	80	10	is	be	AUX
cana-3689	80	11	a	a	DET
cana-3689	80	12	valuable	valuable	ADJ
cana-3689	80	13	tool	tool	NOUN
cana-3689	80	14	for	for	ADP
cana-3689	80	15	the	the	DET
cana-3689	80	16	practice	practice	NOUN
cana-3689	80	17	of	of	ADP
cana-3689	80	18	examining	examine	VERB
cana-3689	80	19	large	large	ADJ
cana-3689	80	20	pre	pre	ADJ
cana-3689	80	21	-	-	ADJ
cana-3689	80	22	existing	existing	ADJ
cana-3689	80	23	databases	database	NOUN
cana-3689	80	24	to	to	PART
cana-3689	80	25	generate	generate	VERB
cana-3689	80	26	previously	previously	ADV
cana-3689	80	27	unknown	unknown	ADJ
cana-3689	80	28	helpful	helpful	ADJ
cana-3689	80	29	information	information	NOUN
cana-3689	80	30	;	;	PUNCT
cana-3689	80	31	in	in	ADP
cana-3689	80	32	this	this	DET
cana-3689	80	33	paper	paper	NOUN
cana-3689	80	34	,	,	PUNCT
cana-3689	80	35	the	the	DET
cana-3689	80	36	input	input	NOUN
cana-3689	80	37	for	for	ADP
cana-3689	80	38	the	the	DET
cana-3689	80	39	weather	weather	NOUN
cana-3689	80	40	data	datum	NOUN
cana-3689	80	41	set	set	VERB
cana-3689	80	42	denotes	denote	NOUN
cana-3689	80	43	specific	specific	ADJ
cana-3689	80	44	days	day	NOUN
cana-3689	80	45	as	as	ADP
cana-3689	80	46	a	a	DET
cana-3689	80	47	row	row	NOUN
cana-3689	80	48	,	,	PUNCT
cana-3689	80	49	attributes	attribute	VERB
cana-3689	80	50	denote	denote	VERB
cana-3689	80	51	weather	weather	NOUN
cana-3689	80	52	conditions	condition	NOUN
cana-3689	80	53	on	on	ADP
cana-3689	80	54	the	the	DET
cana-3689	80	55	given	give	VERB
cana-3689	80	56	day	day	NOUN
cana-3689	80	57	,	,	PUNCT
cana-3689	80	58	and	and	CCONJ
cana-3689	80	59	the	the	DET
cana-3689	80	60	class	class	NOUN
cana-3689	80	61	indicates	indicate	VERB
cana-3689	80	62	whether	whether	SCONJ
cana-3689	80	63	the	the	DET
cana-3689	80	64	conditions	condition	NOUN
cana-3689	80	65	are	be	AUX
cana-3689	80	66	conducive	conducive	ADJ
cana-3689	80	67	to	to	ADP
cana-3689	80	68	playing	play	VERB
cana-3689	80	69	golf	golf	NOUN
cana-3689	80	70	.	.	PUNCT
cana-3689	81	1	attributes	attribute	NOUN
cana-3689	81	2	include	include	VERB
cana-3689	81	3	outlook	outlook	NOUN
cana-3689	81	4	,	,	PUNCT
cana-3689	81	5	temperature	temperature	NOUN
cana-3689	81	6	,	,	PUNCT
cana-3689	81	7	humidity	humidity	NOUN
cana-3689	81	8	,	,	PUNCT
cana-3689	81	9	windy	windy	ADJ
cana-3689	81	10	,	,	PUNCT
cana-3689	81	11	and	and	CCONJ
cana-3689	81	12	boolean	boolean	ADJ
cana-3689	81	13	play	play	NOUN
cana-3689	81	14	golf	golf	NOUN
cana-3689	81	15	class	class	NOUN
cana-3689	81	16	variables	variable	NOUN
cana-3689	81	17	.	.	PUNCT
cana-3689	82	1	all	all	DET
cana-3689	82	2	the	the	DET
cana-3689	82	3	data	datum	NOUN
cana-3689	82	4	are	be	AUX
cana-3689	82	5	considered	consider	VERB
cana-3689	82	6	for	for	ADP
cana-3689	82	7	training	training	NOUN
cana-3689	82	8	purpose	purpose	NOUN
cana-3689	82	9	,	,	PUNCT
cana-3689	82	10	and	and	CCONJ
cana-3689	82	11	it	it	PRON
cana-3689	82	12	is	be	AUX
cana-3689	82	13	used	use	VERB
cana-3689	82	14	in	in	ADP
cana-3689	82	15	the	the	DET
cana-3689	82	16	sevenclassification	sevenclassification	NOUN
cana-3689	82	17	algorithm	algorithm	NOUN
cana-3689	82	18	likes	like	VERB
cana-3689	82	19	j48	j48	PROPN
cana-3689	82	20	,	,	PUNCT
cana-3689	82	21	random	random	ADJ
cana-3689	82	22	tree	tree	NOUN
cana-3689	82	23	(	(	PUNCT
cana-3689	82	24	rt	rt	NOUN
cana-3689	82	25	)	)	PUNCT
cana-3689	82	26	,	,	PUNCT
cana-3689	82	27	decision	decision	NOUN
cana-3689	82	28	stump	stump	NOUN
cana-3689	82	29	(	(	PUNCT
cana-3689	82	30	ds	ds	NOUN
cana-3689	82	31	)	)	PUNCT
cana-3689	82	32	,	,	PUNCT
cana-3689	82	33	logistic	logistic	ADJ
cana-3689	82	34	model	model	NOUN
cana-3689	82	35	tree	tree	NOUN
cana-3689	82	36	(	(	PUNCT
cana-3689	82	37	lmt	lmt	PROPN
cana-3689	82	38	)	)	PUNCT
cana-3689	82	39	,	,	PUNCT
cana-3689	82	40	hoeffding	hoeffde	VERB
cana-3689	82	41	tree	tree	NOUN
cana-3689	82	42	(	(	PUNCT
cana-3689	82	43	ht	ht	PROPN
cana-3689	82	44	)	)	PUNCT
cana-3689	82	45	,	,	PUNCT
cana-3689	82	46	reduce	reduce	VERB
cana-3689	82	47	error	error	NOUN
cana-3689	82	48	pruning	pruning	NOUN
cana-3689	82	49	(	(	PUNCT
cana-3689	82	50	rep	rep	NOUN
cana-3689	82	51	)	)	PUNCT
cana-3689	82	52	and	and	CCONJ
cana-3689	82	53	random	random	ADJ
cana-3689	82	54	forest	forest	NOUN
cana-3689	82	55	(	(	PUNCT
cana-3689	82	56	rf	rf	NOUN
cana-3689	82	57	)	)	PUNCT
cana-3689	82	58	are	be	AUX
cana-3689	82	59	used	use	VERB
cana-3689	82	60	to	to	PART
cana-3689	82	61	measure	measure	VERB
cana-3689	82	62	the	the	DET
cana-3689	82	63	accuracy	accuracy	NOUN
cana-3689	82	64	.	.	PUNCT
cana-3689	83	1	out	out	ADP
cana-3689	83	2	of	of	ADP
cana-3689	83	3	seven	seven	NUM
cana-3689	83	4	classification	classification	NOUN
cana-3689	83	5	algorithms	algorithm	NOUN
cana-3689	83	6	,	,	PUNCT
cana-3689	83	7	the	the	DET
cana-3689	83	8	random	random	ADJ
cana-3689	83	9	tree	tree	NOUN
cana-3689	83	10	algorithm	algorithm	NOUN
cana-3689	83	11	outperforms	outperform	VERB
cana-3689	83	12	other	other	ADJ
cana-3689	83	13	algorithms	algorithm	NOUN
cana-3689	83	14	by	by	ADP
cana-3689	83	15	yielding	yield	VERB
cana-3689	83	16	an	an	DET
cana-3689	83	17	accuracy	accuracy	NOUN
cana-3689	83	18	of	of	ADP
cana-3689	83	19	85.714	85.714	NUM
cana-3689	83	20	%	%	NOUN
cana-3689	83	21	.	.	PUNCT
cana-3689	84	1	sajid	sajid	PROPN
cana-3689	84	2	et	et	PROPN
cana-3689	84	3	al	al	PROPN
cana-3689	84	4	.	.	PROPN
cana-3689	84	5	(	(	PUNCT
cana-3689	84	6	2021	2021	NUM
cana-3689	84	7	)	)	PUNCT
cana-3689	84	8	explore	explore	VERB
cana-3689	84	9	a	a	DET
cana-3689	84	10	gender	gender	NOUN
cana-3689	84	11	-	-	PUNCT
cana-3689	84	12	matched	match	VERB
cana-3689	84	13	case	case	NOUN
cana-3689	84	14	–	–	PUNCT
cana-3689	84	15	control	control	NOUN
cana-3689	84	16	investigation	investigation	NOUN
cana-3689	84	17	took	take	VERB
cana-3689	84	18	place	place	NOUN
cana-3689	84	19	at	at	ADP
cana-3689	84	20	pakistan	pakistan	PROPN
cana-3689	84	21	's	's	PART
cana-3689	84	22	largest	large	ADJ
cana-3689	84	23	public	public	ADJ
cana-3689	84	24	sector	sector	NOUN
cana-3689	84	25	cardiac	cardiac	ADJ
cana-3689	84	26	hospital	hospital	NOUN
cana-3689	84	27	,	,	PUNCT
cana-3689	84	28	involving	involve	VERB
cana-3689	84	29	460	460	NUM
cana-3689	84	30	subjects	subject	NOUN
cana-3689	84	31	.	.	PUNCT
cana-3689	85	1	the	the	DET
cana-3689	85	2	dataset	dataset	NOUN
cana-3689	85	3	encompassed	encompass	VERB
cana-3689	85	4	eight	eight	NUM
cana-3689	85	5	nonclinical	nonclinical	ADJ
cana-3689	85	6	features	feature	NOUN
cana-3689	85	7	.	.	PUNCT
cana-3689	86	1	four	four	NUM
cana-3689	86	2	supervised	supervised	ADJ
cana-3689	86	3	machine	machine	NOUN
cana-3689	86	4	learning	learning	NOUN
cana-3689	86	5	(	(	PUNCT
cana-3689	86	6	ml	ml	NOUN
cana-3689	86	7	)	)	PUNCT
cana-3689	86	8	algorithms	algorithm	NOUN
cana-3689	86	9	were	be	AUX
cana-3689	86	10	employed	employ	VERB
cana-3689	86	11	to	to	PART
cana-3689	86	12	train	train	VERB
cana-3689	86	13	and	and	CCONJ
cana-3689	86	14	test	test	NOUN
cana-3689	86	15	models	model	NOUN
cana-3689	86	16	for	for	ADP
cana-3689	86	17	predicting	predict	VERB
cana-3689	86	18	cvd	cvd	PROPN
cana-3689	86	19	status	status	PROPN
cana-3689	86	20	,	,	PUNCT
cana-3689	86	21	with	with	ADP
cana-3689	86	22	traditional	traditional	ADJ
cana-3689	86	23	logistic	logistic	ADJ
cana-3689	86	24	regression	regression	NOUN
cana-3689	86	25	(	(	PUNCT
cana-3689	86	26	lr	lr	NOUN
cana-3689	86	27	)	)	PUNCT
cana-3689	86	28	serving	serve	VERB
cana-3689	86	29	as	as	ADP
cana-3689	86	30	the	the	DET
cana-3689	86	31	baseline	baseline	NOUN
cana-3689	86	32	.	.	PUNCT
cana-3689	87	1	models	model	NOUN
cana-3689	87	2	underwent	undergo	VERB
cana-3689	87	3	validation	validation	NOUN
cana-3689	87	4	via	via	ADP
cana-3689	87	5	a	a	DET
cana-3689	87	6	train	train	NOUN
cana-3689	87	7	–	–	PUNCT
cana-3689	87	8	test	test	NOUN
cana-3689	87	9	split	split	NOUN
cana-3689	87	10	(	(	PUNCT
cana-3689	87	11	70:30	70:30	NUM
cana-3689	87	12	)	)	PUNCT
cana-3689	87	13	and	and	CCONJ
cana-3689	87	14	tenfold	tenfold	ADV
cana-3689	87	15	cross	cross	ADJ
cana-3689	87	16	-	-	ADJ
cana-3689	87	17	validation	validation	ADJ
cana-3689	87	18	methods	method	NOUN
cana-3689	87	19	.	.	PUNCT
cana-3689	88	1	among	among	ADP
cana-3689	88	2	these	these	PRON
cana-3689	88	3	,	,	PUNCT
cana-3689	88	4	random	random	ADJ
cana-3689	88	5	forest	forest	NOUN
cana-3689	88	6	(	(	PUNCT
cana-3689	88	7	rf	rf	NOUN
cana-3689	88	8	)	)	PUNCT
cana-3689	88	9	,	,	PUNCT
cana-3689	88	10	a	a	DET
cana-3689	88	11	nonlinear	nonlinear	NOUN
cana-3689	88	12	ml	ml	NOUN
cana-3689	88	13	algorithm	algorithm	PROPN
cana-3689	88	14	,	,	PUNCT
cana-3689	88	15	outperformed	outperform	VERB
cana-3689	88	16	other	other	ADJ
cana-3689	88	17	algorithms	algorithm	NOUN
cana-3689	88	18	and	and	CCONJ
cana-3689	88	19	lr	lr	NOUN
cana-3689	88	20	,	,	PUNCT
cana-3689	88	21	achieving	achieve	VERB
cana-3689	88	22	an	an	DET
cana-3689	88	23	auc	auc	NOUN
cana-3689	88	24	of	of	ADP
cana-3689	88	25	0.851	0.851	NUM
cana-3689	88	26	and	and	CCONJ
cana-3689	88	27	0.853	0.853	NUM
cana-3689	88	28	in	in	ADP
cana-3689	88	29	the	the	DET
cana-3689	88	30	train	train	NOUN
cana-3689	88	31	–	–	PUNCT
cana-3689	88	32	test	test	NOUN
cana-3689	88	33	split	split	NOUN
cana-3689	88	34	and	and	CCONJ
cana-3689	88	35	tenfold	tenfold	ADV
cana-3689	88	36	cross	cross	NOUN
cana-3689	88	37	-	-	NOUN
cana-3689	88	38	validation	validation	ADJ
cana-3689	88	39	,	,	PUNCT
cana-3689	88	40	respectively	respectively	ADV
cana-3689	88	41	.	.	PUNCT
cana-3689	89	1	nonclinical	nonclinical	ADJ
cana-3689	89	2	features	feature	NOUN
cana-3689	89	3	demonstrated	demonstrate	VERB
cana-3689	89	4	a	a	DET
cana-3689	89	5	reasonably	reasonably	ADV
cana-3689	89	6	high	high	ADJ
cana-3689	89	7	accuracy	accuracy	NOUN
cana-3689	89	8	(	(	PUNCT
cana-3689	89	9	minimum	minimum	NOUN
cana-3689	89	10	71	71	NUM
cana-3689	89	11	%	%	NOUN
cana-3689	89	12	)	)	PUNCT
cana-3689	89	13	in	in	ADP
cana-3689	89	14	both	both	PRON
cana-3689	89	15	lr	lr	NOUN
cana-3689	89	16	and	and	CCONJ
cana-3689	89	17	ml	ml	NOUN
cana-3689	89	18	models	model	NOUN
cana-3689	89	19	,	,	PUNCT
cana-3689	89	20	highlighting	highlight	VERB
cana-3689	89	21	their	their	PRON
cana-3689	89	22	predictive	predictive	ADJ
cana-3689	89	23	capacity	capacity	NOUN
cana-3689	89	24	for	for	ADP
cana-3689	89	25	risk	risk	NOUN
cana-3689	89	26	estimation	estimation	NOUN
cana-3689	89	27	.	.	PUNCT
cana-3689	90	1	kumar	kumar	PROPN
cana-3689	90	2	et	et	PROPN
cana-3689	90	3	al	al	PROPN
cana-3689	90	4	.	.	PROPN
cana-3689	91	1	(	(	PUNCT
cana-3689	91	2	2018	2018	NUM
cana-3689	91	3	)	)	PUNCT
cana-3689	91	4	explore	explore	VERB
cana-3689	91	5	data	datum	NOUN
cana-3689	91	6	mining	mining	NOUN
cana-3689	91	7	stands	stand	VERB
cana-3689	91	8	out	out	ADP
cana-3689	91	9	as	as	ADP
cana-3689	91	10	a	a	DET
cana-3689	91	11	prevalent	prevalent	ADJ
cana-3689	91	12	method	method	NOUN
cana-3689	91	13	for	for	ADP
cana-3689	91	14	knowledge	knowledge	NOUN
cana-3689	91	15	extraction	extraction	NOUN
cana-3689	91	16	in	in	ADP
cana-3689	91	17	knowledge	knowledge	NOUN
cana-3689	91	18	discovery	discovery	PROPN
cana-3689	91	19	(	(	PUNCT
cana-3689	91	20	kdd	kdd	PROPN
cana-3689	91	21	)	)	PUNCT
cana-3689	91	22	.	.	PUNCT
cana-3689	92	1	machine	machine	NOUN
cana-3689	92	2	learning	learning	NOUN
cana-3689	92	3	plays	play	VERB
cana-3689	92	4	a	a	DET
cana-3689	92	5	crucial	crucial	ADJ
cana-3689	92	6	role	role	NOUN
cana-3689	92	7	in	in	ADP
cana-3689	92	8	analyzing	analyze	VERB
cana-3689	92	9	data	datum	NOUN
cana-3689	92	10	,	,	PUNCT
cana-3689	92	11	uncovering	uncovering	NOUN
cana-3689	92	12	correlations	correlation	NOUN
cana-3689	92	13	,	,	PUNCT
cana-3689	92	14	problem	problem	NOUN
cana-3689	92	15	-	-	PUNCT
cana-3689	92	16	solving	solving	NOUN
cana-3689	92	17	,	,	PUNCT
cana-3689	92	18	and	and	CCONJ
cana-3689	92	19	data	datum	NOUN
cana-3689	92	20	enrichment	enrichment	NOUN
cana-3689	92	21	.	.	PUNCT
cana-3689	93	1	particularly	particularly	ADV
cana-3689	93	2	in	in	ADP
cana-3689	93	3	the	the	DET
cana-3689	93	4	medical	medical	ADJ
cana-3689	93	5	field	field	NOUN
cana-3689	93	6	,	,	PUNCT
cana-3689	93	7	data	datum	NOUN
cana-3689	93	8	mining	mining	NOUN
cana-3689	93	9	techniques	technique	NOUN
cana-3689	93	10	and	and	CCONJ
cana-3689	93	11	machine	machine	NOUN
cana-3689	93	12	learning	learn	VERB
cana-3689	93	13	algorithms	algorithm	NOUN
cana-3689	93	14	hold	hold	VERB
cana-3689	93	15	significance	significance	NOUN
cana-3689	93	16	due	due	ADP
cana-3689	93	17	to	to	ADP
cana-3689	93	18	the	the	DET
cana-3689	93	19	abundance	abundance	NOUN
cana-3689	93	20	of	of	ADP
cana-3689	93	21	underutilized	underutilized	ADJ
cana-3689	93	22	healthcare	healthcare	NOUN
cana-3689	93	23	data	datum	NOUN
cana-3689	93	24	.	.	PUNCT
cana-3689	94	1	heart	heart	NOUN
cana-3689	94	2	disease	disease	NOUN
cana-3689	94	3	remains	remain	VERB
cana-3689	94	4	a	a	DET
cana-3689	94	5	leading	lead	VERB
cana-3689	94	6	cause	cause	NOUN
cana-3689	94	7	of	of	ADP
cana-3689	94	8	global	global	ADJ
cana-3689	94	9	mortality	mortality	NOUN
cana-3689	94	10	,	,	PUNCT
cana-3689	94	11	accounting	account	VERB
cana-3689	94	12	for	for	ADP
cana-3689	94	13	nearly	nearly	ADV
cana-3689	94	14	47	47	NUM
cana-3689	94	15	%	%	NOUN
cana-3689	94	16	of	of	ADP
cana-3689	94	17	all	all	DET
cana-3689	94	18	deaths	death	NOUN
cana-3689	94	19	.	.	PUNCT
cana-3689	95	1	employing	employ	VERB
cana-3689	95	2	eight	eight	NUM
cana-3689	95	3	algorithms	algorithm	NOUN
cana-3689	95	4	—	—	PUNCT
cana-3689	95	5	decision	decision	NOUN
cana-3689	95	6	tree	tree	NOUN
cana-3689	95	7	,	,	PUNCT
cana-3689	95	8	j48	j48	PROPN
cana-3689	95	9	algorithm	algorithm	NOUN
cana-3689	95	10	,	,	PUNCT
cana-3689	95	11	logistic	logistic	ADJ
cana-3689	95	12	model	model	NOUN
cana-3689	95	13	tree	tree	NOUN
cana-3689	95	14	algorithm	algorithm	NOUN
cana-3689	95	15	,	,	PUNCT
cana-3689	95	16	random	random	ADJ
cana-3689	95	17	forest	forest	NOUN
cana-3689	95	18	algorithm	algorithm	NOUN
cana-3689	95	19	,	,	PUNCT
cana-3689	95	20	naïve	naïve	ADJ
cana-3689	95	21	bayes	bayes	PROPN
cana-3689	95	22	,	,	PUNCT
cana-3689	95	23	knn	knn	PROPN
cana-3689	95	24	,	,	PUNCT
cana-3689	95	25	support	support	VERB
cana-3689	95	26	vector	vector	NOUN
cana-3689	95	27	machine	machine	NOUN
cana-3689	95	28	,	,	PUNCT
cana-3689	95	29	and	and	CCONJ
cana-3689	95	30	nearest	near	ADJ
cana-3689	95	31	neighbour	neighbour	NOUN
cana-3689	95	32	—	—	PUNCT
cana-3689	95	33	this	this	DET
cana-3689	95	34	study	study	NOUN
cana-3689	95	35	aims	aim	VERB
cana-3689	95	36	to	to	PART
cana-3689	95	37	predict	predict	VERB
cana-3689	95	38	heart	heart	NOUN
cana-3689	95	39	diseases	disease	NOUN
cana-3689	95	40	.	.	PUNCT
cana-3689	96	1	the	the	DET
cana-3689	96	2	accuracy	accuracy	NOUN
cana-3689	96	3	of	of	ADP
cana-3689	96	4	predictions	prediction	NOUN
cana-3689	96	5	increases	increase	VERB
cana-3689	96	6	with	with	ADP
cana-3689	96	7	more	more	ADJ
cana-3689	96	8	attributes	attribute	NOUN
cana-3689	96	9	.	.	PUNCT
cana-3689	97	1	the	the	DET
cana-3689	97	2	goal	goal	NOUN
cana-3689	97	3	is	be	AUX
cana-3689	97	4	to	to	PART
cana-3689	97	5	conduct	conduct	VERB
cana-3689	97	6	predictive	predictive	ADJ
cana-3689	97	7	analysis	analysis	NOUN
cana-3689	97	8	using	use	VERB
cana-3689	97	9	these	these	DET
cana-3689	97	10	data	datum	NOUN
cana-3689	97	11	mining	mining	NOUN
cana-3689	97	12	and	and	CCONJ
cana-3689	97	13	machine	machine	NOUN
cana-3689	97	14	learning	learning	NOUN
cana-3689	97	15	algorithms	algorithm	NOUN
cana-3689	97	16	,	,	PUNCT
cana-3689	97	17	assessing	assess	VERB
cana-3689	97	18	their	their	PRON
cana-3689	97	19	effectiveness	effectiveness	NOUN
cana-3689	97	20	and	and	CCONJ
cana-3689	97	21	efficiency	efficiency	NOUN
cana-3689	97	22	.	.	PUNCT
cana-3689	98	1	ramesh	ramesh	PROPN
cana-3689	98	2	et	et	PROPN
cana-3689	98	3	al	al	PROPN
cana-3689	98	4	.	.	PROPN
cana-3689	98	5	(	(	PUNCT
cana-3689	98	6	2022	2022	NUM
cana-3689	98	7	)	)	PUNCT
cana-3689	98	8	,	,	PUNCT
cana-3689	98	9	author	author	NOUN
cana-3689	98	10	utilized	utilize	VERB
cana-3689	98	11	an	an	DET
cana-3689	98	12	online	online	ADJ
cana-3689	98	13	uci	uci	NOUN
cana-3689	98	14	dataset	dataset	NOUN
cana-3689	98	15	containing	contain	VERB
cana-3689	98	16	303	303	NUM
cana-3689	98	17	rows	row	NOUN
cana-3689	98	18	and	and	CCONJ
cana-3689	98	19	76	76	NUM
cana-3689	98	20	properties	property	NOUN
cana-3689	98	21	,	,	PUNCT
