id	sid	tid	token	lemma	pos
bracis-28401	1	1	estimating	estimate	VERB
bracis-28401	1	2	code	code	NOUN
bracis-28401	1	3	running	running	NOUN
bracis-28401	1	4	time	time	NOUN
bracis-28401	1	5	complexity	complexity	NOUN
bracis-28401	1	6	with	with	ADP
bracis-28401	1	7	 	 	SPACE
bracis-28401	1	8	machine	machine	NOUN
bracis-28401	1	9	learning	learn	VERB
bracis-28401	1	10	|	|	ADV
bracis-28401	1	11	springer	springer	NOUN
bracis-28401	1	12	nature	nature	PROPN
bracis-28401	1	13	link	link	PROPN
bracis-28401	1	14	(	(	PUNCT
bracis-28401	1	15	formerly	formerly	ADV
bracis-28401	1	16	springerlink	springerlink	NOUN
bracis-28401	1	17	)	)	PUNCT
bracis-28401	1	18	skip	skip	VERB
bracis-28401	1	19	to	to	ADP
bracis-28401	1	20	main	main	ADJ
bracis-28401	1	21	content	content	NOUN
bracis-28401	1	22	advertisement	advertisement	NOUN
bracis-28401	1	23	log	log	NOUN
bracis-28401	1	24	in	in	ADP
bracis-28401	1	25	menu	menu	NOUN
bracis-28401	1	26	find	find	VERB
bracis-28401	1	27	a	a	DET
bracis-28401	1	28	journal	journal	NOUN
bracis-28401	1	29	publish	publish	VERB
bracis-28401	1	30	with	with	ADP
bracis-28401	1	31	us	we	PRON
bracis-28401	1	32	track	track	VERB
bracis-28401	1	33	your	your	PRON
bracis-28401	1	34	research	research	NOUN
bracis-28401	1	35	search	search	NOUN
bracis-28401	1	36	cart	cart	NOUN
bracis-28401	1	37	home	home	NOUN
bracis-28401	1	38	intelligent	intelligent	ADJ
bracis-28401	1	39	systems	system	NOUN
bracis-28401	1	40	conference	conference	NOUN
bracis-28401	1	41	paper	paper	NOUN
bracis-28401	1	42	estimating	estimate	VERB
bracis-28401	1	43	code	code	NOUN
bracis-28401	1	44	running	running	NOUN
bracis-28401	1	45	time	time	NOUN
bracis-28401	1	46	complexity	complexity	NOUN
bracis-28401	1	47	with	with	ADP
bracis-28401	1	48	 	 	SPACE
bracis-28401	1	49	machine	machine	NOUN
bracis-28401	1	50	learning	learn	VERB
bracis-28401	1	51	conference	conference	NOUN
bracis-28401	1	52	paper	paper	NOUN
bracis-28401	1	53	first	first	ADV
bracis-28401	1	54	online	online	ADV
bracis-28401	1	55	:	:	PUNCT
bracis-28401	1	56	12	12	NUM
bracis-28401	1	57	october	october	NOUN
bracis-28401	1	58	2023	2023	NUM
bracis-28401	1	59	pp	pp	PROPN
bracis-28401	1	60	400–414	400–414	NUM
bracis-28401	1	61	cite	cite	VERB
bracis-28401	1	62	this	this	DET
bracis-28401	1	63	conference	conference	NOUN
bracis-28401	1	64	paper	paper	NOUN
bracis-28401	1	65	access	access	NOUN
bracis-28401	1	66	provided	provide	VERB
bracis-28401	1	67	by	by	ADP
bracis-28401	1	68	university	university	PROPN
bracis-28401	1	69	of	of	ADP
bracis-28401	1	70	notre	notre	PROPN
bracis-28401	1	71	dame	dame	PROPN
bracis-28401	1	72	hesburgh	hesburgh	PROPN
bracis-28401	1	73	library	library	PROPN
bracis-28401	1	74	download	download	PROPN
bracis-28401	1	75	book	book	NOUN
bracis-28401	1	76	pdf	pdf	PROPN
bracis-28401	1	77	download	download	NOUN
bracis-28401	1	78	book	book	NOUN
bracis-28401	1	79	epub	epub	PROPN
bracis-28401	1	80	intelligent	intelligent	ADJ
bracis-28401	1	81	systems	system	NOUN
bracis-28401	1	82	(	(	PUNCT
bracis-28401	1	83	bracis	bracis	NOUN
bracis-28401	1	84	2023	2023	NUM
bracis-28401	1	85	)	)	PUNCT
bracis-28401	1	86	estimating	estimate	VERB
bracis-28401	1	87	code	code	NOUN
bracis-28401	1	88	running	running	NOUN
bracis-28401	1	89	time	time	NOUN
bracis-28401	1	90	complexity	complexity	NOUN
bracis-28401	1	91	with	with	ADP
bracis-28401	1	92	 	 	SPACE
bracis-28401	1	93	machine	machine	NOUN
bracis-28401	1	94	learning	learning	NOUN
