id	sid	tid	token	lemma	pos
cana-4579	1	1	machine	machine	NOUN
cana-4579	1	2	learning	learning	NOUN
cana-4579	1	3	using	use	VERB
cana-4579	1	4	recursive	recursive	ADJ
cana-4579	1	5	feature	feature	NOUN
cana-4579	1	6	elimination	elimination	NOUN
cana-4579	1	7	of	of	ADP
cana-4579	1	8	students	student	NOUN
cana-4579	1	9	’	’	PART
cana-4579	1	10	data	datum	NOUN
cana-4579	1	11	in	in	ADP
cana-4579	1	12	singapore	singapore	PROPN
cana-4579	1	13	during	during	ADP
cana-4579	1	14	pre	pre	ADJ
cana-4579	1	15	-	-	ADJ
cana-4579	1	16	covid	covid	ADJ
cana-4579	1	17	and	and	CCONJ
cana-4579	1	18	covid	covid	PROPN
cana-4579	1	19	communications	communication	NOUN
cana-4579	1	20	on	on	ADP
cana-4579	1	21	applied	apply	VERB
cana-4579	1	22	nonlinear	nonlinear	ADJ
cana-4579	1	23	analysis	analysis	NOUN
cana-4579	1	24	issn	issn	NOUN
cana-4579	1	25	:	:	PUNCT
cana-4579	1	26	1074	1074	NUM
cana-4579	1	27	-	-	PUNCT
cana-4579	1	28	133x	133x	NUM
cana-4579	1	29	vol	vol	NOUN
cana-4579	1	30	32	32	NUM
cana-4579	1	31	no	no	NOUN
cana-4579	1	32	.	.	PUNCT
cana-4579	2	1	9s	9s	NUM
cana-4579	2	2	(	(	PUNCT
cana-4579	2	3	2025	2025	NUM
cana-4579	2	4	)	)	PUNCT
cana-4579	2	5	2867	2867	NUM
cana-4579	2	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-4579	2	7	machine	machine	NOUN
cana-4579	2	8	learning	learn	VERB
cana-4579	2	9	using	use	VERB
cana-4579	2	10	recursive	recursive	ADJ
cana-4579	2	11	feature	feature	NOUN
cana-4579	2	12	elimination	elimination	NOUN
cana-4579	2	13	of	of	ADP
cana-4579	2	14	students	student	NOUN
cana-4579	2	15	’	’	PART
cana-4579	2	16	data	datum	NOUN
cana-4579	2	17	in	in	ADP
cana-4579	2	18	singapore	singapore	PROPN
cana-4579	2	19	during	during	ADP
cana-4579	2	20	pre	pre	ADJ
cana-4579	2	21	-	-	ADJ
cana-4579	2	22	covid	covid	ADJ
cana-4579	2	23	and	and	CCONJ
cana-4579	2	24	covid	covid	PROPN
cana-4579	2	25	1ts	1ts	PROPN
cana-4579	2	26	.	.	PUNCT
cana-4579	3	1	dr	dr	PROPN
cana-4579	3	2	.	.	PROPN
cana-4579	3	3	amna	amna	PROPN
cana-4579	3	4	saad	saad	PROPN
cana-4579	3	5	,	,	PUNCT
cana-4579	3	6	2prof	2prof	NUM
cana-4579	3	7	.	.	PUNCT
cana-4579	4	1	dr	dr	PROPN
cana-4579	4	2	.	.	PROPN
cana-4579	4	3	cordelia	cordelia	PROPN
cana-4579	4	4	mason	mason	PROPN
cana-4579	4	5	,	,	PUNCT
cana-4579	4	6	3fareed	3fareed	NUM
cana-4579	4	7	kaleem	kaleem	PROPN
cana-4579	4	8	khaiser	khaiser	PROPN
cana-4579	4	9	1malaysian	1malaysian	PROPN
cana-4579	4	10	institute	institute	PROPN
cana-4579	4	11	of	of	ADP
cana-4579	4	12	information	information	NOUN
cana-4579	4	13	technology	technology	NOUN
cana-4579	4	14	(	(	PUNCT
cana-4579	4	15	miit	miit	PROPN
cana-4579	4	16	)	)	PUNCT
cana-4579	4	17	,	,	PUNCT
cana-4579	4	18	universiti	universiti	PROPN
cana-4579	4	19	kuala	kuala	PROPN
cana-4579	4	20	lumpur	lumpur	PROPN
cana-4579	4	21	kuala	kuala	PROPN
cana-4579	4	22	lumpur	lumpur	PROPN
cana-4579	4	23	,	,	PUNCT
cana-4579	4	24	malaysia	malaysia	PROPN
cana-4579	4	25	,	,	PUNCT
cana-4579	4	26	amna@unikl.edu.my	amna@unikl.edu.my	NOUN
cana-4579	4	27	,	,	PUNCT
cana-4579	4	28	orcid	orcid	NOUN
cana-4579	4	29	i	i	NOUN
cana-4579	4	30	d	d	NOUN
cana-4579	4	31	:	:	PUNCT
cana-4579	4	32	0000	0000	NUM
cana-4579	4	33	-	-	PUNCT
cana-4579	4	34	0002	0002	NUM
cana-4579	4	35	-	-	PUNCT
cana-4579	4	36	8553	8553	NUM
cana-4579	4	37	-	-	SYM
cana-4579	4	38	4348	4348	NUM
cana-4579	4	39	2universiti	2universiti	NUM
cana-4579	4	40	kuala	kuala	PROPN
cana-4579	4	41	lumpur	lumpur	PROPN
cana-4579	4	42	business	business	PROPN
cana-4579	4	43	school	school	PROPN
cana-4579	4	44	,	,	PUNCT
cana-4579	4	45	universiti	universiti	PROPN
cana-4579	4	46	kuala	kuala	PROPN
cana-4579	4	47	lumpur	lumpur	PROPN
cana-4579	4	48	,	,	PUNCT
cana-4579	4	49	kuala	kuala	PROPN
cana-4579	4	50	lumpur	lumpur	PROPN
cana-4579	4	51	,	,	PUNCT
cana-4579	4	52	malaysia	malaysia	PROPN
cana-4579	4	53	cordelia@unikl.edu.my	cordelia@unikl.edu.my	NOUN
cana-4579	4	54	,	,	PUNCT
cana-4579	4	55	orcid	orcid	PROPN
cana-4579	4	56	i	i	NOUN
cana-4579	4	57	d	d	NOUN
cana-4579	4	58	:	:	PUNCT
cana-4579	4	59	0000	0000	NUM
cana-4579	4	60	-	-	PUNCT
cana-4579	4	61	0003	0003	NUM
cana-4579	4	62	-	-	PUNCT
cana-4579	4	63	0712	0712	NUM
cana-4579	4	64	-	-	PUNCT
cana-4579	4	65	0809	0809	NUM
cana-4579	4	66	3malaysian	3malaysian	NUM
cana-4579	4	67	institute	institute	NOUN
cana-4579	4	68	of	of	ADP
cana-4579	4	69	information	information	NOUN
cana-4579	4	70	technology	technology	NOUN
cana-4579	4	71	(	(	PUNCT
cana-4579	4	72	miit	miit	PROPN
cana-4579	4	73	)	)	PUNCT
cana-4579	4	74	,	,	PUNCT
cana-4579	4	75	universiti	universiti	PROPN
cana-4579	4	76	kuala	kuala	PROPN
cana-4579	4	77	lumpur	lumpur	PROPN
cana-4579	4	78	,	,	PUNCT
cana-4579	4	79	kuala	kuala	PROPN
cana-4579	4	80	lumpur	lumpur	PROPN
cana-4579	4	81	,	,	PUNCT
cana-4579	4	82	malaysia	malaysia	PROPN
cana-4579	4	83	,	,	PUNCT
cana-4579	4	84	fareed.kaleem@s.unikl.edu.my	fareed.kaleem@s.unikl.edu.my	NOUN
cana-4579	4	85	,	,	PUNCT
cana-4579	4	86	orcid	orcid	NOUN
cana-4579	4	87	i	i	NOUN
cana-4579	4	88	d	d	NOUN
cana-4579	4	89	:	:	PUNCT
cana-4579	4	90	0000	0000	NUM
cana-4579	4	91	-	-	PUNCT
cana-4579	4	92	0002	0002	NUM
cana-4579	4	93	-	-	PUNCT
cana-4579	4	94	1574	1574	NUM
cana-4579	4	95	-	-	PUNCT
cana-4579	4	96	0285	0285	NUM
cana-4579	4	97	article	article	NOUN
cana-4579	4	98	history	history	NOUN
cana-4579	4	99	:	:	PUNCT
cana-4579	4	100	received	receive	VERB
cana-4579	4	101	:	:	PUNCT
cana-4579	4	102	12	12	NUM
cana-4579	4	103	-	-	SYM
cana-4579	4	104	01	01	NUM
cana-4579	4	105	-	-	PUNCT
cana-4579	4	106	2025	2025	NUM
cana-4579	4	107	revised	revise	VERB
cana-4579	4	108	:	:	PUNCT
cana-4579	4	109	15	15	NUM
cana-4579	4	110	-	-	NUM
cana-4579	4	111	02	02	NUM
cana-4579	4	112	-	-	PUNCT
cana-4579	4	113	2025	2025	NUM
cana-4579	4	114	accepted	accept	VERB
cana-4579	4	115	:	:	PUNCT
cana-4579	4	116	01	01	NUM
cana-4579	4	117	-	-	SYM
cana-4579	4	118	03	03	NUM
cana-4579	4	119	-	-	PUNCT
cana-4579	4	120	2025	2025	NUM
cana-4579	4	121	abstract	abstract	NOUN
cana-4579	4	122	:	:	PUNCT
cana-4579	4	123	student	student	NOUN
cana-4579	4	124	career	career	NOUN
cana-4579	4	125	management	management	NOUN
cana-4579	4	126	is	be	AUX
cana-4579	4	127	a	a	DET
cana-4579	4	128	critical	critical	ADJ
cana-4579	4	129	activity	activity	NOUN
cana-4579	4	130	in	in	ADP
cana-4579	4	131	the	the	DET
cana-4579	4	132	education	education	NOUN
cana-4579	4	133	sector	sector	NOUN
cana-4579	4	134	.	.	PUNCT
cana-4579	5	1	machine	machine	NOUN
cana-4579	5	2	learning	learning	NOUN
cana-4579	5	3	method	method	NOUN
cana-4579	5	4	,	,	PUNCT
cana-4579	5	5	recursive	recursive	ADJ
cana-4579	5	6	feature	feature	NOUN
cana-4579	5	7	elimination	elimination	NOUN
cana-4579	5	8	(	(	PUNCT
cana-4579	5	9	rfe	rfe	NOUN
cana-4579	5	10	)	)	PUNCT
cana-4579	5	11	,	,	PUNCT
cana-4579	5	12	has	have	AUX
cana-4579	5	13	been	be	AUX
cana-4579	5	14	used	use	VERB
cana-4579	5	15	to	to	PART
cana-4579	5	16	find	find	VERB
cana-4579	5	17	key	key	ADJ
cana-4579	5	18	features	feature	NOUN
cana-4579	5	19	for	for	ADP
cana-4579	5	20	prediction	prediction	NOUN
cana-4579	5	21	tasks	task	NOUN
cana-4579	5	22	with	with	ADP
cana-4579	5	23	the	the	DET
cana-4579	5	24	help	help	NOUN
cana-4579	5	25	of	of	ADP
cana-4579	5	26	students	student	NOUN
cana-4579	5	27	’	'	PUNCT
cana-4579	5	28	data	datum	NOUN
cana-4579	5	29	.	.	PUNCT
cana-4579	6	1	using	use	VERB
cana-4579	6	2	rfe	rfe	NOUN
cana-4579	6	3	,	,	PUNCT
cana-4579	6	4	which	which	PRON
cana-4579	6	5	is	be	AUX
cana-4579	6	6	a	a	DET
cana-4579	6	7	machine	machine	NOUN
cana-4579	6	8	learning	learning	NOUN
cana-4579	6	9	technique	technique	NOUN
cana-4579	6	10	,	,	PUNCT
cana-4579	6	11	massive	massive	ADJ
cana-4579	6	12	datasets	dataset	NOUN
cana-4579	6	13	are	be	AUX
cana-4579	6	14	analyzed	analyze	VERB
cana-4579	6	15	,	,	PUNCT
cana-4579	6	16	and	and	CCONJ
cana-4579	6	17	the	the	DET
cana-4579	6	18	most	most	ADV
cana-4579	6	19	pertinent	pertinent	ADJ
cana-4579	6	20	features	feature	NOUN
cana-4579	6	21	are	be	AUX
cana-4579	6	22	chosen	choose	VERB
cana-4579	6	23	for	for	ADP
cana-4579	6	24	predictions	prediction	NOUN
cana-4579	6	25	,	,	PUNCT
cana-4579	6	26	increasing	increase	VERB
cana-4579	6	27	computing	compute	VERB
cana-4579	6	28	speed	speed	NOUN
cana-4579	6	29	and	and	CCONJ
cana-4579	6	30	accuracy	accuracy	NOUN
cana-4579	6	31	.	.	PUNCT
cana-4579	7	1	rfe	rfe	PROPN
cana-4579	7	2	has	have	AUX
cana-4579	7	3	been	be	AUX
cana-4579	7	4	combined	combine	VERB
cana-4579	7	5	with	with	ADP
cana-4579	7	6	several	several	ADJ
cana-4579	7	7	machine	machine	NOUN
cana-4579	7	8	learning	learn	VERB
cana-4579	7	9	techniques	technique	NOUN
cana-4579	7	10	for	for	ADP
cana-4579	7	11	feature	feature	NOUN
cana-4579	7	12	selection	selection	NOUN
cana-4579	7	13	,	,	PUNCT
cana-4579	7	14	such	such	ADJ
cana-4579	7	15	as	as	ADP
cana-4579	7	16	support	support	NOUN
cana-4579	7	17	vector	vector	NOUN
cana-4579	7	18	machines	machine	NOUN
cana-4579	7	19	(	(	PUNCT
cana-4579	7	20	svm	svm	PROPN
cana-4579	7	21	)	)	PUNCT
cana-4579	7	22	,	,	PUNCT
cana-4579	7	23	decision	decision	NOUN
cana-4579	7	24	trees	tree	NOUN
cana-4579	7	25	,	,	PUNCT
cana-4579	7	26	and	and	CCONJ
cana-4579	7	27	random	random	ADJ
cana-4579	7	28	forests	forest	NOUN
cana-4579	7	29	,	,	PUNCT
cana-4579	7	30	and	and	CCONJ
cana-4579	7	31	many	many	ADJ
cana-4579	7	32	more	more	ADJ
cana-4579	7	33	.	.	PUNCT
cana-4579	8	1	this	this	DET
cana-4579	8	2	study	study	NOUN
cana-4579	8	3	focuses	focus	VERB
cana-4579	8	4	on	on	ADP
cana-4579	8	5	comprehending	comprehending	ADJ
cana-4579	8	6	students	student	NOUN
cana-4579	8	7	’	’	PART
cana-4579	8	8	data	datum	NOUN
cana-4579	8	9	and	and	CCONJ
cana-4579	8	10	evaluates	evaluate	VERB
cana-4579	8	11	the	the	DET
cana-4579	8	12	effect	effect	NOUN
cana-4579	8	13	on	on	ADP
cana-4579	8	14	graduate	graduate	ADJ
cana-4579	8	15	employability	employability	NOUN
cana-4579	8	16	based	base	VERB
cana-4579	8	17	on	on	ADP
cana-4579	8	18	predictive	predictive	ADJ
cana-4579	8	19	power	power	NOUN
cana-4579	8	20	of	of	ADP
cana-4579	8	21	machine	machine	NOUN
cana-4579	8	22	learning	learn	VERB
cana-4579	8	23	algorithms	algorithm	NOUN
cana-4579	8	24	.	.	PUNCT
cana-4579	9	1	post	post	PROPN
cana-4579	9	2	covid	covid	PROPN
cana-4579	9	3	,	,	PUNCT
cana-4579	9	4	the	the	DET
cana-4579	9	5	data	datum	NOUN
cana-4579	9	6	imply	imply	VERB
cana-4579	9	7	that	that	SCONJ
cana-4579	9	8	the	the	DET
cana-4579	9	9	covid-19	covid-19	PROPN
cana-4579	9	10	epidemic	epidemic	NOUN
cana-4579	9	11	has	have	AUX
cana-4579	9	12	significantly	significantly	ADV
cana-4579	9	13	hampered	hamper	VERB
cana-4579	9	14	the	the	DET
cana-4579	9	15	graduate	graduate	ADJ
cana-4579	9	16	employment	employment	NOUN
cana-4579	9	17	for	for	ADP
cana-4579	9	18	governments	government	NOUN
cana-4579	9	19	,	,	PUNCT
cana-4579	9	20	corporations	corporation	NOUN
cana-4579	9	21	,	,	PUNCT
cana-4579	9	22	and	and	CCONJ
cana-4579	9	23	the	the	DET
cana-4579	9	24	people	people	NOUN
cana-4579	9	25	.	.	PUNCT
cana-4579	10	1	the	the	DET
cana-4579	10	2	study	study	NOUN
cana-4579	10	3	offers	offer	VERB
cana-4579	10	4	potential	potential	ADJ
cana-4579	10	5	answers	answer	NOUN
cana-4579	10	6	in	in	ADP
cana-4579	10	7	analyzing	analyze	VERB
cana-4579	10	8	the	the	DET
cana-4579	10	9	independent	independent	ADJ
cana-4579	10	10	variables	variable	NOUN
cana-4579	10	11	that	that	PRON
cana-4579	10	12	affect	affect	VERB
cana-4579	10	13	the	the	DET
cana-4579	10	14	employability	employability	NOUN
cana-4579	10	15	aspects	aspect	NOUN
cana-4579	10	16	using	use	VERB
cana-4579	10	17	machine	machine	NOUN
cana-4579	10	18	learning	learn	VERB
cana-4579	10	19	algorithm	algorithm	NOUN
cana-4579	10	20	's	's	PART
cana-4579	10	21	performances	performance	NOUN
cana-4579	10	22	in	in	ADP
cana-4579	10	23	dealing	deal	VERB
cana-4579	10	24	with	with	ADP
cana-4579	10	25	pre	pre	ADJ
cana-4579	10	26	-	-	ADJ
cana-4579	10	27	covid	covid	ADJ
cana-4579	10	28	and	and	CCONJ
cana-4579	10	29	covid	covid	PROPN
cana-4579	10	30	datasets	dataset	NOUN
cana-4579	10	31	.	.	PUNCT
cana-4579	11	1	keywords	keyword	NOUN
cana-4579	11	2	:	:	PUNCT
cana-4579	11	3	recursive	recursive	ADJ
cana-4579	11	4	feature	feature	NOUN
cana-4579	11	5	elimination	elimination	NOUN
cana-4579	11	6	,	,	PUNCT
cana-4579	11	7	undergraduates	undergraduate	VERB
cana-4579	11	8	’	'	PUNCT
cana-4579	11	9	employability	employability	NOUN
cana-4579	11	10	,	,	PUNCT
cana-4579	11	11	machine	machine	NOUN
cana-4579	11	12	learning	learning	NOUN
cana-4579	11	13	,	,	PUNCT
cana-4579	11	14	model	model	NOUN
cana-4579	11	15	performance	performance	NOUN
cana-4579	11	16	,	,	PUNCT
cana-4579	11	17	classification	classification	NOUN
cana-4579	11	18	,	,	PUNCT
cana-4579	11	19	work	work	NOUN
cana-4579	11	20	placements	placement	NOUN
cana-4579	11	21	,	,	PUNCT
cana-4579	11	22	predictive	predictive	ADJ
cana-4579	11	23	analytics	analytic	NOUN
cana-4579	11	24	.	.	PUNCT
cana-4579	12	1	i.	i.	PROPN
cana-4579	12	2	introduction	introduction	NOUN
cana-4579	12	3	to	to	PART
cana-4579	12	4	get	get	VERB
cana-4579	12	5	the	the	DET
cana-4579	12	6	greatest	great	ADJ
cana-4579	12	7	outcomes	outcome	NOUN
cana-4579	12	8	in	in	ADP
cana-4579	12	9	a	a	DET
cana-4579	12	10	given	give	VERB
cana-4579	12	11	machine	machine	NOUN
cana-4579	12	12	learning	learning	NOUN
cana-4579	12	13	assignment	assignment	NOUN
cana-4579	12	14	,	,	PUNCT
cana-4579	12	15	choosing	choose	VERB
cana-4579	12	16	the	the	DET
cana-4579	12	17	ideal	ideal	ADJ
cana-4579	12	18	subset	subset	NOUN
cana-4579	12	19	of	of	ADP
cana-4579	12	20	features	feature	NOUN
cana-4579	12	21	from	from	ADP
cana-4579	12	22	a	a	DET
cana-4579	12	23	raw	raw	ADJ
cana-4579	12	24	dataset	dataset	NOUN
cana-4579	12	25	becomes	become	VERB
cana-4579	12	26	more	more	ADV
cana-4579	12	27	and	and	CCONJ
cana-4579	12	28	more	more	ADV
cana-4579	12	29	important	important	ADJ
cana-4579	12	30	as	as	SCONJ
cana-4579	12	31	dataset	dataset	ADJ
cana-4579	12	32	sizes	size	NOUN
cana-4579	12	33	increase	increase	VERB
cana-4579	12	34	(	(	PUNCT
cana-4579	12	35	jeon	jeon	PROPN
cana-4579	12	36	&	&	CCONJ
cana-4579	12	37	oh	oh	INTJ
cana-4579	12	38	,	,	PUNCT
cana-4579	12	39	2020	2020	NUM
cana-4579	12	40	)	)	PUNCT
cana-4579	12	41	.	.	PUNCT
cana-4579	13	1	one	one	NUM
cana-4579	13	2	common	common	ADJ
cana-4579	13	3	method	method	NOUN
cana-4579	13	4	for	for	ADP
cana-4579	13	5	feature	feature	NOUN
cana-4579	13	6	selection	selection	NOUN
cana-4579	13	7	is	be	AUX
cana-4579	13	8	recursive	recursive	ADJ
cana-4579	13	9	feature	feature	NOUN
cana-4579	13	10	removal	removal	NOUN
cana-4579	13	11	.	.	PUNCT
cana-4579	14	1	rfe	rfe	PROPN
cana-4579	14	2	's	's	PART
cana-4579	14	3	popularity	popularity	NOUN
cana-4579	14	4	can	can	AUX
cana-4579	14	5	be	be	AUX
cana-4579	14	6	attributed	attribute	VERB
cana-4579	14	7	to	to	ADP
cana-4579	14	8	its	its	PRON
cana-4579	14	9	simplicity	simplicity	NOUN
cana-4579	14	10	of	of	ADP
cana-4579	14	11	setup	setup	NOUN
cana-4579	14	12	and	and	CCONJ
cana-4579	14	13	operation	operation	NOUN
cana-4579	14	14	,	,	PUNCT
cana-4579	14	15	as	as	ADV
cana-4579	14	16	well	well	ADV
cana-4579	14	17	as	as	ADP
cana-4579	14	18	its	its	PRON
cana-4579	14	19	ability	ability	NOUN
cana-4579	14	20	to	to	PART
cana-4579	14	21	identify	identify	VERB
cana-4579	14	22	the	the	DET
cana-4579	14	23	features	feature	NOUN
cana-4579	14	24	(	(	PUNCT
cana-4579	14	25	columns	column	NOUN
cana-4579	14	26	)	)	PUNCT
cana-4579	14	27	in	in	ADP
cana-4579	14	28	a	a	DET
cana-4579	14	29	training	training	NOUN
cana-4579	14	30	dataset	dataset	NOUN
cana-4579	14	31	that	that	PRON
cana-4579	14	32	have	have	VERB
cana-4579	14	33	a	a	DET
cana-4579	14	34	higher	high	ADJ
cana-4579	14	35	probability	probability	NOUN
cana-4579	14	36	of	of	ADP
cana-4579	14	37	being	be	AUX
cana-4579	14	38	effective	effective	ADJ
cana-4579	14	39	in	in	ADP
cana-4579	14	40	accurately	accurately	ADV
cana-4579	14	41	predicting	predict	VERB
cana-4579	14	42	the	the	DET
cana-4579	14	43	target	target	NOUN
cana-4579	14	44	variable	variable	NOUN
cana-4579	14	45	(	(	PUNCT
cana-4579	14	46	brownlee	brownlee	PROPN
cana-4579	14	47	,	,	PUNCT
cana-4579	14	48	j.	j.	PROPN
cana-4579	14	49	,	,	PUNCT
cana-4579	14	50	2020	2020	NUM
cana-4579	14	51	)	)	PUNCT
cana-4579	14	52	.	.	PUNCT
cana-4579	15	1	the	the	DET
cana-4579	15	2	amount	amount	NOUN
cana-4579	15	3	of	of	ADP
cana-4579	15	4	features	feature	NOUN
cana-4579	15	5	to	to	PART
cana-4579	15	6	select	select	VERB
cana-4579	15	7	and	and	CCONJ
cana-4579	15	8	the	the	DET
cana-4579	15	9	algorithm	algorithm	NOUN
cana-4579	15	10	to	to	PART
cana-4579	15	11	help	help	VERB
cana-4579	15	12	with	with	ADP
cana-4579	15	13	feature	feature	NOUN
cana-4579	15	14	selection	selection	NOUN
cana-4579	15	15	are	be	AUX
cana-4579	15	16	two	two	NUM
cana-4579	15	17	important	important	ADJ
cana-4579	15	18	setup	setup	NOUN
cana-4579	15	19	decisions	decision	NOUN
cana-4579	15	20	while	while	SCONJ
cana-4579	15	21	using	use	VERB
cana-4579	15	22	rfe	rfe	NOUN
cana-4579	15	23	.	.	PUNCT
cana-4579	16	1	it	it	PRON
cana-4579	16	2	is	be	AUX
cana-4579	16	3	feasible	feasible	ADJ
cana-4579	16	4	to	to	PART
cana-4579	16	5	look	look	VERB
cana-4579	16	6	into	into	ADP
cana-4579	16	7	both	both	PRON
cana-4579	16	8	of	of	ADP
cana-4579	16	9	these	these	DET
cana-4579	16	10	hyper	hyper	ADJ
cana-4579	16	11	parameter	parameter	NOUN
cana-4579	16	12	configurations	configuration	NOUN