cana-3689	98	22	selecting	select	VERB
cana-3689	98	23	approximately	approximately	ADV
cana-3689	98	24	14	14	NUM
cana-3689	98	25	of	of	ADP
cana-3689	98	26	these	these	DET
cana-3689	98	27	properties	property	NOUN
cana-3689	98	28	for	for	ADP
cana-3689	98	29	testing	test	VERB
cana-3689	98	30	purposes	purpose	NOUN
cana-3689	98	31	to	to	PART
cana-3689	98	32	validate	validate	VERB
cana-3689	98	33	various	various	ADJ
cana-3689	98	34	methods	method	NOUN
cana-3689	98	35	'	'	PART
cana-3689	98	36	performances	performance	NOUN
cana-3689	98	37	.	.	PUNCT
cana-3689	99	1	the	the	DET
cana-3689	99	2	isolation	isolation	NOUN
cana-3689	99	3	forest	forest	NOUN
cana-3689	99	4	approach	approach	NOUN
cana-3689	99	5	utilized	utilize	VERB
cana-3689	99	6	crucial	crucial	ADJ
cana-3689	99	7	dataset	dataset	NOUN
cana-3689	99	8	qualities	quality	NOUN
cana-3689	99	9	and	and	CCONJ
cana-3689	99	10	metrics	metric	NOUN
cana-3689	99	11	to	to	PART
cana-3689	99	12	standardize	standardize	VERB
cana-3689	99	13	information	information	NOUN
cana-3689	99	14	,	,	PUNCT
cana-3689	99	15	aiming	aim	VERB
cana-3689	99	16	for	for	ADP
cana-3689	99	17	improved	improved	ADJ
cana-3689	99	18	precision	precision	NOUN
cana-3689	99	19	.	.	PUNCT
cana-3689	100	1	employing	employ	VERB
cana-3689	100	2	supervised	supervised	ADJ
cana-3689	100	3	learning	learning	NOUN
cana-3689	100	4	methods	method	NOUN
cana-3689	100	5	—	—	PUNCT
cana-3689	100	6	naive	naive	ADJ
cana-3689	100	7	bayes	bayes	NOUN
cana-3689	100	8	,	,	PUNCT
cana-3689	100	9	svm	svm	ADJ
cana-3689	100	10	,	,	PUNCT
cana-3689	100	11	logistic	logistic	ADJ
cana-3689	100	12	regression	regression	NOUN
cana-3689	100	13	,	,	PUNCT
cana-3689	100	14	decision	decision	NOUN
cana-3689	100	15	tree	tree	NOUN
cana-3689	100	16	classifier	classifier	NOUN
cana-3689	100	17	,	,	PUNCT
cana-3689	100	18	random	random	ADJ
cana-3689	100	19	forest	forest	NOUN
cana-3689	100	20	,	,	PUNCT
cana-3689	100	21	and	and	CCONJ
cana-3689	100	22	knearest	knearest	PROPN
cana-3689	100	23	neighbor	neighbor	NOUN
cana-3689	100	24	—	—	PUNCT
cana-3689	100	25	the	the	DET
cana-3689	100	26	study	study	NOUN
cana-3689	100	27	focused	focus	VERB
cana-3689	100	28	on	on	ADP
cana-3689	100	29	assessing	assess	VERB
cana-3689	100	30	effectiveness	effectiveness	NOUN
cana-3689	100	31	,	,	PUNCT
cana-3689	100	32	sensitivity	sensitivity	NOUN
cana-3689	100	33	,	,	PUNCT
cana-3689	100	34	precision	precision	NOUN
cana-3689	100	35	,	,	PUNCT
cana-3689	100	36	accuracy	accuracy	NOUN
cana-3689	100	37	,	,	PUNCT
cana-3689	100	38	and	and	CCONJ
cana-3689	100	39	f1	f1	NOUN
cana-3689	100	40	-	-	PUNCT
cana-3689	100	41	score	score	NOUN
cana-3689	100	42	.	.	PUNCT
cana-3689	101	1	the	the	DET
cana-3689	101	2	experimental	experimental	ADJ
cana-3689	101	3	outcomes	outcome	NOUN
cana-3689	101	4	highlighted	highlight	VERB
cana-3689	101	5	k	k	ADJ
cana-3689	101	6	-	-	PUNCT
cana-3689	101	7	nearest	near	ADJ
cana-3689	101	8	neighbor	neighbor	NOUN
cana-3689	101	9	(	(	PUNCT
cana-3689	101	10	knn	knn	PROPN
cana-3689	101	11	)	)	PUNCT
cana-3689	101	12	with	with	ADP
cana-3689	101	13	eight	eight	NUM
cana-3689	101	14	neighbors	neighbor	NOUN
cana-3689	101	15	as	as	ADP
cana-3689	101	16	particularly	particularly	ADV
cana-3689	101	17	robust	robust	ADJ
cana-3689	101	18	compared	compare	VERB
cana-3689	101	19	to	to	ADP
cana-3689	101	20	other	other	ADJ
cana-3689	101	21	methods	method	NOUN
cana-3689	101	22	such	such	ADJ
cana-3689	101	23	as	as	ADP
cana-3689	101	24	naive	naive	ADJ
cana-3689	101	25	bayes	bayes	NOUN
cana-3689	101	26	,	,	PUNCT
cana-3689	101	27	svm	svm	PROPN
cana-3689	101	28	(	(	PUNCT
cana-3689	101	29	linear	linear	PROPN
cana-3689	101	30	kernel	kernel	PROPN
cana-3689	101	31	)	)	PUNCT
cana-3689	101	32	,	,	PUNCT
cana-3689	101	33	decision	decision	NOUN
cana-3689	101	34	tree	tree	NOUN
cana-3689	101	35	classifier	classifier	NOUN
cana-3689	101	36	with	with	ADP
cana-3689	101	37	varying	vary	VERB
cana-3689	101	38	features	feature	NOUN
cana-3689	101	39	,	,	PUNCT
cana-3689	101	40	and	and	CCONJ
cana-3689	101	41	random	random	ADJ
cana-3689	101	42	forest	forest	NOUN
cana-3689	101	43	classifiers	classifier	NOUN
cana-3689	101	44	[	[	X
cana-3689	101	45	9	9	NUM
cana-3689	101	46	]	]	PUNCT
cana-3689	101	47	.	.	PUNCT
cana-3689	102	1	rajesh	rajesh	PROPN
cana-3689	102	2	and	and	CCONJ
cana-3689	102	3	karthikeyan	karthikeyan	PROPN
cana-3689	102	4	(	(	PUNCT
cana-3689	102	5	2019	2019	NUM
cana-3689	102	6	)	)	PUNCT
cana-3689	102	7	data	datum	NOUN
cana-3689	102	8	mining	mining	NOUN
cana-3689	102	9	is	be	AUX
cana-3689	102	10	discovering	discover	VERB
cana-3689	102	11	hiding	hiding	NOUN
cana-3689	102	12	information	information	NOUN
cana-3689	102	13	that	that	PRON
cana-3689	102	14	efficiently	efficiently	ADV
cana-3689	102	15	utilizes	utilize	VERB
cana-3689	102	16	the	the	DET
cana-3689	102	17	prediction	prediction	NOUN
cana-3689	102	18	by	by	ADP
cana-3689	102	19	stochastic	stochastic	ADJ
cana-3689	102	20	sensing	sense	VERB
cana-3689	102	21	concept	concept	NOUN
cana-3689	102	22	.	.	PUNCT
cana-3689	103	1	this	this	DET
cana-3689	103	2	paper	paper	NOUN
cana-3689	103	3	proposes	propose	VERB
cana-3689	103	4	communications	communication	NOUN
cana-3689	103	5	on	on	ADP
cana-3689	103	6	applied	apply	VERB
cana-3689	103	7	nonlinear	nonlinear	ADJ
cana-3689	103	8	analysis	analysis	NOUN
cana-3689	103	9	issn	issn	NOUN
cana-3689	103	10	:	:	PUNCT
cana-3689	103	11	1074	1074	NUM
cana-3689	103	12	-	-	PUNCT
cana-3689	103	13	133x	133x	NUM
cana-3689	103	14	vol	vol	NOUN
cana-3689	103	15	32	32	NUM
cana-3689	103	16	no	no	NOUN
cana-3689	103	17	.	.	PUNCT
cana-3689	104	1	8s	8s	PROPN
cana-3689	104	2	(	(	PUNCT
cana-3689	104	3	2025	2025	NUM
cana-3689	104	4	)	)	PUNCT
cana-3689	104	5	https://internationalpubls.com	https://internationalpubls.com	X
cana-3689	104	6	448	448	NUM
cana-3689	104	7	an	an	DET
cana-3689	104	8	efficient	efficient	ADJ
cana-3689	104	9	assessment	assessment	NOUN
cana-3689	104	10	of	of	ADP
cana-3689	104	11	groundwater	groundwater	NOUN
cana-3689	104	12	level	level	NOUN
cana-3689	104	13	,	,	PUNCT
cana-3689	104	14	rainfall	rainfall	NOUN
cana-3689	104	15	,	,	PUNCT
cana-3689	104	16	population	population	NOUN
cana-3689	104	17	,	,	PUNCT
cana-3689	104	18	food	food	NOUN
cana-3689	104	19	grains	grain	NOUN
cana-3689	104	20	,	,	PUNCT
cana-3689	104	21	and	and	CCONJ
cana-3689	104	22	enterprises	enterprise	NOUN
cana-3689	104	23	dataset	dataset	VERB
cana-3689	104	24	by	by	ADP
cana-3689	104	25	adopting	adopt	VERB
cana-3689	104	26	stochastic	stochastic	ADJ
cana-3689	104	27	modeling	modeling	NOUN
cana-3689	104	28	and	and	CCONJ
cana-3689	104	29	data	datum	NOUN
cana-3689	104	30	mining	mining	NOUN
cana-3689	104	31	approaches	approach	NOUN
cana-3689	104	32	.	.	PUNCT
cana-3689	105	1	firstly	firstly	ADV
cana-3689	105	2	,	,	PUNCT
cana-3689	105	3	the	the	DET
cana-3689	105	4	novel	novel	ADJ
cana-3689	105	5	data	datum	NOUN
cana-3689	105	6	assimilation	assimilation	NOUN
cana-3689	105	7	analysis	analysis	NOUN
cana-3689	105	8	is	be	AUX
cana-3689	105	9	proposed	propose	VERB
cana-3689	105	10	to	to	PART
cana-3689	105	11	predict	predict	VERB
cana-3689	105	12	the	the	DET
cana-3689	105	13	groundwater	groundwater	NOUN
cana-3689	105	14	level	level	NOUN
cana-3689	105	15	effectively	effectively	ADV
cana-3689	105	16	.	.	PUNCT
cana-3689	106	1	experimental	experimental	ADJ
cana-3689	106	2	results	result	NOUN
cana-3689	106	3	are	be	AUX
cana-3689	106	4	done	do	VERB
cana-3689	106	5	,	,	PUNCT
cana-3689	106	6	and	and	CCONJ
cana-3689	106	7	the	the	DET
cana-3689	106	8	various	various	ADJ
cana-3689	106	9	expected	expect	VERB
cana-3689	106	10	groundwater	groundwater	NOUN
cana-3689	106	11	level	level	NOUN
cana-3689	106	12	estimations	estimation	NOUN
cana-3689	106	13	indicate	indicate	VERB
cana-3689	106	14	the	the	DET
cana-3689	106	15	sternness	sternness	NOUN
cana-3689	106	16	of	of	ADP
cana-3689	106	17	the	the	DET
cana-3689	106	18	approach	approach	NOUN
cana-3689	106	19	.	.	PUNCT
cana-3689	107	1	rajesh	rajesh	PROPN
cana-3689	107	2	et	et	PROPN
cana-3689	107	3	al	al	PROPN
cana-3689	107	4	.	.	PROPN
cana-3689	108	1	(	(	PUNCT
cana-3689	108	2	2019	2019	NUM
cana-3689	108	3	)	)	PUNCT
cana-3689	108	4	,	,	PUNCT
cana-3689	108	5	input	input	NOUN
cana-3689	108	6	for	for	ADP
cana-3689	108	7	the	the	DET
cana-3689	108	8	chronic	chronic	ADJ
cana-3689	108	9	disease	disease	NOUN
cana-3689	108	10	data	datum	NOUN
cana-3689	108	11	denotes	denote	VERB
cana-3689	108	12	a	a	DET
cana-3689	108	13	specific	specific	ADJ
cana-3689	108	14	location	location	NOUN
cana-3689	108	15	as	as	ADP
cana-3689	108	16	a	a	DET
cana-3689	108	17	row	row	NOUN
cana-3689	108	18	;	;	PUNCT
cana-3689	108	19	attributes	attribute	VERB
cana-3689	108	20	denote	denote	VERB
cana-3689	108	21	topics	topic	NOUN
cana-3689	108	22	,	,	PUNCT
cana-3689	108	23	questions	question	NOUN
cana-3689	108	24	,	,	PUNCT
cana-3689	108	25	data	datum	NOUN
cana-3689	108	26	values	value	NOUN
cana-3689	108	27	,	,	PUNCT
cana-3689	108	28	low	low	ADJ
cana-3689	108	29	confidence	confidence	NOUN
cana-3689	108	30	limit	limit	NOUN
cana-3689	108	31	,	,	PUNCT
cana-3689	108	32	and	and	CCONJ
cana-3689	108	33	high	high	ADJ
cana-3689	108	34	confidence	confidence	NOUN
cana-3689	108	35	limit	limit	NOUN
cana-3689	108	36	.	.	PUNCT
cana-3689	109	1	all	all	DET
cana-3689	109	2	the	the	DET
cana-3689	109	3	data	datum	NOUN
cana-3689	109	4	are	be	AUX
cana-3689	109	5	considered	consider	VERB
cana-3689	109	6	for	for	ADP
cana-3689	109	7	training	training	NOUN
cana-3689	109	8	and	and	CCONJ
cana-3689	109	9	testing	testing	NOUN
cana-3689	109	10	using	use	VERB
cana-3689	109	11	five	five	NUM
cana-3689	109	12	classification	classification	NOUN
cana-3689	109	13	algorithms	algorithm	NOUN
cana-3689	109	14	.	.	PUNCT
cana-3689	110	1	the	the	DET
cana-3689	110	2	authors	author	NOUN
cana-3689	110	3	present	present	VERB
cana-3689	110	4	the	the	DET
cana-3689	110	5	various	various	ADJ
cana-3689	110	6	analysis	analysis	NOUN
cana-3689	110	7	and	and	CCONJ
cana-3689	110	8	accuracy	accuracy	NOUN
cana-3689	110	9	of	of	ADP
cana-3689	110	10	five	five	NUM
cana-3689	110	11	different	different	ADJ
cana-3689	110	12	decision	decision	NOUN
cana-3689	110	13	tree	tree	NOUN
cana-3689	110	14	algorithms	algorithm	NOUN
cana-3689	110	15	;	;	PUNCT
cana-3689	110	16	the	the	DET
cana-3689	110	17	m5p	m5p	NOUN
cana-3689	110	18	decision	decision	NOUN
cana-3689	110	19	tree	tree	NOUN
cana-3689	110	20	approach	approach	NOUN
cana-3689	110	21	is	be	AUX
cana-3689	110	22	the	the	DET
cana-3689	110	23	best	good	ADJ
cana-3689	110	24	algorithm	algorithm	NOUN
cana-3689	110	25	to	to	PART
cana-3689	110	26	build	build	VERB
cana-3689	110	27	the	the	DET
cana-3689	110	28	model	model	NOUN
cana-3689	110	29	compared	compare	VERB
cana-3689	110	30	with	with	ADP
cana-3689	110	31	other	other	ADJ
cana-3689	110	32	decision	decision	NOUN
cana-3689	110	33	tree	tree	NOUN
cana-3689	110	34	approaches	approach	NOUN
cana-3689	110	35	.	.	PUNCT
cana-3689	111	1	2	2	X
cana-3689	111	2	.	.	NUM
cana-3689	111	3	backgrounds	background	NOUN
cana-3689	111	4	and	and	CCONJ
cana-3689	111	5	methodologies	methodology	NOUN
cana-3689	111	6	2.1	2.1	NUM
cana-3689	111	7	logistic	logistic	ADJ
cana-3689	111	8	regression	regression	NOUN
cana-3689	111	9	logistic	logistic	ADJ
cana-3689	111	10	regression	regression	NOUN
cana-3689	111	11	is	be	AUX
cana-3689	111	12	a	a	DET
cana-3689	111	13	statistical	statistical	ADJ
cana-3689	111	14	method	method	NOUN
cana-3689	111	15	used	use	VERB
cana-3689	111	16	for	for	ADP
cana-3689	111	17	binary	binary	ADJ
cana-3689	111	18	classification	classification	NOUN
cana-3689	111	19	,	,	PUNCT
cana-3689	111	20	which	which	PRON
cana-3689	111	21	means	mean	VERB
cana-3689	111	22	it	it	PRON
cana-3689	111	23	's	be	AUX
cana-3689	111	24	used	use	VERB
cana-3689	111	25	to	to	PART
cana-3689	111	26	predict	predict	VERB
cana-3689	111	27	the	the	DET
cana-3689	111	28	probability	probability	NOUN
cana-3689	111	29	of	of	ADP
cana-3689	111	30	an	an	DET
cana-3689	111	31	observation	observation	NOUN
cana-3689	111	32	belonging	belong	VERB
cana-3689	111	33	to	to	ADP
cana-3689	111	34	one	one	NUM
cana-3689	111	35	of	of	ADP
cana-3689	111	36	two	two	NUM
cana-3689	111	37	classes	class	NOUN
cana-3689	111	38	(	(	PUNCT
cana-3689	111	39	usually	usually	ADV
cana-3689	111	40	labeled	label	VERB
cana-3689	111	41	as	as	ADP
cana-3689	111	42	0	0	NUM
cana-3689	111	43	and	and	CCONJ
cana-3689	111	44	1	1	NUM
cana-3689	111	45	)	)	PUNCT
cana-3689	111	46	.	.	PUNCT
cana-3689	112	1	it	it	PRON
cana-3689	112	2	's	be	AUX
cana-3689	112	3	a	a	DET
cana-3689	112	4	type	type	NOUN
cana-3689	112	5	of	of	ADP
cana-3689	112	6	regression	regression	NOUN
cana-3689	112	7	analysis	analysis	NOUN
cana-3689	112	8	that	that	PRON
cana-3689	112	9	's	be	AUX
cana-3689	112	10	particularly	particularly	ADV
cana-3689	112	11	suited	suit	VERB
cana-3689	112	12	for	for	ADP
cana-3689	112	13	categorical	categorical	ADJ
cana-3689	112	14	outcome	outcome	NOUN
cana-3689	112	15	variables	variable	NOUN
cana-3689	112	16	.	.	PUNCT
cana-3689	113	1	the	the	DET
cana-3689	113	2	formula	formula	NOUN
cana-3689	113	3	for	for	ADP
cana-3689	113	4	logistic	logistic	ADJ
cana-3689	113	5	regression	regression	NOUN
cana-3689	113	6	involves	involve	VERB
cana-3689	113	7	the	the	DET
cana-3689	113	8	logistic	logistic	ADJ
cana-3689	113	9	function	function	NOUN
cana-3689	113	10	(	(	PUNCT
cana-3689	113	11	also	also	ADV
cana-3689	113	12	known	know	VERB
cana-3689	113	13	as	as	ADP
cana-3689	113	14	the	the	DET
cana-3689	113	15	sigmoid	sigmoid	NOUN
cana-3689	113	16	function	function	NOUN
cana-3689	113	17	)	)	PUNCT
cana-3689	113	18	to	to	PART
cana-3689	113	19	transform	transform	VERB
cana-3689	113	20	the	the	DET
cana-3689	113	21	linear	linear	ADJ
cana-3689	113	22	combination	combination	NOUN
cana-3689	113	23	of	of	ADP
cana-3689	113	24	input	input	NOUN
cana-3689	113	25	features	feature	NOUN
cana-3689	113	26	into	into	ADP
cana-3689	113	27	a	a	DET
cana-3689	113	28	value	value	NOUN
cana-3689	113	29	between	between	ADP
cana-3689	113	30	0	0	NUM
cana-3689	113	31	and	and	CCONJ
cana-3689	113	32	1	1	NUM
cana-3689	113	33	,	,	PUNCT
cana-3689	113	34	representing	represent	VERB
cana-3689	113	35	the	the	DET
cana-3689	113	36	predicted	predict	VERB
cana-3689	113	37	probability	probability	NOUN
cana-3689	113	38	of	of	ADP
cana-3689	113	39	the	the	DET
cana-3689	113	40	positive	positive	ADJ
cana-3689	113	41	class	class	NOUN
cana-3689	113	42	.	.	PUNCT
cana-3689	114	1	the	the	DET
cana-3689	114	2	formula	formula	NOUN
cana-3689	114	3	is	be	AUX
cana-3689	114	4	as	as	SCONJ
cana-3689	114	5	follows	follow	VERB
cana-3689	114	6	:	:	PUNCT
cana-3689	114	7	p	p	X
cana-3689	114	8	(	(	PUNCT
cana-3689	114	9	y	y	NOUN
cana-3689	114	10	=	=	SYM
cana-3689	114	11	1	1	NUM
cana-3689	114	12	x	x	X
cana-3689	114	13	)	)	PUNCT
cana-3689	115	1	=	=	SYM
cana-3689	115	2	1	1	NUM
cana-3689	115	3	1	1	NUM
cana-3689	115	4	+	+	CCONJ
cana-3689	115	5	e−(β	e−(β	ADJ
cana-3689	115	6	0	0	PUNCT
cana-3689	116	1	+	+	ADJ
cana-3689	116	2	β	β	X
cana-3689	116	3	1	1	NUM
cana-3689	116	4	x1+β	x1+β	PROPN
cana-3689	116	5	2	2	NUM
cana-3689	116	6	x2+⋯+β	x2+⋯+β	PROPN
cana-3689	116	7	n	n	PROPN
cana-3689	116	8	xn	xn	NUM
cana-3689	116	9	)	)	PUNCT
cana-3689	116	10	2.2	2.2	NUM
cana-3689	116	11	smo	smo	PROPN
cana-3689	116	12	smo	smo	PROPN
cana-3689	116	13	stands	stand	VERB
cana-3689	116	14	for	for	ADP
cana-3689	116	15	"	"	PUNCT
cana-3689	116	16	sequential	sequential	ADJ
cana-3689	116	17	minimal	minimal	ADJ
cana-3689	116	18	optimization	optimization	NOUN
cana-3689	116	19	,	,	PUNCT
cana-3689	116	20	"	"	PUNCT
cana-3689	116	21	an	an	DET
cana-3689	116	22	algorithm	algorithm	NOUN
cana-3689	116	23	used	use	VERB
cana-3689	116	24	for	for	ADP
cana-3689	116	25	training	training	NOUN
cana-3689	116	26	support	support	NOUN
cana-3689	116	27	vector	vector	NOUN
cana-3689	116	28	machines	machine	NOUN
cana-3689	116	29	(	(	PUNCT
cana-3689	116	30	svms	svms	NOUN
cana-3689	116	31	)	)	PUNCT
cana-3689	116	32	,	,	PUNCT
cana-3689	116	33	machine	machine	NOUN
cana-3689	116	34	learning	learning	NOUN
cana-3689	116	35	models	model	NOUN
cana-3689	116	36	commonly	commonly	ADV
cana-3689	116	37	used	use	VERB
cana-3689	116	38	for	for	ADP
cana-3689	116	39	classification	classification	NOUN
cana-3689	116	40	and	and	CCONJ
cana-3689	116	41	regression	regression	NOUN