bracis-28401	1	95	download	download	PROPN
bracis-28401	1	96	book	book	NOUN
bracis-28401	1	97	pdf	pdf	PROPN
bracis-28401	1	98	download	download	NOUN
bracis-28401	1	99	book	book	PROPN
bracis-28401	1	100	epub	epub	PROPN
bracis-28401	1	101	ricardo	ricardo	PROPN
bracis-28401	1	102	j.	j.	PROPN
bracis-28401	1	103	pfitscher9	pfitscher9	PROPN
bracis-28401	1	104	,	,	PUNCT
bracis-28401	1	105	gabriel	gabriel	PROPN
bracis-28401	1	106	b.	b.	PROPN
bracis-28401	1	107	rodenbusch9	rodenbusch9	PROPN
bracis-28401	1	108	,	,	PUNCT
bracis-28401	1	109	anderson	anderson	PROPN
bracis-28401	1	110	dias10	dias10	PROPN
bracis-28401	1	111	,	,	PUNCT
bracis-28401	1	112	paulo	paulo	PROPN
bracis-28401	1	113	vieira10	vieira10	PROPN
bracis-28401	1	114	&	&	CCONJ
bracis-28401	1	115	…	…	PUNCT
bracis-28401	1	116	nuno	nuno	PROPN
bracis-28401	1	117	m.	m.	PROPN
bracis-28401	1	118	m.	m.	PROPN
bracis-28401	1	119	d.	d.	PROPN
bracis-28401	1	120	fouto11	fouto11	PROPN
bracis-28401	1	121	  	  	SPACE
bracis-28401	1	122	show	show	VERB
bracis-28401	1	123	authors	author	NOUN
bracis-28401	1	124	part	part	NOUN
bracis-28401	1	125	of	of	ADP
bracis-28401	1	126	the	the	DET
bracis-28401	1	127	book	book	NOUN
bracis-28401	1	128	series	series	NOUN
bracis-28401	1	129	:	:	PUNCT
bracis-28401	1	130	lecture	lecture	NOUN
bracis-28401	1	131	notes	note	NOUN
bracis-28401	1	132	in	in	ADP
bracis-28401	1	133	computer	computer	NOUN
bracis-28401	1	134	science	science	NOUN
bracis-28401	1	135	(	(	PUNCT
bracis-28401	1	136	(	(	PUNCT
bracis-28401	1	137	lnai	lnai	ADJ
bracis-28401	1	138	,	,	PUNCT
bracis-28401	1	139	volume	volume	NOUN
bracis-28401	1	140	14196	14196	NUM
bracis-28401	1	141	)	)	PUNCT
bracis-28401	1	142	)	)	PUNCT
bracis-28401	1	143	included	include	VERB
bracis-28401	1	144	in	in	ADP
bracis-28401	1	145	the	the	DET
bracis-28401	1	146	following	follow	VERB
bracis-28401	1	147	conference	conference	NOUN
bracis-28401	1	148	series	series	NOUN
bracis-28401	1	149	:	:	PUNCT
bracis-28401	1	150	brazilian	brazilian	ADJ
bracis-28401	1	151	conference	conference	NOUN
bracis-28401	1	152	on	on	ADP
bracis-28401	1	153	intelligent	intelligent	ADJ
bracis-28401	1	154	systems	system	NOUN
bracis-28401	1	155	645	645	NUM
bracis-28401	1	156	accesses	access	NOUN
bracis-28401	1	157	2	2	NUM
bracis-28401	1	158	citations	citation	NOUN
bracis-28401	1	159	abstract	abstract	ADV
bracis-28401	1	160	the	the	DET
bracis-28401	1	161	running	running	NOUN
bracis-28401	1	162	time	time	NOUN
bracis-28401	1	163	complexity	complexity	NOUN
bracis-28401	1	164	is	be	AUX
bracis-28401	1	165	a	a	DET
bracis-28401	1	166	crucial	crucial	ADJ
bracis-28401	1	167	measure	measure	NOUN
bracis-28401	1	168	for	for	ADP
bracis-28401	1	169	determining	determine	VERB
bracis-28401	1	170	the	the	DET
bracis-28401	1	171	computational	computational	ADJ
bracis-28401	1	172	efficiency	efficiency	NOUN
bracis-28401	1	173	of	of	ADP
bracis-28401	1	174	a	a	DET
bracis-28401	1	175	given	give	VERB
bracis-28401	1	176	program	program	NOUN
bracis-28401	1	177	or	or	CCONJ
bracis-28401	1	178	algorithm	algorithm	NOUN
bracis-28401	1	179	.	.	PUNCT
bracis-28401	2	1	depending	depend	VERB
bracis-28401	2	2	on	on	ADP
bracis-28401	2	3	the	the	DET
bracis-28401	2	4	problem	problem	NOUN
bracis-28401	2	5	complexity	complexity	NOUN
bracis-28401	2	6	class	class	NOUN
bracis-28401	2	7	,	,	PUNCT
bracis-28401	2	8	it	it	PRON
bracis-28401	2	9	can	can	AUX
bracis-28401	2	10	be	be	AUX
bracis-28401	2	11	considered	consider	VERB