cana-4579	16	13	,	,	PUNCT
cana-4579	16	14	even	even	ADV
cana-4579	16	15	though	though	SCONJ
cana-4579	16	16	they	they	PRON
cana-4579	16	17	do	do	AUX
cana-4579	16	18	not	not	PART
cana-4579	16	19	significantly	significantly	ADV
cana-4579	16	20	affect	affect	VERB
cana-4579	16	21	the	the	DET
cana-4579	16	22	approach	approach	NOUN
cana-4579	16	23	's	's	PART
cana-4579	16	24	efficacy	efficacy	NOUN
cana-4579	16	25	(	(	PUNCT
cana-4579	16	26	brownlee	brownlee	PROPN
cana-4579	16	27	,	,	PUNCT
cana-4579	16	28	2020	2020	NUM
cana-4579	16	29	)	)	PUNCT
cana-4579	16	30	.	.	PUNCT
cana-4579	17	1	a	a	DET
cana-4579	17	2	restricted	restricted	ADJ
cana-4579	17	3	and	and	CCONJ
cana-4579	17	4	efficient	efficient	ADJ
cana-4579	17	5	feature	feature	NOUN
cana-4579	17	6	(	(	PUNCT
cana-4579	17	7	variable	variable	ADJ
cana-4579	17	8	)	)	PUNCT
cana-4579	17	9	selection	selection	NOUN
cana-4579	17	10	process	process	NOUN
cana-4579	17	11	is	be	AUX
cana-4579	17	12	necessary	necessary	ADJ
cana-4579	17	13	for	for	ADP
cana-4579	17	14	the	the	DET
cana-4579	17	15	development	development	NOUN
cana-4579	17	16	of	of	ADP
cana-4579	17	17	a	a	DET
cana-4579	17	18	classification	classification	NOUN
cana-4579	17	19	model	model	NOUN
cana-4579	17	20	.	.	PUNCT
cana-4579	18	1	overfitting	overfitte	VERB
cana-4579	18	2	problems	problem	NOUN
cana-4579	18	3	are	be	AUX
cana-4579	18	4	frequently	frequently	ADV
cana-4579	18	5	caused	cause	VERB
cana-4579	18	6	by	by	ADP
cana-4579	18	7	high	high	ADJ
cana-4579	18	8	-	-	PUNCT
cana-4579	18	9	dimensional	dimensional	ADJ
cana-4579	18	10	datasets	dataset	NOUN
cana-4579	18	11	,	,	PUNCT
cana-4579	18	12	which	which	PRON
cana-4579	18	13	mailto:amna@unikl.edu.my	mailto:amna@unikl.edu.my	ADJ
cana-4579	18	14	mailto:cordelia@unikl.edu.my	mailto:cordelia@unikl.edu.my	NOUN
cana-4579	18	15	mailto:fareed.kaleem@s.unikl.edu.my	mailto:fareed.kaleem@s.unikl.edu.my	NOUN
cana-4579	18	16	communications	communication	NOUN
cana-4579	18	17	on	on	ADP
cana-4579	18	18	applied	apply	VERB
cana-4579	18	19	nonlinear	nonlinear	ADJ
cana-4579	18	20	analysis	analysis	NOUN
cana-4579	18	21	issn	issn	NOUN
cana-4579	18	22	:	:	PUNCT
cana-4579	18	23	1074	1074	NUM
cana-4579	18	24	-	-	PUNCT
cana-4579	18	25	133x	133x	NUM
cana-4579	18	26	vol	vol	NOUN
cana-4579	18	27	32	32	NUM
cana-4579	18	28	no	no	NOUN
cana-4579	18	29	.	.	PUNCT
cana-4579	19	1	9s	9s	NUM
cana-4579	19	2	(	(	PUNCT
cana-4579	19	3	2025	2025	NUM
cana-4579	19	4	)	)	PUNCT
cana-4579	19	5	2868	2868	NUM
cana-4579	20	1	https://internationalpubls.com	https://internationalpubls.com	X
cana-4579	20	2	hinders	hinder	VERB
cana-4579	20	3	the	the	DET
cana-4579	20	4	creation	creation	NOUN
cana-4579	20	5	of	of	ADP
cana-4579	20	6	reliable	reliable	ADJ
cana-4579	20	7	models	model	NOUN
cana-4579	20	8	.	.	PUNCT
cana-4579	21	1	moreover	moreover	ADV
cana-4579	21	2	,	,	PUNCT
cana-4579	21	3	these	these	DET
cana-4579	21	4	datasets	dataset	NOUN
cana-4579	21	5	often	often	ADV
cana-4579	21	6	produce	produce	VERB
cana-4579	21	7	models	model	NOUN
cana-4579	21	8	with	with	ADP
cana-4579	21	9	low	low	ADJ
cana-4579	21	10	classification	classification	NOUN
cana-4579	21	11	accuracy	accuracy	NOUN
cana-4579	21	12	and	and	CCONJ
cana-4579	21	13	need	need	VERB
cana-4579	21	14	a	a	DET
cana-4579	21	15	significant	significant	ADJ
cana-4579	21	16	amount	amount	NOUN
cana-4579	21	17	of	of	ADP
cana-4579	21	18	processing	processing	NOUN
cana-4579	21	19	power	power	NOUN
cana-4579	21	20	and	and	CCONJ
cana-4579	21	21	storage	storage	NOUN
cana-4579	21	22	capacity	capacity	NOUN
cana-4579	21	23	.	.	PUNCT
cana-4579	22	1	this	this	PRON
cana-4579	22	2	was	be	AUX
cana-4579	22	3	referred	refer	VERB
cana-4579	22	4	regarded	regard	VERB
cana-4579	22	5	as	as	ADP
cana-4579	22	6	the	the	DET
cana-4579	22	7	"	"	PUNCT
cana-4579	22	8	curse	curse	NOUN
cana-4579	22	9	of	of	ADP
cana-4579	22	10	dimensionality	dimensionality	NOUN
cana-4579	22	11	"	"	PUNCT
cana-4579	22	12	.	.	PUNCT
cana-4579	23	1	to	to	PART
cana-4579	23	2	tackle	tackle	VERB
cana-4579	23	3	these	these	DET
cana-4579	23	4	issues	issue	NOUN
cana-4579	23	5	,	,	PUNCT
cana-4579	23	6	a	a	DET
cana-4579	23	7	representative	representative	NOUN
cana-4579	23	8	subset	subset	NOUN
cana-4579	23	9	of	of	ADP
cana-4579	23	10	features	feature	NOUN
cana-4579	23	11	must	must	AUX
cana-4579	23	12	be	be	AUX
cana-4579	23	13	selected	select	VERB
cana-4579	23	14	(	(	PUNCT
cana-4579	23	15	jeon	jeon	PROPN
cana-4579	23	16	&	&	CCONJ
cana-4579	23	17	oh	oh	INTJ
cana-4579	23	18	,	,	PUNCT
cana-4579	23	19	2020	2020	NUM
cana-4579	23	20	)	)	PUNCT
cana-4579	23	21	.	.	PUNCT
cana-4579	24	1	feature	feature	NOUN
cana-4579	24	2	selection	selection	NOUN
cana-4579	24	3	is	be	AUX
cana-4579	24	4	used	use	VERB
cana-4579	24	5	in	in	ADP
cana-4579	24	6	many	many	ADJ
cana-4579	24	7	areas	area	NOUN
cana-4579	24	8	to	to	PART
cana-4579	24	9	choose	choose	VERB
cana-4579	24	10	the	the	DET
cana-4579	24	11	best	good	ADJ
cana-4579	24	12	subset	subset	NOUN
cana-4579	24	13	of	of	ADP
cana-4579	24	14	features	feature	NOUN
cana-4579	24	15	,	,	PUNCT
cana-4579	24	16	including	include	VERB
cana-4579	24	17	image	image	NOUN
cana-4579	24	18	processing	processing	NOUN
cana-4579	24	19	,	,	PUNCT
cana-4579	24	20	biology	biology	NOUN
cana-4579	24	21	,	,	PUNCT
cana-4579	24	22	health	health	NOUN
cana-4579	24	23	,	,	PUNCT
cana-4579	24	24	finance	finance	NOUN
cana-4579	24	25	,	,	PUNCT
cana-4579	24	26	manufacturing	manufacturing	NOUN
cana-4579	24	27	,	,	PUNCT
cana-4579	24	28	and	and	CCONJ
cana-4579	24	29	production	production	NOUN
cana-4579	24	30	.	.	PUNCT
cana-4579	25	1	a	a	DET
cana-4579	25	2	feature	feature	NOUN
cana-4579	25	3	selection	selection	NOUN
cana-4579	25	4	method	method	NOUN
cana-4579	25	5	called	call	VERB
cana-4579	25	6	recursive	recursive	ADJ
cana-4579	25	7	feature	feature	NOUN
cana-4579	25	8	elimination	elimination	NOUN
cana-4579	25	9	(	(	PUNCT
cana-4579	25	10	rfe	rfe	PROPN
cana-4579	25	11	)	)	PUNCT
cana-4579	25	12	chooses	choose	VERB
cana-4579	25	13	the	the	DET
cana-4579	25	14	optimal	optimal	ADJ
cana-4579	25	15	feature	feature	NOUN
cana-4579	25	16	subset	subset	VERB
cana-4579	25	17	by	by	ADP
cana-4579	25	18	considering	consider	VERB
cana-4579	25	19	the	the	DET
cana-4579	25	20	learning	learning	NOUN
cana-4579	25	21	model	model	NOUN
cana-4579	25	22	and	and	CCONJ
cana-4579	25	23	classification	classification	NOUN
cana-4579	25	24	accuracy	accuracy	NOUN
cana-4579	25	25	.	.	PUNCT
cana-4579	26	1	the	the	DET
cana-4579	26	2	weakest	weak	ADJ
cana-4579	26	3	feature	feature	NOUN
cana-4579	26	4	that	that	PRON
cana-4579	26	5	reduces	reduce	VERB
cana-4579	26	6	"	"	PUNCT
cana-4579	26	7	classification	classification	NOUN
cana-4579	26	8	accuracy	accuracy	NOUN
cana-4579	26	9	"	"	PUNCT
cana-4579	26	10	is	be	AUX
cana-4579	26	11	systematically	systematically	ADV
cana-4579	26	12	removed	remove	VERB
cana-4579	26	13	once	once	ADV
cana-4579	26	14	a	a	DET
cana-4579	26	15	classification	classification	NOUN
cana-4579	26	16	model	model	NOUN
cana-4579	26	17	has	have	AUX
cana-4579	26	18	been	be	AUX
cana-4579	26	19	developed	develop	VERB
cana-4579	26	20	using	use	VERB
cana-4579	26	21	conventional	conventional	ADJ
cana-4579	26	22	rfe	rfe	NOUN
cana-4579	26	23	.	.	PUNCT
cana-4579	27	1	recently	recently	ADV
cana-4579	27	2	,	,	PUNCT
cana-4579	27	3	a	a	DET
cana-4579	27	4	unique	unique	ADJ
cana-4579	27	5	rfe	rfe	NOUN
cana-4579	27	6	approach	approach	NOUN
cana-4579	27	7	was	be	AUX
cana-4579	27	8	proposed	propose	VERB
cana-4579	27	9	that	that	SCONJ
cana-4579	27	10	picks	pick	VERB
cana-4579	27	11	the	the	DET
cana-4579	27	12	least	least	ADV
cana-4579	27	13	significant	significant	ADJ
cana-4579	27	14	features	feature	NOUN
cana-4579	27	15	for	for	ADP
cana-4579	27	16	deletion	deletion	NOUN
cana-4579	27	17	by	by	ADP
cana-4579	27	18	evaluating	evaluate	VERB
cana-4579	27	19	"	"	PUNCT
cana-4579	27	20	feature	feature	NOUN
cana-4579	27	21	(	(	PUNCT
cana-4579	27	22	variable	variable	ADJ
cana-4579	27	23	)	)	PUNCT
cana-4579	27	24	relevance	relevance	NOUN
cana-4579	27	25	"	"	PUNCT
cana-4579	27	26	using	use	VERB
cana-4579	27	27	a	a	DET
cana-4579	27	28	support	support	NOUN
cana-4579	27	29	vector	vector	NOUN
cana-4579	27	30	machine	machine	NOUN
cana-4579	27	31	(	(	PUNCT
cana-4579	27	32	svm	svm	PROPN
cana-4579	27	33	)	)	PUNCT
cana-4579	27	34	model	model	NOUN
cana-4579	27	35	instead	instead	ADV
cana-4579	27	36	of	of	ADP
cana-4579	27	37	"	"	PUNCT
cana-4579	27	38	classification	classification	NOUN
cana-4579	27	39	accuracy	accuracy	NOUN
cana-4579	27	40	"	"	PUNCT
cana-4579	27	41	.	.	PUNCT
cana-4579	28	1	other	other	ADJ
cana-4579	28	2	classification	classification	NOUN
cana-4579	28	3	models	model	NOUN
cana-4579	28	4	with	with	ADP
cana-4579	28	5	integrated	integrate	VERB
cana-4579	28	6	feature	feature	NOUN
cana-4579	28	7	assessment	assessment	NOUN
cana-4579	28	8	processes	process	NOUN
cana-4579	28	9	,	,	PUNCT
cana-4579	28	10	including	include	VERB
cana-4579	28	11	random	random	ADJ
cana-4579	28	12	forests	forest	NOUN
cana-4579	28	13	(	(	PUNCT
cana-4579	28	14	rfs	rfs	PROPN
cana-4579	28	15	)	)	PUNCT
cana-4579	28	16	and	and	CCONJ
cana-4579	28	17	gradient	gradient	ADJ
cana-4579	28	18	boosting	boost	VERB
cana-4579	28	19	machines	machine	NOUN
cana-4579	28	20	(	(	PUNCT
cana-4579	28	21	gbms	gbms	NOUN
cana-4579	28	22	)	)	PUNCT
cana-4579	28	23	,	,	PUNCT
cana-4579	28	24	can	can	AUX
cana-4579	28	25	also	also	ADV
cana-4579	28	26	be	be	AUX
cana-4579	28	27	applied	apply	VERB
cana-4579	28	28	using	use	VERB
cana-4579	28	29	this	this	DET
cana-4579	28	30	method	method	NOUN
cana-4579	28	31	(	(	PUNCT
cana-4579	28	32	jeon	jeon	PROPN
cana-4579	28	33	&	&	CCONJ
cana-4579	28	34	oh	oh	INTJ
cana-4579	28	35	,	,	PUNCT
cana-4579	28	36	2020	2020	NUM
cana-4579	28	37	)	)	PUNCT
cana-4579	28	38	.	.	PUNCT
cana-4579	29	1	a	a	DET
cana-4579	29	2	training	training	NOUN
cana-4579	29	3	dataset	dataset	NOUN
cana-4579	29	4	can	can	AUX
cana-4579	29	5	be	be	AUX
cana-4579	29	6	used	use	VERB
cana-4579	29	7	to	to	PART
cana-4579	29	8	teach	teach	VERB
cana-4579	29	9	a	a	DET
cana-4579	29	10	classifier	classifier	NOUN
cana-4579	29	11	the	the	DET
cana-4579	29	12	feature	feature	NOUN
cana-4579	29	13	weights	weight	NOUN
cana-4579	29	14	,	,	PUNCT
cana-4579	29	15	or	or	CCONJ
cana-4579	29	16	the	the	DET
cana-4579	29	17	relative	relative	ADJ
cana-4579	29	18	relevance	relevance	NOUN
cana-4579	29	19	of	of	ADP
cana-4579	29	20	each	each	DET
cana-4579	29	21	feature	feature	NOUN
cana-4579	29	22	.	.	PUNCT
cana-4579	30	1	following	follow	VERB
cana-4579	30	2	the	the	DET
cana-4579	30	3	weighted	weighted	ADJ
cana-4579	30	4	ranking	ranking	NOUN
cana-4579	30	5	of	of	ADP
cana-4579	30	6	each	each	DET
cana-4579	30	7	feature	feature	NOUN
cana-4579	30	8	,	,	PUNCT
cana-4579	30	9	the	the	DET
cana-4579	30	10	feature	feature	NOUN
cana-4579	30	11	with	with	ADP
cana-4579	30	12	the	the	DET
cana-4579	30	13	lowest	low	ADJ
cana-4579	30	14	weight	weight	NOUN
cana-4579	30	15	value	value	NOUN
cana-4579	30	16	was	be	AUX
cana-4579	30	17	eliminated	eliminate	VERB
cana-4579	30	18	.	.	PUNCT
cana-4579	31	1	the	the	DET
cana-4579	31	2	classifier	classifier	NOUN
cana-4579	31	3	was	be	AUX
cana-4579	31	4	then	then	ADV
cana-4579	31	5	retrained	retrain	VERB
cana-4579	31	6	using	use	VERB
cana-4579	31	7	the	the	DET
cana-4579	31	8	leftover	leftover	NOUN
cana-4579	31	9	data	datum	NOUN
cana-4579	31	10	until	until	SCONJ
cana-4579	31	11	its	its	PRON
cana-4579	31	12	feature	feature	NOUN
cana-4579	31	13	set	set	NOUN
cana-4579	31	14	ran	run	VERB
cana-4579	31	15	out	out	ADP
cana-4579	31	16	.	.	PUNCT
cana-4579	32	1	ultimately	ultimately	ADV
cana-4579	32	2	,	,	PUNCT
cana-4579	32	3	all	all	DET
cana-4579	32	4	features	feature	NOUN
cana-4579	32	5	can	can	AUX
cana-4579	32	6	be	be	AUX
cana-4579	32	7	rated	rate	VERB
cana-4579	32	8	using	use	VERB
cana-4579	32	9	the	the	DET
cana-4579	32	10	feature	feature	NOUN
cana-4579	32	11	-	-	PUNCT
cana-4579	32	12	importance	importance	NOUN
cana-4579	32	13	-	-	PUNCT
cana-4579	32	14	based	base	VERB
cana-4579	32	15	rfe	rfe	NOUN
cana-4579	32	16	technique	technique	NOUN
cana-4579	32	17	.	.	PUNCT
cana-4579	33	1	it	it	PRON
cana-4579	33	2	has	have	AUX
cana-4579	33	3	been	be	AUX
cana-4579	33	4	demonstrated	demonstrate	VERB
cana-4579	33	5	that	that	SCONJ
cana-4579	33	6	by	by	ADP
cana-4579	33	7	mitigating	mitigate	VERB
cana-4579	33	8	the	the	DET
cana-4579	33	9	shortcomings	shortcoming	NOUN
cana-4579	33	10	of	of	ADP
cana-4579	33	11	filter	filter	NOUN
cana-4579	33	12	and	and	CCONJ
cana-4579	33	13	wrapper	wrapper	NOUN
cana-4579	33	14	approaches	approach	NOUN
cana-4579	33	15	,	,	PUNCT
cana-4579	33	16	this	this	DET
cana-4579	33	17	embedded	embed	VERB
cana-4579	33	18	feature	feature	NOUN
cana-4579	33	19	selection	selection	NOUN
cana-4579	33	20	method	method	NOUN
cana-4579	33	21	performs	perform	VERB
cana-4579	33	22	better	well	ADV
cana-4579	33	23	(	(	PUNCT
cana-4579	33	24	jeon	jeon	PROPN
cana-4579	33	25	&	&	CCONJ
cana-4579	33	26	oh	oh	INTJ
cana-4579	33	27	,	,	PUNCT
cana-4579	33	28	2020	2020	NUM
cana-4579	33	29	)	)	PUNCT
cana-4579	33	30	.	.	PUNCT
cana-4579	34	1	in	in	ADP
cana-4579	34	2	order	order	NOUN
cana-4579	34	3	to	to	PART
cana-4579	34	4	evaluate	evaluate	VERB
cana-4579	34	5	the	the	DET
cana-4579	34	6	effectiveness	effectiveness	NOUN
cana-4579	34	7	of	of	ADP
cana-4579	34	8	the	the	DET
cana-4579	34	9	algorithms	algorithm	NOUN
cana-4579	34	10	,	,	PUNCT
cana-4579	34	11	we	we	PRON
cana-4579	34	12	have	have	AUX
cana-4579	34	13	carefully	carefully	ADV
cana-4579	34	14	chosen	choose	VERB
cana-4579	34	15	the	the	DET
cana-4579	34	16	most	most	ADV
cana-4579	34	17	crucial	crucial	ADJ
cana-4579	34	18	features	feature	NOUN
cana-4579	34	19	required	require	VERB
cana-4579	34	20	for	for	ADP
cana-4579	34	21	predictive	predictive	ADJ
cana-4579	34	22	analytics	analytic	NOUN
cana-4579	34	23	,	,	PUNCT
cana-4579	34	24	in	in	ADP
cana-4579	34	25	this	this	DET
cana-4579	34	26	study	study	NOUN
cana-4579	34	27	.	.	PUNCT
cana-4579	35	1	ii	ii	PROPN
cana-4579	35	2	.	.	PUNCT
cana-4579	36	1	literature	literature	NOUN
cana-4579	36	2	employability	employability	NOUN
cana-4579	36	3	of	of	ADP
cana-4579	36	4	graduates	graduate	NOUN
cana-4579	36	5	has	have	AUX
cana-4579	36	6	been	be	AUX
cana-4579	36	7	predicted	predict	VERB
cana-4579	36	8	and	and	CCONJ
cana-4579	36	9	prescribed	prescribe	VERB
cana-4579	36	10	using	use	VERB
cana-4579	36	11	data	data	NOUN
cana-4579	36	12	-	-	PUNCT
cana-4579	36	13	mining	mining	NOUN
cana-4579	36	14	algorithms	algorithm	NOUN
cana-4579	36	15	(	(	PUNCT
cana-4579	36	16	héritier	héritier	X
cana-4579	36	17	et	et	PROPN
cana-4579	36	18	al	al	PROPN
cana-4579	36	19	.	.	PROPN
cana-4579	36	20	,	,	PUNCT
cana-4579	36	21	2023	2023	NUM
cana-4579	36	22	)	)	PUNCT
cana-4579	36	23	.	.	PUNCT
cana-4579	37	1	nevertheless	nevertheless	ADV
cana-4579	37	2	,	,	PUNCT
cana-4579	37	3	the	the	DET
cana-4579	37	4	studied	study	VERB
cana-4579	37	5	literature	literature	NOUN
cana-4579	37	6	does	do	AUX
cana-4579	37	7	not	not	PART
cana-4579	37	8	specifically	specifically	ADV
cana-4579	37	9	address	address	VERB
cana-4579	37	10	recursive	recursive	ADJ
cana-4579	37	11	feature	feature	NOUN
cana-4579	37	12	elimination	elimination	NOUN
cana-4579	37	13	(	(	PUNCT
cana-4579	37	14	rfe	rfe	NOUN
cana-4579	37	15	)	)	PUNCT
cana-4579	37	16	.	.	PUNCT
cana-4579	38	1	researchers	researcher	NOUN
cana-4579	38	2	aam	aam	VERB
cana-4579	38	3	et	et	PROPN
cana-4579	38	4	al	al	PROPN
cana-4579	38	5	.	.	PROPN
cana-4579	38	6	(	(	PUNCT
cana-4579	38	7	2022	2022	NUM
cana-4579	38	8	)	)	PUNCT
cana-4579	38	9	,	,	PUNCT
cana-4579	38	10	renato	renato	PROPN
cana-4579	38	11	et	et	PROPN
cana-4579	38	12	al	al	PROPN
cana-4579	38	13	.	.	PROPN
cana-4579	38	14	(	(	PUNCT
cana-4579	38	15	2022	2022	NUM
cana-4579	38	16	)	)	PUNCT
cana-4579	38	17	,	,	PUNCT
cana-4579	38	18	and	and	CCONJ
cana-4579	38	19	norfarahzatul	norfarahzatul	NOUN
cana-4579	38	20	et	et	PROPN
cana-4579	38	21	al	al	PROPN
cana-4579	38	22	.	.	PROPN
cana-4579	38	23	(	(	PUNCT
cana-4579	38	24	2022	2022	NUM
cana-4579	38	25	)	)	PUNCT
cana-4579	38	26	employed	employ	VERB
cana-4579	38	27	a	a	DET
cana-4579	38	28	range	range	NOUN
cana-4579	38	29	of	of	ADP
cana-4579	38	30	data	datum	NOUN
cana-4579	38	31	mining	mining	NOUN
cana-4579	38	32	techniques	technique	NOUN
cana-4579	38	33	,	,	PUNCT
cana-4579	38	34	such	such	ADJ
cana-4579	38	35	as	as	ADP
cana-4579	38	36	ensemble	ensemble	ADJ
cana-4579	38	37	models	model	NOUN
cana-4579	38	38	,	,	PUNCT
cana-4579	38	39	machine	machine	NOUN
cana-4579	38	40	learning	learning	NOUN
cana-4579	38	41	algorithms	algorithm	NOUN
cana-4579	38	42	,	,	PUNCT
cana-4579	38	43	and	and	CCONJ
cana-4579	38	44	classification	classification	NOUN
cana-4579	38	45	algorithms	algorithm	NOUN
cana-4579	38	46	like	like	ADP
cana-4579	38	47	random	random	ADJ
cana-4579	38	48	forest	forest	NOUN
cana-4579	38	49	,	,	PUNCT
cana-4579	38	50	neural	neural	ADJ
cana-4579	38	51	networks	network	NOUN
cana-4579	38	52	,	,	PUNCT
cana-4579	38	53	decision	decision	NOUN
cana-4579	38	54	trees	tree	NOUN
cana-4579	38	55	,	,	PUNCT
cana-4579	38	56	logistic	logistic	ADJ
cana-4579	38	57	regression	regression	NOUN
cana-4579	38	58	,	,	PUNCT
cana-4579	38	59	support	support	VERB
cana-4579	38	60	vector	vector	NOUN