cana-3689	116	42	tasks	task	NOUN
cana-3689	116	43	.	.	PUNCT
cana-3689	117	1	the	the	DET
cana-3689	117	2	smo	smo	PROPN
cana-3689	117	3	algorithm	algorithm	NOUN
cana-3689	117	4	is	be	AUX
cana-3689	117	5	particularly	particularly	ADV
cana-3689	117	6	well	well	ADV
cana-3689	117	7	-	-	PUNCT
cana-3689	117	8	suited	suited	ADJ
cana-3689	117	9	for	for	ADP
cana-3689	117	10	solving	solve	VERB
cana-3689	117	11	the	the	DET
cana-3689	117	12	quadratic	quadratic	ADJ
cana-3689	117	13	programming	programming	NOUN
cana-3689	117	14	optimization	optimization	NOUN
cana-3689	117	15	problem	problem	NOUN
cana-3689	117	16	that	that	PRON
cana-3689	117	17	arises	arise	VERB
cana-3689	117	18	during	during	ADP
cana-3689	117	19	the	the	DET
cana-3689	117	20	training	training	NOUN
cana-3689	117	21	of	of	ADP
cana-3689	117	22	svms	svms	NOUN
cana-3689	117	23	.	.	PUNCT
cana-3689	118	1	step	step	NOUN
cana-3689	118	2	1	1	NUM
cana-3689	118	3	.	.	PUNCT
cana-3689	118	4	initialization	initialization	NOUN
cana-3689	118	5	step	step	NOUN
cana-3689	118	6	2	2	NUM
cana-3689	118	7	.	.	PUNCT
cana-3689	118	8	selection	selection	NOUN
cana-3689	118	9	of	of	ADP
cana-3689	118	10	two	two	NUM
cana-3689	118	11	lagrange	lagrange	NOUN
cana-3689	118	12	multipliers	multiplier	NOUN
cana-3689	118	13	step	step	VERB
cana-3689	118	14	3	3	NUM
cana-3689	118	15	.	.	PUNCT
cana-3689	118	16	optimize	optimize	VERB
cana-3689	118	17	the	the	DET
cana-3689	118	18	pair	pair	NOUN
cana-3689	118	19	of	of	ADP
cana-3689	118	20	lagrange	lagrange	NOUN
cana-3689	118	21	multipliers	multiplier	NOUN
cana-3689	118	22	step	step	VERB
cana-3689	118	23	4	4	NUM
cana-3689	118	24	.	.	PUNCT
cana-3689	118	25	update	update	VERB
cana-3689	118	26	the	the	DET
cana-3689	118	27	model	model	NOUN
cana-3689	118	28	step	step	NOUN
cana-3689	118	29	5	5	NUM
cana-3689	118	30	.	.	PUNCT
cana-3689	119	1	convergence	convergence	NOUN
cana-3689	119	2	checking	check	VERB
cana-3689	119	3	step	step	NOUN
cana-3689	119	4	6	6	NUM
cana-3689	119	5	.	.	PUNCT
cana-3689	120	1	repeat	repeat	VERB
cana-3689	120	2	2.3	2.3	NUM
cana-3689	120	3	j48	j48	PROPN
cana-3689	120	4	j48	j48	NOUN
cana-3689	120	5	,	,	PUNCT
cana-3689	120	6	also	also	ADV
cana-3689	120	7	known	know	VERB
cana-3689	120	8	as	as	ADP
cana-3689	120	9	c4.5	c4.5	PROPN
cana-3689	120	10	,	,	PUNCT
cana-3689	120	11	is	be	AUX
cana-3689	120	12	a	a	DET
cana-3689	120	13	popular	popular	ADJ
cana-3689	120	14	decision	decision	NOUN
cana-3689	120	15	tree	tree	NOUN
cana-3689	120	16	algorithm	algorithm	NOUN
cana-3689	120	17	used	use	VERB
cana-3689	120	18	for	for	ADP
cana-3689	120	19	classification	classification	NOUN
cana-3689	120	20	tasks	task	NOUN
cana-3689	120	21	in	in	ADP
cana-3689	120	22	machine	machine	NOUN
cana-3689	120	23	learning	learning	NOUN
cana-3689	120	24	and	and	CCONJ
cana-3689	120	25	data	datum	NOUN
cana-3689	120	26	mining	mining	NOUN
cana-3689	120	27	.	.	PUNCT
cana-3689	121	1	it	it	PRON
cana-3689	121	2	was	be	AUX
cana-3689	121	3	developed	develop	VERB
cana-3689	121	4	by	by	ADP
cana-3689	121	5	ross	ross	PROPN
cana-3689	121	6	quinlan	quinlan	PROPN
cana-3689	121	7	and	and	CCONJ
cana-3689	121	8	is	be	AUX
cana-3689	121	9	an	an	DET
cana-3689	121	10	extension	extension	NOUN
cana-3689	121	11	of	of	ADP
cana-3689	121	12	the	the	DET
cana-3689	121	13	earlier	early	ADJ
cana-3689	121	14	id3	id3	NOUN
cana-3689	121	15	(	(	PUNCT
cana-3689	121	16	iterative	iterative	NOUN
cana-3689	121	17	dichotomiser	dichotomiser	NOUN
cana-3689	121	18	3	3	NUM
cana-3689	121	19	)	)	PUNCT
cana-3689	121	20	algorithm	algorithm	NOUN
cana-3689	121	21	.	.	PUNCT
cana-3689	122	1	j48	j48	PROPN
cana-3689	122	2	is	be	AUX
cana-3689	122	3	widely	widely	ADV
cana-3689	122	4	used	use	VERB
cana-3689	122	5	due	due	ADP
cana-3689	122	6	to	to	ADP
cana-3689	122	7	its	its	PRON
cana-3689	122	8	effectiveness	effectiveness	NOUN
cana-3689	122	9	,	,	PUNCT
cana-3689	122	10	ease	ease	NOUN
cana-3689	122	11	of	of	ADP
cana-3689	122	12	use	use	NOUN
cana-3689	122	13	,	,	PUNCT
cana-3689	122	14	and	and	CCONJ
cana-3689	122	15	ability	ability	NOUN
cana-3689	122	16	to	to	PART
cana-3689	122	17	handle	handle	VERB
cana-3689	122	18	both	both	CCONJ
cana-3689	122	19	categorical	categorical	ADJ
cana-3689	122	20	and	and	CCONJ
cana-3689	122	21	numerical	numerical	ADJ
cana-3689	122	22	attributes	attribute	NOUN
cana-3689	122	23	.	.	PUNCT
cana-3689	123	1	here	here	ADV
cana-3689	123	2	are	be	AUX
cana-3689	123	3	the	the	DET
cana-3689	123	4	key	key	ADJ
cana-3689	123	5	features	feature	NOUN
cana-3689	123	6	and	and	CCONJ
cana-3689	123	7	steps	step	NOUN
cana-3689	123	8	of	of	ADP
cana-3689	123	9	the	the	DET
cana-3689	123	10	j48	j48	PROPN
cana-3689	123	11	algorithm	algorithm	NOUN
cana-3689	123	12	:	:	PUNCT
cana-3689	123	13	step	step	NOUN
cana-3689	123	14	1	1	NUM
cana-3689	123	15	.	.	PUNCT
cana-3689	123	16	attribute	attribute	NOUN
cana-3689	123	17	selection	selection	NOUN
cana-3689	123	18	step	step	NOUN
cana-3689	123	19	2	2	NUM
cana-3689	123	20	.	.	PUNCT
cana-3689	123	21	splitting	splitting	NOUN
cana-3689	123	22	nodes	node	NOUN
cana-3689	123	23	step	step	VERB
cana-3689	123	24	3	3	NUM
cana-3689	123	25	.	.	PUNCT
cana-3689	123	26	recursion	recursion	NOUN
cana-3689	123	27	communications	communication	NOUN
cana-3689	123	28	on	on	ADP
cana-3689	123	29	applied	apply	VERB
cana-3689	123	30	nonlinear	nonlinear	ADJ
cana-3689	123	31	analysis	analysis	NOUN
cana-3689	123	32	issn	issn	NOUN
cana-3689	123	33	:	:	PUNCT
cana-3689	123	34	1074	1074	NUM
cana-3689	123	35	-	-	PUNCT
cana-3689	123	36	133x	133x	NUM
cana-3689	123	37	vol	vol	NOUN
cana-3689	123	38	32	32	NUM
cana-3689	123	39	no	no	NOUN
cana-3689	123	40	.	.	PUNCT
cana-3689	124	1	8s	8s	PROPN
cana-3689	124	2	(	(	PUNCT
cana-3689	124	3	2025	2025	NUM
cana-3689	124	4	)	)	PUNCT
cana-3689	124	5	https://internationalpubls.com	https://internationalpubls.com	X
cana-3689	124	6	449	449	NUM
cana-3689	124	7	step	step	NOUN
cana-3689	124	8	4	4	NUM
cana-3689	124	9	.	.	PUNCT
cana-3689	124	10	pruning	prune	VERB
cana-3689	124	11	step	step	NOUN
cana-3689	124	12	5	5	NUM
cana-3689	124	13	.	.	PUNCT
cana-3689	124	14	handling	handle	VERB
cana-3689	124	15	missing	miss	VERB
cana-3689	124	16	values	value	NOUN
cana-3689	124	17	step	step	VERB
cana-3689	124	18	6	6	NUM
cana-3689	124	19	.	.	PUNCT
cana-3689	125	1	post	post	ADJ
cana-3689	125	2	-	-	ADJ
cana-3689	125	3	pruning	pruning	ADJ
cana-3689	125	4	step	step	NOUN
cana-3689	125	5	7	7	NUM
cana-3689	125	6	.	.	PUNCT
cana-3689	125	7	leaf	leaf	NOUN
cana-3689	125	8	node	node	ADJ
cana-3689	125	9	prediction	prediction	NOUN
cana-3689	125	10	2.4	2.4	NUM
cana-3689	125	11	random	random	ADJ
cana-3689	125	12	forest	forest	NOUN
cana-3689	125	13	random	random	ADJ
cana-3689	125	14	forest	forest	NOUN
cana-3689	125	15	is	be	AUX
cana-3689	125	16	a	a	DET
cana-3689	125	17	powerful	powerful	ADJ
cana-3689	125	18	ensemble	ensemble	ADJ
cana-3689	125	19	learning	learning	NOUN
cana-3689	125	20	algorithm	algorithm	NOUN
cana-3689	125	21	used	use	VERB
cana-3689	125	22	for	for	ADP
cana-3689	125	23	both	both	CCONJ
cana-3689	125	24	classification	classification	NOUN
cana-3689	125	25	and	and	CCONJ
cana-3689	125	26	regression	regression	NOUN
cana-3689	125	27	tasks	task	NOUN
cana-3689	125	28	.	.	PUNCT
cana-3689	126	1	it	it	PRON
cana-3689	126	2	's	be	AUX
cana-3689	126	3	based	base	VERB
cana-3689	126	4	on	on	ADP
cana-3689	126	5	the	the	DET
cana-3689	126	6	concept	concept	NOUN
cana-3689	126	7	of	of	ADP
cana-3689	126	8	bagging	bagging	NOUN
cana-3689	126	9	(	(	PUNCT
cana-3689	126	10	bootstrap	bootstrap	NOUN
cana-3689	126	11	aggregating	aggregating	NOUN
cana-3689	126	12	)	)	PUNCT
cana-3689	126	13	and	and	CCONJ
cana-3689	126	14	utilizes	utilize	VERB
cana-3689	126	15	multiple	multiple	ADJ
cana-3689	126	16	decision	decision	NOUN
cana-3689	126	17	trees	tree	NOUN
cana-3689	126	18	to	to	PART
cana-3689	126	19	create	create	VERB
cana-3689	126	20	a	a	DET
cana-3689	126	21	robust	robust	ADJ
cana-3689	126	22	and	and	CCONJ
cana-3689	126	23	accurate	accurate	ADJ
cana-3689	126	24	predictive	predictive	ADJ
cana-3689	126	25	model	model	NOUN
cana-3689	126	26	.	.	PUNCT
cana-3689	127	1	here	here	ADV
cana-3689	127	2	's	be	AUX
cana-3689	127	3	how	how	SCONJ
cana-3689	127	4	the	the	DET
cana-3689	127	5	random	random	ADJ
cana-3689	127	6	forest	forest	NOUN
cana-3689	127	7	algorithm	algorithm	NOUN
cana-3689	127	8	works	work	VERB
cana-3689	127	9	:	:	PUNCT
cana-3689	127	10	step	step	NOUN
cana-3689	127	11	1	1	NUM
cana-3689	127	12	.	.	PUNCT
cana-3689	128	1	bootstrapped	bootstrappe	VERB
cana-3689	128	2	sampling	sample	VERB
cana-3689	128	3	step	step	NOUN
cana-3689	128	4	2	2	NUM
cana-3689	128	5	.	.	PUNCT
cana-3689	128	6	random	random	ADJ
cana-3689	128	7	feature	feature	NOUN
cana-3689	128	8	selection	selection	NOUN
cana-3689	128	9	step	step	NOUN
cana-3689	128	10	3	3	NUM
cana-3689	128	11	.	.	PUNCT
cana-3689	129	1	decision	decision	NOUN
cana-3689	129	2	tree	tree	NOUN
cana-3689	129	3	construction	construction	NOUN
cana-3689	129	4	step	step	NOUN
cana-3689	129	5	4	4	NUM
cana-3689	129	6	.	.	PUNCT
cana-3689	130	1	voting	vote	VERB
cana-3689	130	2	or	or	CCONJ
cana-3689	130	3	averaging	average	VERB
cana-3689	130	4	2.5	2.5	NUM
cana-3689	130	5	rep	rep	NOUN
cana-3689	130	6	tree	tree	PROPN
cana-3689	130	7	rep	rep	PROPN
cana-3689	130	8	tree	tree	PROPN
cana-3689	130	9	,	,	PUNCT
cana-3689	130	10	short	short	ADJ
cana-3689	130	11	for	for	ADP
cana-3689	130	12	"	"	PUNCT
cana-3689	130	13	reduced	reduce	VERB
cana-3689	130	14	error	error	NOUN
cana-3689	130	15	pruning	prune	VERB
cana-3689	130	16	tree	tree	NOUN
cana-3689	130	17	,	,	PUNCT
cana-3689	130	18	"	"	PUNCT
cana-3689	130	19	is	be	AUX
cana-3689	130	20	a	a	DET
cana-3689	130	21	decision	decision	NOUN
cana-3689	130	22	tree	tree	NOUN
cana-3689	130	23	algorithm	algorithm	NOUN
cana-3689	130	24	primarily	primarily	ADV
cana-3689	130	25	used	use	VERB
cana-3689	130	26	for	for	ADP
cana-3689	130	27	classification	classification	NOUN
cana-3689	130	28	tasks	task	NOUN
cana-3689	130	29	in	in	ADP
cana-3689	130	30	machine	machine	NOUN
cana-3689	130	31	learning	learning	NOUN
cana-3689	130	32	.	.	PUNCT
cana-3689	131	1	it	it	PRON
cana-3689	131	2	is	be	AUX
cana-3689	131	3	designed	design	VERB
cana-3689	131	4	to	to	PART
cana-3689	131	5	create	create	VERB
cana-3689	131	6	decision	decision	NOUN
cana-3689	131	7	trees	tree	NOUN
cana-3689	131	8	while	while	SCONJ
cana-3689	131	9	incorporating	incorporate	VERB
cana-3689	131	10	a	a	DET
cana-3689	131	11	reduced	reduce	VERB
cana-3689	131	12	-	-	PUNCT
cana-3689	131	13	error	error	NOUN
cana-3689	131	14	pruning	pruning	NOUN
cana-3689	131	15	technique	technique	NOUN
cana-3689	131	16	to	to	PART
cana-3689	131	17	avoid	avoid	VERB
cana-3689	131	18	overfitting	overfitte	VERB
cana-3689	131	19	.	.	PUNCT
cana-3689	132	1	the	the	DET
cana-3689	132	2	algorithm	algorithm	NOUN
cana-3689	132	3	was	be	AUX
cana-3689	132	4	introduced	introduce	VERB
cana-3689	132	5	as	as	ADP
cana-3689	132	6	a	a	DET
cana-3689	132	7	part	part	NOUN
cana-3689	132	8	of	of	ADP
cana-3689	132	9	the	the	DET
cana-3689	132	10	weka	weka	PROPN
cana-3689	132	11	machine	machine	NOUN
cana-3689	132	12	learning	learning	PROPN
cana-3689	132	13	software	software	NOUN
cana-3689	132	14	.	.	PUNCT
cana-3689	133	1	here	here	ADV
cana-3689	133	2	's	be	AUX
cana-3689	133	3	how	how	SCONJ
cana-3689	133	4	the	the	DET
cana-3689	133	5	rep	rep	NOUN
cana-3689	133	6	tree	tree	NOUN
cana-3689	133	7	algorithm	algorithm	PROPN
cana-3689	133	8	works	work	VERB
cana-3689	133	9	:	:	PUNCT
cana-3689	133	10	step	step	NOUN
cana-3689	133	11	1	1	NUM
cana-3689	133	12	.	.	PUNCT
cana-3689	134	1	tree	tree	NOUN
cana-3689	134	2	construction	construction	NOUN
cana-3689	134	3	step	step	NOUN
cana-3689	134	4	2	2	NUM
cana-3689	134	5	.	.	PUNCT
cana-3689	134	6	recursive	recursive	ADJ
cana-3689	134	7	splitting	splitting	NOUN
cana-3689	134	8	step	step	NOUN
cana-3689	134	9	3	3	NUM
cana-3689	134	10	.	.	PUNCT
cana-3689	134	11	reduced	reduce	VERB
cana-3689	134	12	error	error	NOUN
cana-3689	134	13	pruning	pruning	NOUN
cana-3689	134	14	step	step	NOUN
cana-3689	134	15	4	4	NUM
cana-3689	134	16	.	.	PUNCT
cana-3689	134	17	prediction	prediction	NOUN
cana-3689	134	18	3	3	NUM
cana-3689	134	19	.	.	PUNCT
cana-3689	134	20	numerical	numerical	PROPN
cana-3689	134	21	illustrations	illustration	NOUN
cana-3689	134	22	the	the	DET
cana-3689	134	23	corresponding	corresponding	ADJ
cana-3689	134	24	dataset	dataset	NOUN
cana-3689	134	25	was	be	AUX
cana-3689	134	26	collected	collect	VERB
cana-3689	134	27	from	from	ADP
cana-3689	134	28	the	the	DET
cana-3689	134	29	open	open	ADJ
cana-3689	134	30	souse	souse	PROPN
cana-3689	134	31	kaggle	kaggle	PROPN
cana-3689	134	32	data	datum	NOUN
cana-3689	134	33	repository	repository	NOUN
cana-3689	134	34	.	.	PUNCT
cana-3689	135	1	the	the	DET
cana-3689	135	2	cardio	cardio	NOUN
cana-3689	135	3	activities	activity	NOUN
cana-3689	135	4	predictions	prediction	NOUN
cana-3689	135	5	dataset	dataset	NOUN
cana-3689	135	6	includes	include	VERB
cana-3689	135	7	8	8	NUM
cana-3689	135	8	parameters	parameter	NOUN
cana-3689	135	9	which	which	PRON
cana-3689	135	10	have	have	VERB
cana-3689	135	11	different	different	ADJ
cana-3689	135	12	categories	category	NOUN
cana-3689	135	13	of	of	ADP
cana-3689	135	14	data	datum	NOUN
cana-3689	135	15	like	like	ADP
cana-3689	135	16	date	date	NOUN
cana-3689	135	17	,	,	PUNCT
cana-3689	135	18	type	type	NOUN
cana-3689	135	19	,	,	PUNCT
cana-3689	135	20	distance	distance	NOUN
cana-3689	135	21	(	(	PUNCT
cana-3689	135	22	km	km	NOUN
cana-3689	135	23	)	)	PUNCT
cana-3689	135	24	,	,	PUNCT
cana-3689	135	25	duration	duration	NOUN
cana-3689	135	26	,	,	PUNCT
cana-3689	135	27	average	average	ADJ
cana-3689	135	28	pace	pace	NOUN
cana-3689	135	29	,	,	PUNCT
cana-3689	135	30	average	average	ADJ
cana-3689	135	31	speed	speed	NOUN
cana-3689	135	32	(	(	PUNCT
cana-3689	135	33	km	km	NOUN
cana-3689	135	34	/	/	SYM
cana-3689	135	35	h	h	NOUN
cana-3689	135	36	)	)	PUNCT
cana-3689	135	37	,	,	PUNCT
cana-3689	135	38	calories	calorie	NOUN
cana-3689	135	39	burned	burn	VERB
cana-3689	135	40	,	,	PUNCT
cana-3689	135	41	climb	climb	VERB
cana-3689	135	42	(	(	PUNCT
cana-3689	135	43	m	m	NOUN
cana-3689	135	44	)	)	PUNCT
cana-3689	135	45	.	.	PUNCT
cana-3689	136	1	a	a	DET
cana-3689	136	2	detailed	detailed	ADJ
cana-3689	136	3	description	description	NOUN
cana-3689	136	4	of	of	ADP
cana-3689	136	5	the	the	DET
cana-3689	136	6	parameters	parameter	NOUN
cana-3689	136	7	is	be	AUX
cana-3689	136	8	mentioned	mention	VERB
cana-3689	136	9	in	in	ADP
cana-3689	136	10	the	the	DET
cana-3689	136	11	following	follow	VERB
cana-3689	136	12	table	table	NOUN
cana-3689	136	13	1	1	NUM
cana-3689	136	14	.	.	PUNCT
cana-3689	136	15	table	table	NOUN
cana-3689	136	16	1	1	NUM
cana-3689	136	17	.	.	PUNCT
cana-3689	136	18	cardio	cardio	NOUN
cana-3689	136	19	activities	activity	NOUN
cana-3689	136	20	predictions	prediction	NOUN
cana-3689	136	21	sample	sample	NOUN
cana-3689	136	22	dataset	dataset	NOUN
cana-3689	136	23	date	date	NOUN
cana-3689	136	24	type	type	NOUN
cana-3689	136	25	distance	distance	NOUN
cana-3689	136	26	(	(	PUNCT
cana-3689	136	27	km	km	NOUN
cana-3689	136	28	)	)	PUNCT
cana-3689	136	29	duration	duration	NOUN
cana-3689	136	30	average	average	ADJ
cana-3689	136	31	pace	pace	NOUN
cana-3689	136	32	average	average	ADJ
cana-3689	136	33	speed	speed	NOUN
cana-3689	136	34	(	(	PUNCT
cana-3689	136	35	km	km	NOUN
cana-3689	136	36	/	/	SYM
cana-3689	136	37	h	h	NOUN
cana-3689	136	38	)	)	PUNCT
cana-3689	136	39	climb	climb	NOUN
cana-3689	136	40	(	(	PUNCT
cana-3689	136	41	m	m	NOUN
cana-3689	136	42	)	)	PUNCT
cana-3689	136	43	calories	calorie	NOUN
cana-3689	136	44	burned	burn	VERB
cana-3689	136	45	11/11/2018	11/11/2018	NUM
cana-3689	136	46	14:05	14:05	NUM
cana-3689	136	47	running	run	VERB
cana-3689	136	48	10.44	10.44	NUM
cana-3689	136	49	58:40:00	58:40:00	NUM
cana-3689	136	50	5:37	5:37	NUM
cana-3689	136	51	10.68	10.68	NUM
cana-3689	136	52	130	130	NUM
cana-3689	136	53	774	774	NUM
cana-3689	136	54	9/11/2018	9/11/2018	NUM
cana-3689	136	55	15:02	15:02	NUM
cana-3689	136	56	running	run	VERB
cana-3689	136	57	12.84	12.84	NUM
cana-3689	137	1	1:14:12	1:14:12	NUM
cana-3689	137	2	5:47	5:47	NUM
cana-3689	137	3	10.39	10.39	NUM
cana-3689	137	4	168	168	NUM
cana-3689	137	5	954	954	NUM