bracis-28401	2	12	intractable	intractable	ADJ
bracis-28401	2	13	;	;	PUNCT
bracis-28401	2	14	a	a	DET
bracis-28401	2	15	program	program	NOUN
bracis-28401	2	16	that	that	PRON
bracis-28401	2	17	solves	solve	VERB
bracis-28401	2	18	this	this	DET
bracis-28401	2	19	problem	problem	NOUN
bracis-28401	2	20	will	will	AUX
bracis-28401	2	21	consume	consume	VERB
bracis-28401	2	22	so	so	ADV
bracis-28401	2	23	many	many	ADJ
bracis-28401	2	24	resources	resource	NOUN
bracis-28401	2	25	for	for	ADP
bracis-28401	2	26	a	a	DET
bracis-28401	2	27	sufficiently	sufficiently	ADV
bracis-28401	2	28	large	large	ADJ
bracis-28401	2	29	input	input	NOUN
bracis-28401	2	30	that	that	SCONJ
bracis-28401	2	31	it	it	PRON
bracis-28401	2	32	will	will	AUX
bracis-28401	2	33	be	be	AUX
bracis-28401	2	34	unfeasible	unfeasible	ADJ
bracis-28401	2	35	to	to	PART
bracis-28401	2	36	execute	execute	VERB
bracis-28401	2	37	it	it	PRON
bracis-28401	2	38	.	.	PUNCT
bracis-28401	3	1	due	due	ADP
bracis-28401	3	2	to	to	ADP
bracis-28401	3	3	alan	alan	PROPN
bracis-28401	3	4	turing	ture	VERB
bracis-28401	3	5	’s	’s	PART
bracis-28401	3	6	halting	halting	ADJ
bracis-28401	3	7	problem	problem	NOUN
bracis-28401	3	8	,	,	PUNCT
bracis-28401	3	9	it	it	PRON
bracis-28401	3	10	is	be	AUX
bracis-28401	3	11	impossible	impossible	ADJ
bracis-28401	3	12	to	to	PART
bracis-28401	3	13	write	write	VERB
bracis-28401	3	14	a	a	DET
bracis-28401	3	15	program	program	NOUN
bracis-28401	3	16	capable	capable	ADJ
bracis-28401	3	17	of	of	ADP
bracis-28401	3	18	determining	determine	VERB
bracis-28401	3	19	the	the	DET
bracis-28401	3	20	execution	execution	NOUN
bracis-28401	3	21	time	time	NOUN
bracis-28401	3	22	of	of	ADP
bracis-28401	3	23	a	a	DET
bracis-28401	3	24	given	give	VERB
bracis-28401	3	25	program	program	NOUN
bracis-28401	3	26	and	and	CCONJ
bracis-28401	3	27	,	,	PUNCT
bracis-28401	3	28	therefore	therefore	ADV
bracis-28401	3	29	,	,	PUNCT
bracis-28401	3	30	classifying	classify	VERB
bracis-28401	3	31	it	it	PRON
bracis-28401	3	32	according	accord	VERB
bracis-28401	3	33	to	to	ADP
bracis-28401	3	34	its	its	PRON
bracis-28401	3	35	complexity	complexity	NOUN
bracis-28401	3	36	class	class	NOUN
bracis-28401	3	37	.	.	PUNCT
bracis-28401	4	1	despite	despite	SCONJ
bracis-28401	4	2	this	this	DET
bracis-28401	4	3	limitation	limitation	NOUN
bracis-28401	4	4	,	,	PUNCT
bracis-28401	4	5	an	an	DET
bracis-28401	4	6	approximate	approximate	ADJ
bracis-28401	4	7	running	running	NOUN
bracis-28401	4	8	time	time	NOUN
bracis-28401	4	9	value	value	NOUN
bracis-28401	4	10	can	can	AUX
bracis-28401	4	11	be	be	AUX
bracis-28401	4	12	helpful	helpful	ADJ
bracis-28401	4	13	to	to	PART
bracis-28401	4	14	support	support	VERB
bracis-28401	4	15	development	development	NOUN
bracis-28401	4	16	teams	team	NOUN
bracis-28401	4	17	in	in	ADP
bracis-28401	4	18	evaluating	evaluate	VERB
bracis-28401	4	19	the	the	DET
bracis-28401	4	20	efficiency	efficiency	NOUN
bracis-28401	4	21	of	of	ADP
bracis-28401	4	22	their	their	PRON
bracis-28401	4	23	produced	produce	VERB
bracis-28401	4	24	code	code	NOUN
bracis-28401	4	25	.	.	PUNCT
bracis-28401	5	1	furthermore	furthermore	ADV
bracis-28401	5	2	,	,	PUNCT
bracis-28401	5	3	software	software	NOUN
bracis-28401	5	4	-	-	PUNCT
bracis-28401	5	5	integrated	integrate	VERB
bracis-28401	5	6	development	development	NOUN
bracis-28401	5	7	environments	environment	NOUN
bracis-28401	5	8	(	(	PUNCT
bracis-28401	5	9	ides	ide	NOUN