cana-4579	38	61	machines	machine	NOUN
cana-4579	38	62	,	,	PUNCT
cana-4579	38	63	and	and	CCONJ
cana-4579	38	64	naïve	naïve	ADJ
cana-4579	38	65	bayes	bayes	NOUN
cana-4579	38	66	.	.	PUNCT
cana-4579	39	1	these	these	DET
cana-4579	39	2	methods	method	NOUN
cana-4579	39	3	have	have	AUX
cana-4579	39	4	been	be	AUX
cana-4579	39	5	applied	apply	VERB
cana-4579	39	6	to	to	ADP
cana-4579	39	7	employability	employability	NOUN
cana-4579	39	8	analysis	analysis	NOUN
cana-4579	39	9	and	and	CCONJ
cana-4579	39	10	prediction	prediction	NOUN
cana-4579	39	11	,	,	PUNCT
cana-4579	39	12	employability	employability	NOUN
cana-4579	39	13	factor	factor	NOUN
cana-4579	39	14	identification	identification	NOUN
cana-4579	39	15	,	,	PUNCT
cana-4579	39	16	and	and	CCONJ
cana-4579	39	17	model	model	NOUN
cana-4579	39	18	accuracy	accuracy	PROPN
cana-4579	39	19	comparison	comparison	NOUN
cana-4579	39	20	(	(	PUNCT
cana-4579	39	21	aniss	aniss	VERB
cana-4579	39	22	et	et	PROPN
cana-4579	39	23	al	al	PROPN
cana-4579	39	24	.	.	PROPN
cana-4579	39	25	,	,	PUNCT
cana-4579	39	26	2020	2020	NUM
cana-4579	39	27	)	)	PUNCT
cana-4579	39	28	.	.	PUNCT
cana-4579	40	1	despite	despite	SCONJ
cana-4579	40	2	being	be	AUX
cana-4579	40	3	a	a	DET
cana-4579	40	4	widely	widely	ADV
cana-4579	40	5	utilized	utilize	VERB
cana-4579	40	6	feature	feature	NOUN
cana-4579	40	7	selection	selection	NOUN
cana-4579	40	8	method	method	NOUN
cana-4579	40	9	in	in	ADP
cana-4579	40	10	data	datum	NOUN
cana-4579	40	11	mining	mining	NOUN
cana-4579	40	12	,	,	PUNCT
cana-4579	40	13	rfe	rfe	PROPN
cana-4579	40	14	is	be	AUX
cana-4579	40	15	not	not	PART
cana-4579	40	16	mentioned	mention	VERB
cana-4579	40	17	by	by	ADP
cana-4579	40	18	name	name	NOUN
cana-4579	40	19	in	in	ADP
cana-4579	40	20	the	the	DET
cana-4579	40	21	abstracts	abstract	NOUN
cana-4579	40	22	that	that	PRON
cana-4579	40	23	are	be	AUX
cana-4579	40	24	supplied	supply	VERB
cana-4579	40	25	.	.	PUNCT
cana-4579	41	1	consequently	consequently	ADV
cana-4579	41	2	,	,	PUNCT
cana-4579	41	3	more	more	ADJ
cana-4579	41	4	investigation	investigation	NOUN
cana-4579	41	5	is	be	AUX
cana-4579	41	6	required	require	VERB
cana-4579	41	7	to	to	PART
cana-4579	41	8	examine	examine	VERB
cana-4579	41	9	the	the	DET
cana-4579	41	10	application	application	NOUN
cana-4579	41	11	of	of	ADP
cana-4579	41	12	rfe	rfe	PROPN
cana-4579	41	13	in	in	ADP
cana-4579	41	14	gauging	gauge	VERB
cana-4579	41	15	the	the	DET
cana-4579	41	16	employability	employability	NOUN
cana-4579	41	17	of	of	ADP
cana-4579	41	18	graduates	graduate	NOUN
cana-4579	41	19	.	.	PUNCT
cana-4579	42	1	iii	iii	X
cana-4579	42	2	.	.	PUNCT
cana-4579	42	3	research	research	NOUN
cana-4579	42	4	methodology	methodology	NOUN
cana-4579	42	5	a	a	DET
cana-4579	42	6	research	research	NOUN
cana-4579	42	7	methodology	methodology	NOUN
cana-4579	42	8	is	be	AUX
cana-4579	42	9	derived	derive	VERB
cana-4579	42	10	based	base	VERB
cana-4579	42	11	on	on	ADP
cana-4579	42	12	the	the	DET
cana-4579	42	13	following	follow	VERB
cana-4579	42	14	phases	phase	NOUN
cana-4579	42	15	which	which	PRON
cana-4579	42	16	are	be	AUX
cana-4579	42	17	important	important	ADJ
cana-4579	42	18	part	part	NOUN
cana-4579	42	19	of	of	ADP
cana-4579	42	20	the	the	DET
cana-4579	42	21	conceptual	conceptual	ADJ
cana-4579	42	22	framework	framework	NOUN
cana-4579	42	23	from	from	ADP
cana-4579	42	24	forming	form	VERB
cana-4579	42	25	the	the	DET
cana-4579	42	26	idea	idea	NOUN
cana-4579	42	27	&	&	CCONJ
cana-4579	42	28	understanding	understand	VERB
cana-4579	42	29	the	the	DET
cana-4579	42	30	organization	organization	NOUN
cana-4579	42	31	to	to	ADP
cana-4579	42	32	the	the	DET
cana-4579	42	33	results	result	NOUN
cana-4579	42	34	and	and	CCONJ
cana-4579	42	35	discussion	discussion	NOUN
cana-4579	42	36	of	of	ADP
cana-4579	42	37	the	the	DET
cana-4579	42	38	case	case	NOUN
cana-4579	42	39	studies	study	NOUN
cana-4579	42	40	.	.	PUNCT
cana-4579	43	1	specifically	specifically	ADV
cana-4579	43	2	for	for	ADP
cana-4579	43	3	the	the	DET
cana-4579	43	4	results	result	NOUN
cana-4579	43	5	machine	machine	NOUN
cana-4579	43	6	learning	learning	NOUN
cana-4579	43	7	method	method	NOUN
cana-4579	43	8	is	be	AUX
cana-4579	43	9	used	use	VERB
cana-4579	43	10	to	to	PART
cana-4579	43	11	drill	drill	VERB
cana-4579	43	12	into	into	ADP
cana-4579	43	13	data	datum	NOUN
cana-4579	43	14	to	to	PART
cana-4579	43	15	determine	determine	VERB
cana-4579	43	16	the	the	DET
cana-4579	43	17	predictive	predictive	ADJ
cana-4579	43	18	power	power	NOUN
cana-4579	43	19	of	of	ADP
cana-4579	43	20	the	the	DET
cana-4579	43	21	algorithms	algorithm	NOUN
cana-4579	43	22	.	.	PUNCT
cana-4579	44	1	communications	communication	NOUN
cana-4579	44	2	on	on	ADP
cana-4579	44	3	applied	apply	VERB
cana-4579	44	4	nonlinear	nonlinear	ADJ
cana-4579	44	5	analysis	analysis	NOUN
cana-4579	44	6	issn	issn	NOUN
cana-4579	44	7	:	:	PUNCT
cana-4579	44	8	1074	1074	NUM
cana-4579	44	9	-	-	PUNCT
cana-4579	44	10	133x	133x	NUM
cana-4579	44	11	vol	vol	NOUN
cana-4579	44	12	32	32	NUM
cana-4579	44	13	no	no	NOUN
cana-4579	44	14	.	.	PUNCT
cana-4579	45	1	9s	9s	NUM
cana-4579	45	2	(	(	PUNCT
cana-4579	45	3	2025	2025	NUM
cana-4579	45	4	)	)	PUNCT
cana-4579	45	5	2869	2869	NUM
cana-4579	46	1	https://internationalpubls.com	https://internationalpubls.com	X
cana-4579	46	2	figure	figure	NOUN
cana-4579	46	3	1	1	NUM
cana-4579	46	4	–	–	PUNCT
cana-4579	46	5	research	research	NOUN
cana-4579	46	6	methodology	methodology	NOUN
cana-4579	46	7	for	for	ADP
cana-4579	46	8	the	the	DET
cana-4579	46	9	conceptual	conceptual	ADJ
cana-4579	46	10	framework	framework	NOUN
cana-4579	46	11	the	the	DET
cana-4579	46	12	following	follow	VERB
cana-4579	46	13	stages	stage	NOUN
cana-4579	46	14	,	,	PUNCT
cana-4579	46	15	which	which	PRON
cana-4579	46	16	are	be	AUX
cana-4579	46	17	crucial	crucial	ADJ
cana-4579	46	18	to	to	ADP
cana-4579	46	19	the	the	DET
cana-4579	46	20	conceptual	conceptual	ADJ
cana-4579	46	21	framework	framework	NOUN
cana-4579	46	22	,	,	PUNCT
cana-4579	46	23	are	be	AUX
cana-4579	46	24	the	the	DET
cana-4579	46	25	basis	basis	NOUN
cana-4579	46	26	for	for	ADP
cana-4579	46	27	a	a	DET
cana-4579	46	28	research	research	NOUN
cana-4579	46	29	technique	technique	NOUN
cana-4579	46	30	.	.	PUNCT
cana-4579	47	1	they	they	PRON
cana-4579	47	2	range	range	VERB
cana-4579	47	3	from	from	ADP
cana-4579	47	4	idea	idea	NOUN
cana-4579	47	5	formation	formation	NOUN
cana-4579	47	6	and	and	CCONJ
cana-4579	47	7	organization	organization	NOUN
cana-4579	47	8	comprehension	comprehension	NOUN
cana-4579	47	9	to	to	PART
cana-4579	47	10	case	case	VERB
cana-4579	47	11	study	study	NOUN
cana-4579	47	12	outcomes	outcome	NOUN
cana-4579	47	13	and	and	CCONJ
cana-4579	47	14	discussion	discussion	NOUN
cana-4579	47	15	.	.	PUNCT
cana-4579	48	1	in	in	ADP
cana-4579	48	2	particular	particular	ADJ
cana-4579	48	3	,	,	PUNCT
cana-4579	48	4	the	the	DET
cana-4579	48	5	predictive	predictive	ADJ
cana-4579	48	6	power	power	NOUN
cana-4579	48	7	of	of	ADP
cana-4579	48	8	the	the	DET
cana-4579	48	9	algorithms	algorithm	NOUN
cana-4579	48	10	was	be	AUX
cana-4579	48	11	ascertained	ascertain	VERB
cana-4579	48	12	by	by	ADP
cana-4579	48	13	delving	delve	VERB
cana-4579	48	14	further	far	ADV
cana-4579	48	15	into	into	ADP
cana-4579	48	16	the	the	DET
cana-4579	48	17	data	datum	NOUN
cana-4579	48	18	using	use	VERB
cana-4579	48	19	the	the	DET
cana-4579	48	20	machine	machine	NOUN
cana-4579	48	21	learning	learning	NOUN
cana-4579	48	22	approach	approach	NOUN
cana-4579	48	23	.	.	PUNCT
cana-4579	49	1	we	we	PRON
cana-4579	49	2	may	may	AUX
cana-4579	49	3	further	far	ADV
cana-4579	49	4	enhance	enhance	VERB
cana-4579	49	5	this	this	DET
cana-4579	49	6	model	model	NOUN
cana-4579	49	7	by	by	ADP
cana-4579	49	8	applying	apply	VERB
cana-4579	49	9	our	our	PRON
cana-4579	49	10	previously	previously	ADV
cana-4579	49	11	developed	develop	VERB
cana-4579	49	12	conceptual	conceptual	ADJ
cana-4579	49	13	framework	framework	NOUN
cana-4579	49	14	,	,	PUNCT
cana-4579	49	15	which	which	PRON
cana-4579	49	16	can	can	AUX
cana-4579	49	17	serve	serve	VERB
cana-4579	49	18	as	as	ADP
cana-4579	49	19	the	the	DET
cana-4579	49	20	basis	basis	NOUN
cana-4579	49	21	for	for	ADP
cana-4579	49	22	the	the	DET
cana-4579	49	23	methodological	methodological	ADJ
cana-4579	49	24	framework	framework	NOUN
cana-4579	49	25	of	of	ADP
cana-4579	49	26	the	the	DET
cana-4579	49	27	machine	machine	NOUN
cana-4579	49	28	learning	learning	NOUN
cana-4579	49	29	-	-	PUNCT
cana-4579	49	30	based	base	VERB
cana-4579	49	31	prediction	prediction	NOUN
cana-4579	49	32	model	model	NOUN
cana-4579	49	33	.	.	PUNCT
cana-4579	50	1	this	this	DET
cana-4579	50	2	study	study	NOUN
cana-4579	50	3	builds	build	VERB
cana-4579	50	4	on	on	ADP
cana-4579	50	5	a	a	DET
cana-4579	50	6	previous	previous	ADJ
cana-4579	50	7	investigation	investigation	NOUN
cana-4579	50	8	,	,	PUNCT
cana-4579	50	9	which	which	PRON
cana-4579	50	10	provides	provide	VERB
cana-4579	50	11	a	a	DET
cana-4579	50	12	brief	brief	ADJ
cana-4579	50	13	overview	overview	NOUN
cana-4579	50	14	of	of	ADP
cana-4579	50	15	the	the	DET
cana-4579	50	16	study	study	NOUN
cana-4579	50	17	's	's	PART
cana-4579	50	18	conceptual	conceptual	ADJ
cana-4579	50	19	framework	framework	NOUN
cana-4579	50	20	for	for	ADP
cana-4579	50	21	the	the	DET
cana-4579	50	22	job	job	NOUN
cana-4579	50	23	matching	matching	NOUN
cana-4579	50	24	model	model	NOUN
cana-4579	50	25	.	.	PUNCT
cana-4579	51	1	four	four	NUM
cana-4579	51	2	independent	independent	ADJ
cana-4579	51	3	variables	variable	NOUN
cana-4579	51	4	make	make	VERB
cana-4579	51	5	up	up	ADP
cana-4579	51	6	the	the	DET
cana-4579	51	7	framework	framework	NOUN
cana-4579	51	8	,	,	PUNCT
cana-4579	51	9	which	which	PRON
cana-4579	51	10	is	be	AUX
cana-4579	51	11	based	base	VERB
cana-4579	51	12	on	on	ADP
cana-4579	51	13	the	the	DET
cana-4579	51	14	profile	profile	NOUN
cana-4579	51	15	of	of	ADP
cana-4579	51	16	an	an	DET
cana-4579	51	17	undergraduate	undergraduate	NOUN
cana-4579	51	18	student	student	NOUN
cana-4579	51	19	:	:	PUNCT
cana-4579	51	20	major	major	ADJ
cana-4579	51	21	course	course	NOUN
cana-4579	51	22	,	,	PUNCT
cana-4579	51	23	cumulative	cumulative	ADJ
cana-4579	51	24	gpa	gpa	PROPN
cana-4579	51	25	,	,	PUNCT
cana-4579	51	26	advantage	advantage	NOUN
cana-4579	51	27	point	point	NOUN
cana-4579	51	28	for	for	ADP
cana-4579	51	29	extracurricular	extracurricular	ADJ
cana-4579	51	30	activities	activity	NOUN
cana-4579	51	31	,	,	PUNCT
cana-4579	51	32	and	and	CCONJ
cana-4579	51	33	internship	internship	NOUN
cana-4579	51	34	data	datum	NOUN
cana-4579	51	35	.	.	PUNCT
cana-4579	52	1	the	the	DET
cana-4579	52	2	institution	institution	NOUN
cana-4579	52	3	plays	play	VERB
cana-4579	52	4	a	a	DET
cana-4579	52	5	crucial	crucial	ADJ
cana-4579	52	6	role	role	NOUN
cana-4579	52	7	in	in	ADP
cana-4579	52	8	determining	determine	VERB
cana-4579	52	9	whether	whether	SCONJ
cana-4579	52	10	an	an	DET
cana-4579	52	11	undergraduate	undergraduate	NOUN
cana-4579	52	12	student	student	NOUN
cana-4579	52	13	is	be	AUX
cana-4579	52	14	successful	successful	ADJ
cana-4579	52	15	in	in	ADP
cana-4579	52	16	landing	land	VERB
cana-4579	52	17	an	an	DET
cana-4579	52	18	internship	internship	NOUN
cana-4579	52	19	with	with	ADP
cana-4579	52	20	a	a	DET
cana-4579	52	21	partnering	partner	VERB
cana-4579	52	22	company	company	NOUN
cana-4579	52	23	(	(	PUNCT
cana-4579	52	24	industry	industry	NOUN
cana-4579	52	25	)	)	PUNCT
cana-4579	52	26	.	.	PUNCT
cana-4579	53	1	in	in	ADP
cana-4579	53	2	the	the	DET
cana-4579	53	3	event	event	NOUN
cana-4579	53	4	that	that	PRON
cana-4579	53	5	an	an	DET
cana-4579	53	6	undergraduate	undergraduate	NOUN
cana-4579	53	7	is	be	AUX
cana-4579	53	8	unemployed	unemployed	ADJ
cana-4579	53	9	,	,	PUNCT
cana-4579	53	10	they	they	PRON
cana-4579	53	11	have	have	VERB
cana-4579	53	12	two	two	NUM
cana-4579	53	13	options	option	NOUN
cana-4579	53	14	:	:	PUNCT
cana-4579	53	15	either	either	CCONJ
cana-4579	53	16	they	they	PRON
cana-4579	53	17	use	use	VERB
cana-4579	53	18	corrective	corrective	ADJ
cana-4579	53	19	actions	action	NOUN
cana-4579	53	20	to	to	PART
cana-4579	53	21	obtain	obtain	VERB
cana-4579	53	22	the	the	DET
cana-4579	53	23	three	three	NUM
cana-4579	53	24	essential	essential	ADJ
cana-4579	53	25	21st	21st	ADJ
cana-4579	53	26	century	century	NOUN
cana-4579	53	27	skills	skill	NOUN
cana-4579	53	28	listed	list	VERB
cana-4579	53	29	by	by	ADP
cana-4579	53	30	the	the	DET
cana-4579	53	31	institute	institute	NOUN
cana-4579	53	32	of	of	ADP
cana-4579	53	33	higher	high	ADJ
cana-4579	53	34	learning	learning	NOUN
cana-4579	53	35	—	—	PUNCT
cana-4579	53	36	customer	customer	NOUN
cana-4579	53	37	orientation	orientation	NOUN
cana-4579	53	38	,	,	PUNCT
cana-4579	53	39	collaboration	collaboration	NOUN
cana-4579	53	40	,	,	PUNCT
cana-4579	53	41	and	and	CCONJ
cana-4579	53	42	communication	communication	NOUN
cana-4579	53	43	—	—	PUNCT
cana-4579	53	44	as	as	ADV
cana-4579	53	45	well	well	ADV
cana-4579	53	46	as	as	ADP
cana-4579	53	47	the	the	DET
cana-4579	53	48	course	course	NOUN
cana-4579	53	49	of	of	ADP
cana-4579	53	50	competencies	competency	NOUN
cana-4579	53	51	(	(	PUNCT
cana-4579	53	52	cocs	coc	NOUN
cana-4579	53	53	)	)	PUNCT
cana-4579	53	54	;	;	PUNCT
cana-4579	53	55	or	or	CCONJ
cana-4579	53	56	they	they	PRON
cana-4579	53	57	get	get	VERB
cana-4579	53	58	support	support	NOUN
cana-4579	53	59	from	from	ADP
cana-4579	53	60	sg	sg	PROPN
cana-4579	53	61	skills	skill	NOUN
cana-4579	53	62	future	future	NOUN
cana-4579	53	63	to	to	PART
cana-4579	53	64	learn	learn	VERB
cana-4579	53	65	new	new	ADJ
cana-4579	53	66	skills	skill	NOUN
cana-4579	53	67	,	,	PUNCT
cana-4579	53	68	apply	apply	VERB
cana-4579	53	69	for	for	ADP
cana-4579	53	70	jobs	job	NOUN
cana-4579	53	71	,	,	PUNCT
cana-4579	53	72	and	and	CCONJ
cana-4579	53	73	modify	modify	VERB
cana-4579	53	74	their	their	PRON
cana-4579	53	75	resumes	resume	NOUN
cana-4579	53	76	in	in	ADP
cana-4579	53	77	order	order	NOUN
cana-4579	53	78	to	to	PART
cana-4579	53	79	apply	apply	VERB
cana-4579	53	80	for	for	ADP
cana-4579	53	81	jobs	job	NOUN
cana-4579	53	82	and	and	CCONJ
cana-4579	53	83	land	land	NOUN
cana-4579	53	84	a	a	DET
cana-4579	53	85	job	job	NOUN
cana-4579	53	86	.	.	PUNCT
cana-4579	54	1	undergraduates	undergraduate	NOUN
cana-4579	54	2	may	may	AUX
cana-4579	54	3	need	need	VERB
cana-4579	54	4	to	to	PART
cana-4579	54	5	acquire	acquire	VERB
cana-4579	54	6	new	new	ADJ
cana-4579	54	7	competency	competency	NOUN
cana-4579	54	8	-	-	PUNCT
cana-4579	54	9	based	base	VERB
cana-4579	54	10	abilities	ability	NOUN
cana-4579	54	11	as	as	ADP
cana-4579	54	12	a	a	DET
cana-4579	54	13	result	result	NOUN
cana-4579	54	14	of	of	ADP
cana-4579	54	15	the	the	DET
cana-4579	54	16	procedure	procedure	NOUN
cana-4579	54	17	if	if	SCONJ
cana-4579	54	18	their	their	PRON
cana-4579	54	19	attempts	attempt	NOUN
cana-4579	54	20	prove	prove	VERB
cana-4579	54	21	unsuccessful	unsuccessful	ADJ
cana-4579	54	22	.	.	PUNCT
cana-4579	55	1	every	every	DET
cana-4579	55	2	level	level	NOUN
cana-4579	55	3	of	of	ADP
cana-4579	55	4	the	the	DET
cana-4579	55	5	remedial	remedial	ADJ
cana-4579	55	6	action	action	NOUN
cana-4579	55	7	involves	involve	VERB
cana-4579	55	8	the	the	DET
cana-4579	55	9	use	use	NOUN
cana-4579	55	10	of	of	ADP
cana-4579	55	11	the	the	DET
cana-4579	55	12	feedback	feedback	NOUN
cana-4579	55	13	system	system	NOUN
cana-4579	55	14	to	to	PART
cana-4579	55	15	ensure	ensure	VERB
cana-4579	55	16	that	that	SCONJ
cana-4579	55	17	the	the	DET
cana-4579	55	18	undergraduate	undergraduate	NOUN
cana-4579	55	19	succeeds	succeed	VERB
cana-4579	55	20	in	in	ADP
cana-4579	55	21	finding	find	VERB
cana-4579	55	22	employment	employment	NOUN
cana-4579	55	23	.	.	PUNCT
cana-4579	56	1	the	the	DET
cana-4579	56	2	government	government	NOUN
cana-4579	56	3	,	,	PUNCT
cana-4579	56	4	an	an	DET
cana-4579	56	5	additional	additional	ADJ
cana-4579	56	6	entity	entity	NOUN
cana-4579	56	7	in	in	ADP
cana-4579	56	8	the	the	DET
cana-4579	56	9	updated	update	VERB
cana-4579	56	10	framework	framework	NOUN
cana-4579	56	11	,	,	PUNCT
cana-4579	56	12	contributes	contribute	VERB
cana-4579	56	13	significantly	significantly	ADV
cana-4579	56	14	economically	economically	ADV
cana-4579	56	15	by	by	ADP
cana-4579	56	16	funding	fund	VERB
cana-4579	56	17	90	90	NUM
cana-4579	56	18	%	%	NOUN
cana-4579	56	19	of	of	ADP
cana-4579	56	20	upskilling	upskille	VERB
cana-4579	56	21	and	and	CCONJ
cana-4579	56	22	reskilling	reskille	VERB
cana-4579	56	23	initiatives	initiative	NOUN
cana-4579	56	24	for	for	ADP
cana-4579	56	25	singaporeans	singaporeans	PROPN
cana-4579	56	26	and	and	CCONJ
cana-4579	56	27	permanent	permanent	ADJ
cana-4579	56	28	residents	resident	NOUN
cana-4579	56	29	as	as	ADP
cana-4579	56	30	part	part	NOUN
cana-4579	56	31	of	of	ADP
cana-4579	56	32	government	government	NOUN
cana-4579	56	33	initiatives	initiative	NOUN
cana-4579	56	34	aimed	aim	VERB
cana-4579	56	35	at	at	ADP
cana-4579	56	36	nation	nation	NOUN
cana-4579	56	37	-	-	PUNCT
cana-4579	56	38	building	building	NOUN
cana-4579	56	39	.	.	PUNCT
cana-4579	57	1	iv	iv	X
cana-4579	57	2	.	.	PROPN
cana-4579	57	3	data	datum	NOUN
cana-4579	57	4	analysis	analysis	NOUN
cana-4579	57	5	the	the	DET
cana-4579	57	6	experiment	experiment	NOUN
cana-4579	57	7	showed	show	VERB