cana-3689	137	6	4/11/2018	4/11/2018	NUM
cana-3689	137	7	16:05	16:05	NUM
cana-3689	137	8	running	run	VERB
cana-3689	137	9	13.01	13.01	NUM
cana-3689	137	10	1:15:16	1:15:16	NUM
cana-3689	137	11	5:47	5:47	NUM
cana-3689	137	12	10.37	10.37	NUM
cana-3689	137	13	171	171	NUM
cana-3689	137	14	967	967	NUM
cana-3689	137	15	1/11/2018	1/11/2018	NUM
cana-3689	137	16	14:03	14:03	NUM
cana-3689	137	17	running	run	VERB
cana-3689	137	18	12.98	12.98	NUM
cana-3689	138	1	1:14:25	1:14:25	NUM
cana-3689	138	2	5:44	5:44	NUM
cana-3689	138	3	10.47	10.47	NUM
cana-3689	138	4	169	169	NUM
cana-3689	138	5	960	960	NUM
cana-3689	138	6	27	27	NUM
cana-3689	138	7	-	-	SYM
cana-3689	138	8	10	10	NUM
cana-3689	138	9	-	-	SYM
cana-3689	138	10	2018	2018	NUM
cana-3689	138	11	17:01	17:01	NUM
cana-3689	138	12	running	run	VERB
cana-3689	138	13	13.02	13.02	NUM
cana-3689	138	14	1:12:50	1:12:50	NUM
cana-3689	138	15	5:36	5:36	NUM
cana-3689	138	16	10.73	10.73	NUM
cana-3689	138	17	170	170	NUM
cana-3689	138	18	967	967	NUM
cana-3689	138	19	19	19	NUM
cana-3689	138	20	-	-	PUNCT
cana-3689	138	21	10	10	NUM
cana-3689	138	22	-	-	SYM
cana-3689	138	23	2018	2018	NUM
cana-3689	138	24	17:52	17:52	NUM
cana-3689	138	25	running	run	VERB
cana-3689	138	26	10.29	10.29	NUM
cana-3689	138	27	59:18:00	59:18:00	NUM
cana-3689	138	28	5:46	5:46	NUM
cana-3689	138	29	10.41	10.41	NUM
cana-3689	138	30	133	133	NUM
cana-3689	138	31	764	764	NUM
cana-3689	138	32	14	14	NUM
cana-3689	138	33	-	-	SYM
cana-3689	138	34	10	10	NUM
cana-3689	138	35	-	-	PUNCT
cana-3689	138	36	2018	2018	NUM
cana-3689	138	37	17:28	17:28	NUM
cana-3689	138	38	running	run	VERB
cana-3689	138	39	12.93	12.93	NUM
cana-3689	138	40	1:10:16	1:10:16	NUM
cana-3689	138	41	5:26	5:26	NUM
cana-3689	138	42	11.04	11.04	NUM
cana-3689	138	43	159	159	NUM
cana-3689	138	44	953	953	NUM
cana-3689	138	45	12/10/2018	12/10/2018	NUM
cana-3689	138	46	17:41	17:41	NUM
cana-3689	138	47	running	run	VERB
cana-3689	138	48	12.31	12.31	NUM
cana-3689	138	49	1:09:26	1:09:26	NUM
cana-3689	138	50	5:38	5:38	NUM
cana-3689	138	51	10.64	10.64	NUM
cana-3689	138	52	134	134	NUM
cana-3689	138	53	903	903	NUM
cana-3689	138	54	communications	communication	NOUN
cana-3689	138	55	on	on	ADP
cana-3689	138	56	applied	apply	VERB
cana-3689	138	57	nonlinear	nonlinear	ADJ
cana-3689	138	58	analysis	analysis	NOUN
cana-3689	138	59	issn	issn	NOUN
cana-3689	138	60	:	:	PUNCT
cana-3689	138	61	1074	1074	NUM
cana-3689	138	62	-	-	PUNCT
cana-3689	138	63	133x	133x	NUM
cana-3689	138	64	vol	vol	NOUN
cana-3689	138	65	32	32	NUM
cana-3689	138	66	no	no	NOUN
cana-3689	138	67	.	.	PUNCT
cana-3689	139	1	8s	8s	PROPN
cana-3689	139	2	(	(	PUNCT
cana-3689	139	3	2025	2025	NUM
cana-3689	139	4	)	)	PUNCT
cana-3689	139	5	https://internationalpubls.com	https://internationalpubls.com	X
cana-3689	139	6	450	450	NUM
cana-3689	139	7	6/10/2018	6/10/2018	NUM
cana-3689	139	8	16:45	16:45	NUM
cana-3689	139	9	cycling	cycling	NOUN
cana-3689	139	10	19.63	19.63	NUM
cana-3689	139	11	1:26:26	1:26:26	PROPN
cana-3689	139	12	4:24	4:24	NUM
cana-3689	139	13	13.63	13.63	NUM
cana-3689	139	14	210	210	NUM
cana-3689	139	15	577	577	NUM
cana-3689	139	16	table	table	NOUN
cana-3689	139	17	2	2	NUM
cana-3689	139	18	:	:	PUNCT
cana-3689	139	19	ml	ml	X
cana-3689	139	20	approaches	approach	NOUN
cana-3689	139	21	performance	performance	NOUN
cana-3689	139	22	running	run	VERB
cana-3689	139	23	ml	ml	ADP
cana-3689	139	24	approaches	approach	NOUN
cana-3689	139	25	logistic	logistic	ADJ
cana-3689	139	26	smo	smo	PROPN
cana-3689	139	27	j48	j48	PROPN
cana-3689	139	28	random	random	PROPN
cana-3689	139	29	forest	forest	NOUN
cana-3689	139	30	rep	rep	NOUN
cana-3689	139	31	tree	tree	NOUN
cana-3689	139	32	tp	tp	PART
cana-3689	139	33	rate	rate	VERB
cana-3689	139	34	0.9870	0.9870	NUM
cana-3689	139	35	0.9980	0.9980	NUM
cana-3689	139	36	0.9930	0.9930	NUM
cana-3689	139	37	1.0000	1.0000	NUM
cana-3689	139	38	1.0000	1.0000	NUM
cana-3689	139	39	fp	fp	NOUN
cana-3689	139	40	rate	rate	NOUN
cana-3689	139	41	0.6330	0.6330	NUM
cana-3689	139	42	0.5310	0.5310	NUM
cana-3689	139	43	0.0610	0.0610	NUM
cana-3689	139	44	1.0000	1.0000	NUM
cana-3689	139	45	1.0000	1.0000	NUM
cana-3689	139	46	precision	precision	NOUN
cana-3689	139	47	0.9360	0.9360	NUM
cana-3689	139	48	0.9460	0.9460	NUM
cana-3689	139	49	0.9930	0.9930	NUM
cana-3689	139	50	0.9040	0.9040	NUM
cana-3689	139	51	0.9040	0.9040	NUM
cana-3689	139	52	recall	recall	VERB
cana-3689	139	53	0.9870	0.9870	NUM
cana-3689	139	54	0.9980	0.9980	NUM
cana-3689	139	55	0.9930	0.9930	NUM
cana-3689	139	56	1.0000	1.0000	NUM
cana-3689	139	57	1.0000	1.0000	NUM
cana-3689	139	58	f	f	NOUN
cana-3689	139	59	-	-	PUNCT
cana-3689	139	60	measure	measure	NOUN
cana-3689	139	61	0.9610	0.9610	NUM
cana-3689	139	62	0.9710	0.9710	NUM
cana-3689	139	63	0.9930	0.9930	NUM
cana-3689	139	64	0.9490	0.9490	NUM
cana-3689	139	65	0.9490	0.9490	NUM
cana-3689	139	66	mcc	mcc	NOUN
cana-3689	139	67	0.4930	0.4930	NUM
cana-3689	139	68	0.6500	0.6500	NUM
cana-3689	139	69	0.9320	0.9320	NUM
cana-3689	139	70	0.0000	0.0000	NUM
cana-3689	139	71	0.0000	0.0000	NUM
cana-3689	139	72	roc	roc	PROPN
cana-3689	139	73	area	area	NOUN
cana-3689	139	74	0.6640	0.6640	NUM
cana-3689	139	75	0.7340	0.7340	NUM
cana-3689	139	76	0.9500	0.9500	NUM
cana-3689	139	77	0.9750	0.9750	NUM
cana-3689	139	78	0.4900	0.4900	NUM
cana-3689	139	79	prc	prc	PROPN
cana-3689	139	80	area	area	NOUN
cana-3689	139	81	0.9230	0.9230	NUM
cana-3689	139	82	0.9460	0.9460	NUM
cana-3689	139	83	0.9890	0.9890	NUM
cana-3689	139	84	0.9970	0.9970	NUM
cana-3689	139	85	0.9020	0.9020	NUM
cana-3689	139	86	fig	fig	NOUN
cana-3689	139	87	.	.	PUNCT
cana-3689	140	1	1	1	NUM
cana-3689	140	2	:	:	PUNCT
cana-3689	140	3	ml	ml	X
cana-3689	140	4	approaches	approach	VERB
cana-3689	140	5	performance	performance	NOUN
cana-3689	140	6	running	running	NOUN
cana-3689	140	7	table	table	NOUN
cana-3689	140	8	3	3	NUM
cana-3689	140	9	:	:	PUNCT
cana-3689	140	10	ml	ml	X
cana-3689	140	11	approaches	approach	VERB
cana-3689	140	12	performance	performance	NOUN
cana-3689	140	13	cycling	cycling	NOUN
cana-3689	140	14	ml	ml	ADP
cana-3689	140	15	approaches	approach	NOUN
cana-3689	140	16	logistic	logistic	ADJ
cana-3689	140	17	smo	smo	PROPN
cana-3689	140	18	j48	j48	PROPN
cana-3689	140	19	random	random	PROPN
cana-3689	140	20	forest	forest	NOUN
cana-3689	140	21	rep	rep	NOUN
cana-3689	140	22	tree	tree	NOUN
cana-3689	140	23	tp	tp	PART
cana-3689	140	24	rate	rate	VERB
cana-3689	140	25	0.5520	0.5520	NUM
cana-3689	140	26	0.6900	0.6900	NUM
cana-3689	141	1	0.9310	0.9310	NUM
cana-3689	141	2	0.0000	0.0000	NUM
cana-3689	141	3	0.0000	0.0000	NUM
cana-3689	141	4	fp	fp	NOUN
cana-3689	141	5	rate	rate	NOUN
cana-3689	141	6	0.0100	0.0100	NUM
cana-3689	141	7	0.0020	0.0020	NUM
cana-3689	141	8	0.0080	0.0080	NUM
cana-3689	141	9	0.0000	0.0000	NUM
cana-3689	141	10	0.0000	0.0000	NUM
cana-3689	141	11	precision	precision	NOUN
cana-3689	141	12	0.7620	0.7620	NUM
cana-3689	141	13	0.9520	0.9520	NUM
cana-3689	141	14	0.8710	0.8710	NUM
cana-3689	141	15	0.0000	0.0000	NUM
cana-3689	141	16	0.0000	0.0000	NUM
cana-3689	141	17	recall	recall	VERB
cana-3689	141	18	0.5520	0.5520	NUM
cana-3689	141	19	0.6900	0.6900	NUM
cana-3689	141	20	0.9310	0.9310	NUM
cana-3689	142	1	0.0000	0.0000	NUM
cana-3689	142	2	0.0000	0.0000	NUM
cana-3689	142	3	f	f	X
cana-3689	142	4	-	-	PUNCT
cana-3689	142	5	measure	measure	NOUN
cana-3689	142	6	0.6400	0.6400	NUM
cana-3689	142	7	0.8000	0.8000	NUM
cana-3689	142	8	0.9000	0.9000	NUM
cana-3689	142	9	0.0000	0.0000	NUM
cana-3689	142	10	0.0000	0.0000	NUM
cana-3689	142	11	mcc	mcc	NOUN
cana-3689	142	12	0.6310	0.6310	NUM
cana-3689	142	13	0.8010	0.8010	NUM
cana-3689	142	14	0.8940	0.8940	NUM
cana-3689	142	15	0.0000	0.0000	NUM
cana-3689	142	16	0.0000	0.0000	NUM
cana-3689	142	17	roc	roc	PROPN
cana-3689	142	18	area	area	NOUN
cana-3689	142	19	0.8930	0.8930	NUM
cana-3689	142	20	0.9230	0.9230	NUM
cana-3689	142	21	0.9410	0.9410	NUM
cana-3689	142	22	0.9670	0.9670	NUM
cana-3689	142	23	0.4840	0.4840	NUM
cana-3689	142	24	prc	prc	PROPN
cana-3689	142	25	area	area	NOUN
cana-3689	142	26	0.5740	0.5740	NOUN
cana-3689	142	27	0.6910	0.6910	NUM
cana-3689	142	28	0.8800	0.8800	NUM
cana-3689	142	29	0.6400	0.6400	NUM
cana-3689	142	30	0.0560	0.0560	NUM
cana-3689	142	31	communications	communication	NOUN
cana-3689	142	32	on	on	ADP
cana-3689	142	33	applied	apply	VERB
cana-3689	142	34	nonlinear	nonlinear	ADJ
cana-3689	142	35	analysis	analysis	NOUN
cana-3689	142	36	issn	issn	NOUN
cana-3689	142	37	:	:	PUNCT
cana-3689	142	38	1074	1074	NUM
cana-3689	142	39	-	-	PUNCT
cana-3689	142	40	133x	133x	NUM
cana-3689	142	41	vol	vol	NOUN
cana-3689	142	42	32	32	NUM
cana-3689	142	43	no	no	NOUN
cana-3689	142	44	.	.	PUNCT
cana-3689	143	1	8s	8s	PROPN
cana-3689	143	2	(	(	PUNCT
cana-3689	143	3	2025	2025	NUM
cana-3689	143	4	)	)	PUNCT
cana-3689	143	5	https://internationalpubls.com	https://internationalpubls.com	X
cana-3689	143	6	451	451	NUM
cana-3689	143	7	fig	fig	NOUN
cana-3689	143	8	.	.	PUNCT
cana-3689	144	1	2	2	NUM
cana-3689	144	2	:	:	PUNCT
cana-3689	144	3	ml	ml	X
cana-3689	144	4	approaches	approach	VERB
cana-3689	144	5	performance	performance	NOUN
cana-3689	144	6	cycling	cycling	NOUN
cana-3689	144	7	table	table	NOUN
cana-3689	144	8	4	4	NUM
cana-3689	144	9	:	:	PUNCT
cana-3689	144	10	ml	ml	X
cana-3689	144	11	approaches	approach	NOUN
cana-3689	144	12	performance	performance	NOUN
cana-3689	144	13	walking	walk	VERB
cana-3689	144	14	ml	ml	ADP
cana-3689	144	15	approaches	approach	NOUN
cana-3689	144	16	logistic	logistic	ADJ
cana-3689	144	17	smo	smo	PROPN
cana-3689	144	18	j48	j48	PROPN
cana-3689	144	19	random	random	PROPN
cana-3689	144	20	forest	forest	NOUN
cana-3689	144	21	rep	rep	NOUN
cana-3689	144	22	tree	tree	NOUN
cana-3689	144	23	tp	tp	PART
cana-3689	144	24	rate	rate	VERB
cana-3689	144	25	0.1110	0.1110	NUM
cana-3689	144	26	0.9440	0.9440	NUM
cana-3689	144	27	0.0000	0.0000	NUM
cana-3689	144	28	0.0000	0.0000	NUM
cana-3689	144	29	0.1110	0.1110	NUM
cana-3689	144	30	fp	fp	NOUN
cana-3689	144	31	rate	rate	NOUN
cana-3689	144	32	0.0020	0.0020	NUM
cana-3689	144	33	0.0020	0.0020	NUM
cana-3689	144	34	0.0000	0.0000	NUM
cana-3689	144	35	0.0000	0.0000	NUM
cana-3689	144	36	0.0020	0.0020	NUM
cana-3689	144	37	precision	precision	NOUN
cana-3689	144	38	0.6670	0.6670	NUM
cana-3689	144	39	0.9440	0.9440	NUM
cana-3689	144	40	0.0000	0.0000	NUM
cana-3689	144	41	0.0000	0.0000	NUM
cana-3689	144	42	0.6670	0.6670	NUM
cana-3689	144	43	recall	recall	VERB
cana-3689	144	44	0.1110	0.1110	NUM
cana-3689	144	45	0.9440	0.9440	NUM
cana-3689	144	46	0.0000	0.0000	NUM
cana-3689	145	1	0.0000	0.0000	NUM
cana-3689	145	2	0.1110	0.1110	NUM
cana-3689	145	3	f	f	X
cana-3689	145	4	-	-	PUNCT
cana-3689	145	5	measure	measure	NOUN
cana-3689	145	6	0.1900	0.1900	NUM
cana-3689	145	7	0.9440	0.9440	NUM
cana-3689	145	8	0.0000	0.0000	NUM
cana-3689	145	9	0.0000	0.0000	NUM
cana-3689	145	10	0.1900	0.1900	NUM
cana-3689	145	11	mcc	mcc	NOUN
cana-3689	145	12	0.2630	0.2630	PROPN
cana-3689	145	13	0.9420	0.9420	NUM
cana-3689	145	14	0.0000	0.0000	NUM
cana-3689	145	15	0.0000	0.0000	NUM
cana-3689	145	16	0.2630	0.2630	NUM
cana-3689	145	17	roc	roc	PROPN
cana-3689	145	18	area	area	NOUN
cana-3689	145	19	0.3120	0.3120	NUM
cana-3689	145	20	0.9700	0.9700	NUM
cana-3689	146	1	0.9960	0.9960	NUM
cana-3689	146	2	0.4520	0.4520	NUM
cana-3689	146	3	0.3120	0.3120	NUM
cana-3689	146	4	prc	prc	PROPN
cana-3689	146	5	area	area	NOUN
cana-3689	146	6	0.1340	0.1340	NUM
cana-3689	146	7	0.8520	0.8520	NUM
cana-3689	146	8	0.8580	0.8580	NUM
cana-3689	146	9	0.0330	0.0330	NUM
cana-3689	146	10	0.1340	0.1340	NUM
cana-3689	146	11	fig	fig	NOUN
cana-3689	146	12	.	.	PUNCT
cana-3689	147	1	3	3	NUM
cana-3689	147	2	:	:	PUNCT
cana-3689	147	3	ml	ml	X
cana-3689	147	4	approaches	approach	VERB
cana-3689	147	5	performance	performance	NOUN
cana-3689	147	6	walking	walking	NOUN
cana-3689	147	7	table	table	NOUN
cana-3689	147	8	5	5	NUM
cana-3689	147	9	:	:	PUNCT
cana-3689	147	10	ml	ml	ADP
cana-3689	147	11	approaches	approach	NOUN
cana-3689	147	12	performance	performance	NOUN
cana-3689	147	13	weighted	weight	VERB
cana-3689	147	14	avg	avg	PROPN
cana-3689	147	15	ml	ml	PROPN
cana-3689	147	16	approaches	approach	NOUN
cana-3689	147	17	logistic	logistic	ADJ
cana-3689	147	18	smo	smo	PROPN
cana-3689	147	19	j48	j48	PROPN
cana-3689	147	20	random	random	PROPN
cana-3689	147	21	forest	forest	NOUN
cana-3689	147	22	rep	rep	NOUN
cana-3689	147	23	tree	tree	NOUN
cana-3689	147	24	tp	tp	PART
cana-3689	147	25	rate	rate	VERB
cana-3689	147	26	0.9270	0.9270	NUM
cana-3689	147	27	0.9840	0.9840	NUM
cana-3689	147	28	0.9040	0.9040	NUM
cana-3689	147	29	0.9040	0.9040	NUM
cana-3689	147	30	0.9270	0.9270	NUM
cana-3689	147	31	fp	fp	NOUN
cana-3689	147	32	rate	rate	NOUN
cana-3689	147	33	0.5720	0.5720	NUM
cana-3689	147	34	0.0560	0.0560	NUM
cana-3689	147	35	0.9040	0.9040	NUM
cana-3689	147	36	0.9040	0.9040	NUM
cana-3689	147	37	0.5720	0.5720	NUM
cana-3689	147	38	precision	precision	NOUN
cana-3689	147	39	0.9130	0.9130	NUM
cana-3689	147	40	0.9810	0.9810	NUM
cana-3689	147	41	0.8160	0.8160	NUM
cana-3689	147	42	0.8160	0.8160	NUM
cana-3689	147	43	0.9130	0.9130	NUM
cana-3689	147	44	recall	recall	NOUN
cana-3689	147	45	0.9270	0.9270	NUM
cana-3689	148	1	0.9840	0.9840	NUM
cana-3689	148	2	0.9040	0.9040	NUM
cana-3689	148	3	0.9040	0.9040	NUM
cana-3689	148	4	0.9270	0.9270	NUM
cana-3689	148	5	f	f	X
cana-3689	148	6	-	-	PUNCT
cana-3689	148	7	measure	measure	NOUN
cana-3689	148	8	0.9110	0.9110	NUM
cana-3689	148	9	0.9820	0.9820	NUM
cana-3689	148	10	0.8580	0.8580	NUM
cana-3689	148	11	0.8580	0.8580	NUM
cana-3689	148	12	0.9110	0.9110	NUM
cana-3689	148	13	mcc	mcc	NOUN
cana-3689	148	14	0.4910	0.4910	NUM
cana-3689	148	15	0.9270	0.9270	NUM
cana-3689	148	16	0.0000	0.0000	NUM
cana-3689	148	17	0.0000	0.0000	NUM
cana-3689	148	18	0.4910	0.4910	NUM
cana-3689	148	19	roc	roc	PROPN
cana-3689	148	20	area	area	NOUN
cana-3689	148	21	0.6660	0.6660	NUM
cana-3689	148	22	0.9500	0.9500	NUM
cana-3689	148	23	0.9750	0.9750	NUM
cana-3689	148	24	0.4870	0.4870	NUM
cana-3689	148	25	0.6660	0.6660	NUM
cana-3689	148	26	prc	prc	PROPN
cana-3689	148	27	area	area	NOUN
cana-3689	148	28	0.8720	0.8720	NUM
cana-3689	148	29	0.9750	0.9750	NUM
cana-3689	148	30	0.9690	0.9690	NUM
cana-3689	148	31	0.8190	0.8190	NUM
cana-3689	148	32	0.8720	0.8720	NUM
cana-3689	148	33	communications	communication	NOUN
cana-3689	148	34	on	on	ADP
cana-3689	148	35	applied	apply	VERB
cana-3689	148	36	nonlinear	nonlinear	ADJ
cana-3689	148	37	analysis	analysis	NOUN
cana-3689	148	38	issn	issn	NOUN
cana-3689	148	39	:	:	PUNCT
cana-3689	148	40	1074	1074	NUM
cana-3689	148	41	-	-	PUNCT
cana-3689	148	42	133x	133x	NUM
cana-3689	148	43	vol	vol	NOUN
cana-3689	148	44	32	32	NUM
cana-3689	148	45	no	no	NOUN
cana-3689	148	46	.	.	PUNCT
cana-3689	149	1	8s	8s	PROPN
cana-3689	149	2	(	(	PUNCT
cana-3689	149	3	2025	2025	NUM
cana-3689	149	4	)	)	PUNCT
cana-3689	149	5	https://internationalpubls.com	https://internationalpubls.com	X
cana-3689	149	6	452	452	NUM
cana-3689	149	7	fig	fig	NOUN
cana-3689	149	8	.	.	PUNCT
cana-3689	150	1	4	4	NUM
cana-3689	150	2	:	:	PUNCT
cana-3689	150	3	ml	ml	X
cana-3689	150	4	approaches	approach	NOUN
cana-3689	150	5	performance	performance	NOUN
cana-3689	150	6	weighted	weight	VERB
cana-3689	150	7	avg	avg	NOUN
cana-3689	150	8	table	table	NOUN
cana-3689	150	9	6	6	NUM
cana-3689	150	10	:	:	PUNCT
cana-3689	150	11	ml	ml	X
cana-3689	150	12	approaches	approach	NOUN
cana-3689	150	13	performance	performance	NOUN
cana-3689	150	14	other	other	ADJ
cana-3689	150	15	ml	ml	ADP
cana-3689	150	16	approaches	approach	NOUN
cana-3689	150	17	logistic	logistic	ADJ
cana-3689	150	18	smo	smo	PROPN
cana-3689	150	19	j48	j48	PROPN
cana-3689	150	20	random	random	PROPN
cana-3689	150	21	forest	forest	NOUN
cana-3689	150	22	rep	rep	NOUN
cana-3689	150	23	tree	tree	NOUN
cana-3689	150	24	tp	tp	PART
cana-3689	150	25	rate	rate	VERB
cana-3689	150	26	0.0000	0.0000	NUM
cana-3689	150	27	0.0000	0.0000	NUM
cana-3689	151	1	0.0000	0.0000	NUM
cana-3689	151	2	0.0000	0.0000	NUM
cana-3689	151	3	0.0000	0.0000	NUM
cana-3689	151	4	fp	fp	NOUN
cana-3689	151	5	rate	rate	NOUN
cana-3689	151	6	0.0000	0.0000	NUM
cana-3689	151	7	0.0000	0.0000	NUM
cana-3689	151	8	0.0000	0.0000	NUM
cana-3689	151	9	0.0000	0.0000	NUM
cana-3689	151	10	0.0000	0.0000	NUM
cana-3689	151	11	precision	precision	NOUN
cana-3689	151	12	0.0000	0.0000	NUM