bracis-28401	5	10	)	)	PUNCT
bracis-28401	5	11	could	could	AUX
bracis-28401	5	12	show	show	VERB
bracis-28401	5	13	real	real	ADJ
bracis-28401	5	14	-	-	PUNCT
bracis-28401	5	15	time	time	NOUN
bracis-28401	5	16	efficiency	efficiency	NOUN
bracis-28401	5	17	indicators	indicator	NOUN
bracis-28401	5	18	for	for	ADP
bracis-28401	5	19	their	their	PRON
bracis-28401	5	20	programmers	programmer	NOUN
bracis-28401	5	21	.	.	PUNCT
bracis-28401	6	1	recent	recent	ADJ
bracis-28401	6	2	research	research	NOUN
bracis-28401	6	3	efforts	effort	NOUN
bracis-28401	6	4	have	have	AUX
bracis-28401	6	5	made	make	VERB
bracis-28401	6	6	,	,	PUNCT
bracis-28401	6	7	through	through	ADP
bracis-28401	6	8	artificial	artificial	ADJ
bracis-28401	6	9	intelligence	intelligence	NOUN
bracis-28401	6	10	techniques	technique	NOUN
bracis-28401	6	11	,	,	PUNCT
bracis-28401	6	12	complexity	complexity	NOUN
bracis-28401	6	13	estimations	estimation	NOUN
bracis-28401	6	14	based	base	VERB
bracis-28401	6	15	on	on	ADP
bracis-28401	6	16	code	code	NOUN
bracis-28401	6	17	characteristics	characteristic	NOUN
bracis-28401	6	18	(	(	PUNCT
bracis-28401	6	19	e.g.	e.g.	ADV
bracis-28401	6	20	,	,	PUNCT
bracis-28401	6	21	number	number	NOUN
bracis-28401	6	22	of	of	ADP
bracis-28401	6	23	nested	nested	ADJ
bracis-28401	6	24	loops	loop	NOUN
bracis-28401	6	25	and	and	CCONJ
bracis-28401	6	26	number	number	NOUN
bracis-28401	6	27	of	of	ADP
bracis-28401	6	28	conditional	conditional	ADJ
bracis-28401	6	29	tests	test	NOUN
bracis-28401	6	30	)	)	PUNCT
bracis-28401	6	31	.	.	PUNCT
bracis-28401	7	1	however	however	ADV
bracis-28401	7	2	,	,	PUNCT
bracis-28401	7	3	there	there	PRON
bracis-28401	7	4	are	be	VERB
bracis-28401	7	5	no	no	DET
bracis-28401	7	6	databases	database	NOUN
bracis-28401	7	7	that	that	PRON
bracis-28401	7	8	relate	relate	VERB
bracis-28401	7	9	code	code	NOUN
bracis-28401	7	10	characteristics	characteristic	NOUN
bracis-28401	7	11	with	with	ADP
bracis-28401	7	12	complexity	complexity	NOUN
bracis-28401	7	13	classes	class	NOUN
bracis-28401	7	14	considered	consider	VERB
bracis-28401	7	15	inefficient	inefficient	ADJ
bracis-28401	7	16	(	(	PUNCT
bracis-28401	7	17	e.g.	e.g.	ADV
bracis-28401	7	18	,	,	PUNCT
bracis-28401	7	19	\(o(c^n)\	\(o(c^n)\	ADJ
bracis-28401	7	20	)	)	PUNCT
bracis-28401	7	21	and	and	CCONJ
bracis-28401	7	22	o(n	o(n	PROPN
bracis-28401	7	23	!	!	PUNCT
bracis-28401	7	24	)	)	PUNCT
bracis-28401	7	25	)	)	PUNCT
bracis-28401	7	26	,	,	PUNCT
bracis-28401	7	27	which	which	PRON
bracis-28401	7	28	limits	limit	VERB
bracis-28401	7	29	current	current	ADJ
bracis-28401	7	30	research	research	NOUN
bracis-28401	7	31	results	result	NOUN
bracis-28401	7	32	.	.	PUNCT
bracis-28401	8	1	this	this	DET
bracis-28401	8	2	research	research	NOUN
bracis-28401	8	3	compared	compare	VERB
bracis-28401	8	4	three	three	NUM
bracis-28401	8	5	machine	machine	NOUN
bracis-28401	8	6	learning	learn	VERB
bracis-28401	8	7	approaches	approach	NOUN
bracis-28401	8	8	(	(	PUNCT
bracis-28401	8	9	i.e.	i.e.	X
bracis-28401	8	10	,	,	PUNCT
bracis-28401	8	11	random	random	ADJ
bracis-28401	8	12	forest	forest	NOUN
bracis-28401	8	13	,	,	PUNCT
bracis-28401	8	14	extreme	extreme	ADJ
bracis-28401	8	15	gradient	gradient	NOUN
bracis-28401	8	16	boosting	boosting	NOUN
bracis-28401	8	17	,	,	PUNCT
bracis-28401	8	18	and	and	CCONJ
bracis-28401	8	19	artificial	artificial	ADJ
bracis-28401	8	20	neural	neural	ADJ
bracis-28401	8	21	networks	network	NOUN
bracis-28401	8	22	)	)	PUNCT