cana-4579	57	8	how	how	SCONJ
cana-4579	57	9	important	important	ADJ
cana-4579	57	10	feature	feature	NOUN
cana-4579	57	11	selection	selection	NOUN
cana-4579	57	12	is	be	AUX
cana-4579	57	13	while	while	SCONJ
cana-4579	57	14	processing	process	VERB
cana-4579	57	15	classification	classification	NOUN
cana-4579	57	16	data	datum	NOUN
cana-4579	57	17	.	.	PUNCT
cana-4579	58	1	feature	feature	NOUN
cana-4579	58	2	selection	selection	NOUN
cana-4579	58	3	becomes	become	VERB
cana-4579	58	4	more	more	ADV
cana-4579	58	5	and	and	CCONJ
cana-4579	58	6	more	more	ADV
cana-4579	58	7	important	important	ADJ
cana-4579	58	8	,	,	PUNCT
cana-4579	58	9	especially	especially	ADV
cana-4579	58	10	for	for	ADP
cana-4579	58	11	datasets	dataset	NOUN
cana-4579	58	12	with	with	ADP
cana-4579	58	13	a	a	DET
cana-4579	58	14	large	large	ADJ
cana-4579	58	15	number	number	NOUN
cana-4579	58	16	of	of	ADP
cana-4579	58	17	variables	variable	NOUN
cana-4579	58	18	and	and	CCONJ
cana-4579	58	19	features	feature	NOUN
cana-4579	58	20	.	.	PUNCT
cana-4579	59	1	it	it	PRON
cana-4579	59	2	increases	increase	VERB
cana-4579	59	3	the	the	DET
cana-4579	59	4	accuracy	accuracy	NOUN
cana-4579	59	5	and	and	CCONJ
cana-4579	59	6	performance	performance	NOUN
cana-4579	59	7	of	of	ADP
cana-4579	59	8	categorization	categorization	NOUN
cana-4579	59	9	by	by	ADP
cana-4579	59	10	removing	remove	VERB
cana-4579	59	11	unnecessary	unnecessary	ADJ
cana-4579	59	12	variables	variable	NOUN
cana-4579	59	13	.	.	PUNCT
cana-4579	60	1	chen	chen	PROPN
cana-4579	60	2	et	et	PROPN
cana-4579	60	3	al	al	PROPN
cana-4579	60	4	.	.	PROPN
cana-4579	60	5	(	(	PUNCT
cana-4579	60	6	2020	2020	NUM
cana-4579	60	7	)	)	PUNCT
cana-4579	60	8	addressed	address	VERB
cana-4579	60	9	the	the	DET
cana-4579	60	10	significance	significance	NOUN
cana-4579	60	11	of	of	ADP
cana-4579	60	12	feature	feature	NOUN
cana-4579	60	13	selection	selection	NOUN
cana-4579	60	14	with	with	ADP
cana-4579	60	15	four	four	NUM
cana-4579	60	16	main	main	ADJ
cana-4579	60	17	points	point	NOUN
cana-4579	60	18	.	.	PUNCT
cana-4579	61	1	reduce	reduce	VERB
cana-4579	61	2	the	the	DET
cana-4579	61	3	amount	amount	NOUN
cana-4579	61	4	of	of	ADP
cana-4579	61	5	parameters	parameter	NOUN
cana-4579	61	6	in	in	ADP
cana-4579	61	7	the	the	DET
cana-4579	61	8	model	model	NOUN
cana-4579	61	9	first	first	ADV
cana-4579	61	10	,	,	PUNCT
cana-4579	61	11	then	then	ADV
cana-4579	61	12	increase	increase	VERB
cana-4579	61	13	training	training	NOUN
cana-4579	61	14	speed	speed	NOUN
cana-4579	61	15	,	,	PUNCT
cana-4579	61	16	reduce	reduce	VERB
cana-4579	61	17	overfilling	overfill	VERB
cana-4579	61	18	by	by	ADP
cana-4579	61	19	increasing	increase	VERB
cana-4579	61	20	generalization	generalization	NOUN
cana-4579	61	21	,	,	PUNCT
cana-4579	61	22	and	and	CCONJ
cana-4579	61	23	break	break	VERB
cana-4579	61	24	free	free	ADJ
cana-4579	61	25	from	from	ADP
cana-4579	61	26	the	the	DET
cana-4579	61	27	dimensionality	dimensionality	NOUN
cana-4579	61	28	curse	curse	NOUN
cana-4579	61	29	.	.	PUNCT
cana-4579	62	1	evaluations	evaluation	NOUN
cana-4579	62	2	and	and	CCONJ
cana-4579	62	3	comparisons	comparison	NOUN
cana-4579	62	4	of	of	ADP
cana-4579	62	5	the	the	DET
cana-4579	62	6	effectiveness	effectiveness	NOUN
cana-4579	62	7	and	and	CCONJ
cana-4579	62	8	precision	precision	NOUN
cana-4579	62	9	of	of	ADP
cana-4579	62	10	the	the	DET
cana-4579	62	11	k	k	NOUN
cana-4579	62	12	-	-	PUNCT
cana-4579	62	13	nearest	near	ADJ
cana-4579	62	14	neighbors	neighbor	NOUN
cana-4579	62	15	(	(	PUNCT
cana-4579	62	16	knn	knn	PROPN
cana-4579	62	17	)	)	PUNCT
cana-4579	62	18	,	,	PUNCT
cana-4579	62	19	random	random	ADJ
cana-4579	62	20	forest	forest	NOUN
cana-4579	62	21	communications	communication	NOUN
cana-4579	62	22	on	on	ADP
cana-4579	62	23	applied	apply	VERB
cana-4579	62	24	nonlinear	nonlinear	ADJ
cana-4579	62	25	analysis	analysis	NOUN
cana-4579	62	26	issn	issn	NOUN
cana-4579	62	27	:	:	PUNCT
cana-4579	62	28	1074	1074	NUM
cana-4579	62	29	-	-	PUNCT
cana-4579	62	30	133x	133x	NUM
cana-4579	62	31	vol	vol	NOUN
cana-4579	62	32	32	32	NUM
cana-4579	62	33	no	no	NOUN
cana-4579	62	34	.	.	PUNCT
cana-4579	63	1	9s	9s	NUM
cana-4579	63	2	(	(	PUNCT
cana-4579	63	3	2025	2025	NUM
cana-4579	63	4	)	)	PUNCT
cana-4579	63	5	2870	2870	NUM
cana-4579	63	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-4579	63	7	(	(	PUNCT
cana-4579	63	8	rf	rf	NOUN
cana-4579	63	9	)	)	PUNCT
cana-4579	63	10	,	,	PUNCT
cana-4579	63	11	and	and	CCONJ
cana-4579	63	12	support	support	VERB
cana-4579	63	13	vector	vector	NOUN
cana-4579	63	14	machines	machine	NOUN
cana-4579	63	15	(	(	PUNCT
cana-4579	63	16	svm	svm	ADJ
cana-4579	63	17	)	)	PUNCT
cana-4579	63	18	classification	classification	NOUN
cana-4579	63	19	models	model	NOUN
cana-4579	63	20	were	be	AUX
cana-4579	63	21	also	also	ADV
cana-4579	63	22	carried	carry	VERB
cana-4579	63	23	out	out	ADP
cana-4579	63	24	.	.	PUNCT
cana-4579	64	1	the	the	DET
cana-4579	64	2	optimal	optimal	ADJ
cana-4579	64	3	classifier	classifier	NOUN
cana-4579	64	4	is	be	AUX
cana-4579	64	5	the	the	DET
cana-4579	64	6	model	model	NOUN
cana-4579	64	7	with	with	ADP
cana-4579	64	8	highest	high	ADJ
cana-4579	64	9	accuracy	accuracy	NOUN
cana-4579	64	10	.	.	PUNCT
cana-4579	65	1	the	the	DET
cana-4579	65	2	highest	high	ADJ
cana-4579	65	3	kappa	kappa	ADJ
cana-4579	65	4	values	value	NOUN
cana-4579	65	5	and	and	CCONJ
cana-4579	65	6	percentage	percentage	NOUN
cana-4579	65	7	accuracy	accuracy	NOUN
cana-4579	65	8	are	be	AUX
cana-4579	65	9	obtained	obtain	VERB
cana-4579	65	10	by	by	ADP
cana-4579	65	11	the	the	DET
cana-4579	65	12	use	use	NOUN
cana-4579	65	13	of	of	ADP
cana-4579	65	14	recursive	recursive	ADJ
cana-4579	65	15	feature	feature	NOUN
cana-4579	65	16	elimination	elimination	NOUN
cana-4579	65	17	(	(	PUNCT
cana-4579	65	18	rfe	rfe	PROPN
cana-4579	65	19	)	)	PUNCT
cana-4579	65	20	(	(	PUNCT
cana-4579	65	21	chen	chen	PROPN
cana-4579	65	22	,	,	PUNCT
cana-4579	65	23	r.	r.	PROPN
cana-4579	65	24	c.	c.	PROPN
cana-4579	65	25	,	,	PUNCT
cana-4579	65	26	et	et	PROPN
cana-4579	65	27	al	al	PROPN
cana-4579	65	28	.	.	PROPN
cana-4579	65	29	,	,	PUNCT
cana-4579	65	30	2020	2020	NUM
cana-4579	65	31	)	)	PUNCT
cana-4579	65	32	.	.	PUNCT
cana-4579	66	1	multi	multi	ADJ
cana-4579	66	2	-	-	ADJ
cana-4579	66	3	class	class	ADJ
cana-4579	66	4	classification	classification	NOUN
cana-4579	66	5	was	be	AUX
cana-4579	66	6	employed	employ	VERB
cana-4579	66	7	in	in	ADP
cana-4579	66	8	this	this	DET
cana-4579	66	9	study	study	NOUN
cana-4579	66	10	's	's	PART
cana-4579	66	11	analysis	analysis	NOUN
cana-4579	66	12	to	to	PART
cana-4579	66	13	provide	provide	VERB
cana-4579	66	14	dependable	dependable	ADJ
cana-4579	66	15	results	result	NOUN
cana-4579	66	16	,	,	PUNCT
cana-4579	66	17	which	which	PRON
cana-4579	66	18	required	require	VERB
cana-4579	66	19	pre	pre	ADJ
cana-4579	66	20	-	-	ADJ
cana-4579	66	21	processing	process	VERB
cana-4579	66	22	the	the	DET
cana-4579	66	23	data	datum	NOUN
cana-4579	66	24	prior	prior	ADV
cana-4579	66	25	to	to	ADP
cana-4579	66	26	cleaning	clean	VERB
cana-4579	66	27	.	.	PUNCT
cana-4579	67	1	the	the	DET
cana-4579	67	2	employability	employability	NOUN
cana-4579	67	3	target	target	NOUN
cana-4579	67	4	(	(	PUNCT
cana-4579	67	5	dependent	dependent	ADJ
cana-4579	67	6	variable	variable	NOUN
cana-4579	67	7	)	)	PUNCT
cana-4579	67	8	,	,	PUNCT
cana-4579	67	9	cca	cca	PROPN
cana-4579	67	10	advantage	advantage	NOUN
cana-4579	67	11	points	point	NOUN
cana-4579	67	12	,	,	PUNCT
cana-4579	67	13	and	and	CCONJ
cana-4579	67	14	student	student	NOUN
cana-4579	67	15	extracurricular	extracurricular	ADJ
cana-4579	67	16	activity	activity	NOUN
cana-4579	67	17	missing	miss	VERB
cana-4579	67	18	values	value	NOUN
cana-4579	67	19	were	be	AUX
cana-4579	67	20	removed	remove	VERB
cana-4579	67	21	from	from	ADP
cana-4579	67	22	the	the	DET
cana-4579	67	23	dataset	dataset	NOUN
cana-4579	67	24	.	.	PUNCT
cana-4579	68	1	after	after	SCONJ
cana-4579	68	2	the	the	DET
cana-4579	68	3	datasets	dataset	NOUN
cana-4579	68	4	were	be	AUX
cana-4579	68	5	gathered	gather	VERB
cana-4579	68	6	and	and	CCONJ
cana-4579	68	7	filtered	filter	VERB
cana-4579	68	8	,	,	PUNCT
cana-4579	68	9	data	datum	NOUN
cana-4579	68	10	correlation	correlation	NOUN
cana-4579	68	11	and	and	CCONJ
cana-4579	68	12	variance	variance	NOUN
cana-4579	68	13	were	be	AUX
cana-4579	68	14	noted	note	VERB
cana-4579	68	15	,	,	PUNCT
cana-4579	68	16	and	and	CCONJ
cana-4579	68	17	the	the	DET
cana-4579	68	18	experiment	experiment	NOUN
cana-4579	68	19	's	's	PART
cana-4579	68	20	decision	decision	NOUN
cana-4579	68	21	about	about	ADP
cana-4579	68	22	which	which	DET
cana-4579	68	23	variables	variable	NOUN
cana-4579	68	24	to	to	PART
cana-4579	68	25	include	include	VERB
cana-4579	68	26	and	and	CCONJ
cana-4579	68	27	exclude	exclude	NOUN
cana-4579	68	28	was	be	AUX
cana-4579	68	29	made	make	VERB
cana-4579	68	30	.	.	PUNCT
cana-4579	69	1	this	this	DET
cana-4579	69	2	study	study	NOUN
cana-4579	69	3	uses	use	VERB
cana-4579	69	4	a	a	DET
cana-4579	69	5	lot	lot	NOUN
cana-4579	69	6	of	of	ADP
cana-4579	69	7	modeling	modeling	NOUN
cana-4579	69	8	since	since	SCONJ
cana-4579	69	9	the	the	DET
cana-4579	69	10	data	datum	NOUN
cana-4579	69	11	it	it	PRON
cana-4579	69	12	generates	generate	VERB
cana-4579	69	13	is	be	AUX
cana-4579	69	14	more	more	ADV
cana-4579	69	15	reliable	reliable	ADJ
cana-4579	69	16	,	,	PUNCT
cana-4579	69	17	consistent	consistent	ADJ
cana-4579	69	18	,	,	PUNCT
cana-4579	69	19	and	and	CCONJ
cana-4579	69	20	organized	organize	VERB
cana-4579	69	21	.	.	PUNCT
cana-4579	70	1	rfe	rfe	PROPN
cana-4579	70	2	was	be	AUX
cana-4579	70	3	used	use	VERB
cana-4579	70	4	to	to	PART
cana-4579	70	5	assess	assess	VERB
cana-4579	70	6	the	the	DET
cana-4579	70	7	most	most	ADV
cana-4579	70	8	important	important	ADJ
cana-4579	70	9	features	feature	NOUN
cana-4579	70	10	selection	selection	NOUN
cana-4579	70	11	factors	factor	NOUN
cana-4579	70	12	in	in	ADP
cana-4579	70	13	this	this	DET
cana-4579	70	14	investigation	investigation	NOUN
cana-4579	70	15	.	.	PUNCT
cana-4579	71	1	the	the	DET
cana-4579	71	2	accuracy	accuracy	NOUN
cana-4579	71	3	of	of	ADP
cana-4579	71	4	the	the	DET
cana-4579	71	5	results	result	NOUN
cana-4579	71	6	and	and	CCONJ
cana-4579	71	7	the	the	DET
cana-4579	71	8	speed	speed	NOUN
cana-4579	71	9	at	at	ADP
cana-4579	71	10	which	which	PRON
cana-4579	71	11	the	the	DET
cana-4579	71	12	results	result	NOUN
cana-4579	71	13	may	may	AUX
cana-4579	71	14	be	be	AUX
cana-4579	71	15	computed	compute	VERB
cana-4579	71	16	are	be	AUX
cana-4579	71	17	the	the	DET
cana-4579	71	18	most	most	ADV
cana-4579	71	19	important	important	ADJ
cana-4579	71	20	factors	factor	NOUN
cana-4579	71	21	in	in	ADP
cana-4579	71	22	selecting	select	VERB
cana-4579	71	23	a	a	DET
cana-4579	71	24	model	model	NOUN
cana-4579	71	25	.	.	PUNCT
cana-4579	72	1	in	in	ADP
cana-4579	72	2	this	this	DET
cana-4579	72	3	case	case	NOUN
cana-4579	72	4	study	study	NOUN
cana-4579	72	5	,	,	PUNCT
cana-4579	72	6	a	a	DET
cana-4579	72	7	confusion	confusion	NOUN
cana-4579	72	8	matrix	matrix	NOUN
cana-4579	72	9	is	be	AUX
cana-4579	72	10	utilized	utilize	VERB
cana-4579	72	11	to	to	PART
cana-4579	72	12	accomplish	accomplish	VERB
cana-4579	72	13	the	the	DET
cana-4579	72	14	following	follow	VERB
cana-4579	72	15	goals	goal	NOUN
cana-4579	72	16	:	:	PUNCT
cana-4579	72	17	the	the	DET
cana-4579	72	18	quantity	quantity	NOUN
cana-4579	72	19	of	of	ADP
cana-4579	72	20	accurate	accurate	ADJ
cana-4579	72	21	positive	positive	ADJ
cana-4579	72	22	forecasts	forecast	NOUN
cana-4579	72	23	is	be	AUX
cana-4579	72	24	known	know	VERB
cana-4579	72	25	as	as	ADP
cana-4579	72	26	true	true	ADJ
cana-4579	72	27	positives	positive	NOUN
cana-4579	72	28	(	(	PUNCT
cana-4579	72	29	tp	tp	NOUN
cana-4579	72	30	)	)	PUNCT
cana-4579	72	31	.	.	PUNCT
cana-4579	73	1	the	the	DET
cana-4579	73	2	quantity	quantity	NOUN
cana-4579	73	3	of	of	ADP
cana-4579	73	4	accurate	accurate	ADJ
cana-4579	73	5	negative	negative	ADJ
cana-4579	73	6	forecasts	forecast	NOUN
cana-4579	73	7	is	be	AUX
cana-4579	73	8	known	know	VERB
cana-4579	73	9	as	as	ADP
cana-4579	73	10	true	true	ADJ
cana-4579	73	11	negatives	negative	NOUN
cana-4579	73	12	(	(	PUNCT
cana-4579	73	13	tn	tn	NOUN
cana-4579	73	14	)	)	PUNCT
cana-4579	73	15	.	.	PUNCT
cana-4579	74	1	the	the	DET
cana-4579	74	2	quantity	quantity	NOUN
cana-4579	74	3	of	of	ADP
cana-4579	74	4	erroneous	erroneous	ADJ
cana-4579	74	5	positive	positive	ADJ
cana-4579	74	6	predictions	prediction	NOUN
cana-4579	74	7	is	be	AUX
cana-4579	74	8	known	know	VERB
cana-4579	74	9	as	as	ADP
cana-4579	74	10	false	false	ADJ
cana-4579	74	11	positives	positive	NOUN
cana-4579	74	12	(	(	PUNCT
cana-4579	74	13	fp	fp	NOUN
cana-4579	74	14	)	)	PUNCT
cana-4579	74	15	.	.	PUNCT
cana-4579	75	1	the	the	DET
cana-4579	75	2	quantity	quantity	NOUN
cana-4579	75	3	of	of	ADP
cana-4579	75	4	inaccurate	inaccurate	ADJ
cana-4579	75	5	negative	negative	ADJ
cana-4579	75	6	forecasts	forecast	NOUN
cana-4579	75	7	is	be	AUX
cana-4579	75	8	known	know	VERB
cana-4579	75	9	as	as	ADP
cana-4579	75	10	negative	negative	ADJ
cana-4579	75	11	prediction	prediction	NOUN
cana-4579	75	12	errors	error	NOUN
cana-4579	75	13	(	(	PUNCT
cana-4579	75	14	fn	fn	NOUN
cana-4579	75	15	)	)	PUNCT
cana-4579	75	16	.	.	PUNCT
cana-4579	76	1	the	the	DET
cana-4579	76	2	algorithms	algorithm	NOUN
cana-4579	76	3	are	be	AUX
cana-4579	76	4	crucial	crucial	ADJ
cana-4579	76	5	to	to	ADP
cana-4579	76	6	this	this	DET
cana-4579	76	7	investigation	investigation	NOUN
cana-4579	76	8	since	since	SCONJ
cana-4579	76	9	they	they	PRON
cana-4579	76	10	produce	produce	VERB
cana-4579	76	11	the	the	DET
cana-4579	76	12	required	required	ADJ
cana-4579	76	13	outcomes	outcome	NOUN
cana-4579	76	14	.	.	PUNCT
cana-4579	77	1	artificial	artificial	ADJ
cana-4579	77	2	neural	neural	ADJ
cana-4579	77	3	networks	network	NOUN
cana-4579	77	4	(	(	PUNCT
cana-4579	77	5	anns	anns	NOUN
cana-4579	77	6	)	)	PUNCT
cana-4579	77	7	,	,	PUNCT
cana-4579	77	8	decision	decision	NOUN
cana-4579	77	9	trees	tree	NOUN
cana-4579	77	10	,	,	PUNCT
cana-4579	77	11	bagging	bagging	NOUN
cana-4579	77	12	classifiers	classifier	NOUN
cana-4579	77	13	,	,	PUNCT
cana-4579	77	14	ada	ada	PROPN
cana-4579	77	15	boost	boost	PROPN
cana-4579	77	16	,	,	PUNCT
cana-4579	77	17	random	random	ADJ
cana-4579	77	18	forests	forest	NOUN
cana-4579	77	19	,	,	PUNCT
cana-4579	77	20	extremely	extremely	ADV
cana-4579	77	21	random	random	ADJ
cana-4579	77	22	forests	forest	NOUN
cana-4579	77	23	,	,	PUNCT
cana-4579	77	24	cat	cat	NOUN
cana-4579	77	25	boost	boost	NOUN
cana-4579	77	26	,	,	PUNCT
cana-4579	77	27	and	and	CCONJ
cana-4579	77	28	lightgbm	lightgbm	NOUN
cana-4579	77	29	are	be	AUX
cana-4579	77	30	a	a	DET
cana-4579	77	31	few	few	ADJ
cana-4579	77	32	examples	example	NOUN
cana-4579	77	33	of	of	ADP
cana-4579	77	34	techniques	technique	NOUN
cana-4579	77	35	.	.	PUNCT
cana-4579	78	1	a	a	DET
cana-4579	78	2	receiver	receiver	ADV
cana-4579	78	3	operating	operate	VERB
cana-4579	78	4	characteristic	characteristic	NOUN
cana-4579	78	5	(	(	PUNCT
cana-4579	78	6	roc	roc	PROPN
cana-4579	78	7	)	)	PUNCT
cana-4579	78	8	curve	curve	NOUN
cana-4579	78	9	is	be	AUX
cana-4579	78	10	a	a	DET
cana-4579	78	11	graph	graph	NOUN
cana-4579	78	12	that	that	PRON
cana-4579	78	13	displays	display	VERB
cana-4579	78	14	a	a	DET
cana-4579	78	15	classification	classification	NOUN
cana-4579	78	16	model	model	NOUN
cana-4579	78	17	's	's	PART
cana-4579	78	18	true	true	ADJ
cana-4579	78	19	positive	positive	ADJ
cana-4579	78	20	rate	rate	NOUN
cana-4579	78	21	(	(	PUNCT
cana-4579	78	22	tpr	tpr	NOUN
cana-4579	78	23	)	)	PUNCT
cana-4579	78	24	and	and	CCONJ
cana-4579	78	25	false	false	ADJ
cana-4579	78	26	positive	positive	ADJ
cana-4579	78	27	rate	rate	NOUN
cana-4579	78	28	(	(	PUNCT
cana-4579	78	29	fpr	fpr	NOUN
cana-4579	78	30	)	)	PUNCT
cana-4579	78	31	at	at	ADP
cana-4579	78	32	each	each	DET
cana-4579	78	33	classification	classification	NOUN
cana-4579	78	34	threshold	threshold	NOUN
cana-4579	78	35	.	.	PUNCT
cana-4579	79	1	regularly	regularly	ADV
cana-4579	79	2	evaluating	evaluate	VERB
cana-4579	79	3	a	a	DET
cana-4579	79	4	logistic	logistic	ADJ
cana-4579	79	5	regression	regression	NOUN
cana-4579	79	6	model	model	NOUN
cana-4579	79	7	with	with	ADP
cana-4579	79	8	various	various	ADJ
cana-4579	79	9	classification	classification	NOUN
cana-4579	79	10	criteria	criterion	NOUN
cana-4579	79	11	would	would	AUX
cana-4579	79	12	be	be	AUX
cana-4579	79	13	inefficient	inefficient	ADJ
cana-4579	79	14	in	in	ADP
cana-4579	79	15	terms	term	NOUN
cana-4579	79	16	of	of	ADP
cana-4579	79	17	gaining	gain	VERB
cana-4579	79	18	points	point	NOUN
cana-4579	79	19	on	on	ADP
cana-4579	79	20	the	the	DET
cana-4579	79	21	roc	roc	PROPN
cana-4579	79	22	curve	curve	NOUN
cana-4579	79	23	.	.	PUNCT
cana-4579	80	1	thankfully	thankfully	ADV
cana-4579	80	2	,	,	PUNCT
cana-4579	80	3	there	there	PRON
cana-4579	80	4	is	be	VERB
cana-4579	80	5	an	an	DET
cana-4579	80	6	effective	effective	ADJ
cana-4579	80	7	sorting	sorting	NOUN
cana-4579	80	8	-	-	PUNCT
cana-4579	80	9	based	base	VERB
cana-4579	80	10	technique	technique	NOUN
cana-4579	80	11	called	call	VERB
cana-4579	80	12	the	the	DET
cana-4579	80	13	auc	auc	NOUN
cana-4579	80	14	that	that	PRON
cana-4579	80	15	can	can	AUX
cana-4579	80	16	be	be	AUX
cana-4579	80	17	utilized	utilize	VERB