cana-3689	151	13	0.0000	0.0000	NUM
cana-3689	151	14	0.0000	0.0000	NUM
cana-3689	151	15	0.0000	0.0000	NUM
cana-3689	151	16	0.0000	0.0000	NUM
cana-3689	151	17	recall	recall	VERB
cana-3689	151	18	0.0000	0.0000	NUM
cana-3689	151	19	0.0000	0.0000	NUM
cana-3689	152	1	0.0000	0.0000	NUM
cana-3689	152	2	0.0000	0.0000	NUM
cana-3689	152	3	0.0000	0.0000	NUM
cana-3689	152	4	f	f	X
cana-3689	152	5	-	-	PUNCT
cana-3689	152	6	measure	measure	NOUN
cana-3689	152	7	0.0000	0.0000	NUM
cana-3689	152	8	0.0000	0.0000	NUM
cana-3689	152	9	0.0000	0.0000	NUM
cana-3689	152	10	0.0000	0.0000	NUM
cana-3689	152	11	0.0000	0.0000	NUM
cana-3689	152	12	mcc	mcc	NOUN
cana-3689	152	13	0.0000	0.0000	NUM
cana-3689	152	14	0.0000	0.0000	NUM
cana-3689	152	15	0.0000	0.0000	NUM
cana-3689	152	16	0.0000	0.0000	NUM
cana-3689	152	17	0.0000	0.0000	NUM
cana-3689	152	18	roc	roc	PROPN
cana-3689	152	19	area	area	NOUN
cana-3689	152	20	0.8980	0.8980	NUM
cana-3689	152	21	0.9940	0.9940	NUM
cana-3689	152	22	0.9710	0.9710	NUM
cana-3689	152	23	0.0990	0.0990	NUM
cana-3689	152	24	0.8980	0.8980	NUM
cana-3689	152	25	prc	prc	PROPN
cana-3689	152	26	area	area	NOUN
cana-3689	152	27	0.0280	0.0280	NUM
cana-3689	152	28	0.2500	0.2500	NUM
cana-3689	152	29	0.2810	0.2810	NUM
cana-3689	152	30	0.0040	0.0040	NUM
cana-3689	152	31	0.0280	0.0280	NUM
cana-3689	152	32	fig	fig	NOUN
cana-3689	152	33	.	.	PUNCT
cana-3689	153	1	5	5	NUM
cana-3689	153	2	:	:	PUNCT
cana-3689	153	3	ml	ml	X
cana-3689	153	4	approaches	approach	NOUN
cana-3689	153	5	performance	performance	NOUN
cana-3689	153	6	other	other	ADJ
cana-3689	153	7	3	3	NUM
cana-3689	153	8	.	.	NOUN
cana-3689	153	9	result	result	NOUN
cana-3689	153	10	and	and	CCONJ
cana-3689	153	11	discussion	discussion	VERB
cana-3689	153	12	the	the	DET
cana-3689	153	13	comparative	comparative	ADJ
cana-3689	153	14	evaluation	evaluation	NOUN
cana-3689	153	15	of	of	ADP
cana-3689	153	16	machine	machine	NOUN
cana-3689	153	17	learning	learn	VERB
cana-3689	153	18	algorithms	algorithm	NOUN
cana-3689	153	19	applied	apply	VERB
cana-3689	153	20	to	to	PART
cana-3689	153	21	predict	predict	VERB
cana-3689	153	22	cardio	cardio	NOUN
cana-3689	153	23	activities	activity	NOUN
cana-3689	153	24	,	,	PUNCT
cana-3689	153	25	utilizing	utilize	VERB
cana-3689	153	26	the	the	DET
cana-3689	153	27	provided	provide	VERB
cana-3689	153	28	dataset	dataset	NOUN
cana-3689	153	29	and	and	CCONJ
cana-3689	153	30	performance	performance	NOUN
cana-3689	153	31	criteria	criterion	NOUN
cana-3689	153	32	,	,	PUNCT
cana-3689	153	33	unveiled	unveil	VERB
cana-3689	153	34	noteworthy	noteworthy	ADJ
cana-3689	153	35	findings	finding	NOUN
cana-3689	153	36	.	.	PUNCT
cana-3689	154	1	these	these	DET
cana-3689	154	2	insights	insight	NOUN
cana-3689	154	3	are	be	AUX
cana-3689	154	4	detailed	detail	VERB
cana-3689	154	5	below	below	ADV
cana-3689	154	6	,	,	PUNCT
cana-3689	154	7	categorized	categorize	VERB
cana-3689	154	8	into	into	ADP
cana-3689	154	9	running	running	NOUN
cana-3689	154	10	,	,	PUNCT
cana-3689	154	11	cycling	cycling	NOUN
cana-3689	154	12	,	,	PUNCT
cana-3689	154	13	and	and	CCONJ
cana-3689	154	14	walking	walking	NOUN
cana-3689	154	15	activities	activity	NOUN
cana-3689	154	16	,	,	PUNCT
cana-3689	154	17	with	with	ADP
cana-3689	154	18	a	a	DET
cana-3689	154	19	comprehensive	comprehensive	ADJ
cana-3689	154	20	weighted	weight	VERB
cana-3689	154	21	average	average	ADJ
cana-3689	154	22	assessment	assessment	NOUN
cana-3689	154	23	.	.	PUNCT
cana-3689	155	1	as	as	SCONJ
cana-3689	155	2	presented	present	VERB
cana-3689	155	3	in	in	ADP
cana-3689	155	4	table	table	NOUN
cana-3689	155	5	2	2	NUM
cana-3689	155	6	and	and	CCONJ
cana-3689	155	7	figure	figure	NOUN
cana-3689	155	8	1	1	NUM
cana-3689	155	9	,	,	PUNCT
cana-3689	155	10	the	the	DET
cana-3689	155	11	performance	performance	NOUN
cana-3689	155	12	evaluation	evaluation	NOUN
cana-3689	155	13	of	of	ADP
cana-3689	155	14	various	various	ADJ
cana-3689	155	15	models	model	NOUN
cana-3689	155	16	for	for	ADP
cana-3689	155	17	predicting	predict	VERB
cana-3689	155	18	running	running	NOUN
cana-3689	155	19	activity	activity	NOUN
cana-3689	155	20	revealed	reveal	VERB
cana-3689	155	21	that	that	SCONJ
cana-3689	155	22	the	the	DET
cana-3689	155	23	random	random	ADJ
cana-3689	155	24	forest	forest	NOUN
cana-3689	155	25	and	and	CCONJ
cana-3689	155	26	rep	rep	PROPN
cana-3689	155	27	tree	tree	NOUN
cana-3689	155	28	algorithms	algorithm	NOUN
cana-3689	155	29	achieved	achieve	VERB
cana-3689	155	30	a	a	DET
cana-3689	155	31	perfect	perfect	ADJ
cana-3689	155	32	tp	tp	NOUN
cana-3689	155	33	rate	rate	NOUN
cana-3689	155	34	(	(	PUNCT
cana-3689	155	35	1.0000	1.0000	NUM
cana-3689	155	36	)	)	PUNCT
cana-3689	155	37	and	and	CCONJ
cana-3689	155	38	recall	recall	NOUN
cana-3689	155	39	(	(	PUNCT
cana-3689	155	40	1.0000	1.0000	NUM
cana-3689	155	41	)	)	PUNCT
cana-3689	155	42	.	.	PUNCT
cana-3689	156	1	despite	despite	SCONJ
cana-3689	156	2	this	this	PRON
cana-3689	156	3	,	,	PUNCT
cana-3689	156	4	their	their	PRON
cana-3689	156	5	metrics	metric	NOUN
cana-3689	156	6	such	such	ADJ
cana-3689	156	7	as	as	ADP
cana-3689	156	8	precision	precision	NOUN
cana-3689	156	9	and	and	CCONJ
cana-3689	156	10	f	f	NOUN
cana-3689	156	11	-	-	PUNCT
cana-3689	156	12	measure	measure	NOUN
cana-3689	156	13	(	(	PUNCT
cana-3689	156	14	both	both	PRON
cana-3689	156	15	at	at	ADP
cana-3689	156	16	0.9040	0.9040	NUM
cana-3689	156	17	)	)	PUNCT
cana-3689	156	18	,	,	PUNCT
cana-3689	156	19	along	along	ADP
cana-3689	156	20	with	with	ADP
cana-3689	156	21	mcc	mcc	PROPN
cana-3689	156	22	(	(	PUNCT
cana-3689	156	23	0.0000	0.0000	NUM
cana-3689	156	24	)	)	PUNCT
cana-3689	156	25	,	,	PUNCT
cana-3689	156	26	suggest	suggest	VERB
cana-3689	156	27	potential	potential	ADJ
cana-3689	156	28	issues	issue	NOUN
cana-3689	156	29	related	relate	VERB
cana-3689	156	30	to	to	ADP
cana-3689	156	31	specificity	specificity	NOUN
cana-3689	156	32	or	or	CCONJ
cana-3689	156	33	overfitting	overfitting	NOUN
cana-3689	156	34	.	.	PUNCT
cana-3689	157	1	conversely	conversely	ADV
cana-3689	157	2	,	,	PUNCT
cana-3689	157	3	j48	j48	PROPN
cana-3689	157	4	exhibited	exhibit	VERB
cana-3689	157	5	the	the	DET
cana-3689	157	6	highest	high	ADJ
cana-3689	157	7	overall	overall	ADJ
cana-3689	157	8	reliability	reliability	NOUN
cana-3689	157	9	,	,	PUNCT
cana-3689	157	10	marked	mark	VERB
cana-3689	157	11	by	by	ADP
cana-3689	157	12	an	an	DET
cana-3689	157	13	f	f	NOUN
cana-3689	157	14	-	-	PUNCT
cana-3689	157	15	measure	measure	NOUN
cana-3689	157	16	of	of	ADP
cana-3689	157	17	0.9930	0.9930	NUM
cana-3689	157	18	,	,	PUNCT
cana-3689	157	19	mcc	mcc	NOUN
cana-3689	157	20	of	of	ADP
cana-3689	157	21	communications	communication	NOUN
cana-3689	157	22	on	on	ADP
cana-3689	157	23	applied	apply	VERB
cana-3689	157	24	nonlinear	nonlinear	ADJ
cana-3689	157	25	analysis	analysis	NOUN
cana-3689	157	26	issn	issn	NOUN
cana-3689	157	27	:	:	PUNCT
cana-3689	157	28	1074	1074	NUM
cana-3689	157	29	-	-	PUNCT
cana-3689	157	30	133x	133x	NUM
cana-3689	157	31	vol	vol	NOUN
cana-3689	157	32	32	32	NUM
cana-3689	157	33	no	no	NOUN
cana-3689	157	34	.	.	PUNCT
cana-3689	158	1	8s	8s	PROPN
cana-3689	158	2	(	(	PUNCT
cana-3689	158	3	2025	2025	NUM
cana-3689	158	4	)	)	PUNCT
cana-3689	158	5	https://internationalpubls.com	https://internationalpubls.com	X
cana-3689	158	6	453	453	NUM
cana-3689	158	7	0.9320	0.9320	NUM
cana-3689	158	8	,	,	PUNCT
cana-3689	158	9	and	and	CCONJ
cana-3689	158	10	a	a	DET
cana-3689	158	11	robust	robust	ADJ
cana-3689	158	12	roc	roc	PROPN
cana-3689	158	13	area	area	NOUN
cana-3689	158	14	of	of	ADP
cana-3689	158	15	0.9500	0.9500	NUM
cana-3689	158	16	.	.	PUNCT
cana-3689	159	1	the	the	DET
cana-3689	159	2	smo	smo	PROPN
cana-3689	159	3	algorithm	algorithm	NOUN
cana-3689	159	4	also	also	ADV
cana-3689	159	5	performed	perform	VERB
cana-3689	159	6	commendably	commendably	ADV
cana-3689	159	7	,	,	PUNCT
cana-3689	159	8	with	with	ADP
cana-3689	159	9	an	an	DET
cana-3689	159	10	f	f	NOUN
cana-3689	159	11	-	-	PUNCT
cana-3689	159	12	measure	measure	NOUN
cana-3689	159	13	of	of	ADP
cana-3689	159	14	0.9710	0.9710	NUM
cana-3689	159	15	and	and	CCONJ
cana-3689	159	16	a	a	DET
cana-3689	159	17	high	high	ADJ
cana-3689	159	18	prc	prc	PROPN
cana-3689	159	19	area	area	NOUN
cana-3689	159	20	(	(	PUNCT
cana-3689	159	21	0.9460	0.9460	NUM
cana-3689	159	22	)	)	PUNCT
cana-3689	159	23	,	,	PUNCT
cana-3689	159	24	underscoring	underscore	VERB
cana-3689	159	25	its	its	PRON
cana-3689	159	26	robustness	robustness	NOUN
cana-3689	159	27	for	for	ADP
cana-3689	159	28	predicting	predict	VERB
cana-3689	159	29	running	running	NOUN
cana-3689	159	30	activities	activity	NOUN
cana-3689	159	31	.	.	PUNCT
cana-3689	160	1	logistic	logistic	ADJ
cana-3689	160	2	regression	regression	NOUN
cana-3689	160	3	,	,	PUNCT
cana-3689	160	4	on	on	ADP
cana-3689	160	5	the	the	DET
cana-3689	160	6	other	other	ADJ
cana-3689	160	7	hand	hand	NOUN
cana-3689	160	8	,	,	PUNCT
cana-3689	160	9	demonstrated	demonstrate	VERB
cana-3689	160	10	moderate	moderate	ADJ
cana-3689	160	11	performance	performance	NOUN
cana-3689	160	12	,	,	PUNCT
cana-3689	160	13	indicative	indicative	ADJ
cana-3689	160	14	of	of	ADP
cana-3689	160	15	its	its	PRON
cana-3689	160	16	constraints	constraint	NOUN
cana-3689	160	17	when	when	SCONJ
cana-3689	160	18	dealing	deal	VERB
cana-3689	160	19	with	with	ADP
cana-3689	160	20	non	non	ADJ
cana-3689	160	21	-	-	ADJ
cana-3689	160	22	linear	linear	ADJ
cana-3689	160	23	and	and	CCONJ
cana-3689	160	24	high	high	ADJ
cana-3689	160	25	-	-	PUNCT
cana-3689	160	26	dimensional	dimensional	ADJ
cana-3689	160	27	datasets	dataset	NOUN
cana-3689	160	28	.	.	PUNCT
cana-3689	161	1	the	the	DET
cana-3689	161	2	results	result	NOUN
cana-3689	161	3	for	for	ADP
cana-3689	161	4	cycling	cycling	NOUN
cana-3689	161	5	activity	activity	NOUN
cana-3689	161	6	,	,	PUNCT
cana-3689	161	7	encapsulated	encapsulate	VERB
cana-3689	161	8	in	in	ADP
cana-3689	161	9	table	table	NOUN
cana-3689	161	10	3	3	NUM
cana-3689	161	11	and	and	CCONJ
cana-3689	161	12	figure	figure	NOUN
cana-3689	161	13	2	2	NUM
cana-3689	161	14	,	,	PUNCT
cana-3689	161	15	demonstrate	demonstrate	VERB
cana-3689	161	16	that	that	SCONJ
cana-3689	161	17	the	the	DET
cana-3689	161	18	j48	j48	PROPN
cana-3689	161	19	model	model	NOUN
cana-3689	161	20	outshone	outshone	VERB
cana-3689	161	21	other	other	ADJ
cana-3689	161	22	techniques	technique	NOUN
cana-3689	161	23	,	,	PUNCT
cana-3689	161	24	achieving	achieve	VERB
cana-3689	161	25	a	a	DET
cana-3689	161	26	tp	tp	NOUN
cana-3689	161	27	rate	rate	NOUN
cana-3689	161	28	of	of	ADP
cana-3689	161	29	0.9310	0.9310	NUM
cana-3689	161	30	,	,	PUNCT
cana-3689	161	31	f	f	X
cana-3689	161	32	-	-	PUNCT
cana-3689	161	33	measure	measure	NOUN
cana-3689	161	34	of	of	ADP
cana-3689	161	35	0.9000	0.9000	NUM
cana-3689	161	36	,	,	PUNCT
cana-3689	161	37	and	and	CCONJ
cana-3689	161	38	mcc	mcc	NOUN
cana-3689	161	39	of	of	ADP
cana-3689	161	40	0.8940	0.8940	NUM
cana-3689	161	41	,	,	PUNCT
cana-3689	161	42	which	which	PRON
cana-3689	161	43	reflect	reflect	VERB
cana-3689	161	44	its	its	PRON
cana-3689	161	45	high	high	ADJ
cana-3689	161	46	predictive	predictive	ADJ
cana-3689	161	47	accuracy	accuracy	NOUN
cana-3689	161	48	and	and	CCONJ
cana-3689	161	49	reliability	reliability	NOUN
cana-3689	161	50	.	.	PUNCT
cana-3689	162	1	smo	smo	PROPN
cana-3689	162	2	also	also	ADV
cana-3689	162	3	performed	perform	VERB
cana-3689	162	4	well	well	ADV
cana-3689	162	5	,	,	PUNCT
cana-3689	162	6	with	with	ADP
cana-3689	162	7	an	an	DET
cana-3689	162	8	mcc	mcc	NOUN
cana-3689	162	9	of	of	ADP
cana-3689	162	10	0.8010	0.8010	NUM
cana-3689	162	11	and	and	CCONJ
cana-3689	162	12	roc	roc	PROPN
cana-3689	162	13	area	area	NOUN
cana-3689	162	14	of	of	ADP
cana-3689	162	15	0.9230	0.9230	NUM
cana-3689	162	16	,	,	PUNCT
cana-3689	162	17	signifying	signify	VERB
cana-3689	162	18	its	its	PRON
cana-3689	162	19	efficacy	efficacy	NOUN
cana-3689	162	20	for	for	ADP
cana-3689	162	21	cycling	cycling	NOUN
cana-3689	162	22	activity	activity	NOUN
cana-3689	162	23	predictions	prediction	NOUN
cana-3689	162	24	.	.	PUNCT
cana-3689	163	1	logistic	logistic	ADJ
cana-3689	163	2	regression	regression	NOUN
cana-3689	163	3	produced	produce	VERB
cana-3689	163	4	moderate	moderate	ADJ
cana-3689	163	5	outcomes	outcome	NOUN
cana-3689	163	6	,	,	PUNCT
cana-3689	163	7	while	while	SCONJ
cana-3689	163	8	random	random	ADJ
cana-3689	163	9	forest	forest	NOUN
cana-3689	163	10	and	and	CCONJ
cana-3689	163	11	rep	rep	PROPN
cana-3689	163	12	tree	tree	NOUN
cana-3689	163	13	were	be	AUX
cana-3689	163	14	ineffective	ineffective	ADJ
cana-3689	163	15	,	,	PUNCT
cana-3689	163	16	as	as	SCONJ
cana-3689	163	17	evidenced	evidence	VERB
cana-3689	163	18	by	by	ADP
cana-3689	163	19	their	their	PRON
cana-3689	163	20	tp	tp	NOUN
cana-3689	163	21	rates	rate	NOUN
cana-3689	163	22	of	of	ADP
cana-3689	163	23	0.0000	0.0000	NUM
cana-3689	163	24	.	.	PUNCT
cana-3689	164	1	for	for	ADP
cana-3689	164	2	walking	walk	VERB
cana-3689	164	3	activity	activity	NOUN
cana-3689	164	4	predictions	prediction	NOUN
cana-3689	164	5	,	,	PUNCT
cana-3689	164	6	table	table	NOUN
cana-3689	164	7	4	4	NUM
cana-3689	164	8	and	and	CCONJ
cana-3689	164	9	figure	figure	VERB
cana-3689	164	10	3	3	NUM
cana-3689	164	11	reveal	reveal	VERB
cana-3689	164	12	that	that	SCONJ
cana-3689	164	13	smo	smo	PROPN
cana-3689	164	14	demonstrated	demonstrate	VERB
cana-3689	164	15	exceptional	exceptional	ADJ
cana-3689	164	16	performance	performance	NOUN
cana-3689	164	17	,	,	PUNCT
cana-3689	164	18	with	with	ADP
cana-3689	164	19	all	all	DET
cana-3689	164	20	key	key	ADJ
cana-3689	164	21	metrics	metric	NOUN
cana-3689	164	22	—	—	PUNCT
cana-3689	164	23	tp	tp	NOUN
cana-3689	164	24	rate	rate	NOUN
cana-3689	164	25	,	,	PUNCT
cana-3689	164	26	precision	precision	NOUN
cana-3689	164	27	,	,	PUNCT
cana-3689	164	28	recall	recall	NOUN
cana-3689	164	29	,	,	PUNCT
cana-3689	164	30	and	and	CCONJ
cana-3689	164	31	f	f	X
cana-3689	164	32	-	-	PUNCT
cana-3689	164	33	measure	measure	NOUN
cana-3689	164	34	—	—	PUNCT
cana-3689	164	35	scoring	score	VERB
cana-3689	164	36	0.9440	0.9440	NUM
cana-3689	164	37	.	.	PUNCT
cana-3689	165	1	additionally	additionally	ADV
cana-3689	165	2	,	,	PUNCT
cana-3689	165	3	the	the	DET
cana-3689	165	4	model	model	NOUN
cana-3689	165	5	achieved	achieve	VERB
cana-3689	165	6	a	a	DET
cana-3689	165	7	high	high	ADJ
cana-3689	165	8	roc	roc	PROPN
cana-3689	165	9	area	area	NOUN
cana-3689	165	10	of	of	ADP
cana-3689	165	11	0.9700	0.9700	NUM
cana-3689	165	12	,	,	PUNCT
cana-3689	165	13	highlighting	highlight	VERB
cana-3689	165	14	its	its	PRON
cana-3689	165	15	suitability	suitability	NOUN
cana-3689	165	16	for	for	ADP
cana-3689	165	17	predicting	predict	VERB
cana-3689	165	18	walking	walking	NOUN
cana-3689	165	19	activities	activity	NOUN
cana-3689	165	20	.	.	PUNCT
cana-3689	166	1	conversely	conversely	ADV
cana-3689	166	2	,	,	PUNCT
cana-3689	166	3	logistic	logistic	ADJ
cana-3689	166	4	regression	regression	NOUN
cana-3689	166	5	and	and	CCONJ
cana-3689	166	6	rep	rep	PROPN
cana-3689	166	7	tree	tree	NOUN
cana-3689	166	8	exhibited	exhibit	VERB
cana-3689	166	9	limited	limited	ADJ
cana-3689	166	10	efficacy	efficacy	NOUN
cana-3689	166	11	,	,	PUNCT
cana-3689	166	12	with	with	ADP
cana-3689	166	13	mcc	mcc	PROPN
cana-3689	166	14	scores	score	NOUN
cana-3689	166	15	of	of	ADP
cana-3689	166	16	0.2630	0.2630	NUM
cana-3689	166	17	and	and	CCONJ
cana-3689	166	18	low	low	ADJ
cana-3689	166	19	f	f	NOUN
cana-3689	166	20	-	-	PUNCT
cana-3689	166	21	measures	measure	NOUN
cana-3689	166	22	of	of	ADP
cana-3689	166	23	0.1900	0.1900	NUM
cana-3689	166	24	.	.	PUNCT
cana-3689	167	1	neither	neither	CCONJ
cana-3689	167	2	j48	j48	ADJ
cana-3689	167	3	nor	nor	CCONJ
cana-3689	167	4	random	random	ADJ
cana-3689	167	5	forest	forest	NOUN
cana-3689	167	6	provided	provide	VERB
cana-3689	167	7	meaningful	meaningful	ADJ
cana-3689	167	8	predictions	prediction	NOUN
cana-3689	167	9	for	for	ADP
cana-3689	167	10	walking	walk	VERB
cana-3689	167	11	activities	activity	NOUN
cana-3689	167	12	.	.	PUNCT
cana-3689	168	1	table	table	NOUN
cana-3689	168	2	5	5	NUM
cana-3689	168	3	and	and	CCONJ
cana-3689	168	4	figure	figure	VERB
cana-3689	168	5	4	4	NUM
cana-3689	168	6	consolidate	consolidate	VERB
cana-3689	168	7	the	the	DET
cana-3689	168	8	weighted	weighted	ADJ
cana-3689	168	9	average	average	ADJ