bracis-28401	8	23	regarding	regard	VERB
bracis-28401	8	24	their	their	PRON
bracis-28401	8	25	accuracy	accuracy	NOUN
bracis-28401	8	26	in	in	ADP
bracis-28401	8	27	predicting	predict	VERB
bracis-28401	8	28	java	java	PROPN
bracis-28401	8	29	program	program	PROPN
bracis-28401	8	30	codes	code	NOUN
bracis-28401	8	31	’	’	PART
bracis-28401	8	32	efficiency	efficiency	NOUN
bracis-28401	8	33	and	and	CCONJ
bracis-28401	8	34	complexity	complexity	NOUN
bracis-28401	8	35	class	class	NOUN
bracis-28401	8	36	.	.	PUNCT
bracis-28401	9	1	we	we	PRON
bracis-28401	9	2	train	train	VERB
bracis-28401	9	3	each	each	DET
bracis-28401	9	4	model	model	NOUN
bracis-28401	9	5	using	use	VERB
bracis-28401	9	6	a	a	DET
bracis-28401	9	7	dataset	dataset	NOUN
bracis-28401	9	8	that	that	PRON
bracis-28401	9	9	merges	merge	VERB
bracis-28401	9	10	data	datum	NOUN
bracis-28401	9	11	from	from	ADP
bracis-28401	9	12	literature	literature	NOUN
bracis-28401	9	13	and	and	CCONJ
bracis-28401	9	14	394	394	NUM
bracis-28401	9	15	program	program	NOUN
bracis-28401	9	16	codes	code	NOUN
bracis-28401	9	17	with	with	ADP
bracis-28401	9	18	their	their	PRON
bracis-28401	9	19	respective	respective	ADJ
bracis-28401	9	20	complexity	complexity	NOUN
bracis-28401	9	21	classes	class	NOUN
bracis-28401	9	22	crawled	crawl	VERB
bracis-28401	9	23	from	from	ADP
bracis-28401	9	24	a	a	DET
bracis-28401	9	25	publicly	publicly	ADV
bracis-28401	9	26	available	available	ADJ
bracis-28401	9	27	website	website	NOUN
bracis-28401	9	28	.	.	PUNCT
bracis-28401	10	1	results	result	NOUN
bracis-28401	10	2	show	show	VERB
bracis-28401	10	3	that	that	SCONJ
bracis-28401	10	4	random	random	ADJ
bracis-28401	10	5	forest	forest	NOUN
bracis-28401	10	6	resulted	result	VERB
bracis-28401	10	7	in	in	ADP
bracis-28401	10	8	the	the	DET
bracis-28401	10	9	best	good	ADJ
bracis-28401	10	10	accuracy	accuracy	NOUN
bracis-28401	10	11	,	,	PUNCT
bracis-28401	10	12	being	be	AUX
bracis-28401	10	13	90.17	90.17	NUM
bracis-28401	10	14	%	%	NOUN
bracis-28401	10	15	accurate	accurate	ADJ
bracis-28401	10	16	when	when	SCONJ
bracis-28401	10	17	predicting	predict	VERB
bracis-28401	10	18	codes	code	NOUN
bracis-28401	10	19	’	'	PUNCT
bracis-28401	10	20	efficiency	efficiency	NOUN
bracis-28401	10	21	and	and	CCONJ
bracis-28401	10	22	89.84	89.84	NUM
bracis-28401	10	23	%	%	NOUN
bracis-28401	10	24	in	in	ADP
bracis-28401	10	25	estimating	estimate	VERB
bracis-28401	10	26	complexity	complexity	NOUN
bracis-28401	10	27	classes	class	NOUN
bracis-28401	10	28	.	.	PUNCT
bracis-28401	11	1	access	access	NOUN
bracis-28401	11	2	provided	provide	VERB
bracis-28401	11	3	by	by	ADP
bracis-28401	11	4	university	university	PROPN
bracis-28401	11	5	of	of	ADP
bracis-28401	11	6	notre	notre	PROPN
bracis-28401	11	7	dame	dame	PROPN
bracis-28401	11	8	hesburgh	hesburgh	PROPN
bracis-28401	11	9	library	library	PROPN
bracis-28401	11	10	.	.	PUNCT
bracis-28401	12	1	download	download	PROPN
bracis-28401	12	2	conference	conference	NOUN
bracis-28401	12	3	paper	paper	NOUN
bracis-28401	12	4	pdf	pdf	NOUN
bracis-28401	12	5	similar	similar	ADJ
bracis-28401	12	6	content	content	NOUN
bracis-28401	12	7	being	be	AUX
bracis-28401	12	8	viewed	view	VERB
bracis-28401	12	9	by	by	ADP
bracis-28401	12	10	others	other	NOUN
bracis-28401	12	11	learning	learn	VERB
bracis-28401	12	12	based	base	VERB
bracis-28401	12	13	methods	method	NOUN
bracis-28401	12	14	for	for	ADP
bracis-28401	12	15	code	code	NOUN
bracis-28401	12	16	runtime	runtime	NOUN