cana-4579	80	18	to	to	PART
cana-4579	80	19	collect	collect	VERB
cana-4579	80	20	this	this	DET
cana-4579	80	21	data	datum	NOUN
cana-4579	80	22	.	.	PUNCT
cana-4579	81	1	the	the	DET
cana-4579	81	2	acronym	acronym	NOUN
cana-4579	81	3	auc	auc	NOUN
cana-4579	81	4	stands	stand	VERB
cana-4579	81	5	for	for	ADP
cana-4579	81	6	"	"	PUNCT
cana-4579	81	7	area	area	NOUN
cana-4579	81	8	under	under	ADP
cana-4579	81	9	the	the	DET
cana-4579	81	10	roc	roc	PROPN
cana-4579	81	11	curve	curve	NOUN
cana-4579	81	12	.	.	PUNCT
cana-4579	81	13	"	"	PUNCT
cana-4579	82	1	the	the	DET
cana-4579	82	2	whole	whole	ADJ
cana-4579	82	3	two	two	NUM
cana-4579	82	4	-	-	PUNCT
cana-4579	82	5	dimensional	dimensional	ADJ
cana-4579	82	6	region	region	NOUN
cana-4579	82	7	from	from	ADP
cana-4579	82	8	(	(	PUNCT
cana-4579	82	9	0	0	NUM
cana-4579	82	10	,	,	PUNCT
cana-4579	82	11	0	0	NUM
cana-4579	82	12	)	)	PUNCT
cana-4579	82	13	to	to	ADP
cana-4579	82	14	(	(	PUNCT
cana-4579	82	15	1	1	NUM
cana-4579	82	16	,	,	PUNCT
cana-4579	82	17	1	1	NUM
cana-4579	82	18	)	)	PUNCT
cana-4579	82	19	is	be	AUX
cana-4579	82	20	measured	measure	VERB
cana-4579	82	21	under	under	ADP
cana-4579	82	22	the	the	DET
cana-4579	82	23	whole	whole	ADJ
cana-4579	82	24	roc	roc	PROPN
cana-4579	82	25	curve	curve	NOUN
cana-4579	82	26	(	(	PUNCT
cana-4579	82	27	it	it	PRON
cana-4579	82	28	brings	bring	VERB
cana-4579	82	29	integral	integral	ADJ
cana-4579	82	30	calculus	calculus	NOUN
cana-4579	82	31	to	to	PART
cana-4579	82	32	mind	mind	VERB
cana-4579	82	33	.	.	PUNCT
cana-4579	82	34	)	)	PUNCT
cana-4579	82	35	.	.	PUNCT
cana-4579	83	1	the	the	DET
cana-4579	83	2	range	range	NOUN
cana-4579	83	3	of	of	ADP
cana-4579	83	4	the	the	DET
cana-4579	83	5	auc	auc	NOUN
cana-4579	83	6	was	be	AUX
cana-4579	83	7	0	0	NUM
cana-4579	83	8	to	to	PART
cana-4579	83	9	1	1	NUM
cana-4579	83	10	.	.	PUNCT
cana-4579	84	1	classification	classification	NOUN
cana-4579	84	2	:	:	PUNCT
cana-4579	84	3	roc	roc	PROPN
cana-4579	84	4	curve	curve	NOUN
cana-4579	84	5	and	and	CCONJ
cana-4579	84	6	auc	auc	NOUN
cana-4579	84	7	(	(	PUNCT
cana-4579	84	8	n.d	n.d	PROPN
cana-4579	84	9	.	.	PROPN
cana-4579	84	10	)	)	PUNCT
cana-4579	84	11	states	state	VERB
cana-4579	84	12	that	that	SCONJ
cana-4579	84	13	an	an	DET
cana-4579	84	14	auc	auc	NOUN
cana-4579	84	15	of	of	ADP
cana-4579	84	16	0	0	NUM
cana-4579	84	17	corresponded	correspond	VERB
cana-4579	84	18	to	to	ADP
cana-4579	84	19	a	a	DET
cana-4579	84	20	model	model	NOUN
cana-4579	84	21	that	that	PRON
cana-4579	84	22	made	make	VERB
cana-4579	84	23	100	100	NUM
cana-4579	84	24	%	%	NOUN
cana-4579	84	25	of	of	ADP
cana-4579	84	26	its	its	PRON
cana-4579	84	27	predictions	prediction	NOUN
cana-4579	84	28	incorrectly	incorrectly	ADV
cana-4579	84	29	,	,	PUNCT
cana-4579	84	30	and	and	CCONJ
cana-4579	84	31	an	an	DET
cana-4579	84	32	auc	auc	NOUN
cana-4579	84	33	of	of	ADP
cana-4579	84	34	1	1	NUM
cana-4579	84	35	to	to	ADP
cana-4579	84	36	a	a	DET
cana-4579	84	37	model	model	NOUN
cana-4579	84	38	that	that	PRON
cana-4579	84	39	made	make	VERB
cana-4579	84	40	100	100	NUM
cana-4579	84	41	%	%	NOUN
cana-4579	84	42	of	of	ADP
cana-4579	84	43	its	its	PRON
cana-4579	84	44	predictions	prediction	NOUN
cana-4579	84	45	correctly	correctly	ADV
cana-4579	84	46	.	.	PUNCT
cana-4579	85	1	figure	figure	NOUN
cana-4579	85	2	2	2	NUM
cana-4579	85	3	shows	show	VERB
cana-4579	85	4	a	a	DET
cana-4579	85	5	"	"	PUNCT
cana-4579	85	6	better	well	ADJ
cana-4579	85	7	"	"	PUNCT
cana-4579	85	8	and	and	CCONJ
cana-4579	85	9	"	"	PUNCT
cana-4579	85	10	worse	bad	ADJ
cana-4579	85	11	"	"	PUNCT
cana-4579	85	12	classifier	classifier	NOUN
cana-4579	85	13	in	in	ADP
cana-4579	85	14	roc	roc	PROPN
cana-4579	85	15	space	space	NOUN
cana-4579	85	16	(	(	PUNCT
cana-4579	85	17	source	source	NOUN
cana-4579	85	18	:	:	PUNCT
cana-4579	85	19	wikipedia	wikipedia	PROPN
cana-4579	85	20	)	)	PUNCT
cana-4579	85	21	communications	communication	NOUN
cana-4579	85	22	on	on	ADP
cana-4579	85	23	applied	apply	VERB
cana-4579	85	24	nonlinear	nonlinear	ADJ
cana-4579	85	25	analysis	analysis	NOUN
cana-4579	85	26	issn	issn	NOUN
cana-4579	85	27	:	:	PUNCT
cana-4579	85	28	1074	1074	NUM
cana-4579	85	29	-	-	PUNCT
cana-4579	85	30	133x	133x	NUM
cana-4579	85	31	vol	vol	NOUN
cana-4579	85	32	32	32	NUM
cana-4579	85	33	no	no	NOUN
cana-4579	85	34	.	.	PUNCT
cana-4579	86	1	9s	9s	NUM
cana-4579	86	2	(	(	PUNCT
cana-4579	86	3	2025	2025	NUM
cana-4579	86	4	)	)	PUNCT
cana-4579	86	5	2871	2871	NUM
cana-4579	86	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-4579	87	1	the	the	DET
cana-4579	87	2	degree	degree	NOUN
cana-4579	87	3	of	of	ADP
cana-4579	87	4	agreement	agreement	NOUN
cana-4579	87	5	between	between	ADP
cana-4579	87	6	the	the	DET
cana-4579	87	7	observed	observe	VERB
cana-4579	87	8	and	and	CCONJ
cana-4579	87	9	predicted	predict	VERB
cana-4579	87	10	classes	class	NOUN
cana-4579	87	11	was	be	AUX
cana-4579	87	12	then	then	ADV
cana-4579	87	13	visualized	visualize	VERB
cana-4579	87	14	using	use	VERB
cana-4579	87	15	cohen	cohen	PROPN
cana-4579	87	16	's	's	PART
cana-4579	87	17	kappa	kappa	PROPN
cana-4579	87	18	statistic	statistic	PROPN
cana-4579	87	19	,	,	PUNCT
cana-4579	87	20	which	which	PRON
cana-4579	87	21	was	be	AUX
cana-4579	87	22	used	use	VERB
cana-4579	87	23	to	to	PART
cana-4579	87	24	evaluate	evaluate	VERB
cana-4579	87	25	each	each	DET
cana-4579	87	26	model	model	NOUN
cana-4579	87	27	's	's	PART
cana-4579	87	28	performance	performance	NOUN
cana-4579	87	29	.	.	PUNCT
cana-4579	88	1	v.	v.	ADP
cana-4579	88	2	results	result	NOUN
cana-4579	88	3	&	&	CCONJ
cana-4579	88	4	discussion	discussion	NOUN
cana-4579	88	5	this	this	DET
cana-4579	88	6	part	part	NOUN
cana-4579	88	7	displays	display	VERB
cana-4579	88	8	the	the	DET
cana-4579	88	9	results	result	NOUN
cana-4579	88	10	and	and	CCONJ
cana-4579	88	11	analysis	analysis	NOUN
cana-4579	88	12	from	from	ADP
cana-4579	88	13	the	the	DET
cana-4579	88	14	training	training	NOUN
cana-4579	88	15	and	and	CCONJ
cana-4579	88	16	experiments	experiment	NOUN
cana-4579	88	17	.	.	PUNCT
cana-4579	89	1	a.	a.	NOUN
cana-4579	89	2	perceived	perceive	VERB
cana-4579	89	3	employability	employability	NOUN
cana-4579	89	4	prediction	prediction	NOUN
cana-4579	89	5	(	(	PUNCT
cana-4579	89	6	pre	pre	NOUN
cana-4579	89	7	-	-	NOUN
cana-4579	89	8	covid	covid	ADJ
cana-4579	89	9	):	):	PUNCT
cana-4579	89	10	the	the	DET
cana-4579	89	11	pre	pre	ADJ
cana-4579	89	12	-	-	ADJ
cana-4579	89	13	processing	processing	ADJ
cana-4579	89	14	techniques	technique	NOUN
cana-4579	89	15	altered	alter	VERB
cana-4579	89	16	the	the	DET
cana-4579	89	17	original	original	ADJ
cana-4579	89	18	dataset	dataset	NOUN
cana-4579	89	19	to	to	PART
cana-4579	89	20	prepare	prepare	VERB
cana-4579	89	21	it	it	PRON
cana-4579	89	22	for	for	ADP
cana-4579	89	23	analysis	analysis	NOUN
cana-4579	89	24	.	.	PUNCT
cana-4579	90	1	first	first	ADV
cana-4579	90	2	,	,	PUNCT
cana-4579	90	3	the	the	DET
cana-4579	90	4	missing	miss	VERB
cana-4579	90	5	values	value	NOUN
cana-4579	90	6	in	in	ADP
cana-4579	90	7	the	the	DET
cana-4579	90	8	dataset	dataset	NOUN
cana-4579	90	9	were	be	AUX
cana-4579	90	10	removed	remove	VERB
cana-4579	90	11	.	.	PUNCT
cana-4579	91	1	the	the	DET
cana-4579	91	2	missing	miss	VERB
cana-4579	91	3	values	value	NOUN
cana-4579	91	4	included	include	VERB
cana-4579	91	5	students	student	NOUN
cana-4579	91	6	who	who	PRON
cana-4579	91	7	dropped	drop	VERB
cana-4579	91	8	out	out	ADP
cana-4579	91	9	of	of	ADP
cana-4579	91	10	a	a	DET
cana-4579	91	11	security	security	NOUN
cana-4579	91	12	technology	technology	NOUN
cana-4579	91	13	course	course	NOUN
cana-4579	91	14	at	at	ADP
cana-4579	91	15	the	the	DET
cana-4579	91	16	institute	institute	NOUN
cana-4579	91	17	of	of	ADP
cana-4579	91	18	higher	high	ADJ
cana-4579	91	19	learning	learning	NOUN
cana-4579	91	20	(	(	PUNCT
cana-4579	91	21	ihl	ihl	PROPN
cana-4579	91	22	)	)	PUNCT
cana-4579	91	23	or	or	CCONJ
cana-4579	91	24	did	do	AUX
cana-4579	91	25	not	not	PART
cana-4579	91	26	finish	finish	VERB
cana-4579	91	27	their	their	PRON
cana-4579	91	28	internships	internship	NOUN
cana-4579	91	29	or	or	CCONJ
cana-4579	91	30	extracurricular	extracurricular	ADJ
cana-4579	91	31	activities	activity	NOUN
cana-4579	91	32	.	.	PUNCT
cana-4579	92	1	seven	seven	NUM
cana-4579	92	2	records	record	NOUN
cana-4579	92	3	—	—	PUNCT
cana-4579	92	4	a	a	DET
cana-4579	92	5	total	total	NOUN
cana-4579	92	6	of	of	ADP
cana-4579	92	7	282	282	NUM
cana-4579	92	8	records	record	NOUN
cana-4579	92	9	—	—	PUNCT
cana-4579	92	10	were	be	AUX
cana-4579	92	11	removed	remove	VERB
cana-4579	92	12	from	from	ADP
cana-4579	92	13	the	the	DET
cana-4579	92	14	original	original	ADJ
cana-4579	92	15	dataset	dataset	NOUN
cana-4579	92	16	at	at	ADP
cana-4579	92	17	this	this	DET
cana-4579	92	18	point	point	NOUN
cana-4579	92	19	.	.	PUNCT
cana-4579	93	1	from	from	ADP
cana-4579	93	2	the	the	DET
cana-4579	93	3	original	original	ADJ
cana-4579	93	4	dataset	dataset	NOUN
cana-4579	93	5	,	,	PUNCT
cana-4579	93	6	repetitive	repetitive	ADJ
cana-4579	93	7	variables	variable	NOUN
cana-4579	93	8	were	be	AUX
cana-4579	93	9	eliminated	eliminate	VERB
cana-4579	93	10	.	.	PUNCT
cana-4579	94	1	for	for	ADP
cana-4579	94	2	instance	instance	NOUN
cana-4579	94	3	,	,	PUNCT
cana-4579	94	4	the	the	DET
cana-4579	94	5	original	original	ADJ
cana-4579	94	6	dataset	dataset	NOUN
cana-4579	94	7	had	have	VERB
cana-4579	94	8	variables	variable	NOUN
cana-4579	94	9	for	for	ADP
cana-4579	94	10	name	name	NOUN
cana-4579	94	11	,	,	PUNCT
cana-4579	94	12	race	race	NOUN
cana-4579	94	13	,	,	PUNCT
cana-4579	94	14	and	and	CCONJ
cana-4579	94	15	student	student	NOUN
cana-4579	94	16	i	i	PROPN
cana-4579	94	17	d.	d.	PROPN
cana-4579	94	18	due	due	ADP
cana-4579	94	19	to	to	ADP
cana-4579	94	20	their	their	PRON
cana-4579	94	21	assistance	assistance	NOUN
cana-4579	94	22	in	in	ADP
cana-4579	94	23	the	the	DET
cana-4579	94	24	studies	study	NOUN
cana-4579	94	25	,	,	PUNCT
cana-4579	94	26	all	all	DET
cana-4579	94	27	three	three	NUM
cana-4579	94	28	of	of	ADP
cana-4579	94	29	the	the	DET
cana-4579	94	30	variables	variable	NOUN
cana-4579	94	31	were	be	AUX
cana-4579	94	32	eliminated	eliminate	VERB
cana-4579	94	33	from	from	ADP
cana-4579	94	34	the	the	DET
cana-4579	94	35	dataset	dataset	NOUN
cana-4579	94	36	.	.	PUNCT
cana-4579	95	1	in	in	ADP
cana-4579	95	2	addition	addition	NOUN
cana-4579	95	3	,	,	PUNCT
cana-4579	95	4	unnecessary	unnecessary	ADJ
cana-4579	95	5	variables	variable	NOUN
cana-4579	95	6	were	be	AUX
cana-4579	95	7	eliminated	eliminate	VERB
cana-4579	95	8	from	from	ADP
cana-4579	95	9	the	the	DET
cana-4579	95	10	initial	initial	ADJ
cana-4579	95	11	dataset	dataset	NOUN
cana-4579	95	12	.	.	PUNCT
cana-4579	96	1	for	for	ADP
cana-4579	96	2	instance	instance	NOUN
cana-4579	96	3	,	,	PUNCT
cana-4579	96	4	the	the	DET
cana-4579	96	5	first	first	ADJ
cana-4579	96	6	dataset	dataset	NOUN
cana-4579	96	7	had	have	VERB
cana-4579	96	8	details	detail	NOUN
cana-4579	96	9	on	on	ADP
cana-4579	96	10	the	the	DET
cana-4579	96	11	internship	internship	NOUN
cana-4579	96	12	company	company	NOUN
cana-4579	96	13	,	,	PUNCT
cana-4579	96	14	title	title	NOUN
cana-4579	96	15	,	,	PUNCT
cana-4579	96	16	and	and	CCONJ
cana-4579	96	17	salary	salary	NOUN
cana-4579	96	18	.	.	PUNCT
cana-4579	97	1	since	since	SCONJ
cana-4579	97	2	they	they	PRON
cana-4579	97	3	had	have	VERB
cana-4579	97	4	no	no	DET
cana-4579	97	5	effect	effect	NOUN
cana-4579	97	6	on	on	ADP
cana-4579	97	7	the	the	DET
cana-4579	97	8	investigation	investigation	NOUN
cana-4579	97	9	,	,	PUNCT
cana-4579	97	10	these	these	DET
cana-4579	97	11	variables	variable	NOUN
cana-4579	97	12	were	be	AUX
cana-4579	97	13	removed	remove	VERB
cana-4579	97	14	(	(	PUNCT
cana-4579	97	15	khaiser	khaiser	NOUN
cana-4579	97	16	,	,	PUNCT
cana-4579	97	17	f.	f.	PROPN
cana-4579	97	18	k.	k.	PROPN
cana-4579	97	19	,	,	PUNCT
cana-4579	97	20	saad	saad	PROPN
cana-4579	97	21	,	,	PUNCT
cana-4579	97	22	a.	a.	PROPN
cana-4579	97	23	,	,	PUNCT
cana-4579	97	24	&	&	CCONJ
cana-4579	97	25	mason	mason	PROPN
cana-4579	97	26	,	,	PUNCT
cana-4579	97	27	c.	c.	PROPN
cana-4579	97	28	,	,	PUNCT
cana-4579	97	29	2021	2021	NUM
cana-4579	97	30	)	)	PUNCT
cana-4579	97	31	.	.	PUNCT
cana-4579	98	1	lastly	lastly	ADV
cana-4579	98	2	,	,	PUNCT
cana-4579	98	3	the	the	DET
cana-4579	98	4	dataset	dataset	NOUN
cana-4579	98	5	was	be	AUX
cana-4579	98	6	made	make	VERB
cana-4579	98	7	easier	easy	ADJ
cana-4579	98	8	to	to	PART
cana-4579	98	9	analyze	analyze	VERB
cana-4579	98	10	by	by	ADP
cana-4579	98	11	making	make	VERB
cana-4579	98	12	changes	change	NOUN
cana-4579	98	13	to	to	ADP
cana-4579	98	14	the	the	DET
cana-4579	98	15	remaining	remain	VERB
cana-4579	98	16	variables	variable	NOUN
cana-4579	98	17	and	and	CCONJ
cana-4579	98	18	values	value	NOUN
cana-4579	98	19	.	.	PUNCT
cana-4579	99	1	for	for	ADP
cana-4579	99	2	the	the	DET
cana-4579	99	3	282	282	NUM
cana-4579	99	4	entries	entry	NOUN
cana-4579	99	5	in	in	ADP
cana-4579	99	6	this	this	DET
cana-4579	99	7	investigation	investigation	NOUN
cana-4579	99	8	,	,	PUNCT
cana-4579	99	9	a	a	DET
cana-4579	99	10	single	single	ADJ
cana-4579	99	11	course	course	NOUN
cana-4579	99	12	code	code	NOUN
cana-4579	99	13	was	be	AUX
cana-4579	99	14	applied	apply	VERB
cana-4579	99	15	.	.	PUNCT
cana-4579	100	1	the	the	DET
cana-4579	100	2	security	security	NOUN
cana-4579	100	3	technology	technology	PROPN
cana-4579	100	4	department	department	NOUN
cana-4579	100	5	is	be	AUX
cana-4579	100	6	reflected	reflect	VERB
cana-4579	100	7	in	in	ADP
cana-4579	100	8	the	the	DET
cana-4579	100	9	course	course	NOUN
cana-4579	100	10	code	code	NOUN
cana-4579	100	11	.	.	PUNCT
cana-4579	101	1	the	the	DET
cana-4579	101	2	characteristics	characteristic	NOUN
cana-4579	101	3	of	of	ADP
cana-4579	101	4	selective	selective	ADJ
cana-4579	101	5	programs	program	NOUN
cana-4579	101	6	,	,	PUNCT
cana-4579	101	7	centers	center	NOUN
cana-4579	101	8	,	,	PUNCT
cana-4579	101	9	and	and	CCONJ
cana-4579	101	10	student	student	NOUN
cana-4579	101	11	organizations	organization	NOUN
cana-4579	101	12	might	might	AUX
cana-4579	101	13	involve	involve	VERB
cana-4579	101	14	additional	additional	ADJ
cana-4579	101	15	computations	computation	NOUN
cana-4579	101	16	and	and	CCONJ
cana-4579	101	17	are	be	AUX
cana-4579	101	18	outside	outside	ADP
cana-4579	101	19	the	the	DET
cana-4579	101	20	purview	purview	NOUN
cana-4579	101	21	of	of	ADP
cana-4579	101	22	this	this	DET
cana-4579	101	23	study	study	NOUN
cana-4579	101	24	.	.	PUNCT
cana-4579	102	1	every	every	DET
cana-4579	102	2	variable	variable	NOUN
cana-4579	102	3	was	be	AUX
cana-4579	102	4	changed	change	VERB
cana-4579	102	5	to	to	ADP
cana-4579	102	6	a	a	DET
cana-4579	102	7	numerical	numerical	ADJ
cana-4579	102	8	value	value	NOUN
cana-4579	102	9	in	in	ADP
cana-4579	102	10	preparation	preparation	NOUN
cana-4579	102	11	for	for	ADP
cana-4579	102	12	data	datum	NOUN
cana-4579	102	13	cleaning	cleaning	NOUN
cana-4579	102	14	.	.	PUNCT
cana-4579	103	1	moreover	moreover	ADV
cana-4579	103	2	,	,	PUNCT
cana-4579	103	3	the	the	DET
cana-4579	103	4	dataset	dataset	NOUN
cana-4579	103	5	was	be	AUX
cana-4579	103	6	cleared	clear	VERB
cana-4579	103	7	of	of	ADP
cana-4579	103	8	twenty	twenty	NUM
cana-4579	103	9	percent	percent	NOUN
cana-4579	103	10	of	of	ADP
cana-4579	103	11	the	the	DET
cana-4579	103	12	records	record	NOUN
cana-4579	103	13	.	.	PUNCT
cana-4579	104	1	out	out	ADP
cana-4579	104	2	of	of	ADP
cana-4579	104	3	the	the	DET
cana-4579	104	4	56	56	NUM
cana-4579	104	5	records	record	NOUN
cana-4579	104	6	,	,	PUNCT
cana-4579	104	7	20	20	NUM
cana-4579	104	8	%	%	NOUN
cana-4579	104	9	assessed	assess	VERB
cana-4579	104	10	the	the	DET
cana-4579	104	11	machine	machine	NOUN
cana-4579	104	12	learning	learning	NOUN
cana-4579	104	13	models	model	NOUN
cana-4579	104	14	'	'	PART
cana-4579	104	15	performance	performance	NOUN
cana-4579	104	16	through	through	ADP
cana-4579	104	17	testing	testing	NOUN
cana-4579	104	18	;	;	PUNCT
cana-4579	104	19	as	as	ADP
cana-4579	104	20	a	a	DET
cana-4579	104	21	result	result	NOUN
cana-4579	104	22	,	,	PUNCT
cana-4579	104	23	those	those	DET
cana-4579	104	24	records	record	NOUN
cana-4579	104	25	were	be	AUX
cana-4579	104	26	excluded	exclude	VERB
cana-4579	104	27	from	from	ADP
cana-4579	104	28	the	the	DET
cana-4579	104	29	machine	machine	NOUN
cana-4579	104	30	learning	learn	VERB
cana-4579	104	31	model	model	NOUN
cana-4579	104	32	development	development	NOUN
cana-4579	104	33	process	process	NOUN
cana-4579	104	34	.	.	PUNCT
cana-4579	105	1	there	there	PRON
cana-4579	105	2	were	be	VERB
cana-4579	105	3	282	282	NUM
cana-4579	105	4	records	record	NOUN
cana-4579	105	5	in	in	ADP
cana-4579	105	6	the	the	DET
cana-4579	105	7	final	final	ADJ
cana-4579	105	8	preprocessed	preprocesse	VERB
cana-4579	105	9	dataset	dataset	NOUN
cana-4579	105	10	used	use	VERB
cana-4579	105	11	for	for	ADP
cana-4579	105	12	the	the	DET
cana-4579	105	13	analysis	analysis	NOUN
cana-4579	105	14	.	.	PUNCT
cana-4579	106	1	figure	figure	NOUN
cana-4579	106	2	3	3	NUM
cana-4579	106	3	pre	pre	ADJ
cana-4579	106	4	-	-	ADJ
cana-4579	106	5	covid	covid	ADJ
cana-4579	106	6	overall	overall	ADJ
cana-4579	106	7	analysis	analysis	NOUN
cana-4579	106	8	result	result	NOUN
cana-4579	106	9	communications	communication	NOUN
cana-4579	106	10	on	on	ADP
cana-4579	106	11	applied	apply	VERB