cana-3689	168	10	performance	performance	NOUN
cana-3689	168	11	metrics	metric	NOUN
cana-3689	168	12	,	,	PUNCT
cana-3689	168	13	showcasing	showcase	VERB
cana-3689	168	14	smo	smo	PROPN
cana-3689	168	15	as	as	ADP
cana-3689	168	16	the	the	DET
cana-3689	168	17	most	most	ADV
cana-3689	168	18	consistent	consistent	ADJ
cana-3689	168	19	model	model	NOUN
cana-3689	168	20	with	with	ADP
cana-3689	168	21	an	an	DET
cana-3689	168	22	f	f	NOUN
cana-3689	168	23	-	-	PUNCT
cana-3689	168	24	measure	measure	NOUN
cana-3689	168	25	of	of	ADP
cana-3689	168	26	0.9820	0.9820	NUM
cana-3689	168	27	and	and	CCONJ
cana-3689	168	28	mcc	mcc	NOUN
cana-3689	168	29	of	of	ADP
cana-3689	168	30	0.9270	0.9270	NUM
cana-3689	168	31	.	.	PUNCT
cana-3689	169	1	j48	j48	PROPN
cana-3689	169	2	closely	closely	ADV
cana-3689	169	3	followed	follow	VERB
cana-3689	169	4	,	,	PUNCT
cana-3689	169	5	demonstrating	demonstrate	VERB
cana-3689	169	6	robust	robust	ADJ
cana-3689	169	7	roc	roc	PROPN
cana-3689	169	8	area	area	NOUN
cana-3689	169	9	(	(	PUNCT
cana-3689	169	10	0.9750	0.9750	NUM
cana-3689	169	11	)	)	PUNCT
cana-3689	169	12	and	and	CCONJ
cana-3689	169	13	prc	prc	PROPN
cana-3689	169	14	area	area	NOUN
cana-3689	169	15	(	(	PUNCT
cana-3689	169	16	0.9690	0.9690	NUM
cana-3689	169	17	)	)	PUNCT
cana-3689	169	18	values	value	NOUN
cana-3689	169	19	.	.	PUNCT
cana-3689	170	1	logistic	logistic	ADJ
cana-3689	170	2	regression	regression	NOUN
cana-3689	170	3	displayed	display	VERB
cana-3689	170	4	satisfactory	satisfactory	ADJ
cana-3689	170	5	metrics	metric	NOUN
cana-3689	170	6	,	,	PUNCT
cana-3689	170	7	whereas	whereas	SCONJ
cana-3689	170	8	random	random	ADJ
cana-3689	170	9	forest	forest	NOUN
cana-3689	170	10	and	and	CCONJ
cana-3689	170	11	rep	rep	NOUN
cana-3689	170	12	tree	tree	NOUN
cana-3689	170	13	faced	face	VERB
cana-3689	170	14	difficulties	difficulty	NOUN
cana-3689	170	15	in	in	ADP
cana-3689	170	16	delivering	deliver	VERB
cana-3689	170	17	balanced	balanced	ADJ
cana-3689	170	18	performance	performance	NOUN
cana-3689	170	19	across	across	ADP
cana-3689	170	20	various	various	ADJ
cana-3689	170	21	activities	activity	NOUN
cana-3689	170	22	.	.	PUNCT
cana-3689	171	1	observations	observation	NOUN
cana-3689	171	2	model	model	ADJ
cana-3689	171	3	-	-	PUNCT
cana-3689	171	4	specific	specific	ADJ
cana-3689	171	5	strengths	strength	NOUN
cana-3689	171	6	:	:	PUNCT
cana-3689	171	7	j48	j48	PROPN
cana-3689	171	8	consistently	consistently	ADV
cana-3689	171	9	excelled	excel	VERB
cana-3689	171	10	with	with	ADP
cana-3689	171	11	structured	structured	ADJ
cana-3689	171	12	datasets	dataset	NOUN
cana-3689	171	13	,	,	PUNCT
cana-3689	171	14	particularly	particularly	ADV
cana-3689	171	15	for	for	ADP
cana-3689	171	16	running	run	VERB
cana-3689	171	17	and	and	CCONJ
cana-3689	171	18	cycling	cycling	NOUN
cana-3689	171	19	activities	activity	NOUN
cana-3689	171	20	,	,	PUNCT
cana-3689	171	21	while	while	SCONJ
cana-3689	171	22	smo	smo	PROPN
cana-3689	171	23	demonstrated	demonstrate	VERB
cana-3689	171	24	exceptional	exceptional	ADJ
cana-3689	171	25	adaptability	adaptability	NOUN
cana-3689	171	26	across	across	ADP
cana-3689	171	27	multiple	multiple	ADJ
cana-3689	171	28	activity	activity	NOUN
cana-3689	171	29	types	type	NOUN
cana-3689	171	30	,	,	PUNCT
cana-3689	171	31	including	include	VERB
cana-3689	171	32	walking	walk	VERB
cana-3689	171	33	.	.	PUNCT
cana-3689	172	1	algorithmic	algorithmic	ADJ
cana-3689	172	2	limitations	limitation	NOUN
cana-3689	172	3	:	:	PUNCT
cana-3689	172	4	random	random	ADJ
cana-3689	172	5	forest	forest	NOUN
cana-3689	172	6	and	and	CCONJ
cana-3689	172	7	rep	rep	PROPN
cana-3689	172	8	tree	tree	NOUN
cana-3689	172	9	encountered	encounter	VERB
cana-3689	172	10	challenges	challenge	NOUN
cana-3689	172	11	in	in	ADP
cana-3689	172	12	scenarios	scenario	NOUN
cana-3689	172	13	that	that	PRON
cana-3689	172	14	required	require	VERB
cana-3689	172	15	nuanced	nuanced	ADJ
cana-3689	172	16	decision	decision	NOUN
cana-3689	172	17	-	-	PUNCT
cana-3689	172	18	making	making	NOUN
cana-3689	172	19	,	,	PUNCT
cana-3689	172	20	particularly	particularly	ADV
cana-3689	172	21	in	in	ADP
cana-3689	172	22	predicting	predict	VERB
cana-3689	172	23	cycling	cycling	NOUN
cana-3689	172	24	and	and	CCONJ
cana-3689	172	25	walking	walking	NOUN
cana-3689	172	26	activities	activity	NOUN
cana-3689	172	27	.	.	PUNCT
cana-3689	173	1	performance	performance	NOUN
cana-3689	173	2	metrics	metric	NOUN
cana-3689	173	3	:	:	PUNCT
cana-3689	173	4	metrics	metric	NOUN
cana-3689	173	5	such	such	ADJ
cana-3689	173	6	as	as	ADP
cana-3689	173	7	mcc	mcc	PROPN
cana-3689	173	8	and	and	CCONJ
cana-3689	173	9	roc	roc	PROPN
cana-3689	173	10	area	area	NOUN
cana-3689	173	11	played	play	VERB
cana-3689	173	12	a	a	DET
cana-3689	173	13	crucial	crucial	ADJ
cana-3689	173	14	role	role	NOUN
cana-3689	173	15	in	in	ADP
cana-3689	173	16	evaluating	evaluate	VERB
cana-3689	173	17	model	model	NOUN
cana-3689	173	18	reliability	reliability	NOUN
cana-3689	173	19	,	,	PUNCT
cana-3689	173	20	emphasizing	emphasize	VERB
cana-3689	173	21	the	the	DET
cana-3689	173	22	trade	trade	NOUN
cana-3689	173	23	-	-	PUNCT
cana-3689	173	24	offs	off	NOUN
cana-3689	173	25	between	between	ADP
cana-3689	173	26	accuracy	accuracy	NOUN
cana-3689	173	27	and	and	CCONJ
cana-3689	173	28	robustness	robustness	NOUN
cana-3689	173	29	.	.	PUNCT
cana-3689	174	1	4	4	X
cana-3689	174	2	.	.	X
cana-3689	174	3	conclusion	conclusion	NOUN
cana-3689	174	4	this	this	DET
cana-3689	174	5	research	research	NOUN
cana-3689	174	6	highlights	highlight	VERB
cana-3689	174	7	the	the	DET
cana-3689	174	8	capability	capability	NOUN
cana-3689	174	9	of	of	ADP
cana-3689	174	10	machine	machine	NOUN
cana-3689	174	11	learning	learning	NOUN
cana-3689	174	12	models	model	NOUN
cana-3689	174	13	in	in	ADP
cana-3689	174	14	predicting	predict	VERB
cana-3689	174	15	cardio	cardio	NOUN
cana-3689	174	16	activities	activity	NOUN
cana-3689	174	17	effectively	effectively	ADV
cana-3689	174	18	.	.	PUNCT
cana-3689	175	1	j48	j48	PROPN
cana-3689	175	2	and	and	CCONJ
cana-3689	175	3	smo	smo	PROPN
cana-3689	175	4	emerged	emerge	VERB
cana-3689	175	5	as	as	ADP
cana-3689	175	6	the	the	DET
cana-3689	175	7	most	most	ADV
cana-3689	175	8	dependable	dependable	ADJ
cana-3689	175	9	algorithms	algorithm	NOUN
cana-3689	175	10	,	,	PUNCT
cana-3689	175	11	with	with	ADP
cana-3689	175	12	j48	j48	PROPN
cana-3689	175	13	excelling	excelling	NOUN
cana-3689	175	14	in	in	ADP
cana-3689	175	15	predictions	prediction	NOUN
cana-3689	175	16	for	for	ADP
cana-3689	175	17	running	run	VERB
cana-3689	175	18	and	and	CCONJ
cana-3689	175	19	cycling	cycling	NOUN
cana-3689	175	20	activities	activity	NOUN
cana-3689	175	21	,	,	PUNCT
cana-3689	175	22	while	while	SCONJ
cana-3689	175	23	smo	smo	PROPN
cana-3689	175	24	showed	show	VERB
cana-3689	175	25	superiority	superiority	NOUN
cana-3689	175	26	in	in	ADP
cana-3689	175	27	walking	walk	VERB
cana-3689	175	28	activity	activity	NOUN
cana-3689	175	29	predictions	prediction	NOUN
cana-3689	175	30	.	.	PUNCT
cana-3689	176	1	conversely	conversely	ADV
cana-3689	176	2	,	,	PUNCT
cana-3689	176	3	random	random	ADJ
cana-3689	176	4	forest	forest	NOUN
cana-3689	176	5	and	and	CCONJ
cana-3689	176	6	rep	rep	PROPN
cana-3689	176	7	tree	tree	NOUN
cana-3689	176	8	exhibited	exhibit	VERB
cana-3689	176	9	limited	limited	ADJ
cana-3689	176	10	applicability	applicability	NOUN
cana-3689	176	11	,	,	PUNCT
cana-3689	176	12	likely	likely	ADJ
cana-3689	176	13	due	due	ADJ
cana-3689	176	14	to	to	ADP
cana-3689	176	15	overfitting	overfitting	NOUN
cana-3689	176	16	or	or	CCONJ
cana-3689	176	17	inadequacies	inadequacy	NOUN
cana-3689	176	18	in	in	ADP
cana-3689	176	19	data	datum	NOUN
cana-3689	176	20	representation	representation	NOUN
cana-3689	176	21	.	.	PUNCT
cana-3689	177	1	the	the	DET
cana-3689	177	2	results	result	NOUN
cana-3689	177	3	underline	underline	VERB
cana-3689	177	4	the	the	DET
cana-3689	177	5	significance	significance	NOUN
cana-3689	177	6	of	of	ADP
cana-3689	177	7	selecting	select	VERB
cana-3689	177	8	appropriate	appropriate	ADJ
cana-3689	177	9	models	model	NOUN
cana-3689	177	10	and	and	CCONJ
cana-3689	177	11	employing	employ	VERB
cana-3689	177	12	comprehensive	comprehensive	ADJ
cana-3689	177	13	evaluation	evaluation	NOUN
cana-3689	177	14	metrics	metric	NOUN
cana-3689	177	15	to	to	PART
cana-3689	177	16	ensure	ensure	VERB
cana-3689	177	17	accurate	accurate	ADJ
cana-3689	177	18	and	and	CCONJ
cana-3689	177	19	reliable	reliable	ADJ
cana-3689	177	20	cardio	cardio	NOUN
cana-3689	177	21	activity	activity	NOUN
cana-3689	177	22	predictions	prediction	NOUN
cana-3689	177	23	.	.	PUNCT
cana-3689	178	1	utilizing	utilize	VERB
cana-3689	178	2	models	model	NOUN
cana-3689	178	3	like	like	ADP
cana-3689	178	4	j48	j48	PROPN
cana-3689	178	5	and	and	CCONJ
cana-3689	178	6	smo	smo	PROPN
cana-3689	178	7	could	could	AUX
cana-3689	178	8	facilitate	facilitate	VERB
cana-3689	178	9	the	the	DET
cana-3689	178	10	development	development	NOUN
cana-3689	178	11	of	of	ADP
cana-3689	178	12	tailored	tailor	VERB
cana-3689	178	13	predictive	predictive	ADJ
cana-3689	178	14	frameworks	framework	NOUN
cana-3689	178	15	that	that	PRON
cana-3689	178	16	enhance	enhance	VERB
cana-3689	178	17	personalized	personalize	VERB
cana-3689	178	18	health	health	NOUN
cana-3689	178	19	monitoring	monitoring	NOUN
cana-3689	178	20	and	and	CCONJ
cana-3689	178	21	fitness	fitness	NOUN
cana-3689	178	22	management	management	NOUN
cana-3689	178	23	.	.	PUNCT
cana-3689	179	1	communications	communication	NOUN
cana-3689	179	2	on	on	ADP
cana-3689	179	3	applied	apply	VERB
cana-3689	179	4	nonlinear	nonlinear	ADJ
cana-3689	179	5	analysis	analysis	NOUN
cana-3689	179	6	issn	issn	NOUN
cana-3689	179	7	:	:	PUNCT
cana-3689	179	8	1074	1074	NUM
cana-3689	179	9	-	-	PUNCT
cana-3689	179	10	133x	133x	NUM
cana-3689	179	11	vol	vol	NOUN
cana-3689	179	12	32	32	NUM
cana-3689	179	13	no	no	NOUN
cana-3689	179	14	.	.	PUNCT
cana-3689	180	1	8s	8s	PROPN
cana-3689	180	2	(	(	PUNCT
cana-3689	180	3	2025	2025	NUM
cana-3689	180	4	)	)	PUNCT
cana-3689	180	5	https://internationalpubls.com	https://internationalpubls.com	X
cana-3689	180	6	454	454	NUM
cana-3689	180	7	further	further	ADJ
cana-3689	180	8	research	research	VERB
cana-3689	180	9	the	the	DET
cana-3689	180	10	outcomes	outcome	NOUN
cana-3689	180	11	of	of	ADP
cana-3689	180	12	this	this	DET
cana-3689	180	13	study	study	NOUN
cana-3689	180	14	,	,	PUNCT
cana-3689	180	15	the	the	DET
cana-3689	180	16	following	follow	VERB
cana-3689	180	17	areas	area	NOUN
cana-3689	180	18	are	be	AUX
cana-3689	180	19	proposed	propose	VERB
cana-3689	180	20	for	for	ADP
cana-3689	180	21	future	future	ADJ
cana-3689	180	22	exploration	exploration	NOUN
cana-3689	180	23	.	.	PUNCT
cana-3689	181	1	incorporating	incorporate	VERB
cana-3689	181	2	data	datum	NOUN
cana-3689	181	3	collected	collect	VERB
cana-3689	181	4	in	in	ADP
cana-3689	181	5	real	real	ADJ
cana-3689	181	6	time	time	NOUN
cana-3689	181	7	from	from	ADP
cana-3689	181	8	wearable	wearable	ADJ
cana-3689	181	9	devices	device	NOUN
cana-3689	181	10	could	could	AUX
cana-3689	181	11	enhance	enhance	VERB
cana-3689	181	12	the	the	DET
cana-3689	181	13	models	model	NOUN
cana-3689	181	14	'	'	PART
cana-3689	181	15	responsiveness	responsiveness	NOUN
cana-3689	181	16	and	and	CCONJ
cana-3689	181	17	accuracy	accuracy	NOUN
cana-3689	181	18	for	for	ADP
cana-3689	181	19	predicting	predict	VERB
cana-3689	181	20	dynamic	dynamic	ADJ
cana-3689	181	21	activities	activity	NOUN
cana-3689	181	22	.	.	PUNCT
cana-3689	182	1	investigating	investigate	VERB
cana-3689	182	2	hybrid	hybrid	ADJ
cana-3689	182	3	methods	method	NOUN
cana-3689	182	4	that	that	PRON
cana-3689	182	5	combine	combine	VERB
cana-3689	182	6	the	the	DET
cana-3689	182	7	strengths	strength	NOUN
cana-3689	182	8	of	of	ADP
cana-3689	182	9	ensemble	ensemble	ADJ
cana-3689	182	10	techniques	technique	NOUN
cana-3689	182	11	(	(	PUNCT
cana-3689	182	12	e.g.	e.g.	ADV
cana-3689	182	13	,	,	PUNCT
cana-3689	182	14	random	random	ADJ
cana-3689	182	15	forest	forest	NOUN
cana-3689	182	16	)	)	PUNCT
cana-3689	182	17	with	with	ADP
cana-3689	182	18	neural	neural	ADJ
cana-3689	182	19	networks	network	NOUN
cana-3689	182	20	may	may	AUX
cana-3689	182	21	improve	improve	VERB
cana-3689	182	22	predictive	predictive	ADJ
cana-3689	182	23	performance	performance	NOUN
cana-3689	182	24	for	for	ADP
cana-3689	182	25	complex	complex	ADJ
cana-3689	182	26	datasets	dataset	NOUN
cana-3689	182	27	.	.	PUNCT
cana-3689	183	1	employing	employ	VERB
cana-3689	183	2	advanced	advanced	ADJ
cana-3689	183	3	feature	feature	NOUN
cana-3689	183	4	engineering	engineering	NOUN
cana-3689	183	5	techniques	technique	NOUN
cana-3689	183	6	to	to	PART
cana-3689	183	7	identify	identify	VERB
cana-3689	183	8	the	the	DET
cana-3689	183	9	most	most	ADV
cana-3689	183	10	influential	influential	ADJ
cana-3689	183	11	parameters	parameter	NOUN
cana-3689	183	12	could	could	AUX
cana-3689	183	13	reduce	reduce	VERB
cana-3689	183	14	computational	computational	ADJ
cana-3689	183	15	complexity	complexity	NOUN
cana-3689	183	16	while	while	SCONJ
cana-3689	183	17	boosting	boost	VERB
cana-3689	183	18	accuracy	accuracy	NOUN
cana-3689	183	19	.	.	PUNCT
cana-3689	184	1	broadening	broaden	VERB
cana-3689	184	2	the	the	DET
cana-3689	184	3	study	study	NOUN
cana-3689	184	4	scope	scope	NOUN
cana-3689	184	5	to	to	PART
cana-3689	184	6	include	include	VERB
cana-3689	184	7	diverse	diverse	ADJ
cana-3689	184	8	cardio	cardio	NOUN
cana-3689	184	9	activities	activity	NOUN
cana-3689	184	10	,	,	PUNCT
cana-3689	184	11	such	such	ADJ
cana-3689	184	12	as	as	ADP
cana-3689	184	13	swimming	swimming	NOUN
cana-3689	184	14	and	and	CCONJ
cana-3689	184	15	high	high	ADJ
cana-3689	184	16	-	-	PUNCT
cana-3689	184	17	intensity	intensity	NOUN
cana-3689	184	18	interval	interval	NOUN
cana-3689	184	19	training	training	NOUN
cana-3689	184	20	(	(	PUNCT
cana-3689	184	21	hiit	hiit	PROPN
cana-3689	184	22	)	)	PUNCT
cana-3689	184	23	,	,	PUNCT
cana-3689	184	24	could	could	AUX
cana-3689	184	25	generalize	generalize	VERB
cana-3689	184	26	the	the	DET
cana-3689	184	27	findings	finding	NOUN
cana-3689	184	28	further	far	ADV
cana-3689	184	29	.	.	PUNCT
cana-3689	185	1	developing	develop	VERB
cana-3689	185	2	explainable	explainable	ADJ
cana-3689	185	3	ai	ai	NOUN
cana-3689	185	4	models	model	NOUN
cana-3689	185	5	to	to	PART
cana-3689	185	6	offer	offer	VERB
cana-3689	185	7	actionable	actionable	ADJ
cana-3689	185	8	insights	insight	NOUN
cana-3689	185	9	behind	behind	ADP
cana-3689	185	10	predictions	prediction	NOUN
cana-3689	185	11	would	would	AUX
cana-3689	185	12	foster	foster	VERB
cana-3689	185	13	user	user	NOUN
cana-3689	185	14	trust	trust	NOUN
cana-3689	185	15	and	and	CCONJ
cana-3689	185	16	improve	improve	VERB
cana-3689	185	17	the	the	DET
cana-3689	185	18	usability	usability	NOUN
cana-3689	185	19	of	of	ADP
cana-3689	185	20	health	health	NOUN
cana-3689	185	21	applications	application	NOUN
cana-3689	185	22	.	.	PUNCT
cana-3689	186	1	by	by	ADP
cana-3689	186	2	addressing	address	VERB
cana-3689	186	3	these	these	DET
cana-3689	186	4	areas	area	NOUN
cana-3689	186	5	,	,	PUNCT
cana-3689	186	6	future	future	ADJ
cana-3689	186	7	research	research	NOUN
cana-3689	186	8	can	can	AUX
cana-3689	186	9	further	far	ADV
cana-3689	186	10	optimize	optimize	VERB
cana-3689	186	11	predictive	predictive	ADJ
cana-3689	186	12	frameworks	framework	NOUN
cana-3689	186	13	,	,	PUNCT
cana-3689	186	14	enhancing	enhance	VERB
cana-3689	186	15	their	their	PRON
cana-3689	186	16	applicability	applicability	NOUN
cana-3689	186	17	for	for	ADP
cana-3689	186	18	personalized	personalized	ADJ
cana-3689	186	19	health	health	NOUN
cana-3689	186	20	and	and	CCONJ
cana-3689	186	21	fitness	fitness	NOUN
cana-3689	186	22	monitoring	monitoring	NOUN
cana-3689	186	23	solutions	solution	NOUN
cana-3689	186	24	.	.	PUNCT
cana-3689	187	1	5	5	X
cana-3689	187	2	.	.	X
cana-3689	187	3	reference	reference	NOUN
cana-3689	187	4	[	[	X
cana-3689	187	5	1	1	NUM
cana-3689	187	6	]	]	X
cana-3689	187	7	ahmed	ahmed	PROPN
cana-3689	187	8	,	,	PUNCT
cana-3689	187	9	m.	m.	NOUN
cana-3689	187	10	,	,	PUNCT
cana-3689	187	11	&	&	CCONJ
cana-3689	187	12	khan	khan	PROPN
cana-3689	187	13	,	,	PUNCT
cana-3689	187	14	f.	f.	PROPN
cana-3689	187	15	(	(	PUNCT
cana-3689	187	16	2021	2021	NUM
cana-3689	187	17	)	)	PUNCT
cana-3689	187	18	.	.	PUNCT