bracis-28401	12	17	complexity	complexity	NOUN
bracis-28401	12	18	prediction	prediction	NOUN
bracis-28401	12	19	chapter	chapter	NOUN
bracis-28401	12	20	©	©	PROPN
bracis-28401	12	21	2020	2020	NUM
bracis-28401	12	22	information	information	NOUN
bracis-28401	12	23	economy	economy	NOUN
bracis-28401	12	24	for	for	ADP
bracis-28401	12	25	the	the	DET
bracis-28401	12	26	fitness	fitness	NOUN
bracis-28401	12	27	of	of	ADP
bracis-28401	12	28	intelligent	intelligent	ADJ
bracis-28401	12	29	algorithms	algorithm	NOUN
bracis-28401	12	30	chapter	chapter	NOUN
bracis-28401	12	31	©	©	PROPN
bracis-28401	12	32	2024	2024	NUM
bracis-28401	12	33	is	be	AUX
bracis-28401	12	34	prüfer	prüfer	NOUN
bracis-28401	12	35	code	code	NOUN
bracis-28401	12	36	encoding	encode	VERB
bracis-28401	12	37	always	always	ADV
bracis-28401	12	38	a	a	DET
bracis-28401	12	39	bad	bad	ADJ
bracis-28401	12	40	idea	idea	NOUN
bracis-28401	12	41	?	?	PUNCT
bracis-28401	13	1	chapter	chapter	NOUN
bracis-28401	13	2	©	©	PROPN
bracis-28401	13	3	2019	2019	NUM
bracis-28401	13	4	explore	explore	VERB
bracis-28401	13	5	related	relate	VERB
bracis-28401	13	6	subjects	subject	NOUN
bracis-28401	13	7	discover	discover	VERB
bracis-28401	13	8	the	the	DET
bracis-28401	13	9	latest	late	ADJ
bracis-28401	13	10	articles	article	NOUN
bracis-28401	13	11	,	,	PUNCT
bracis-28401	13	12	books	book	NOUN
bracis-28401	13	13	and	and	CCONJ
bracis-28401	13	14	news	news	NOUN
bracis-28401	13	15	in	in	ADP
bracis-28401	13	16	related	related	ADJ
bracis-28401	13	17	subjects	subject	NOUN
bracis-28401	13	18	,	,	PUNCT
bracis-28401	13	19	suggested	suggest	VERB
bracis-28401	13	20	using	use	VERB
bracis-28401	13	21	machine	machine	NOUN
bracis-28401	13	22	learning	learning	NOUN
bracis-28401	13	23	.	.	PUNCT
bracis-28401	14	1	algorithmic	algorithmic	ADJ
bracis-28401	14	2	complexity	complexity	NOUN
bracis-28401	14	3	algorithm	algorithm	NOUN
bracis-28401	14	4	analysis	analysis	NOUN
bracis-28401	14	5	and	and	CCONJ
bracis-28401	14	6	problem	problem	NOUN
bracis-28401	14	7	complexity	complexity	NOUN
bracis-28401	14	8	computational	computational	ADJ
bracis-28401	14	9	complexity	complexity	NOUN
bracis-28401	14	10	learning	learn	VERB
bracis-28401	14	11	algorithms	algorithm	NOUN
bracis-28401	14	12	machine	machine	NOUN
bracis-28401	14	13	learning	learn	VERB
bracis-28401	14	14	mathematics	mathematic	NOUN
bracis-28401	14	15	of	of	ADP
bracis-28401	14	16	algorithmic	algorithmic	ADJ
bracis-28401	14	17	complexity	complexity	NOUN
bracis-28401	14	18	1	1	NUM
bracis-28401	14	19	introduction	introduction	NOUN
bracis-28401	14	20	computer	computer	NOUN
bracis-28401	14	21	programming	programming	NOUN
bracis-28401	14	22	is	be	AUX
bracis-28401	14	23	a	a	DET
bracis-28401	14	24	primary	primary	ADJ
bracis-28401	14	25	task	task	NOUN
bracis-28401	14	26	in	in	ADP
bracis-28401	14	27	a	a	DET
bracis-28401	14	28	software	software	NOUN
bracis-28401	14	29	development	development	NOUN
bracis-28401	14	30	lifecycle	lifecycle	NOUN
bracis-28401	14	31	.	.	PUNCT
bracis-28401	15	1	it	it	PRON
bracis-28401	15	2	essentially	essentially	ADV
bracis-28401	15	3	involves	involve	VERB
bracis-28401	15	4	translating	translate	VERB
bracis-28401	15	5	algorithms	algorithm	NOUN
bracis-28401	15	6	into	into	ADP
bracis-28401	15	7	functions	function	NOUN
bracis-28401	15	8	,	,	PUNCT
bracis-28401	15	9	methods	method	NOUN
bracis-28401	15	10	,	,	PUNCT
bracis-28401	15	11	and	and	CCONJ