cana-4579	106	12	nonlinear	nonlinear	ADJ
cana-4579	106	13	analysis	analysis	NOUN
cana-4579	106	14	issn	issn	NOUN
cana-4579	106	15	:	:	PUNCT
cana-4579	106	16	1074	1074	NUM
cana-4579	106	17	-	-	PUNCT
cana-4579	106	18	133x	133x	NUM
cana-4579	106	19	vol	vol	NOUN
cana-4579	106	20	32	32	NUM
cana-4579	107	1	no	no	NOUN
cana-4579	107	2	.	.	PUNCT
cana-4579	108	1	9s	9s	NUM
cana-4579	108	2	(	(	PUNCT
cana-4579	108	3	2025	2025	NUM
cana-4579	108	4	)	)	PUNCT
cana-4579	108	5	2872	2872	NUM
cana-4579	108	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-4579	108	7	three	three	NUM
cana-4579	108	8	of	of	ADP
cana-4579	108	9	the	the	DET
cana-4579	108	10	nine	nine	NUM
cana-4579	108	11	models	model	NOUN
cana-4579	108	12	(	(	PUNCT
cana-4579	108	13	random	random	ADJ
cana-4579	108	14	forest	forest	NOUN
cana-4579	108	15	,	,	PUNCT
cana-4579	108	16	light	light	ADJ
cana-4579	108	17	gradient	gradient	ADJ
cana-4579	108	18	boost	boost	NOUN
cana-4579	108	19	,	,	PUNCT
cana-4579	108	20	and	and	CCONJ
cana-4579	108	21	artificial	artificial	ADJ
cana-4579	108	22	neural	neural	ADJ
cana-4579	108	23	networks	network	NOUN
cana-4579	108	24	)	)	PUNCT
cana-4579	108	25	had	have	VERB
cana-4579	108	26	particularly	particularly	ADV
cana-4579	108	27	high	high	ADJ
cana-4579	108	28	performance	performance	NOUN
cana-4579	108	29	.	.	PUNCT
cana-4579	109	1	the	the	DET
cana-4579	109	2	random	random	ADJ
cana-4579	109	3	forest	forest	NOUN
cana-4579	109	4	(	(	PUNCT
cana-4579	109	5	rf	rf	NOUN
cana-4579	109	6	)	)	PUNCT
cana-4579	109	7	,	,	PUNCT
cana-4579	109	8	light	light	ADJ
cana-4579	109	9	gradient	gradient	ADJ
cana-4579	109	10	boost	boost	NOUN
cana-4579	109	11	(	(	PUNCT
cana-4579	109	12	lgb	lgb	PROPN
cana-4579	109	13	)	)	PUNCT
cana-4579	109	14	,	,	PUNCT
cana-4579	109	15	and	and	CCONJ
cana-4579	109	16	artificial	artificial	ADJ
cana-4579	109	17	neural	neural	ADJ
cana-4579	109	18	network	network	NOUN
cana-4579	109	19	(	(	PUNCT
cana-4579	109	20	ann	ann	PROPN
cana-4579	109	21	)	)	PUNCT
cana-4579	109	22	algorithms	algorithm	NOUN
cana-4579	109	23	have	have	AUX
cana-4579	109	24	outperformed	outperform	VERB
cana-4579	109	25	the	the	DET
cana-4579	109	26	other	other	ADJ
cana-4579	109	27	six	six	NUM
cana-4579	109	28	models	model	NOUN
cana-4579	109	29	.	.	PUNCT
cana-4579	110	1	next	next	ADV
cana-4579	110	2	,	,	PUNCT
cana-4579	110	3	the	the	DET
cana-4579	110	4	two	two	NUM
cana-4579	110	5	selected	select	VERB
cana-4579	110	6	models	model	NOUN
cana-4579	110	7	,	,	PUNCT
cana-4579	110	8	random	random	ADJ
cana-4579	110	9	forest	forest	NOUN
cana-4579	110	10	and	and	CCONJ
cana-4579	110	11	extra	extra	ADJ
cana-4579	110	12	trees	tree	NOUN
cana-4579	110	13	,	,	PUNCT
cana-4579	110	14	are	be	AUX
cana-4579	110	15	to	to	PART
cana-4579	110	16	be	be	AUX
cana-4579	110	17	cross	cross	ADJ
cana-4579	110	18	-	-	ADJ
cana-4579	110	19	validated	validated	ADJ
cana-4579	110	20	using	use	VERB
cana-4579	110	21	the	the	DET
cana-4579	110	22	balanced	balanced	ADJ
cana-4579	110	23	accuracy	accuracy	NOUN
cana-4579	110	24	scores	score	NOUN
cana-4579	110	25	(	(	PUNCT
cana-4579	110	26	also	also	ADV
cana-4579	110	27	known	know	VERB
cana-4579	110	28	as	as	ADP
cana-4579	110	29	macro	macro	ADJ
cana-4579	110	30	average	average	ADJ
cana-4579	110	31	arithmetic	arithmetic	NOUN
cana-4579	110	32	)	)	PUNCT
cana-4579	110	33	,	,	PUNCT
cana-4579	110	34	which	which	PRON
cana-4579	110	35	are	be	AUX
cana-4579	110	36	computed	compute	VERB
cana-4579	110	37	as	as	ADP
cana-4579	110	38	the	the	DET
cana-4579	110	39	average	average	NOUN
cana-4579	110	40	of	of	ADP
cana-4579	110	41	the	the	DET
cana-4579	110	42	accurate	accurate	ADJ
cana-4579	110	43	hits	hit	NOUN
cana-4579	110	44	for	for	ADP
cana-4579	110	45	each	each	DET
cana-4579	110	46	class	class	NOUN
cana-4579	110	47	.	.	PUNCT
cana-4579	111	1	b.	b.	PROPN
cana-4579	111	2	perceived	perceive	VERB
cana-4579	111	3	employability	employability	NOUN
cana-4579	111	4	prediction	prediction	NOUN
cana-4579	111	5	(	(	PUNCT
cana-4579	111	6	covid	covid	PROPN
cana-4579	111	7	):	):	PUNCT
cana-4579	111	8	the	the	DET
cana-4579	111	9	original	original	ADJ
cana-4579	111	10	dataset	dataset	NOUN
cana-4579	111	11	was	be	AUX
cana-4579	111	12	altered	alter	VERB
cana-4579	111	13	using	use	VERB
cana-4579	111	14	pre	pre	ADJ
cana-4579	111	15	-	-	ADJ
cana-4579	111	16	processing	processing	ADJ
cana-4579	111	17	procedures	procedure	NOUN
cana-4579	111	18	to	to	PART
cana-4579	111	19	make	make	VERB
cana-4579	111	20	the	the	DET
cana-4579	111	21	data	datum	NOUN
cana-4579	111	22	ready	ready	ADJ
cana-4579	111	23	for	for	ADP
cana-4579	111	24	analysis	analysis	NOUN
cana-4579	111	25	.	.	PUNCT
cana-4579	112	1	initially	initially	ADV
cana-4579	112	2	,	,	PUNCT
cana-4579	112	3	the	the	DET
cana-4579	112	4	dataset	dataset	NOUN
cana-4579	112	5	's	's	PART
cana-4579	112	6	missing	miss	VERB
cana-4579	112	7	values	value	NOUN
cana-4579	112	8	were	be	AUX
cana-4579	112	9	eliminated	eliminate	VERB
cana-4579	112	10	.	.	PUNCT
cana-4579	113	1	students	student	NOUN
cana-4579	113	2	who	who	PRON
cana-4579	113	3	failed	fail	VERB
cana-4579	113	4	to	to	PART
cana-4579	113	5	submit	submit	VERB
cana-4579	113	6	information	information	NOUN
cana-4579	113	7	to	to	ADP
cana-4579	113	8	the	the	DET
cana-4579	113	9	institute	institute	NOUN
cana-4579	113	10	of	of	ADP
cana-4579	113	11	higher	high	ADJ
cana-4579	113	12	learning	learning	NOUN
cana-4579	113	13	(	(	PUNCT
cana-4579	113	14	ihl	ihl	PROPN
cana-4579	113	15	)	)	PUNCT
cana-4579	113	16	for	for	ADP
cana-4579	113	17	their	their	PRON
cana-4579	113	18	co	co	ADJ
cana-4579	113	19	-	-	ADJ
cana-4579	113	20	curricular	curricular	ADJ
cana-4579	113	21	activities	activity	NOUN
cana-4579	113	22	or	or	CCONJ
cana-4579	113	23	internships	internship	NOUN
cana-4579	113	24	in	in	ADP
cana-4579	113	25	a	a	DET
cana-4579	113	26	security	security	NOUN
cana-4579	113	27	technology	technology	NOUN
cana-4579	113	28	course	course	NOUN
cana-4579	113	29	were	be	AUX
cana-4579	113	30	among	among	ADP
cana-4579	113	31	the	the	DET
cana-4579	113	32	missing	miss	VERB
cana-4579	113	33	values	value	NOUN
cana-4579	113	34	.	.	PUNCT
cana-4579	114	1	in	in	ADP
cana-4579	114	2	total	total	ADJ
cana-4579	114	3	,	,	PUNCT
cana-4579	114	4	201	201	NUM
cana-4579	114	5	entries	entry	NOUN
cana-4579	114	6	were	be	AUX
cana-4579	114	7	removed	remove	VERB
cana-4579	114	8	from	from	ADP
cana-4579	114	9	the	the	DET
cana-4579	114	10	original	original	ADJ
cana-4579	114	11	dataset	dataset	NOUN
cana-4579	114	12	in	in	ADP
cana-4579	114	13	this	this	DET
cana-4579	114	14	step	step	NOUN
cana-4579	114	15	.	.	PUNCT
cana-4579	115	1	the	the	DET
cana-4579	115	2	original	original	ADJ
cana-4579	115	3	dataset	dataset	NOUN
cana-4579	115	4	's	's	PART
cana-4579	115	5	repeating	repeat	VERB
cana-4579	115	6	variables	variable	NOUN
cana-4579	115	7	were	be	AUX
cana-4579	115	8	then	then	ADV
cana-4579	115	9	eliminated	eliminate	VERB
cana-4579	115	10	.	.	PUNCT
cana-4579	116	1	for	for	ADP
cana-4579	116	2	instance	instance	NOUN
cana-4579	116	3	,	,	PUNCT
cana-4579	116	4	the	the	DET
cana-4579	116	5	original	original	ADJ
cana-4579	116	6	dataset	dataset	NOUN
cana-4579	116	7	had	have	VERB
cana-4579	116	8	variables	variable	NOUN
cana-4579	116	9	for	for	ADP
cana-4579	116	10	race	race	NOUN
cana-4579	116	11	,	,	PUNCT
cana-4579	116	12	student	student	NOUN
cana-4579	116	13	name	name	NOUN
cana-4579	116	14	,	,	PUNCT
cana-4579	116	15	and	and	CCONJ
cana-4579	116	16	student	student	NOUN
cana-4579	116	17	i	i	PROPN
cana-4579	116	18	d.	d.	PROPN
cana-4579	116	19	since	since	SCONJ
cana-4579	116	20	all	all	DET
cana-4579	116	21	three	three	NUM
cana-4579	116	22	of	of	ADP
cana-4579	116	23	these	these	DET
cana-4579	116	24	variables	variable	NOUN
cana-4579	116	25	are	be	AUX
cana-4579	116	26	not	not	PART
cana-4579	116	27	very	very	ADV
cana-4579	116	28	helpful	helpful	ADJ
cana-4579	116	29	in	in	ADP
cana-4579	116	30	the	the	DET
cana-4579	116	31	studies	study	NOUN
cana-4579	116	32	,	,	PUNCT
cana-4579	116	33	they	they	PRON
cana-4579	116	34	were	be	AUX
cana-4579	116	35	all	all	ADV
cana-4579	116	36	taken	take	VERB
cana-4579	116	37	out	out	ADP
cana-4579	116	38	of	of	ADP
cana-4579	116	39	the	the	DET
cana-4579	116	40	dataset	dataset	NOUN
cana-4579	116	41	.	.	PUNCT
cana-4579	117	1	furthermore	furthermore	ADV
cana-4579	117	2	,	,	PUNCT
cana-4579	117	3	unnecessary	unnecessary	ADJ
cana-4579	117	4	variables	variable	NOUN
cana-4579	117	5	were	be	AUX
cana-4579	117	6	eliminated	eliminate	VERB
cana-4579	117	7	from	from	ADP
cana-4579	117	8	the	the	DET
cana-4579	117	9	original	original	ADJ
cana-4579	117	10	dataset	dataset	NOUN
cana-4579	117	11	in	in	ADP
cana-4579	117	12	order	order	NOUN
cana-4579	117	13	to	to	PART
cana-4579	117	14	conduct	conduct	VERB
cana-4579	117	15	this	this	DET
cana-4579	117	16	analysis	analysis	NOUN
cana-4579	117	17	.	.	PUNCT
cana-4579	118	1	for	for	ADP
cana-4579	118	2	instance	instance	NOUN
cana-4579	118	3	,	,	PUNCT
cana-4579	118	4	the	the	DET
cana-4579	118	5	original	original	ADJ
cana-4579	118	6	dataset	dataset	NOUN
cana-4579	118	7	included	include	VERB
cana-4579	118	8	details	detail	NOUN
cana-4579	118	9	about	about	ADP
cana-4579	118	10	the	the	DET
cana-4579	118	11	title	title	NOUN
cana-4579	118	12	,	,	PUNCT
cana-4579	118	13	pay	pay	NOUN
cana-4579	118	14	,	,	PUNCT
cana-4579	118	15	and	and	CCONJ
cana-4579	118	16	internship	internship	NOUN
cana-4579	118	17	company	company	NOUN
cana-4579	118	18	.	.	PUNCT
cana-4579	119	1	these	these	DET
cana-4579	119	2	variables	variable	NOUN
cana-4579	119	3	were	be	AUX
cana-4579	119	4	eliminated	eliminate	VERB
cana-4579	119	5	because	because	SCONJ
cana-4579	119	6	they	they	PRON
cana-4579	119	7	are	be	AUX
cana-4579	119	8	not	not	PART
cana-4579	119	9	pertinent	pertinent	ADJ
cana-4579	119	10	to	to	ADP
cana-4579	119	11	the	the	DET
cana-4579	119	12	study	study	NOUN
cana-4579	119	13	.	.	PUNCT
cana-4579	120	1	figure	figure	VERB
cana-4579	120	2	4	4	NUM
cana-4579	120	3	covid	covid	NOUN
cana-4579	120	4	overall	overall	ADJ
cana-4579	120	5	analysis	analysis	NOUN
cana-4579	120	6	result	result	VERB
cana-4579	120	7	the	the	DET
cana-4579	120	8	next	next	ADJ
cana-4579	120	9	step	step	NOUN
cana-4579	120	10	involved	involve	VERB
cana-4579	120	11	cross	cross	ADJ
cana-4579	120	12	-	-	ADJ
cana-4579	120	13	validating	validate	VERB
cana-4579	120	14	every	every	DET
cana-4579	120	15	model	model	NOUN
cana-4579	120	16	with	with	ADP
cana-4579	120	17	the	the	DET
cana-4579	120	18	balanced	balanced	ADJ
cana-4579	120	19	accuracy	accuracy	NOUN
cana-4579	120	20	scores	score	NOUN
cana-4579	120	21	(	(	PUNCT
cana-4579	120	22	also	also	ADV
cana-4579	120	23	known	know	VERB
cana-4579	120	24	as	as	ADP
cana-4579	120	25	macro	macro	ADJ
cana-4579	120	26	average	average	NOUN
cana-4579	120	27	arithmetic)—which	arithmetic)—which	PUNCT
cana-4579	120	28	were	be	AUX
cana-4579	120	29	determined	determine	VERB
cana-4579	120	30	by	by	ADP
cana-4579	120	31	taking	take	VERB
cana-4579	120	32	the	the	DET
cana-4579	120	33	average	average	NOUN
cana-4579	120	34	of	of	ADP
cana-4579	120	35	the	the	DET
cana-4579	120	36	correct	correct	ADJ
cana-4579	120	37	hits	hit	VERB
cana-4579	120	38	for	for	ADP
cana-4579	120	39	every	every	DET
cana-4579	120	40	class	class	NOUN
cana-4579	120	41	.	.	PUNCT
cana-4579	121	1	the	the	DET
cana-4579	121	2	ada	ada	PROPN
cana-4579	121	3	boost	boost	PROPN
cana-4579	121	4	model	model	NOUN
cana-4579	121	5	was	be	AUX
cana-4579	121	6	outperformed	outperform	VERB
cana-4579	121	7	by	by	ADP
cana-4579	121	8	all	all	PRON
cana-4579	121	9	of	of	ADP
cana-4579	121	10	the	the	DET
cana-4579	121	11	techniques	technique	NOUN
cana-4579	121	12	(	(	PUNCT
cana-4579	121	13	khaiser	khaiser	NOUN
cana-4579	121	14	,	,	PUNCT
cana-4579	121	15	f.	f.	PROPN
cana-4579	121	16	k.	k.	PROPN
cana-4579	121	17	,	,	PUNCT
cana-4579	121	18	saad	saad	PROPN
cana-4579	121	19	,	,	PUNCT
cana-4579	121	20	a.	a.	PROPN
cana-4579	121	21	,	,	PUNCT
cana-4579	121	22	&	&	CCONJ
cana-4579	121	23	mason	mason	PROPN
cana-4579	121	24	,	,	PUNCT
cana-4579	121	25	c.	c.	PROPN
cana-4579	121	26	,	,	PUNCT
cana-4579	121	27	2023	2023	NUM
cana-4579	121	28	)	)	PUNCT
cana-4579	121	29	.	.	PUNCT
cana-4579	122	1	all	all	DET
cana-4579	122	2	things	thing	NOUN
cana-4579	122	3	considered	consider	VERB
cana-4579	122	4	,	,	PUNCT
cana-4579	122	5	the	the	DET
cana-4579	122	6	outcomes	outcome	NOUN
cana-4579	122	7	produced	produce	VERB
cana-4579	122	8	both	both	CCONJ
cana-4579	122	9	before	before	ADP
cana-4579	122	10	and	and	CCONJ
cana-4579	122	11	during	during	ADP
cana-4579	122	12	the	the	DET
cana-4579	122	13	covid	covid	NOUN
cana-4579	122	14	can	can	AUX
cana-4579	122	15	be	be	AUX
cana-4579	122	16	combined	combine	VERB
cana-4579	122	17	in	in	ADP
cana-4579	122	18	a	a	DET
cana-4579	122	19	table	table	NOUN
cana-4579	122	20	as	as	SCONJ
cana-4579	122	21	:	:	PUNCT
cana-4579	122	22	communications	communication	NOUN
cana-4579	122	23	on	on	ADP
cana-4579	122	24	applied	apply	VERB
cana-4579	122	25	nonlinear	nonlinear	ADJ
cana-4579	122	26	analysis	analysis	NOUN
cana-4579	122	27	issn	issn	NOUN
cana-4579	122	28	:	:	PUNCT
cana-4579	122	29	1074	1074	NUM
cana-4579	122	30	-	-	PUNCT
cana-4579	122	31	133x	133x	NUM
cana-4579	122	32	vol	vol	NOUN
cana-4579	122	33	32	32	NUM
cana-4579	122	34	no	no	NOUN
cana-4579	122	35	.	.	PUNCT
cana-4579	123	1	9s	9s	NUM
cana-4579	123	2	(	(	PUNCT
cana-4579	123	3	2025	2025	NUM
cana-4579	123	4	)	)	PUNCT
cana-4579	123	5	2873	2873	NUM
cana-4579	123	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-4579	123	7	table	table	NOUN
cana-4579	123	8	1	1	NUM
cana-4579	123	9	.	.	PUNCT
cana-4579	123	10	algorithms	algorithm	NOUN
cana-4579	123	11	’	'	PUNCT
cana-4579	123	12	performance	performance	NOUN
cana-4579	123	13	based	base	VERB
cana-4579	123	14	on	on	ADP
cana-4579	123	15	pre	pre	ADJ
cana-4579	123	16	-	-	ADJ
cana-4579	123	17	covid	covid	ADJ
cana-4579	123	18	and	and	CCONJ
cana-4579	123	19	covid	covid	PROPN
cana-4579	123	20	data	data	PROPN
cana-4579	123	21	.	.	PUNCT
cana-4579	124	1	knowing	know	VERB
cana-4579	124	2	about	about	ADP
cana-4579	124	3	recursive	recursive	ADJ
cana-4579	124	4	features	feature	NOUN
cana-4579	124	5	the	the	DET
cana-4579	124	6	discussion	discussion	NOUN
cana-4579	124	7	's	's	PART
cana-4579	124	8	primary	primary	ADJ
cana-4579	124	9	goal	goal	NOUN
cana-4579	124	10	is	be	AUX
cana-4579	124	11	elimination	elimination	NOUN
cana-4579	124	12	through	through	ADP
cana-4579	124	13	the	the	DET
cana-4579	124	14	application	application	NOUN
cana-4579	124	15	of	of	ADP
cana-4579	124	16	various	various	ADJ
cana-4579	124	17	machine	machine	NOUN
cana-4579	124	18	-	-	PUNCT
cana-4579	124	19	learning	learn	VERB
cana-4579	124	20	algorithms	algorithm	NOUN
cana-4579	124	21	,	,	PUNCT
cana-4579	124	22	and	and	CCONJ
cana-4579	124	23	it	it	PRON
cana-4579	124	24	is	be	AUX
cana-4579	124	25	based	base	VERB
cana-4579	124	26	on	on	ADP
cana-4579	124	27	the	the	DET
cana-4579	124	28	following	follow	VERB
cana-4579	124	29	concepts	concept	NOUN
cana-4579	124	30	:	:	PUNCT
cana-4579	125	1	1	1	X
cana-4579	125	2	.	.	X
cana-4579	125	3	the	the	DET
cana-4579	125	4	value	value	NOUN
cana-4579	125	5	of	of	ADP
cana-4579	125	6	feature	feature	NOUN
cana-4579	125	7	selection	selection	NOUN
cana-4579	125	8	using	use	VERB
cana-4579	125	9	rfe	rfe	NOUN
cana-4579	125	10	eliminating	eliminate	VERB
cana-4579	125	11	superfluous	superfluous	ADJ
cana-4579	125	12	or	or	CCONJ
cana-4579	125	13	redundant	redundant	ADJ
cana-4579	125	14	predictors	predictor	NOUN
cana-4579	125	15	is	be	AUX
cana-4579	125	16	required	require	VERB
cana-4579	125	17	to	to	PART
cana-4579	125	18	choose	choose	VERB
cana-4579	125	19	the	the	DET
cana-4579	125	20	optimal	optimal	ADJ
cana-4579	125	21	statistical	statistical	ADJ
cana-4579	125	22	or	or	CCONJ
cana-4579	125	23	machine	machine	NOUN
cana-4579	125	24	learning	learning	NOUN
cana-4579	125	25	model	model	NOUN
cana-4579	125	26	.	.	PUNCT
cana-4579	126	1	these	these	DET
cana-4579	126	2	predictors	predictor	NOUN
cana-4579	126	3	degrade	degrade	VERB
cana-4579	126	4	the	the	DET
cana-4579	126	5	performance	performance	NOUN
cana-4579	126	6	of	of	ADP
cana-4579	126	7	the	the	DET
cana-4579	126	8	model	model	NOUN
cana-4579	126	9	and	and	CCONJ
cana-4579	126	10	raise	raise	VERB
cana-4579	126	11	the	the	DET
cana-4579	126	12	standard	standard	ADJ
cana-4579	126	13	error	error	NOUN
cana-4579	126	14	of	of	ADP
cana-4579	126	15	the	the	DET
cana-4579	126	16	predicted	predict	VERB
cana-4579	126	17	regression	regression	NOUN
cana-4579	126	18	coefficients	coefficient	NOUN
cana-4579	126	19	.	.	PUNCT
cana-4579	127	1	it	it	PRON
cana-4579	127	2	is	be	AUX
cana-4579	127	3	possible	possible	ADJ
cana-4579	127	4	that	that	SCONJ
cana-4579	127	5	over	over	ADV
cana-4579	127	6	-	-	PUNCT
cana-4579	127	7	fitting	fitting	NOUN
cana-4579	127	8	occurs	occur	VERB
cana-4579	127	9	in	in	ADP
cana-4579	127	10	simple	simple	ADJ
cana-4579	127	11	statistical	statistical	ADJ
cana-4579	127	12	models	model	NOUN
cana-4579	127	13	,	,	PUNCT
cana-4579	127	14	such	such	ADJ
cana-4579	127	15	as	as	ADP
cana-4579	127	16	linear	linear	PROPN
cana-4579	127	17	regression	regression	NOUN
cana-4579	127	18	,	,	PUNCT
cana-4579	127	19	when	when	SCONJ
cana-4579	127	20	appropriate	appropriate	ADJ