cana-3689	188	1	integrating	integrate	VERB
cana-3689	188	2	neural	neural	ADJ
cana-3689	188	3	and	and	CCONJ
cana-3689	188	4	regression	regression	NOUN
cana-3689	188	5	models	model	NOUN
cana-3689	188	6	for	for	ADP
cana-3689	188	7	accurate	accurate	ADJ
cana-3689	188	8	cardio	cardio	NOUN
cana-3689	188	9	activity	activity	NOUN
cana-3689	188	10	predictions	prediction	NOUN
cana-3689	188	11	.	.	PUNCT
cana-3689	189	1	journal	journal	PROPN
cana-3689	189	2	of	of	ADP
cana-3689	189	3	biomedical	biomedical	ADJ
cana-3689	189	4	data	datum	NOUN
cana-3689	189	5	science	science	NOUN
cana-3689	189	6	,	,	PUNCT
cana-3689	189	7	18(2	18(2	NUM
cana-3689	189	8	)	)	PUNCT
cana-3689	189	9	,	,	PUNCT
cana-3689	189	10	56–70	56–70	NUM
cana-3689	189	11	.	.	PUNCT
cana-3689	190	1	[	[	X
cana-3689	190	2	2	2	NUM
cana-3689	190	3	]	]	X
cana-3689	190	4	bhatt	bhatt	PROPN
cana-3689	190	5	,	,	PUNCT
cana-3689	190	6	a.	a.	PROPN
cana-3689	190	7	,	,	PUNCT
cana-3689	190	8	dubey	dubey	PROPN
cana-3689	190	9	,	,	PUNCT
cana-3689	190	10	s.k	s.k	PROPN
cana-3689	190	11	.	.	PROPN
cana-3689	190	12	,	,	PUNCT
cana-3689	190	13	bhatt	bhatt	PROPN
cana-3689	190	14	,	,	PUNCT
cana-3689	190	15	a.k	a.k	PROPN
cana-3689	190	16	.	.	PROPN
cana-3689	190	17	and	and	CCONJ
cana-3689	190	18	joshi	joshi	PROPN
cana-3689	190	19	,	,	PUNCT
cana-3689	190	20	m.	m.	NOUN
cana-3689	190	21	,	,	PUNCT
cana-3689	190	22	(	(	PUNCT
cana-3689	190	23	2017	2017	NUM
cana-3689	190	24	)	)	PUNCT
cana-3689	190	25	.	.	PUNCT
cana-3689	191	1	data	datum	NOUN
cana-3689	191	2	mining	mining	NOUN
cana-3689	191	3	approach	approach	NOUN
cana-3689	191	4	to	to	PART
cana-3689	191	5	predict	predict	VERB
cana-3689	191	6	and	and	CCONJ
cana-3689	191	7	analyze	analyze	VERB
cana-3689	191	8	the	the	DET
cana-3689	191	9	cardiovascular	cardiovascular	ADJ
cana-3689	191	10	disease	disease	NOUN
cana-3689	191	11	.	.	PUNCT
cana-3689	192	1	in	in	ADP
cana-3689	192	2	proceedings	proceeding	NOUN
cana-3689	192	3	of	of	ADP
cana-3689	192	4	the	the	DET
cana-3689	192	5	5th	5th	ADJ
cana-3689	192	6	international	international	ADJ
cana-3689	192	7	conference	conference	NOUN
cana-3689	192	8	on	on	ADP
cana-3689	192	9	frontiers	frontier	NOUN
cana-3689	192	10	in	in	ADP
cana-3689	192	11	intelligent	intelligent	ADJ
cana-3689	192	12	computing	computing	NOUN
cana-3689	192	13	:	:	PUNCT
cana-3689	192	14	theory	theory	NOUN
cana-3689	192	15	and	and	CCONJ
cana-3689	192	16	applications	application	NOUN
cana-3689	192	17	:	:	PUNCT
cana-3689	192	18	ficta	ficta	NOUN
cana-3689	192	19	2016	2016	NUM
cana-3689	192	20	,	,	PUNCT
cana-3689	192	21	vol	vol	NOUN
cana-3689	192	22	.	.	PROPN
cana-3689	192	23	1	1	NUM
cana-3689	192	24	,	,	PUNCT
cana-3689	192	25	117	117	NUM
cana-3689	192	26	-	-	SYM
cana-3689	192	27	126	126	NUM
cana-3689	192	28	.	.	PUNCT
cana-3689	192	29	springer	springer	PROPN
cana-3689	192	30	singapore	singapore	PROPN
cana-3689	192	31	.	.	PUNCT
cana-3689	193	1	[	[	X
cana-3689	193	2	3	3	NUM
cana-3689	193	3	]	]	X
cana-3689	193	4	brown	brown	ADJ
cana-3689	193	5	,	,	PUNCT
cana-3689	193	6	t.	t.	PROPN
cana-3689	193	7	,	,	PUNCT
cana-3689	193	8	&	&	CCONJ
cana-3689	193	9	lee	lee	PROPN
cana-3689	193	10	,	,	PUNCT
cana-3689	193	11	m.	m.	NOUN
cana-3689	193	12	(	(	PUNCT
cana-3689	193	13	2020	2020	NUM
cana-3689	193	14	)	)	PUNCT
cana-3689	193	15	.	.	PUNCT
cana-3689	194	1	logistic	logistic	ADJ
cana-3689	194	2	regression	regression	NOUN
cana-3689	194	3	and	and	CCONJ
cana-3689	194	4	smo	smo	NOUN
cana-3689	194	5	for	for	ADP
cana-3689	194	6	cardio	cardio	NOUN
cana-3689	194	7	activity	activity	NOUN
cana-3689	194	8	prediction	prediction	NOUN
cana-3689	194	9	:	:	PUNCT
cana-3689	194	10	a	a	DET
cana-3689	194	11	comparative	comparative	ADJ
cana-3689	194	12	study	study	NOUN
cana-3689	194	13	.	.	PUNCT
cana-3689	195	1	computational	computational	ADJ
cana-3689	195	2	health	health	NOUN
cana-3689	195	3	analytics	analytic	NOUN
cana-3689	195	4	,	,	PUNCT
cana-3689	195	5	12(4	12(4	NUM
cana-3689	195	6	)	)	PUNCT
cana-3689	195	7	,	,	PUNCT
cana-3689	195	8	78–92	78–92	NOUN
cana-3689	195	9	.	.	PUNCT
cana-3689	196	1	[	[	X
cana-3689	196	2	4	4	NUM
cana-3689	196	3	]	]	X
cana-3689	196	4	gupta	gupta	PROPN
cana-3689	196	5	,	,	PUNCT
cana-3689	196	6	r.	r.	PROPN
cana-3689	196	7	,	,	PUNCT
cana-3689	196	8	verma	verma	PROPN
cana-3689	196	9	,	,	PUNCT
cana-3689	196	10	a.	a.	PROPN
cana-3689	196	11	,	,	PUNCT
cana-3689	196	12	&	&	CCONJ
cana-3689	196	13	patel	patel	PROPN
cana-3689	196	14	,	,	PUNCT
cana-3689	196	15	k.	k.	PROPN
cana-3689	196	16	(	(	PUNCT
cana-3689	196	17	2020	2020	NUM
cana-3689	196	18	)	)	PUNCT
cana-3689	196	19	.	.	PUNCT
cana-3689	197	1	feature	feature	NOUN
cana-3689	197	2	selection	selection	NOUN
cana-3689	197	3	and	and	CCONJ
cana-3689	197	4	its	its	PRON
cana-3689	197	5	impact	impact	NOUN
cana-3689	197	6	on	on	ADP
cana-3689	197	7	cardio	cardio	NOUN
cana-3689	197	8	activity	activity	NOUN
cana-3689	197	9	predictions	prediction	NOUN
cana-3689	197	10	using	use	VERB
cana-3689	197	11	machine	machine	NOUN
cana-3689	197	12	learning	learning	NOUN
cana-3689	197	13	models	model	NOUN
cana-3689	197	14	.	.	PUNCT
cana-3689	198	1	data	datum	NOUN
cana-3689	198	2	science	science	NOUN
cana-3689	198	3	in	in	ADP
cana-3689	198	4	health	health	NOUN
cana-3689	198	5	,	,	PUNCT
cana-3689	198	6	15(3	15(3	NUM
cana-3689	198	7	)	)	PUNCT
cana-3689	198	8	,	,	PUNCT
cana-3689	198	9	89–103	89–103	PROPN
cana-3689	198	10	.	.	PUNCT
cana-3689	199	1	[	[	X
cana-3689	199	2	5	5	NUM
cana-3689	199	3	]	]	PUNCT
cana-3689	199	4	https://www.kaggle.com/datasets/deependraverma13/cardio-activities	https://www.kaggle.com/datasets/deependraverma13/cardio-activitie	NOUN
cana-3689	199	5	.	.	PUNCT
cana-3689	200	1	[	[	X
cana-3689	200	2	6	6	NUM
cana-3689	200	3	]	]	X
cana-3689	200	4	johnson	johnson	PROPN
cana-3689	200	5	,	,	PUNCT
cana-3689	200	6	p.	p.	PROPN
cana-3689	200	7	,	,	PUNCT
cana-3689	200	8	kumar	kumar	PROPN
cana-3689	200	9	,	,	PUNCT
cana-3689	200	10	s.	s.	PROPN
cana-3689	200	11	,	,	PUNCT
cana-3689	200	12	&	&	CCONJ
cana-3689	200	13	lin	lin	PROPN
cana-3689	200	14	,	,	PUNCT
cana-3689	200	15	h.	h.	PROPN
cana-3689	200	16	(	(	PUNCT
cana-3689	200	17	2018	2018	NUM
cana-3689	200	18	)	)	PUNCT
cana-3689	200	19	.	.	PUNCT
cana-3689	201	1	performance	performance	NOUN
cana-3689	201	2	analysis	analysis	NOUN
cana-3689	201	3	of	of	ADP
cana-3689	201	4	decision	decision	NOUN
cana-3689	201	5	trees	tree	NOUN
cana-3689	201	6	in	in	ADP
cana-3689	201	7	predicting	predict	VERB
cana-3689	201	8	cardio	cardio	NOUN
cana-3689	201	9	activities	activity	NOUN
cana-3689	201	10	.	.	PUNCT
cana-3689	202	1	machine	machine	NOUN
cana-3689	202	2	learning	learn	VERB
cana-3689	202	3	applications	application	NOUN
cana-3689	202	4	in	in	ADP
cana-3689	202	5	healthcare	healthcare	PROPN
cana-3689	202	6	,	,	PUNCT
cana-3689	202	7	27(1	27(1	NUM
cana-3689	202	8	)	)	PUNCT
cana-3689	202	9	,	,	PUNCT
cana-3689	202	10	22–35	22–35	NUM
cana-3689	202	11	.	.	PUNCT
cana-3689	203	1	[	[	X
cana-3689	203	2	7	7	X
cana-3689	203	3	]	]	X
cana-3689	203	4	kim	kim	PROPN
cana-3689	203	5	,	,	PUNCT
cana-3689	203	6	j.	j.	PROPN
cana-3689	203	7	,	,	PUNCT
cana-3689	203	8	park	park	PROPN
cana-3689	203	9	,	,	PUNCT
cana-3689	203	10	s.	s.	PROPN
cana-3689	203	11	,	,	PUNCT
cana-3689	203	12	&	&	CCONJ
cana-3689	203	13	choi	choi	PROPN
cana-3689	203	14	,	,	PUNCT
cana-3689	203	15	y.	y.	PROPN
cana-3689	203	16	(	(	PUNCT
cana-3689	203	17	2019	2019	NUM
cana-3689	203	18	)	)	PUNCT
cana-3689	203	19	.	.	PUNCT
cana-3689	204	1	ensemble	ensemble	ADJ
cana-3689	204	2	methods	method	NOUN
cana-3689	204	3	for	for	ADP
cana-3689	204	4	predicting	predict	VERB
cana-3689	204	5	cardio	cardio	NOUN
cana-3689	204	6	activities	activity	NOUN
cana-3689	204	7	using	use	VERB
cana-3689	204	8	high	high	ADJ
cana-3689	204	9	-	-	PUNCT
cana-3689	204	10	dimensional	dimensional	ADJ
cana-3689	204	11	data	datum	NOUN
cana-3689	204	12	.	.	PUNCT
cana-3689	205	1	advances	advance	NOUN
cana-3689	205	2	in	in	ADP
cana-3689	205	3	machine	machine	NOUN
cana-3689	205	4	learning	learning	NOUN
cana-3689	205	5	,	,	PUNCT
cana-3689	205	6	14(6	14(6	NOUN
cana-3689	205	7	)	)	PUNCT
cana-3689	205	8	,	,	PUNCT
cana-3689	205	9	67–80	67–80	NOUN
cana-3689	205	10	.	.	PUNCT
cana-3689	206	1	[	[	X
cana-3689	206	2	8	8	NUM
cana-3689	206	3	]	]	X
cana-3689	206	4	kumar	kumar	PROPN
cana-3689	206	5	,	,	PUNCT
cana-3689	206	6	m.n	m.n	PROPN
cana-3689	206	7	.	.	PROPN
cana-3689	206	8	,	,	PUNCT
cana-3689	206	9	koushik	koushik	PROPN
cana-3689	206	10	,	,	PUNCT
cana-3689	206	11	k.v.s	k.v.s	PROPN
cana-3689	206	12	.	.	PROPN
cana-3689	206	13	and	and	CCONJ
cana-3689	206	14	deepak	deepak	PROPN
cana-3689	206	15	,	,	PUNCT
cana-3689	206	16	k.	k.	PROPN
cana-3689	206	17	,	,	PUNCT
cana-3689	206	18	(	(	PUNCT
cana-3689	206	19	2018	2018	NUM
cana-3689	206	20	)	)	PUNCT
cana-3689	206	21	.	.	PUNCT
cana-3689	207	1	prediction	prediction	NOUN
cana-3689	207	2	of	of	ADP
cana-3689	207	3	heart	heart	NOUN
cana-3689	207	4	diseases	disease	NOUN
cana-3689	207	5	using	use	VERB
cana-3689	207	6	data	datum	NOUN
cana-3689	207	7	mining	mining	NOUN
cana-3689	207	8	and	and	CCONJ
cana-3689	207	9	machine	machine	NOUN
cana-3689	207	10	learning	learn	VERB
cana-3689	207	11	algorithms	algorithm	NOUN
cana-3689	207	12	and	and	CCONJ
cana-3689	207	13	tools	tool	NOUN
cana-3689	207	14	.	.	PUNCT
cana-3689	208	1	international	international	ADJ
cana-3689	208	2	journal	journal	NOUN
cana-3689	208	3	of	of	ADP
cana-3689	208	4	scientific	scientific	ADJ
cana-3689	208	5	research	research	NOUN
cana-3689	208	6	in	in	ADP
cana-3689	208	7	computer	computer	NOUN
cana-3689	208	8	science	science	NOUN
cana-3689	208	9	,	,	PUNCT
cana-3689	208	10	engineering	engineering	NOUN
cana-3689	208	11	and	and	CCONJ
cana-3689	208	12	information	information	NOUN
cana-3689	208	13	technology	technology	NOUN
cana-3689	208	14	,	,	PUNCT
cana-3689	208	15	3(3	3(3	NUM
cana-3689	208	16	)	)	PUNCT
cana-3689	208	17	,	,	PUNCT
cana-3689	208	18	887	887	NUM
cana-3689	208	19	-	-	SYM
cana-3689	208	20	898	898	NUM
cana-3689	208	21	.	.	PUNCT
cana-3689	209	1	[	[	X
cana-3689	209	2	9	9	NUM
cana-3689	209	3	]	]	X
cana-3689	209	4	liu	liu	PROPN
cana-3689	209	5	,	,	PUNCT
cana-3689	209	6	c.	c.	PROPN
cana-3689	209	7	,	,	PUNCT
cana-3689	209	8	yang	yang	PROPN
cana-3689	209	9	,	,	PUNCT
cana-3689	209	10	j.	j.	PROPN
cana-3689	209	11	,	,	PUNCT
cana-3689	209	12	&	&	CCONJ
cana-3689	209	13	feng	feng	PROPN
cana-3689	209	14	,	,	PUNCT
cana-3689	209	15	l.	l.	PROPN
cana-3689	209	16	(	(	PUNCT
cana-3689	209	17	2020	2020	NUM
cana-3689	209	18	)	)	PUNCT
cana-3689	209	19	.	.	PUNCT
cana-3689	210	1	real	real	ADJ
cana-3689	210	2	-	-	PUNCT
cana-3689	210	3	time	time	NOUN
cana-3689	210	4	cardio	cardio	NOUN
cana-3689	210	5	activity	activity	NOUN
cana-3689	210	6	predictions	prediction	NOUN
cana-3689	210	7	using	use	VERB
cana-3689	210	8	decision	decision	NOUN
cana-3689	210	9	tree	tree	NOUN
cana-3689	210	10	and	and	CCONJ
cana-3689	210	11	smo	smo	PROPN
cana-3689	210	12	models	model	NOUN
cana-3689	210	13	.	.	PUNCT
cana-3689	211	1	computational	computational	ADJ
cana-3689	211	2	fitness	fitness	NOUN
cana-3689	211	3	analytics	analytic	NOUN
cana-3689	211	4	,	,	PUNCT
cana-3689	211	5	22(5	22(5	NOUN
cana-3689	211	6	)	)	PUNCT
cana-3689	211	7	,	,	PUNCT
cana-3689	211	8	321–336	321–336	NUM
cana-3689	211	9	.	.	PUNCT
cana-3689	212	1	[	[	X
cana-3689	212	2	10	10	NUM
cana-3689	212	3	]	]	X
cana-3689	212	4	martinez	martinez	PROPN
cana-3689	212	5	,	,	PUNCT
cana-3689	212	6	a.	a.	PROPN
cana-3689	212	7	,	,	PUNCT
cana-3689	212	8	chen	chen	PROPN
cana-3689	212	9	,	,	PUNCT
cana-3689	212	10	w.	w.	PROPN
cana-3689	212	11	,	,	PUNCT
cana-3689	212	12	&	&	CCONJ
cana-3689	212	13	lopez	lopez	PROPN
cana-3689	212	14	,	,	PUNCT
cana-3689	212	15	r.	r.	PROPN
cana-3689	212	16	(	(	PUNCT
cana-3689	212	17	2021	2021	NUM
cana-3689	212	18	)	)	PUNCT
cana-3689	212	19	.	.	PUNCT
cana-3689	213	1	hybrid	hybrid	ADJ
cana-3689	213	2	machine	machine	NOUN
cana-3689	213	3	learning	learning	NOUN
cana-3689	213	4	models	model	NOUN
cana-3689	213	5	for	for	ADP
cana-3689	213	6	high	high	ADJ
cana-3689	213	7	-	-	PUNCT
cana-3689	213	8	intensity	intensity	NOUN
cana-3689	213	9	cardio	cardio	NOUN
cana-3689	213	10	activity	activity	NOUN
cana-3689	213	11	prediction	prediction	NOUN
cana-3689	213	12	.	.	PUNCT
cana-3689	214	1	artificial	artificial	ADJ
cana-3689	214	2	intelligence	intelligence	NOUN
cana-3689	214	3	in	in	ADP
cana-3689	214	4	medicine	medicine	NOUN
cana-3689	214	5	,	,	PUNCT
cana-3689	214	6	39(2	39(2	NUM
cana-3689	214	7	)	)	PUNCT
cana-3689	214	8	,	,	PUNCT
cana-3689	214	9	201–215	201–215	NUM
cana-3689	214	10	.	.	PUNCT
cana-3689	215	1	[	[	X
cana-3689	215	2	11	11	NUM
cana-3689	215	3	]	]	X
cana-3689	215	4	patel	patel	PROPN
cana-3689	215	5	,	,	PUNCT
cana-3689	215	6	d.	d.	PROPN
cana-3689	215	7	,	,	PUNCT
cana-3689	215	8	sharma	sharma	PROPN
cana-3689	215	9	,	,	PUNCT
cana-3689	215	10	m.	m.	NOUN
cana-3689	215	11	,	,	PUNCT
cana-3689	215	12	&	&	CCONJ
cana-3689	215	13	jain	jain	PROPN
cana-3689	215	14	,	,	PUNCT
cana-3689	215	15	s.	s.	PROPN
cana-3689	215	16	(	(	PUNCT
cana-3689	215	17	2022	2022	NUM
cana-3689	215	18	)	)	PUNCT
cana-3689	215	19	.	.	PUNCT
cana-3689	216	1	comparative	comparative	ADJ
cana-3689	216	2	evaluation	evaluation	NOUN
cana-3689	216	3	of	of	ADP
cana-3689	216	4	decision	decision	NOUN
cana-3689	216	5	tree	tree	NOUN
cana-3689	216	6	algorithms	algorithm	NOUN
cana-3689	216	7	for	for	ADP
cana-3689	216	8	cardio	cardio	NOUN
cana-3689	216	9	activity	activity	NOUN
cana-3689	216	10	prediction	prediction	NOUN
cana-3689	216	11	.	.	PUNCT
cana-3689	217	1	journal	journal	NOUN
cana-3689	217	2	of	of	ADP
cana-3689	217	3	predictive	predictive	ADJ
cana-3689	217	4	analytics	analytic	NOUN
cana-3689	217	5	,	,	PUNCT
cana-3689	217	6	9(7	9(7	NUM
cana-3689	217	7	)	)	PUNCT
cana-3689	217	8	,	,	PUNCT
cana-3689	217	9	102–118	102–118	NUM
cana-3689	217	10	.	.	PUNCT
cana-3689	218	1	[	[	X
cana-3689	218	2	12	12	NUM
cana-3689	218	3	]	]	X
cana-3689	218	4	rajesh	rajesh	PROPN
cana-3689	218	5	,	,	PUNCT
cana-3689	218	6	p.	p.	NOUN
cana-3689	218	7	and	and	CCONJ
cana-3689	218	8	karthikeyan	karthikeyan	PROPN
cana-3689	218	9	,	,	PUNCT
cana-3689	218	10	m.	m.	NOUN
cana-3689	218	11	,	,	PUNCT
cana-3689	218	12	(	(	PUNCT
cana-3689	218	13	2017	2017	NUM
cana-3689	218	14	)	)	PUNCT
cana-3689	218	15	.	.	PUNCT
cana-3689	219	1	a	a	DET
cana-3689	219	2	comparative	comparative	ADJ
cana-3689	219	3	study	study	NOUN
cana-3689	219	4	of	of	ADP
cana-3689	219	5	data	datum	NOUN
cana-3689	219	6	mining	mining	NOUN
cana-3689	219	7	algorithms	algorithm	NOUN
cana-3689	219	8	for	for	ADP
cana-3689	219	9	decision	decision	NOUN
cana-3689	219	10	tree	tree	NOUN
cana-3689	219	11	approaches	approach	NOUN
cana-3689	219	12	using	use	VERB
cana-3689	219	13	the	the	DET
cana-3689	219	14	weka	weka	PROPN
cana-3689	219	15	tool	tool	PROPN
cana-3689	219	16	.	.	PUNCT
cana-3689	220	1	advances	advance	NOUN
cana-3689	220	2	in	in	ADP
cana-3689	220	3	natural	natural	ADJ
cana-3689	220	4	and	and	CCONJ
cana-3689	220	5	applied	applied	ADJ
cana-3689	220	6	sciences	science	NOUN
cana-3689	220	7	,	,	PUNCT
cana-3689	220	8	11(9	11(9	PROPN
cana-3689	220	9	)	)	PUNCT
cana-3689	220	10	,	,	PUNCT
cana-3689	220	11	230	230	NUM
cana-3689	220	12	-	-	SYM
cana-3689	220	13	243	243	NUM
cana-3689	220	14	.	.	PUNCT
cana-3689	221	1	[	[	X
cana-3689	221	2	13	13	NUM
cana-3689	221	3	]	]	X
cana-3689	221	4	rajesh	rajesh	PROPN
cana-3689	221	5	,	,	PUNCT
cana-3689	221	6	p.	p.	NOUN
cana-3689	221	7	and	and	CCONJ
cana-3689	221	8	karthikeyan	karthikeyan	PROPN
cana-3689	221	9	,	,	PUNCT
cana-3689	221	10	m.	m.	NOUN
cana-3689	221	11	,	,	PUNCT
cana-3689	221	12	(	(	PUNCT
cana-3689	221	13	2019	2019	NUM
cana-3689	221	14	)	)	PUNCT
cana-3689	221	15	.	.	PUNCT
cana-3689	222	1	data	datum	NOUN
cana-3689	222	2	mining	mining	NOUN
cana-3689	222	3	approaches	approach	NOUN
cana-3689	222	4	to	to	PART
cana-3689	222	5	predict	predict	VERB
cana-3689	222	6	the	the	DET
cana-3689	222	7	factors	factor	NOUN
cana-3689	222	8	that	that	PRON
cana-3689	222	9	affect	affect	VERB
cana-3689	222	10	agriculture	agriculture	NOUN
cana-3689	222	11	growth	growth	NOUN
cana-3689	222	12	using	use	VERB
cana-3689	222	13	stochastic	stochastic	ADJ
cana-3689	222	14	models	model	NOUN
cana-3689	222	15	.	.	PUNCT
cana-3689	223	1	international	international	ADJ
cana-3689	223	2	journal	journal	PROPN
cana-3689	223	3	of	of	ADP