bracis-28401	15	12	procedures	procedure	NOUN
bracis-28401	15	13	that	that	PRON
bracis-28401	15	14	perform	perform	VERB
bracis-28401	15	15	tasks	task	NOUN
bracis-28401	15	16	that	that	SCONJ
bracis-28401	15	17	,	,	PUNCT
bracis-28401	15	18	in	in	ADP
bracis-28401	15	19	conjunction	conjunction	NOUN
bracis-28401	15	20	,	,	PUNCT
bracis-28401	15	21	solve	solve	VERB
bracis-28401	15	22	a	a	DET
bracis-28401	15	23	specific	specific	ADJ
bracis-28401	15	24	problem	problem	NOUN
bracis-28401	15	25	.	.	PUNCT
bracis-28401	16	1	before	before	ADP
bracis-28401	16	2	the	the	DET
bracis-28401	16	3	programming	programming	NOUN
bracis-28401	16	4	action	action	NOUN
bracis-28401	16	5	,	,	PUNCT
bracis-28401	16	6	analysts	analyst	NOUN
bracis-28401	16	7	should	should	AUX
bracis-28401	16	8	determine	determine	VERB
bracis-28401	16	9	the	the	DET
bracis-28401	16	10	algorithms	algorithm	NOUN
bracis-28401	16	11	that	that	PRON
bracis-28401	16	12	apply	apply	VERB
bracis-28401	16	13	to	to	ADP
bracis-28401	16	14	the	the	DET
bracis-28401	16	15	referred	refer	VERB
bracis-28401	16	16	situation	situation	NOUN
bracis-28401	16	17	.	.	PUNCT
bracis-28401	17	1	such	such	DET
bracis-28401	17	2	an	an	DET
bracis-28401	17	3	analysis	analysis	NOUN
bracis-28401	17	4	task	task	NOUN
bracis-28401	17	5	requires	require	VERB
bracis-28401	17	6	technical	technical	ADJ
bracis-28401	17	7	knowledge	knowledge	NOUN
bracis-28401	17	8	in	in	ADP
bracis-28401	17	9	many	many	ADJ
bracis-28401	17	10	areas	area	NOUN
bracis-28401	17	11	,	,	PUNCT
bracis-28401	17	12	from	from	ADP
bracis-28401	17	13	business	business	NOUN
bracis-28401	17	14	rules	rule	NOUN
bracis-28401	17	15	to	to	ADP
bracis-28401	17	16	computational	computational	ADJ
bracis-28401	17	17	resource	resource	NOUN
bracis-28401	17	18	efficiency	efficiency	NOUN
bracis-28401	17	19	.	.	PUNCT
bracis-28401	18	1	regarding	regard	VERB
bracis-28401	18	2	the	the	DET
bracis-28401	18	3	latter	latter	ADJ
bracis-28401	18	4	,	,	PUNCT
bracis-28401	18	5	a	a	DET
bracis-28401	18	6	relevant	relevant	ADJ
bracis-28401	18	7	discipline	discipline	NOUN
bracis-28401	18	8	is	be	AUX
bracis-28401	18	9	algorithm	algorithm	NOUN
bracis-28401	18	10	analysis	analysis	NOUN
bracis-28401	18	11	.	.	PUNCT
bracis-28401	19	1	one	one	NUM
bracis-28401	19	2	result	result	NOUN
bracis-28401	19	3	of	of	ADP
bracis-28401	19	4	its	its	PRON
bracis-28401	19	5	activities	activity	NOUN
bracis-28401	19	6	is	be	AUX
bracis-28401	19	7	a	a	DET
bracis-28401	19	8	mathematical	mathematical	ADJ
bracis-28401	19	9	function	function	NOUN
bracis-28401	19	10	that	that	PRON
bracis-28401	19	11	expresses	express	VERB
bracis-28401	19	12	the	the	DET
bracis-28401	19	13	upper	upper	ADJ
bracis-28401	19	14	bound	bind	VERB
bracis-28401	19	15	running	running	NOUN
bracis-28401	19	16	time	time	NOUN
bracis-28401	19	17	of	of	ADP
bracis-28401	19	18	a	a	DET
bracis-28401	19	19	specific	specific	ADJ
bracis-28401	19	20	algorithm	algorithm	NOUN
bracis-28401	19	21	,	,	PUNCT
bracis-28401	19	22	a.k.a	a.k.a	INTJ
bracis-28401	19	23	.	.	PUNCT
bracis-28401	19	24	running	run	VERB
bracis-28401	19	25	time	time	NOUN
bracis-28401	19	26	complexity	complexity	NOUN
bracis-28401	19	27	[	[	X
bracis-28401	19	28	10	10	NUM
bracis-28401	19	29	]	]	PUNCT
bracis-28401	19	30	.	.	PUNCT
bracis-28401	20	1	the	the	DET
bracis-28401	20	2	complexity	complexity	NOUN
bracis-28401	20	3	class	class	NOUN
bracis-28401	20	4	of	of	ADP
bracis-28401	20	5	an	an	DET