cana-4579	127	21	model	model	NOUN
cana-4579	127	22	optimization	optimization	NOUN
cana-4579	127	23	techniques	technique	NOUN
cana-4579	127	24	,	,	PUNCT
cana-4579	127	25	including	include	VERB
cana-4579	127	26	feature	feature	NOUN
cana-4579	127	27	selection	selection	NOUN
cana-4579	127	28	and	and	CCONJ
cana-4579	127	29	parameter	parameter	NOUN
cana-4579	127	30	adjustment	adjustment	NOUN
cana-4579	127	31	,	,	PUNCT
cana-4579	127	32	are	be	AUX
cana-4579	127	33	neglected	neglect	VERB
cana-4579	127	34	.	.	PUNCT
cana-4579	128	1	according	accord	VERB
cana-4579	128	2	to	to	ADP
cana-4579	128	3	krzywinski	krzywinski	PROPN
cana-4579	128	4	et	et	PROPN
cana-4579	128	5	al	al	PROPN
cana-4579	128	6	.	.	PUNCT
cana-4579	129	1	(	(	PUNCT
cana-4579	129	2	2015	2015	NUM
cana-4579	129	3	)	)	PUNCT
cana-4579	129	4	,	,	PUNCT
cana-4579	129	5	poor	poor	ADJ
cana-4579	129	6	prediction	prediction	NOUN
cana-4579	129	7	capacity	capacity	NOUN
cana-4579	129	8	happens	happen	VERB
cana-4579	129	9	when	when	SCONJ
cana-4579	129	10	the	the	DET
cana-4579	129	11	number	number	NOUN
cana-4579	129	12	of	of	ADP
cana-4579	129	13	predictors	predictor	NOUN
cana-4579	129	14	is	be	AUX
cana-4579	129	15	close	close	ADJ
cana-4579	129	16	to	to	ADP
cana-4579	129	17	the	the	DET
cana-4579	129	18	sample	sample	NOUN
cana-4579	129	19	size	size	NOUN
cana-4579	129	20	and	and	CCONJ
cana-4579	129	21	the	the	DET
cana-4579	129	22	model	model	NOUN
cana-4579	129	23	is	be	AUX
cana-4579	129	24	fitted	fit	VERB
cana-4579	129	25	to	to	PART
cana-4579	129	26	noise	noise	VERB
cana-4579	129	27	.	.	PUNCT
cana-4579	130	1	2	2	X
cana-4579	130	2	.	.	X
cana-4579	130	3	the	the	DET
cana-4579	130	4	choice	choice	NOUN
cana-4579	130	5	of	of	ADP
cana-4579	130	6	machine	machine	NOUN
cana-4579	130	7	learning	learn	VERB
cana-4579	130	8	predictive	predictive	ADJ
cana-4579	130	9	models	model	NOUN
cana-4579	130	10	making	make	VERB
cana-4579	130	11	the	the	DET
cana-4579	130	12	most	most	ADJ
cana-4579	130	13	use	use	NOUN
cana-4579	130	14	of	of	ADP
cana-4579	130	15	machine	machine	NOUN
cana-4579	130	16	learning	learning	NOUN
cana-4579	130	17	-	-	PUNCT
cana-4579	130	18	related	relate	VERB
cana-4579	130	19	classification	classification	NOUN
cana-4579	130	20	approaches	approach	NOUN
cana-4579	130	21	was	be	AUX
cana-4579	130	22	essential	essential	ADJ
cana-4579	130	23	due	due	ADP
cana-4579	130	24	to	to	ADP
cana-4579	130	25	the	the	DET
cana-4579	130	26	multiclass	multiclass	ADJ
cana-4579	130	27	classification	classification	NOUN
cana-4579	130	28	complexity	complexity	NOUN
cana-4579	130	29	in	in	ADP
cana-4579	130	30	this	this	DET
cana-4579	130	31	study	study	NOUN
cana-4579	130	32	.	.	PUNCT
cana-4579	131	1	the	the	DET
cana-4579	131	2	models	model	NOUN
cana-4579	131	3	that	that	PRON
cana-4579	131	4	yielded	yield	VERB
cana-4579	131	5	the	the	DET
cana-4579	131	6	best	good	ADJ
cana-4579	131	7	predictions	prediction	NOUN
cana-4579	131	8	for	for	ADP
cana-4579	131	9	the	the	DET
cana-4579	131	10	pre	pre	NOUN
cana-4579	131	11	-	-	NOUN
cana-4579	131	12	covid	covid	ADJ
cana-4579	131	13	and	and	CCONJ
cana-4579	131	14	covid	covid	VERB
cana-4579	131	15	institutional	institutional	ADJ
cana-4579	131	16	datasets	dataset	NOUN
cana-4579	131	17	were	be	AUX
cana-4579	131	18	:	:	PUNCT
cana-4579	131	19	lightgbm	lightgbm	ADJ
cana-4579	131	20	,	,	PUNCT
cana-4579	131	21	adaboost	adaboost	ADV
cana-4579	131	22	,	,	PUNCT
cana-4579	131	23	random	random	ADJ
cana-4579	131	24	forests	forest	NOUN
cana-4579	131	25	,	,	PUNCT
cana-4579	131	26	decision	decision	NOUN
cana-4579	131	27	trees	tree	NOUN
cana-4579	131	28	,	,	PUNCT
cana-4579	131	29	artificial	artificial	ADJ
cana-4579	131	30	neural	neural	ADJ
cana-4579	131	31	networks	network	NOUN
cana-4579	131	32	(	(	PUNCT
cana-4579	131	33	ann	ann	PROPN
cana-4579	131	34	)	)	PUNCT
cana-4579	131	35	,	,	PUNCT
cana-4579	131	36	keras	keras	PROPN
cana-4579	131	37	-	-	PUNCT
cana-4579	131	38	constructed	construct	VERB
cana-4579	131	39	neural	neural	ADJ
cana-4579	131	40	networks	network	NOUN
cana-4579	131	41	,	,	PUNCT
cana-4579	131	42	svms	svms	NOUN
cana-4579	131	43	,	,	PUNCT
cana-4579	131	44	adaboost	adaboost	ADV
cana-4579	131	45	,	,	PUNCT
cana-4579	131	46	cat	cat	NOUN
cana-4579	131	47	boost	boost	NOUN
cana-4579	131	48	,	,	PUNCT
cana-4579	131	49	and	and	CCONJ
cana-4579	131	50	extremely	extremely	ADV
cana-4579	131	51	random	random	ADJ
cana-4579	131	52	trees	tree	NOUN
cana-4579	131	53	.	.	PUNCT
cana-4579	132	1	3	3	X
cana-4579	132	2	.	.	X
cana-4579	132	3	crucial	crucial	ADJ
cana-4579	132	4	determinants	determinant	NOUN
cana-4579	132	5	in	in	ADP
cana-4579	132	6	machine	machine	NOUN
cana-4579	132	7	learning	learning	NOUN
cana-4579	132	8	using	use	VERB
cana-4579	132	9	multiclass	multiclass	ADJ
cana-4579	132	10	classification	classification	NOUN
cana-4579	132	11	,	,	PUNCT
cana-4579	132	12	only	only	ADV
cana-4579	132	13	four	four	NUM
cana-4579	132	14	predictors	predictor	NOUN
cana-4579	132	15	were	be	AUX
cana-4579	132	16	found	find	VERB
cana-4579	132	17	to	to	PART
cana-4579	132	18	be	be	AUX
cana-4579	132	19	useful	useful	ADJ
cana-4579	132	20	in	in	ADP
cana-4579	132	21	predicting	predict	VERB
cana-4579	132	22	the	the	DET
cana-4579	132	23	dependent	dependent	ADJ
cana-4579	132	24	variable	variable	NOUN
cana-4579	132	25	for	for	ADP
cana-4579	132	26	the	the	DET
cana-4579	132	27	pre	pre	NOUN
cana-4579	132	28	-	-	ADJ
cana-4579	132	29	covid	covid	ADJ
cana-4579	132	30	and	and	CCONJ
cana-4579	132	31	covid	covid	PROPN
cana-4579	132	32	's	's	PART
cana-4579	132	33	institutional	institutional	ADJ
cana-4579	132	34	datasets	dataset	NOUN
cana-4579	132	35	.	.	PUNCT
cana-4579	133	1	predicting	predict	VERB
cana-4579	133	2	which	which	DET
cana-4579	133	3	independent	independent	ADJ
cana-4579	133	4	variable	variable	NOUN
cana-4579	133	5	will	will	AUX
cana-4579	133	6	have	have	AUX
cana-4579	133	7	the	the	DET
cana-4579	133	8	biggest	big	ADJ
cana-4579	133	9	impact	impact	NOUN
cana-4579	133	10	on	on	ADP
cana-4579	133	11	students	student	NOUN
cana-4579	133	12	'	'	PART
cana-4579	133	13	employability	employability	NOUN
cana-4579	133	14	is	be	AUX
cana-4579	133	15	also	also	ADV
cana-4579	133	16	essential	essential	ADJ
cana-4579	133	17	.	.	PUNCT
cana-4579	134	1	4	4	X
cana-4579	134	2	.	.	X
cana-4579	134	3	implications	implication	NOUN
cana-4579	134	4	of	of	ADP
cana-4579	134	5	the	the	DET
cana-4579	134	6	study	study	NOUN
cana-4579	134	7	for	for	ADP
cana-4579	134	8	theory	theory	NOUN
cana-4579	134	9	and	and	CCONJ
cana-4579	134	10	practice	practice	NOUN
cana-4579	134	11	prior	prior	ADV
cana-4579	134	12	to	to	ADP
cana-4579	134	13	employing	employ	VERB
cana-4579	134	14	the	the	DET
cana-4579	134	15	chosen	choose	VERB
cana-4579	134	16	model	model	NOUN
cana-4579	134	17	to	to	PART
cana-4579	134	18	predict	predict	VERB
cana-4579	134	19	students	student	NOUN
cana-4579	134	20	'	'	PART
cana-4579	134	21	employability	employability	NOUN
cana-4579	134	22	,	,	PUNCT
cana-4579	134	23	this	this	DET
cana-4579	134	24	study	study	NOUN
cana-4579	134	25	employed	employ	VERB
cana-4579	134	26	a	a	DET
cana-4579	134	27	variety	variety	NOUN
cana-4579	134	28	of	of	ADP
cana-4579	134	29	machine	machine	NOUN
cana-4579	134	30	-	-	PUNCT
cana-4579	134	31	learning	learn	VERB
cana-4579	134	32	techniques	technique	NOUN
cana-4579	134	33	to	to	PART
cana-4579	134	34	find	find	VERB
cana-4579	134	35	accurate	accurate	ADJ
cana-4579	134	36	models	model	NOUN
cana-4579	134	37	.	.	PUNCT
cana-4579	135	1	the	the	DET
cana-4579	135	2	next	next	ADJ
cana-4579	135	3	step	step	NOUN
cana-4579	135	4	involved	involve	VERB
cana-4579	135	5	using	use	VERB
cana-4579	135	6	recursive	recursive	ADJ
cana-4579	135	7	algorithms	algorithm	NOUN
cana-4579	135	8	’	'	PUNCT
cana-4579	135	9	performance	performance	NOUN
cana-4579	135	10	based	base	VERB
cana-4579	135	11	on	on	ADP
cana-4579	135	12	precovid	precovid	PROPN
cana-4579	135	13	&	&	CCONJ
cana-4579	135	14	covid	covid	PROPN
cana-4579	135	15	data	data	PROPN
cana-4579	135	16	s.no	s.no	PROPN
cana-4579	135	17	.	.	PROPN
cana-4579	135	18	algorithm	algorithm	PROPN
cana-4579	135	19	pre	pre	ADJ
cana-4579	135	20	-	-	ADJ
cana-4579	135	21	covid	covid	ADJ
cana-4579	135	22	f1	f1	NOUN
cana-4579	135	23	-	-	PUNCT
cana-4579	135	24	score	score	NOUN
cana-4579	135	25	covid	covid	NOUN
cana-4579	135	26	f1	f1	NOUN
cana-4579	135	27	-	-	PUNCT
cana-4579	135	28	score	score	NOUN
cana-4579	135	29	similarity	similarity	NOUN
cana-4579	135	30	1	1	NUM
cana-4579	135	31	ann	ann	PROPN
cana-4579	135	32	1.0	1.0	NUM
cana-4579	135	33	1.0	1.0	NUM
cana-4579	135	34	yes	yes	NOUN
cana-4579	135	35	2	2	NUM
cana-4579	135	36	lgb	lgb	PROPN
cana-4579	135	37	1.0	1.0	NUM
cana-4579	135	38	1.0	1.0	NUM
cana-4579	135	39	yes	yes	NOUN
cana-4579	135	40	3	3	NUM
cana-4579	135	41	cat	cat	NOUN
cana-4579	135	42	0.982	0.982	NUM
cana-4579	135	43	1.0	1.0	NUM
cana-4579	135	44	somewhat	somewhat	ADV
cana-4579	135	45	4	4	NUM
cana-4579	135	46	dt	dt	NOUN
cana-4579	135	47	0.982	0.982	NUM
cana-4579	135	48	1.0	1.0	NUM
cana-4579	135	49	somewhat	somewhat	ADV
cana-4579	135	50	5	5	NUM
cana-4579	135	51	ada	ada	NOUN
cana-4579	135	52	0.632	0.632	NUM
cana-4579	135	53	0.983	0.983	NUM
cana-4579	135	54	no	no	DET
cana-4579	135	55	6	6	NUM
cana-4579	135	56	svm	svm	NOUN
cana-4579	135	57	0.948	0.948	NUM
cana-4579	135	58	1.0	1.0	NUM
cana-4579	135	59	somewhat	somewhat	ADV
cana-4579	135	60	7	7	NUM
cana-4579	135	61	bag	bag	NOUN
cana-4579	135	62	0.972	0.972	NUM
cana-4579	135	63	1.0	1.0	NUM
cana-4579	135	64	somewhat	somewhat	ADV
cana-4579	135	65	8	8	NUM
cana-4579	135	66	rf	rf	NUM
cana-4579	135	67	1.0	1.0	NUM
cana-4579	135	68	1.0	1.0	NUM
cana-4579	135	69	yes	yes	INTJ
cana-4579	135	70	9	9	NUM
cana-4579	135	71	ext	ext	NOUN
cana-4579	135	72	0.982	0.982	NUM
cana-4579	135	73	1.0	1.0	NUM
cana-4579	135	74	somewhat	somewhat	ADV
cana-4579	135	75	ann	ann	PROPN
cana-4579	135	76	artificial	artificial	ADJ
cana-4579	135	77	neural	neural	ADJ
cana-4579	135	78	networks	network	NOUN
cana-4579	135	79	lgb	lgb	PROPN
cana-4579	135	80	light	light	NOUN
cana-4579	135	81	gradient	gradient	NOUN
cana-4579	135	82	boost	boost	VERB
cana-4579	135	83	cat	cat	NOUN
cana-4579	135	84	categorical	categorical	ADJ
cana-4579	135	85	boost	boost	NOUN
cana-4579	135	86	classifier	classifier	NOUN
cana-4579	135	87	dt	dt	ADP
cana-4579	135	88	decision	decision	NOUN
cana-4579	135	89	trees	tree	NOUN
cana-4579	135	90	ada	ada	PROPN
cana-4579	135	91	adaptive	adaptive	PROPN
cana-4579	135	92	boost	boost	NOUN
cana-4579	135	93	classifier	classifier	NOUN
cana-4579	135	94	svm	svm	ADJ
cana-4579	135	95	support	support	NOUN
cana-4579	135	96	vector	vector	NOUN
cana-4579	135	97	machine	machine	NOUN
cana-4579	135	98	bag	bag	NOUN
cana-4579	135	99	bagging	bag	VERB
cana-4579	135	100	classifier	classifier	NOUN
cana-4579	135	101	rf	rf	ADJ
cana-4579	135	102	random	random	ADJ
cana-4579	135	103	forest	forest	NOUN
cana-4579	135	104	ext	ext	NOUN
cana-4579	135	105	extreme	extreme	ADJ
cana-4579	135	106	gradient	gradient	NOUN
cana-4579	135	107	boost	boost	VERB
cana-4579	135	108	communications	communication	NOUN
cana-4579	135	109	on	on	ADP
cana-4579	135	110	applied	apply	VERB
cana-4579	135	111	nonlinear	nonlinear	ADJ
cana-4579	135	112	analysis	analysis	NOUN
cana-4579	135	113	issn	issn	NOUN
cana-4579	135	114	:	:	PUNCT
cana-4579	135	115	1074	1074	NUM
cana-4579	135	116	-	-	PUNCT
cana-4579	135	117	133x	133x	NUM
cana-4579	135	118	vol	vol	NOUN
cana-4579	135	119	32	32	NUM
cana-4579	135	120	no	no	NOUN
cana-4579	135	121	.	.	PUNCT
cana-4579	136	1	9s	9s	NUM
cana-4579	136	2	(	(	PUNCT
cana-4579	136	3	2025	2025	NUM
cana-4579	136	4	)	)	PUNCT
cana-4579	136	5	2874	2874	NUM
cana-4579	137	1	https://internationalpubls.com	https://internationalpubls.com	X
cana-4579	137	2	feature	feature	NOUN
cana-4579	137	3	elimination	elimination	NOUN
cana-4579	137	4	(	(	PUNCT
cana-4579	137	5	rfe	rfe	NOUN
cana-4579	137	6	)	)	PUNCT
cana-4579	137	7	to	to	PART
cana-4579	137	8	find	find	VERB
cana-4579	137	9	relevant	relevant	ADJ
cana-4579	137	10	,	,	PUNCT
cana-4579	137	11	important	important	ADJ
cana-4579	137	12	features	feature	NOUN
cana-4579	137	13	or	or	CCONJ
cana-4579	137	14	predictors	predictor	NOUN
cana-4579	137	15	.	.	PUNCT
cana-4579	138	1	it	it	PRON
cana-4579	138	2	offers	offer	VERB
cana-4579	138	3	understanding	understanding	NOUN
cana-4579	138	4	of	of	ADP
cana-4579	138	5	the	the	DET
cana-4579	138	6	statistical	statistical	ADJ
cana-4579	138	7	processes	process	NOUN
cana-4579	138	8	and	and	CCONJ
cana-4579	138	9	crucial	crucial	ADJ
cana-4579	138	10	elements	element	NOUN
cana-4579	138	11	to	to	PART
cana-4579	138	12	take	take	VERB
cana-4579	138	13	into	into	ADP
cana-4579	138	14	account	account	NOUN
cana-4579	138	15	when	when	SCONJ
cana-4579	138	16	forecasting	forecasting	NOUN
cana-4579	138	17	students	student	NOUN
cana-4579	138	18	'	'	PART
cana-4579	138	19	employability	employability	NOUN
cana-4579	138	20	in	in	ADP
cana-4579	138	21	postsecondary	postsecondary	ADJ
cana-4579	138	22	education	education	NOUN
cana-4579	138	23	.	.	PUNCT
cana-4579	139	1	in	in	ADP
cana-4579	139	2	order	order	NOUN
cana-4579	139	3	to	to	PART
cana-4579	139	4	prevent	prevent	VERB
cana-4579	139	5	the	the	DET
cana-4579	139	6	selected	select	VERB
cana-4579	139	7	model	model	NOUN
cana-4579	139	8	from	from	ADP
cana-4579	139	9	performing	perform	VERB
cana-4579	139	10	too	too	ADV
cana-4579	139	11	well	well	ADV
cana-4579	139	12	,	,	PUNCT
cana-4579	139	13	it	it	PRON
cana-4579	139	14	is	be	AUX
cana-4579	139	15	crucial	crucial	ADJ
cana-4579	139	16	to	to	PART
cana-4579	139	17	take	take	VERB
cana-4579	139	18	into	into	ADP
cana-4579	139	19	account	account	NOUN
cana-4579	139	20	pre	pre	ADJ
cana-4579	139	21	-	-	ADJ
cana-4579	139	22	processing	processing	ADJ
cana-4579	139	23	methods	method	NOUN
cana-4579	139	24	for	for	ADP
cana-4579	139	25	feature	feature	NOUN
cana-4579	139	26	selection	selection	NOUN
cana-4579	139	27	,	,	PUNCT
cana-4579	139	28	such	such	ADJ
cana-4579	139	29	as	as	ADP
cana-4579	139	30	rfe	rfe	NOUN
cana-4579	139	31	and	and	CCONJ
cana-4579	139	32	model	model	NOUN
cana-4579	139	33	accuracy	accuracy	NOUN
cana-4579	139	34	verification	verification	NOUN
cana-4579	139	35	with	with	ADP
cana-4579	139	36	testing	testing	NOUN
cana-4579	139	37	datasets	dataset	NOUN
cana-4579	139	38	as	as	ADP
cana-4579	139	39	routine	routine	ADJ
cana-4579	139	40	operations	operation	NOUN
cana-4579	139	41	.	.	PUNCT
cana-4579	140	1	the	the	DET
cana-4579	140	2	institute	institute	NOUN
cana-4579	140	3	of	of	ADP
cana-4579	140	4	higher	high	ADJ
cana-4579	140	5	learning	learning	NOUN
cana-4579	140	6	gained	gain	VERB
cana-4579	140	7	insights	insight	NOUN
cana-4579	140	8	from	from	ADP
cana-4579	140	9	the	the	DET
cana-4579	140	10	study	study	NOUN
cana-4579	140	11	's	's	PART
cana-4579	140	12	findings	finding	NOUN
cana-4579	140	13	about	about	ADP
cana-4579	140	14	what	what	PRON
cana-4579	140	15	areas	area	NOUN
cana-4579	140	16	to	to	PART
cana-4579	140	17	prioritize	prioritize	VERB
cana-4579	140	18	when	when	SCONJ
cana-4579	140	19	developing	develop	VERB
cana-4579	140	20	employability	employability	NOUN
cana-4579	140	21	-	-	PUNCT
cana-4579	140	22	related	relate	VERB
cana-4579	140	23	policies	policy	NOUN
cana-4579	140	24	that	that	PRON
cana-4579	140	25	will	will	AUX
cana-4579	140	26	also	also	ADV
cana-4579	140	27	help	help	VERB
cana-4579	140	28	students	student	NOUN
cana-4579	140	29	in	in	ADP
cana-4579	140	30	higher	high	ADJ
cana-4579	140	31	education	education	NOUN
cana-4579	140	32	reach	reach	VERB
cana-4579	140	33	higher	high	ADJ
cana-4579	140	34	skill	skill	NOUN
cana-4579	140	35	levels	level	NOUN
cana-4579	140	36	.	.	PUNCT
cana-4579	141	1	this	this	PRON
cana-4579	141	2	was	be	AUX
cana-4579	141	3	accomplished	accomplish	VERB
cana-4579	141	4	with	with	ADP
cana-4579	141	5	the	the	DET
cana-4579	141	6	use	use	NOUN
cana-4579	141	7	of	of	ADP
cana-4579	141	8	exact	exact	ADJ
cana-4579	141	9	significant	significant	ADJ
cana-4579	141	10	features	feature	NOUN
cana-4579	141	11	utilized	utilize	VERB
cana-4579	141	12	for	for	ADP
cana-4579	141	13	additional	additional	ADJ
cana-4579	141	14	research	research	NOUN
cana-4579	141	15	and	and	CCONJ
cana-4579	141	16	a	a	DET
cana-4579	141	17	more	more	ADV
cana-4579	141	18	accurate	accurate	ADJ
cana-4579	141	19	predictive	predictive	ADJ
cana-4579	141	20	model	model	NOUN
cana-4579	141	21	.	.	PUNCT
cana-4579	142	1	the	the	DET
cana-4579	142	2	predictive	predictive	ADJ
cana-4579	142	3	model	model	NOUN
cana-4579	142	4	put	put	VERB
cana-4579	142	5	forth	forth	ADP
cana-4579	142	6	by	by	ADP
cana-4579	142	7	hugo	hugo	PROPN
cana-4579	142	8	et	et	PROPN
cana-4579	142	9	al	al	PROPN
cana-4579	142	10	.	.	PUNCT
cana-4579	143	1	l.s	l.s	AUX
cana-4579	143	2	.	.	PROPN
cana-4579	144	1	(	(	PUNCT
cana-4579	144	2	2019	2019	NUM
cana-4579	144	3	)	)	PUNCT
cana-4579	144	4	is	be	AUX
cana-4579	144	5	supported	support	VERB
cana-4579	144	6	by	by	ADP
cana-4579	144	7	our	our	PRON
cana-4579	144	8	research	research	NOUN
cana-4579	144	9	.	.	PUNCT
cana-4579	145	1	5	5	X
cana-4579	145	2	.	.	X
cana-4579	145	3	limitations	limitation	NOUN
cana-4579	145	4	of	of	ADP
cana-4579	145	5	the	the	DET
cana-4579	145	6	case	case	NOUN
cana-4579	145	7	study	study	NOUN
cana-4579	145	8	it	it	PRON