cana-3689	223	4	computer	computer	NOUN
cana-3689	223	5	sciences	science	NOUN
cana-3689	223	6	and	and	CCONJ
cana-3689	223	7	engineering	engineering	NOUN
cana-3689	223	8	,	,	PUNCT
cana-3689	223	9	7(4	7(4	NUM
cana-3689	223	10	)	)	PUNCT
cana-3689	223	11	,	,	PUNCT
cana-3689	223	12	18	18	NUM
cana-3689	223	13	-	-	SYM
cana-3689	223	14	23	23	NUM
cana-3689	223	15	.	.	PUNCT
cana-3689	224	1	[	[	X
cana-3689	224	2	14	14	NUM
cana-3689	224	3	]	]	X
cana-3689	224	4	rajesh	rajesh	PROPN
cana-3689	224	5	,	,	PUNCT
cana-3689	224	6	p.	p.	PROPN
cana-3689	224	7	,	,	PUNCT
cana-3689	224	8	karthikeyan	karthikeyan	PROPN
cana-3689	224	9	,	,	PUNCT
cana-3689	224	10	m.	m.	NOUN
cana-3689	224	11	and	and	CCONJ
cana-3689	224	12	arulpavai	arulpavai	PROPN
cana-3689	224	13	,	,	PUNCT
cana-3689	224	14	r.	r.	PROPN
cana-3689	224	15	,	,	PUNCT
cana-3689	224	16	(	(	PUNCT
cana-3689	224	17	2019	2019	NUM
cana-3689	224	18	)	)	PUNCT
cana-3689	224	19	.	.	PUNCT
cana-3689	225	1	data	datum	NOUN
cana-3689	225	2	mining	mining	NOUN
cana-3689	225	3	approaches	approach	NOUN
cana-3689	225	4	to	to	PART
cana-3689	225	5	predict	predict	VERB
cana-3689	225	6	the	the	DET
cana-3689	225	7	factors	factor	NOUN
cana-3689	225	8	that	that	PRON
cana-3689	225	9	affect	affect	VERB
cana-3689	225	10	the	the	DET
cana-3689	225	11	groundwater	groundwater	NOUN
cana-3689	225	12	level	level	NOUN
cana-3689	225	13	using	use	VERB
cana-3689	225	14	a	a	DET
cana-3689	225	15	stochastic	stochastic	ADJ
cana-3689	225	16	model	model	NOUN
cana-3689	225	17	.	.	PUNCT
cana-3689	226	1	in	in	ADP
cana-3689	226	2	aip	aip	PROPN
cana-3689	226	3	conference	conference	NOUN
cana-3689	226	4	proceedings	proceeding	NOUN
cana-3689	226	5	,	,	PUNCT
cana-3689	226	6	2177(1	2177(1	NUM
cana-3689	226	7	)	)	PUNCT
cana-3689	226	8	,	,	PUNCT
cana-3689	226	9	aip	aip	PROPN
cana-3689	226	10	publishing	publishing	NOUN
cana-3689	226	11	.	.	PUNCT
cana-3689	227	1	[	[	X
cana-3689	227	2	15	15	NUM
cana-3689	227	3	]	]	X
cana-3689	227	4	rajesh	rajesh	PROPN
cana-3689	227	5	,	,	PUNCT
cana-3689	227	6	p.	p.	PROPN
cana-3689	227	7	,	,	PUNCT
cana-3689	227	8	karthikeyan	karthikeyan	PROPN
cana-3689	227	9	,	,	PUNCT
cana-3689	227	10	m.	m.	NOUN
cana-3689	227	11	,	,	PUNCT
cana-3689	227	12	santhosh	santhosh	PROPN
cana-3689	227	13	kumar	kumar	PROPN
cana-3689	227	14	,	,	PUNCT
cana-3689	227	15	b.	b.	PROPN
cana-3689	227	16	and	and	CCONJ
cana-3689	227	17	mohamed	mohamed	PROPN
cana-3689	227	18	parvees	parvees	PROPN
cana-3689	227	19	,	,	PUNCT
cana-3689	227	20	m.y	m.y	PROPN
cana-3689	227	21	.	.	PROPN
cana-3689	227	22	,	,	PUNCT
cana-3689	227	23	(	(	PUNCT
cana-3689	227	24	2019	2019	NUM
cana-3689	227	25	)	)	PUNCT
cana-3689	227	26	.	.	PUNCT
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cana-3689	228	2	study	study	NOUN
cana-3689	228	3	of	of	ADP
cana-3689	228	4	decision	decision	NOUN
cana-3689	228	5	tree	tree	NOUN
cana-3689	228	6	approaches	approach	VERB
cana-3689	228	7	in	in	ADP
cana-3689	228	8	data	datum	NOUN
cana-3689	228	9	mining	mining	NOUN
cana-3689	228	10	using	use	VERB
cana-3689	228	11	chronic	chronic	ADJ
cana-3689	228	12	disease	disease	NOUN
cana-3689	228	13	indicators	indicator	NOUN
cana-3689	228	14	(	(	PUNCT
cana-3689	228	15	cdi	cdi	PROPN
cana-3689	228	16	)	)	PUNCT
cana-3689	228	17	data	data	PROPN
cana-3689	228	18	.	.	PUNCT
cana-3689	229	1	journal	journal	PROPN
cana-3689	229	2	of	of	ADP
cana-3689	229	3	computational	computational	ADJ
cana-3689	229	4	and	and	CCONJ
cana-3689	229	5	theoretical	theoretical	ADJ
cana-3689	229	6	nanoscience	nanoscience	NOUN
cana-3689	229	7	,	,	PUNCT
cana-3689	229	8	16(4	16(4	PROPN
cana-3689	229	9	)	)	PUNCT
cana-3689	229	10	,	,	PUNCT
cana-3689	229	11	1472	1472	NUM
cana-3689	229	12	-	-	SYM
cana-3689	229	13	1477	1477	NUM
cana-3689	229	14	.	.	PUNCT
cana-3689	230	1	[	[	X
cana-3689	230	2	16	16	NUM
cana-3689	230	3	]	]	PUNCT
cana-3689	230	4	rajliwall	rajliwall	PROPN
cana-3689	230	5	,	,	PUNCT
cana-3689	230	6	n.s	n.s	PROPN
cana-3689	230	7	.	.	PROPN
cana-3689	230	8	,	,	PUNCT
cana-3689	230	9	davey	davey	PROPN
cana-3689	230	10	,	,	PUNCT
cana-3689	230	11	r.	r.	PROPN
cana-3689	230	12	and	and	CCONJ
cana-3689	230	13	chetty	chetty	PROPN
cana-3689	230	14	,	,	PUNCT
cana-3689	230	15	g.	g.	PROPN
cana-3689	230	16	,	,	PUNCT
cana-3689	230	17	(	(	PUNCT
cana-3689	230	18	2018	2018	NUM
cana-3689	230	19	)	)	PUNCT
cana-3689	230	20	.	.	PUNCT
cana-3689	231	1	machine	machine	NOUN
cana-3689	231	2	learning	learning	NOUN
cana-3689	231	3	based	base	VERB
cana-3689	231	4	models	model	NOUN
cana-3689	231	5	for	for	ADP
cana-3689	231	6	cardiovascular	cardiovascular	ADJ
cana-3689	231	7	risk	risk	NOUN
cana-3689	231	8	prediction	prediction	NOUN
cana-3689	231	9	.	.	PUNCT
cana-3689	232	1	in	in	ADP
cana-3689	232	2	2018	2018	NUM
cana-3689	232	3	international	international	ADJ
cana-3689	232	4	conference	conference	NOUN
cana-3689	232	5	on	on	ADP
cana-3689	232	6	machine	machine	NOUN
cana-3689	232	7	learning	learning	NOUN
cana-3689	232	8	and	and	CCONJ
cana-3689	232	9	data	datum	NOUN
cana-3689	232	10	engineering	engineering	NOUN
cana-3689	232	11	(	(	PUNCT
cana-3689	232	12	icmlde	icmlde	ADJ
cana-3689	232	13	)	)	PUNCT
cana-3689	232	14	(	(	PUNCT
cana-3689	232	15	pp	pp	X
cana-3689	232	16	.	.	PUNCT
cana-3689	233	1	142	142	NUM
cana-3689	233	2	-	-	SYM
cana-3689	233	3	148	148	NUM
cana-3689	233	4	)	)	PUNCT
cana-3689	233	5	.	.	PUNCT
cana-3689	234	1	ieee	ieee	PROPN
cana-3689	234	2	.	.	PUNCT
cana-3689	235	1	https://www.kaggle.com/datasets/deependraverma13/cardio-activities	https://www.kaggle.com/datasets/deependraverma13/cardio-activitie	NOUN
cana-3689	235	2	communications	communication	NOUN
cana-3689	235	3	on	on	ADP
cana-3689	235	4	applied	apply	VERB
cana-3689	235	5	nonlinear	nonlinear	ADJ
cana-3689	235	6	analysis	analysis	NOUN
cana-3689	235	7	issn	issn	NOUN
cana-3689	235	8	:	:	PUNCT
cana-3689	235	9	1074	1074	NUM
cana-3689	235	10	-	-	PUNCT
cana-3689	235	11	133x	133x	NUM
cana-3689	235	12	vol	vol	NOUN
cana-3689	235	13	32	32	NUM
cana-3689	235	14	no	no	NOUN
cana-3689	235	15	.	.	PUNCT
cana-3689	236	1	8s	8s	PROPN
cana-3689	236	2	(	(	PUNCT
cana-3689	236	3	2025	2025	NUM
cana-3689	236	4	)	)	PUNCT
cana-3689	236	5	https://internationalpubls.com	https://internationalpubls.com	X
cana-3689	236	6	455	455	NUM
cana-3689	237	1	[	[	X
cana-3689	237	2	17	17	NUM
cana-3689	237	3	]	]	X
cana-3689	237	4	ramesh	ramesh	PROPN
cana-3689	237	5	,	,	PUNCT
cana-3689	237	6	t.r	t.r	PROPN
cana-3689	237	7	.	.	PROPN
cana-3689	237	8	,	,	PUNCT
cana-3689	237	9	lilhore	lilhore	PROPN
cana-3689	237	10	,	,	PUNCT
cana-3689	237	11	u.k	u.k	PROPN
cana-3689	237	12	.	.	PROPN
cana-3689	237	13	,	,	PUNCT
cana-3689	237	14	poongodi	poongodi	PROPN
cana-3689	237	15	,	,	PUNCT
cana-3689	237	16	m.	m.	NOUN
cana-3689	237	17	,	,	PUNCT
cana-3689	237	18	simaiya	simaiya	PROPN
cana-3689	237	19	,	,	PUNCT
cana-3689	237	20	s.	s.	PROPN
cana-3689	237	21	,	,	PUNCT
cana-3689	237	22	kaur	kaur	PROPN
cana-3689	237	23	,	,	PUNCT
cana-3689	237	24	a.	a.	NOUN
cana-3689	237	25	and	and	CCONJ
cana-3689	237	26	hamdi	hamdi	PROPN
cana-3689	237	27	,	,	PUNCT
cana-3689	237	28	m.	m.	NOUN
cana-3689	237	29	,	,	PUNCT
cana-3689	237	30	(	(	PUNCT
cana-3689	237	31	2022	2022	NUM
cana-3689	237	32	)	)	PUNCT
cana-3689	237	33	.	.	PUNCT
cana-3689	238	1	predictive	predictive	ADJ
cana-3689	238	2	analysis	analysis	NOUN
cana-3689	238	3	of	of	ADP
cana-3689	238	4	heart	heart	NOUN
cana-3689	238	5	diseases	disease	NOUN
cana-3689	238	6	with	with	ADP
cana-3689	238	7	machine	machine	NOUN
cana-3689	238	8	learning	learning	NOUN
cana-3689	238	9	approaches	approach	NOUN
cana-3689	238	10	.	.	PUNCT
cana-3689	239	1	malaysian	malaysian	ADJ
cana-3689	239	2	journal	journal	PROPN
cana-3689	239	3	of	of	ADP
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cana-3689	239	5	science	science	NOUN
cana-3689	239	6	,	,	PUNCT
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cana-3689	239	8	-	-	SYM
cana-3689	239	9	148	148	NUM
cana-3689	239	10	.	.	PUNCT
cana-3689	240	1	[	[	X
cana-3689	240	2	18	18	NUM
cana-3689	240	3	]	]	X
cana-3689	240	4	sajid	sajid	PROPN
cana-3689	240	5	,	,	PUNCT
cana-3689	240	6	m.r	m.r	PROPN
cana-3689	240	7	.	.	PROPN
cana-3689	240	8	,	,	PUNCT
cana-3689	240	9	muhammad	muhammad	PROPN
cana-3689	240	10	,	,	PUNCT
cana-3689	240	11	n.	n.	NOUN
cana-3689	240	12	,	,	PUNCT
cana-3689	240	13	zakaria	zakaria	PROPN
cana-3689	240	14	,	,	PUNCT
cana-3689	240	15	r.	r.	PROPN
cana-3689	240	16	,	,	PUNCT
cana-3689	240	17	shahbaz	shahbaz	PROPN
cana-3689	240	18	,	,	PUNCT
cana-3689	240	19	a.	a.	PROPN
cana-3689	240	20	,	,	PUNCT
cana-3689	240	21	bukhari	bukhari	NOUN
cana-3689	240	22	,	,	PUNCT
cana-3689	240	23	s.a.c	s.a.c	NOUN
cana-3689	240	24	.	.	PUNCT
cana-3689	240	25	,	,	PUNCT
cana-3689	240	26	kadry	kadry	PROPN
cana-3689	240	27	,	,	PUNCT
cana-3689	240	28	s.	s.	PROPN
cana-3689	240	29	and	and	CCONJ
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cana-3689	240	31	,	,	PUNCT
cana-3689	240	32	a.	a.	PROPN
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cana-3689	240	35	2021	2021	NUM
cana-3689	240	36	)	)	PUNCT
cana-3689	240	37	.	.	PUNCT
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cana-3689	241	2	features	feature	NOUN
cana-3689	241	3	in	in	ADP
cana-3689	241	4	predictive	predictive	ADJ
cana-3689	241	5	modeling	modeling	NOUN
cana-3689	241	6	of	of	ADP
cana-3689	241	7	cardiovascular	cardiovascular	ADJ
cana-3689	241	8	diseases	disease	NOUN
cana-3689	241	9	:	:	PUNCT
cana-3689	241	10	a	a	DET
cana-3689	241	11	machine	machine	NOUN
cana-3689	241	12	learning	learning	NOUN
cana-3689	241	13	approach	approach	NOUN
cana-3689	241	14	.	.	PUNCT
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cana-3689	242	2	sciences	science	NOUN
cana-3689	242	3	:	:	PUNCT
cana-3689	242	4	computational	computational	ADJ
cana-3689	242	5	life	life	NOUN
cana-3689	242	6	sciences	science	NOUN
cana-3689	242	7	,	,	PUNCT
cana-3689	242	8	13	13	NUM
cana-3689	242	9	,	,	PUNCT
cana-3689	242	10	201	201	NUM
cana-3689	242	11	-	-	SYM
cana-3689	242	12	211	211	NUM
cana-3689	242	13	.	.	PUNCT
cana-3689	243	1	[	[	X
cana-3689	243	2	19	19	NUM
cana-3689	243	3	]	]	X
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cana-3689	243	5	,	,	PUNCT
cana-3689	243	6	s.	s.	PROPN
cana-3689	243	7	,	,	PUNCT
cana-3689	243	8	elshawi	elshawi	PROPN
cana-3689	243	9	,	,	PUNCT
cana-3689	243	10	r.	r.	PROPN
cana-3689	243	11	,	,	PUNCT
cana-3689	243	12	ahmed	ahmed	PROPN
cana-3689	243	13	,	,	PUNCT
cana-3689	243	14	a.	a.	PROPN
cana-3689	243	15	,	,	PUNCT
cana-3689	243	16	qureshi	qureshi	PROPN
cana-3689	243	17	,	,	PUNCT
cana-3689	243	18	w.t	w.t	PROPN
cana-3689	243	19	.	.	PROPN
cana-3689	243	20	,	,	PUNCT
cana-3689	243	21	brawner	brawner	NOUN
cana-3689	243	22	,	,	PUNCT
cana-3689	243	23	c.	c.	PROPN
cana-3689	243	24	,	,	PUNCT
cana-3689	243	25	keteyian	keteyian	PROPN
cana-3689	243	26	,	,	PUNCT
cana-3689	243	27	s.	s.	PROPN
cana-3689	243	28	,	,	PUNCT
cana-3689	243	29	blaha	blaha	PROPN
cana-3689	243	30	,	,	PUNCT
cana-3689	243	31	m.j	m.j	PROPN
cana-3689	243	32	.	.	PROPN
cana-3689	243	33	and	and	CCONJ
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cana-3689	243	35	-	-	PUNCT
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cana-3689	243	37	,	,	PUNCT
cana-3689	243	38	m.h	m.h	PROPN
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cana-3689	243	40	,	,	PUNCT
cana-3689	243	41	(	(	PUNCT
cana-3689	243	42	2018	2018	NUM
cana-3689	243	43	)	)	PUNCT
cana-3689	243	44	.	.	PUNCT
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cana-3689	244	4	on	on	ADP
cana-3689	244	5	cardiorespiratory	cardiorespiratory	NOUN
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cana-3689	244	7	data	datum	NOUN
cana-3689	244	8	for	for	ADP
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cana-3689	244	10	hypertension	hypertension	NOUN
cana-3689	244	11	:	:	PUNCT
cana-3689	244	12	the	the	DET
cana-3689	244	13	henry	henry	PROPN
cana-3689	244	14	ford	ford	PROPN
cana-3689	244	15	exercise	exercise	NOUN
cana-3689	244	16	testing	testing	NOUN
cana-3689	244	17	(	(	PUNCT
cana-3689	244	18	fit	fit	ADJ
cana-3689	244	19	)	)	PUNCT
cana-3689	244	20	project	project	NOUN
cana-3689	244	21	.	.	PUNCT
cana-3689	245	1	plos	plos	PROPN
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cana-3689	245	3	,	,	PUNCT
cana-3689	245	4	13(4	13(4	NUM
cana-3689	245	5	)	)	PUNCT
cana-3689	245	6	,	,	PUNCT
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cana-3689	245	8	.	.	PUNCT
cana-3689	246	1	[	[	X
cana-3689	246	2	20	20	NUM
cana-3689	246	3	]	]	SYM
cana-3689	246	4	smith	smith	PROPN
cana-3689	246	5	,	,	PUNCT
cana-3689	246	6	j.	j.	PROPN
cana-3689	246	7	,	,	PUNCT
cana-3689	246	8	brown	brown	PROPN
cana-3689	246	9	,	,	PUNCT
cana-3689	246	10	r.	r.	PROPN
cana-3689	246	11	,	,	PUNCT
cana-3689	246	12	&	&	CCONJ
cana-3689	246	13	davis	davis	PROPN
cana-3689	246	14	,	,	PUNCT
cana-3689	246	15	l.	l.	PROPN
cana-3689	246	16	(	(	PUNCT
cana-3689	246	17	2019	2019	NUM
cana-3689	246	18	)	)	PUNCT
cana-3689	246	19	.	.	PUNCT
cana-3689	246	20	machine	machine	NOUN
cana-3689	246	21	learning	learning	NOUN
cana-3689	246	22	models	model	NOUN
cana-3689	246	23	for	for	ADP
cana-3689	246	24	predicting	predict	VERB
cana-3689	246	25	cardio	cardio	NOUN
cana-3689	246	26	activities	activity	NOUN
cana-3689	246	27	using	use	VERB
cana-3689	246	28	wearable	wearable	ADJ
cana-3689	246	29	data	datum	NOUN
cana-3689	246	30	.	.	PUNCT
cana-3689	247	1	journal	journal	PROPN
cana-3689	247	2	of	of	ADP
cana-3689	247	3	health	health	NOUN
cana-3689	247	4	informatics	informatic	NOUN
cana-3689	247	5	,	,	PUNCT
cana-3689	247	6	45(3	45(3	NUM
cana-3689	247	7	)	)	PUNCT
cana-3689	247	8	,	,	PUNCT
cana-3689	247	9	345–360	345–360	NUM
cana-3689	247	10	.	.	PUNCT
cana-3689	248	1	[	[	X
cana-3689	248	2	21	21	NUM
cana-3689	248	3	]	]	SYM
cana-3689	248	4	swathy	swathy	ADJ
cana-3689	248	5	,	,	PUNCT
cana-3689	248	6	m.	m.	NOUN
cana-3689	248	7	and	and	CCONJ
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cana-3689	248	9	,	,	PUNCT
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cana-3689	248	11	,	,	PUNCT
cana-3689	248	12	(	(	PUNCT
cana-3689	248	13	2022	2022	NUM
cana-3689	248	14	)	)	PUNCT
cana-3689	248	15	.	.	PUNCT
cana-3689	249	1	a	a	DET
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cana-3689	249	3	study	study	NOUN
cana-3689	249	4	of	of	ADP
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cana-3689	249	6	and	and	CCONJ
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cana-3689	249	8	of	of	ADP
cana-3689	249	9	cardio	cardio	NOUN
cana-3689	249	10	-	-	PUNCT
cana-3689	249	11	vascular	vascular	ADJ
cana-3689	249	12	diseases	disease	NOUN
cana-3689	249	13	(	(	PUNCT
cana-3689	249	14	cvd	cvd	NOUN
cana-3689	249	15	)	)	PUNCT
cana-3689	249	16	using	use	VERB
cana-3689	249	17	machine	machine	NOUN
cana-3689	249	18	learning	learning	NOUN
cana-3689	249	19	and	and	CCONJ
cana-3689	249	20	deep	deep	ADJ
cana-3689	249	21	learning	learning	NOUN
cana-3689	249	22	techniques	technique	NOUN
cana-3689	249	23	.	.	PUNCT
cana-3689	250	1	ict	ict	PROPN
cana-3689	250	2	express	express	PROPN
cana-3689	250	3	,	,	PUNCT
cana-3689	250	4	8(1	8(1	NOUN
cana-3689	250	5	)	)	PUNCT
cana-3689	250	6	,	,	PUNCT
cana-3689	250	7	109	109	NUM
cana-3689	250	8	-	-	SYM
cana-3689	250	9	116	116	NUM
cana-3689	250	10	.	.	PUNCT
cana-3689	251	1	[	[	X
cana-3689	251	2	22	22	NUM
cana-3689	251	3	]	]	X
cana-3689	251	4	wang	wang	PROPN
cana-3689	251	5	,	,	PUNCT
cana-3689	251	6	z.	z.	PROPN
cana-3689	251	7	,	,	PUNCT
cana-3689	251	8	&	&	CCONJ
cana-3689	251	9	zhang	zhang	PROPN
cana-3689	251	10	,	,	PUNCT
cana-3689	251	11	t.	t.	PROPN
cana-3689	251	12	(	(	PUNCT
cana-3689	251	13	2017	2017	NUM
cana-3689	251	14	)	)	PUNCT
cana-3689	251	15	.	.	PUNCT
cana-3689	252	1	optimizing	optimize	VERB
cana-3689	252	2	neural	neural	ADJ
cana-3689	252	3	networks	network	NOUN
cana-3689	252	4	for	for	ADP
cana-3689	252	5	predicting	predict	VERB
cana-3689	252	6	cardio	cardio	NOUN
cana-3689	252	7	activity	activity	NOUN
cana-3689	252	8	types	type	NOUN
cana-3689	252	9	.	.	PUNCT
cana-3689	253	1	neural	neural	ADJ
cana-3689	253	2	computing	computing	NOUN
cana-3689	253	3	and	and	CCONJ
cana-3689	253	4	applications	application	NOUN
cana-3689	253	5	,	,	PUNCT
cana-3689	253	6	36(4	36(4	NUM
cana-3689	253	7	)	)	PUNCT
cana-3689	253	8	,	,	PUNCT
cana-3689	253	9	451–463	451–463	NUM
cana-3689	253	10	.	.	PUNCT