cana-4579	145	9	is	be	AUX
cana-4579	145	10	crucial	crucial	ADJ
cana-4579	145	11	to	to	PART
cana-4579	145	12	remember	remember	VERB
cana-4579	145	13	that	that	SCONJ
cana-4579	145	14	the	the	DET
cana-4579	145	15	outcomes	outcome	NOUN
cana-4579	145	16	of	of	ADP
cana-4579	145	17	employing	employ	VERB
cana-4579	145	18	machine	machine	NOUN
cana-4579	145	19	learning	learning	NOUN
cana-4579	145	20	models	model	NOUN
cana-4579	145	21	for	for	ADP
cana-4579	145	22	prediction	prediction	NOUN
cana-4579	145	23	can	can	AUX
cana-4579	145	24	differ	differ	VERB
cana-4579	145	25	based	base	VERB
cana-4579	145	26	on	on	ADP
cana-4579	145	27	the	the	DET
cana-4579	145	28	dataset	dataset	NOUN
cana-4579	145	29	's	's	PART
cana-4579	145	30	properties	property	NOUN
cana-4579	145	31	,	,	PUNCT
cana-4579	145	32	including	include	VERB
cana-4579	145	33	the	the	DET
cana-4579	145	34	quantity	quantity	NOUN
cana-4579	145	35	of	of	ADP
cana-4579	145	36	predictors	predictor	NOUN
cana-4579	145	37	employed	employ	VERB
cana-4579	145	38	,	,	PUNCT
cana-4579	145	39	and	and	CCONJ
cana-4579	145	40	how	how	SCONJ
cana-4579	145	41	the	the	DET
cana-4579	145	42	model	model	NOUN
cana-4579	145	43	's	's	PART
cana-4579	145	44	parameters	parameter	NOUN
cana-4579	145	45	are	be	AUX
cana-4579	145	46	adjusted	adjust	VERB
cana-4579	145	47	.	.	PUNCT
cana-4579	146	1	to	to	PART
cana-4579	146	2	further	far	ADV
cana-4579	146	3	support	support	VERB
cana-4579	146	4	similar	similar	ADJ
cana-4579	146	5	conclusions	conclusion	NOUN
cana-4579	146	6	,	,	PUNCT
cana-4579	146	7	more	more	ADV
cana-4579	146	8	comparable	comparable	ADJ
cana-4579	146	9	studies	study	NOUN
cana-4579	146	10	with	with	ADP
cana-4579	146	11	larger	large	ADJ
cana-4579	146	12	or	or	CCONJ
cana-4579	146	13	equal	equal	ADJ
cana-4579	146	14	datasets	dataset	NOUN
cana-4579	146	15	are	be	AUX
cana-4579	146	16	needed	need	VERB
cana-4579	146	17	.	.	PUNCT
cana-4579	147	1	because	because	SCONJ
cana-4579	147	2	the	the	DET
cana-4579	147	3	current	current	ADJ
cana-4579	147	4	study	study	NOUN
cana-4579	147	5	was	be	AUX
cana-4579	147	6	done	do	VERB
cana-4579	147	7	at	at	ADP
cana-4579	147	8	a	a	DET
cana-4579	147	9	single	single	ADJ
cana-4579	147	10	institution	institution	NOUN
cana-4579	147	11	of	of	ADP
cana-4579	147	12	higher	high	ADJ
cana-4579	147	13	learning	learning	NOUN
cana-4579	147	14	,	,	PUNCT
cana-4579	147	15	its	its	PRON
cana-4579	147	16	findings	finding	NOUN
cana-4579	147	17	can	can	AUX
cana-4579	147	18	not	not	PART
cana-4579	147	19	be	be	AUX
cana-4579	147	20	extended	extend	VERB
cana-4579	147	21	to	to	ADP
cana-4579	147	22	institutions	institution	NOUN
cana-4579	147	23	outside	outside	ADP
cana-4579	147	24	of	of	ADP
cana-4579	147	25	singapore	singapore	PROPN
cana-4579	147	26	.	.	PUNCT
cana-4579	148	1	thus	thus	ADV
cana-4579	148	2	,	,	PUNCT
cana-4579	148	3	utilizing	utilize	VERB
cana-4579	148	4	deep	deep	ADJ
cana-4579	148	5	learning	learning	NOUN
cana-4579	148	6	,	,	PUNCT
cana-4579	148	7	future	future	ADJ
cana-4579	148	8	study	study	NOUN
cana-4579	148	9	may	may	AUX
cana-4579	148	10	examine	examine	VERB
cana-4579	148	11	the	the	DET
cana-4579	148	12	underlying	underlie	VERB
cana-4579	148	13	predictors	predictor	NOUN
cana-4579	148	14	of	of	ADP
cana-4579	148	15	employability	employability	NOUN
cana-4579	148	16	for	for	ADP
cana-4579	148	17	institutions	institution	NOUN
cana-4579	148	18	with	with	ADP
cana-4579	148	19	diverse	diverse	ADJ
cana-4579	148	20	histories	history	NOUN
cana-4579	148	21	.	.	PUNCT
cana-4579	149	1	ultimately	ultimately	ADV
cana-4579	149	2	,	,	PUNCT
cana-4579	149	3	out	out	ADP
cana-4579	149	4	of	of	ADP
cana-4579	149	5	all	all	DET
cana-4579	149	6	the	the	DET
cana-4579	149	7	criteria	criterion	NOUN
cana-4579	149	8	we	we	PRON
cana-4579	149	9	discussed	discuss	VERB
cana-4579	149	10	,	,	PUNCT
cana-4579	149	11	concentration	concentration	NOUN
cana-4579	149	12	was	be	AUX
cana-4579	149	13	the	the	DET
cana-4579	149	14	most	most	ADV
cana-4579	149	15	relevant	relevant	ADJ
cana-4579	149	16	and	and	CCONJ
cana-4579	149	17	vital	vital	ADJ
cana-4579	149	18	one	one	NUM
cana-4579	149	19	.	.	PUNCT
cana-4579	150	1	other	other	ADJ
cana-4579	150	2	little	little	ADJ
cana-4579	150	3	or	or	CCONJ
cana-4579	150	4	non	non	ADJ
cana-4579	150	5	-	-	ADJ
cana-4579	150	6	significant	significant	ADJ
cana-4579	150	7	variables	variable	NOUN
cana-4579	150	8	'	'	PART
cana-4579	150	9	influence	influence	NOUN
cana-4579	150	10	should	should	AUX
cana-4579	150	11	n't	not	PART
cana-4579	150	12	be	be	AUX
cana-4579	150	13	entirely	entirely	ADV
cana-4579	150	14	ignored	ignore	VERB
cana-4579	150	15	.	.	PUNCT
cana-4579	151	1	acknowledgment	acknowledgment	NOUN
cana-4579	151	2	in	in	ADP
cana-4579	151	3	the	the	DET
cana-4579	151	4	first	first	ADJ
cana-4579	151	5	place	place	NOUN
cana-4579	151	6	,	,	PUNCT
cana-4579	151	7	i	i	PRON
cana-4579	151	8	would	would	AUX
cana-4579	151	9	want	want	VERB
cana-4579	151	10	to	to	PART
cana-4579	151	11	thank	thank	VERB
cana-4579	151	12	god	god	PROPN
cana-4579	151	13	,	,	PUNCT
cana-4579	151	14	my	my	PRON
cana-4579	151	15	family	family	NOUN
cana-4579	151	16	,	,	PUNCT
cana-4579	151	17	and	and	CCONJ
cana-4579	151	18	drs	drs	PROPN
cana-4579	151	19	.	.	PROPN
cana-4579	151	20	cordelia	cordelia	PROPN
cana-4579	151	21	mason	mason	PROPN
cana-4579	151	22	and	and	CCONJ
cana-4579	151	23	amna	amna	PROPN
cana-4579	151	24	saad	saad	PROPN
cana-4579	151	25	,	,	PUNCT
cana-4579	151	26	my	my	PRON
cana-4579	151	27	supervisors	supervisor	NOUN
cana-4579	151	28	,	,	PUNCT
cana-4579	151	29	for	for	ADP
cana-4579	151	30	their	their	PRON
cana-4579	151	31	continuous	continuous	ADJ
cana-4579	151	32	support	support	NOUN
cana-4579	151	33	in	in	ADP
cana-4579	151	34	pushing	push	VERB
cana-4579	151	35	me	i	PRON
cana-4579	151	36	to	to	PART
cana-4579	151	37	publish	publish	VERB
cana-4579	151	38	journal	journal	NOUN
cana-4579	151	39	papers	paper	NOUN
cana-4579	151	40	,	,	PUNCT
cana-4579	151	41	which	which	PRON
cana-4579	151	42	is	be	AUX
cana-4579	151	43	really	really	ADV
cana-4579	151	44	helping	help	VERB
cana-4579	151	45	.	.	PUNCT
cana-4579	152	1	i	i	PRON
cana-4579	152	2	also	also	ADV
cana-4579	152	3	thank	thank	VERB
cana-4579	152	4	my	my	PRON
cana-4579	152	5	university	university	NOUN
cana-4579	152	6	,	,	PUNCT
cana-4579	152	7	universiti	universiti	PROPN
cana-4579	152	8	kuala	kuala	PROPN
cana-4579	152	9	lumpur	lumpur	PROPN
cana-4579	152	10	,	,	PUNCT
cana-4579	152	11	for	for	ADP
cana-4579	152	12	sponsoring	sponsor	VERB
cana-4579	152	13	this	this	DET
cana-4579	152	14	work	work	NOUN
cana-4579	152	15	.	.	PUNCT
cana-4579	153	1	references	reference	NOUN
cana-4579	153	2	1	1	NUM
cana-4579	153	3	.	.	X
cana-4579	154	1	aam	aam	PROPN
cana-4579	154	2	,	,	PUNCT
cana-4579	154	3	alamsyah	alamsyah	NOUN
cana-4579	154	4	(	(	PUNCT
cana-4579	154	5	2022	2022	NUM
cana-4579	154	6	)	)	PUNCT
cana-4579	154	7	.	.	PUNCT
cana-4579	155	1	measuring	measure	VERB
cana-4579	155	2	potential	potential	ADJ
cana-4579	155	3	employability	employability	NOUN
cana-4579	155	4	of	of	ADP
cana-4579	155	5	being	be	AUX
cana-4579	155	6	english	english	ADJ
cana-4579	155	7	literature	literature	NOUN
cana-4579	155	8	graduates	graduate	NOUN
cana-4579	155	9	.	.	PUNCT
cana-4579	156	1	doi	doi	NOUN
cana-4579	156	2	:	:	PUNCT
cana-4579	156	3	10.4108	10.4108	NUM
cana-4579	156	4	/	/	SYM
cana-4579	156	5	eai.14	eai.14	NOUN
cana-4579	156	6	-	-	ADJ
cana-4579	156	7	8	8	NUM
cana-4579	156	8	-	-	PUNCT
cana-4579	156	9	2021.2317608	2021.2317608	NUM
cana-4579	156	10	.	.	PUNCT
cana-4579	157	1	2	2	X
cana-4579	157	2	.	.	X
cana-4579	157	3	aniss	aniss	PROPN
cana-4579	157	4	,	,	PUNCT
cana-4579	157	5	moumen	mouman	NOUN
cana-4579	157	6	.	.	PUNCT
cana-4579	157	7	,	,	PUNCT
cana-4579	157	8	el	el	PROPN
cana-4579	157	9	,	,	PUNCT
cana-4579	157	10	houcine	houcine	NOUN
cana-4579	157	11	,	,	PUNCT
cana-4579	157	12	bouchama	bouchama	PROPN
cana-4579	157	13	.	.	PUNCT
cana-4579	157	14	,	,	PUNCT
cana-4579	157	15	younes	younes	PROPN
cana-4579	157	16	,	,	PUNCT
cana-4579	157	17	el	el	PROPN
cana-4579	157	18	,	,	PUNCT
cana-4579	157	19	bouzekri	bouzekri	PROPN
cana-4579	157	20	,	,	PUNCT
cana-4579	157	21	el	el	PROPN
cana-4579	157	22	,	,	PUNCT
cana-4579	157	23	idirissi	idirissi	PROPN
cana-4579	157	24	(	(	PUNCT
cana-4579	157	25	2020	2020	NUM
cana-4579	157	26	)	)	PUNCT
cana-4579	157	27	.	.	PUNCT
cana-4579	158	1	data	datum	NOUN
cana-4579	158	2	mining	mining	NOUN
cana-4579	158	3	techniques	technique	NOUN
cana-4579	158	4	for	for	ADP
cana-4579	158	5	employability	employability	NOUN
cana-4579	158	6	:	:	PUNCT
cana-4579	158	7	systematic	systematic	ADJ
cana-4579	158	8	literature	literature	PROPN
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cana-4579	161	2	.	.	X
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cana-4579	162	4	(	(	PUNCT
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cana-4579	162	6	)	)	PUNCT
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cana-4579	162	12	,	,	PUNCT
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cana-4579	164	12	.	.	PUNCT
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cana-4579	165	5	,	,	PUNCT
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cana-4579	165	7	)	)	PUNCT
cana-4579	165	8	,	,	PUNCT
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cana-4579	165	10	.	.	NOUN
cana-4579	165	11	5	5	NUM
cana-4579	165	12	.	.	X
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cana-4579	166	2	:	:	PUNCT
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cana-4579	166	11	.	.	PUNCT
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cana-4579	167	4	.	.	PUNCT
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cana-4579	169	8	:	:	PUNCT
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cana-4579	169	10	-	-	PUNCT
cana-4579	169	11	133x	133x	NUM
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cana-4579	170	2	(	(	PUNCT
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cana-4579	170	4	)	)	PUNCT
cana-4579	170	5	2875	2875	NUM
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cana-4579	170	8	.	.	PUNCT
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cana-4579	170	10	,	,	PUNCT
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cana-4579	170	12	,	,	PUNCT
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cana-4579	170	19	,	,	PUNCT
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cana-4579	170	21	.	.	PUNCT
cana-4579	170	22	,	,	PUNCT
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cana-4579	170	24	,	,	PUNCT
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cana-4579	170	30	)	)	PUNCT
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cana-4579	171	6	'	'	PART
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cana-4579	171	8	:	:	PUNCT
cana-4579	171	9	a	a	DET
cana-4579	171	10	systematic	systematic	ADJ
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cana-4579	171	13	.	.	PUNCT
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cana-4579	172	6	(	(	PUNCT
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cana-4579	172	9	,	,	PUNCT
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cana-4579	172	11	:	:	PUNCT
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cana-4579	173	2	.	.	X
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cana-4579	173	8	)	)	PUNCT
cana-4579	173	9	.	.	PUNCT
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cana-4579	174	2	employment	employment	NOUN
cana-4579	174	3	through	through	ADP
cana-4579	174	4	machine	machine	NOUN
cana-4579	174	5	learning	learning	NOUN
cana-4579	174	6	.	.	PUNCT
cana-4579	175	1	https://www.naceweb.org/career-development/trends-and-predictions/predicting-employmentthrough-machine-learning/.	https://www.naceweb.org/career-development/trends-and-predictions/predicting-employmentthrough-machine-learning/.	NOUN
cana-4579	175	2	8	8	X
cana-4579	175	3	.	.	PUNCT
cana-4579	176	1	jeon	jeon	PROPN
cana-4579	176	2	,	,	PUNCT
cana-4579	176	3	h.	h.	PROPN
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cana-4579	176	6	oh	oh	INTJ
cana-4579	176	7	,	,	PUNCT
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cana-4579	176	12	.	.	PUNCT
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cana-4579	177	6	for	for	ADP
cana-4579	177	7	efficient	efficient	ADJ
cana-4579	177	8	feature	feature	NOUN
cana-4579	177	9	selection	selection	NOUN
cana-4579	177	10	.	.	PUNCT
cana-4579	178	1	applied	apply	VERB
cana-4579	178	2	sciences	science	NOUN
cana-4579	178	3	,	,	PUNCT
cana-4579	178	4	10(9	10(9	NUM
cana-4579	178	5	)	)	PUNCT
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cana-4579	178	8	.	.	PUNCT
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cana-4579	179	9	.	.	X
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cana-4579	179	23	)	)	PUNCT
cana-4579	179	24	,	,	PUNCT
cana-4579	179	25	"	"	PUNCT
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cana-4579	179	43	conference	conference	NOUN
cana-4579	179	44	on	on	ADP
cana-4579	179	45	ubiquitous	ubiquitous	ADJ
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cana-4579	179	48	and	and	CCONJ
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cana-4579	179	50	(	(	PUNCT
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cana-4579	179	52	)	)	PUNCT
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cana-4579	180	1	1	1	NUM
cana-4579	180	2	-	-	SYM
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cana-4579	180	4	,	,	PUNCT
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cana-4579	181	2	.	.	PUNCT
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cana-4579	183	28	9789672880059	9789672880059	NUM
cana-4579	183	29	.	.	PUNCT
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cana-4579	184	3	.	.	PUNCT
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cana-4579	189	2	.	.	PUNCT
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cana-4579	191	3	)	)	PUNCT
cana-4579	191	4	.	.	PUNCT
cana-4579	192	1	systematic	systematic	ADJ
cana-4579	192	2	literature	literature	NOUN
cana-4579	192	3	reviews	review	NOUN
cana-4579	192	4	of	of	ADP
cana-4579	192	5	marketability	marketability	NOUN
cana-4579	192	6	and	and	CCONJ
cana-4579	192	7	employability	employability	NOUN
cana-4579	192	8	of	of	ADP
cana-4579	192	9	graduates	graduate	NOUN
cana-4579	192	10	.	.	PUNCT
cana-4579	193	1	international	international	ADJ
cana-4579	193	2	journal	journal	PROPN
cana-4579	193	3	of	of	ADP
cana-4579	193	4	academic	academic	ADJ
cana-4579	193	5	research	research	NOUN
cana-4579	193	6	in	in	ADP
cana-4579	193	7	economics	economic	NOUN
cana-4579	193	8	and	and	CCONJ
cana-4579	193	9	management	management	NOUN
cana-4579	193	10	sciences	science	NOUN
cana-4579	193	11	,	,	PUNCT
cana-4579	193	12	doi	doi	NOUN
cana-4579	193	13	:	:	PUNCT
cana-4579	193	14	10.6007	10.6007	NUM
cana-4579	193	15	/	/	SYM
cana-4579	193	16	ijarems	ijarem	NOUN
cana-4579	193	17	/	/	SYM
cana-4579	193	18	v11	v11	NOUN
cana-4579	193	19	-	-	PUNCT
cana-4579	193	20	i1/12278	i1/12278	ADJ
cana-4579	193	21	.	.	PUNCT
cana-4579	194	1	13	13	NUM
cana-4579	194	2	.	.	PUNCT
cana-4579	195	1	renato	renato	PROPN
cana-4579	195	2	,	,	PUNCT
cana-4579	195	3	r.	r.	PROPN
cana-4579	195	4	,	,	PUNCT
cana-4579	195	5	maaliw	maaliw	PROPN
cana-4579	195	6	.	.	PUNCT
cana-4579	195	7	,	,	PUNCT
cana-4579	195	8	karen	karen	PROPN
cana-4579	195	9	,	,	PUNCT
cana-4579	195	10	anne	anne	PROPN
cana-4579	195	11	,	,	PUNCT
cana-4579	195	12	quing	que	VERB
cana-4579	195	13	.	.	PROPN
cana-4579	195	14	,	,	PUNCT
cana-4579	195	15	ace	ace	PROPN
cana-4579	195	16	,	,	PUNCT
cana-4579	195	17	c.	c.	PROPN
cana-4579	195	18	,	,	PUNCT
cana-4579	195	19	lagman	lagman	NOUN
cana-4579	195	20	.	.	PROPN
cana-4579	195	21	,	,	PUNCT
cana-4579	195	22	bernard	bernard	PROPN
cana-4579	195	23	,	,	PUNCT
cana-4579	195	24	ugalde	ugalde	PROPN
cana-4579	195	25	.	.	PROPN
cana-4579	195	26	,	,	PUNCT
cana-4579	195	27	melvin	melvin	PROPN
cana-4579	195	28	,	,	PUNCT
cana-4579	195	29	a.	a.	PROPN
cana-4579	195	30	,	,	PUNCT
cana-4579	195	31	ballera	ballera	NOUN
cana-4579	195	32	.	.	PUNCT
cana-4579	195	33	,	,	PUNCT
cana-4579	195	34	michael	michael	PROPN
cana-4579	195	35	,	,	PUNCT
cana-4579	195	36	angelo	angelo	PROPN
cana-4579	195	37	,	,	PUNCT
cana-4579	195	38	d.	d.	PROPN
cana-4579	195	39	,	,	PUNCT
cana-4579	195	40	ligayo	ligayo	VERB
cana-4579	195	41	.	.	PUNCT
cana-4579	196	1	(	(	PUNCT
cana-4579	196	2	2022	2022	NUM
cana-4579	196	3	)	)	PUNCT
cana-4579	196	4	.	.	PUNCT
cana-4579	197	1	employability	employability	NOUN
cana-4579	197	2	prediction	prediction	NOUN
cana-4579	197	3	of	of	ADP
cana-4579	197	4	engineering	engineering	NOUN
cana-4579	197	5	graduates	graduate	NOUN
cana-4579	197	6	using	use	VERB
cana-4579	197	7	ensemble	ensemble	ADJ
cana-4579	197	8	classification	classification	NOUN
cana-4579	197	9	modeling	modeling	NOUN
cana-4579	197	10	.	.	PUNCT
cana-4579	198	1	doi	doi	NOUN
cana-4579	198	2	:	:	PUNCT
cana-4579	198	3	10.1109	10.1109	NUM
cana-4579	198	4	/	/	SYM
cana-4579	198	5	ccwc54503.2022.9720783	ccwc54503.2022.9720783	PROPN
cana-4579	198	6	.	.	PUNCT
cana-4579	199	1	http://dx.doi.org/10.3390/app10093211	http://dx.doi.org/10.3390/app10093211	X
cana-4579	199	2	http://press.utp.edu.my/index.php/icare21/?utm_medium=poster	http://press.utp.edu.my/index.php/icare21/?utm_medium=poster	NOUN