bracis-28401	20	6	algorithm	algorithm	NOUN
bracis-28401	20	7	or	or	CCONJ
bracis-28401	20	8	code	code	NOUN
bracis-28401	20	9	directly	directly	ADV
bracis-28401	20	10	impacts	impact	VERB
bracis-28401	20	11	its	its	PRON
bracis-28401	20	12	resource	resource	NOUN
bracis-28401	20	13	usage	usage	NOUN
bracis-28401	20	14	efficiency	efficiency	NOUN
bracis-28401	20	15	.	.	PUNCT
bracis-28401	21	1	such	such	DET
bracis-28401	21	2	an	an	DET
bracis-28401	21	3	impact	impact	NOUN
bracis-28401	21	4	on	on	ADP
bracis-28401	21	5	the	the	DET
bracis-28401	21	6	software	software	NOUN
bracis-28401	21	7	’s	’s	PART
bracis-28401	21	8	future	future	ADJ
bracis-28401	21	9	performance	performance	NOUN
bracis-28401	21	10	highlights	highlight	NOUN
bracis-28401	21	11	the	the	DET
bracis-28401	21	12	need	need	NOUN
bracis-28401	21	13	for	for	ADP
bracis-28401	21	14	a	a	DET
bracis-28401	21	15	precise	precise	ADJ
bracis-28401	21	16	analysis	analysis	NOUN
bracis-28401	21	17	.	.	PUNCT
bracis-28401	22	1	also	also	ADV
bracis-28401	22	2	,	,	PUNCT
bracis-28401	22	3	depending	depend	VERB
bracis-28401	22	4	on	on	ADP
bracis-28401	22	5	its	its	PRON
bracis-28401	22	6	asymptotic	asymptotic	ADJ
bracis-28401	22	7	behavior	behavior	NOUN
bracis-28401	22	8	,	,	PUNCT
bracis-28401	22	9	the	the	DET
bracis-28401	22	10	study	study	NOUN
bracis-28401	22	11	may	may	AUX
bracis-28401	22	12	indicate	indicate	VERB
bracis-28401	22	13	that	that	SCONJ
bracis-28401	22	14	the	the	DET
bracis-28401	22	15	program	program	NOUN
bracis-28401	22	16	takes	take	VERB
bracis-28401	22	17	so	so	ADV
bracis-28401	22	18	long	long	ADJ
bracis-28401	22	19	to	to	PART
bracis-28401	22	20	run	run	VERB
bracis-28401	22	21	that	that	SCONJ
bracis-28401	22	22	it	it	PRON
bracis-28401	22	23	is	be	AUX
bracis-28401	22	24	considered	consider	VERB
bracis-28401	22	25	intractable	intractable	ADJ
bracis-28401	22	26	[	[	X
bracis-28401	22	27	6	6	NUM
bracis-28401	22	28	]	]	PUNCT
bracis-28401	22	29	.	.	PUNCT
bracis-28401	23	1	on	on	ADP
bracis-28401	23	2	the	the	DET
bracis-28401	23	3	other	other	ADJ
bracis-28401	23	4	hand	hand	NOUN
bracis-28401	23	5	,	,	PUNCT
bracis-28401	23	6	beginner	beginner	NOUN
bracis-28401	23	7	developers	developer	NOUN
bracis-28401	23	8	may	may	AUX
bracis-28401	23	9	rely	rely	VERB
bracis-28401	23	10	on	on	ADP
bracis-28401	23	11	inefficient	inefficient	ADJ
bracis-28401	23	12	solutions	solution	NOUN
bracis-28401	23	13	to	to	PART
bracis-28401	23	14	solve	solve	VERB
bracis-28401	23	15	coding	code	VERB
bracis-28401	23	16	problems	problem	NOUN
bracis-28401	23	17	without	without	ADP
bracis-28401	23	18	understanding	understand	VERB
bracis-28401	23	19	the	the	DET
bracis-28401	23	20	impacts	impact	NOUN
bracis-28401	23	21	on	on	ADP
bracis-28401	23	22	running	run	VERB
bracis-28401	23	23	time	time	NOUN
bracis-28401	23	24	complexity	complexity	NOUN
bracis-28401	23	25	.	.	PUNCT
bracis-28401	24	1	determining	determine	VERB
bracis-28401	24	2	the	the	DET
bracis-28401	24	3	running	running	NOUN
bracis-28401	24	4	time	time	NOUN
bracis-28401	24	5	complexity	complexity	NOUN
bracis-28401	24	6	is	be	AUX
bracis-28401	24	7	arduous	arduous	ADJ
bracis-28401	24	8	and	and	CCONJ
bracis-28401	24	9	requires	require	VERB
bracis-28401	24	10	a	a	DET
bracis-28401	24	11	deep	deep	ADJ
bracis-28401	24	12	understanding	understanding	NOUN
bracis-28401	24	13	of	of	ADP
bracis-28401	24	14	code	code	NOUN
bracis-28401	24	15	behavior	behavior	NOUN
bracis-28401	24	16	.	.	PUNCT
bracis-28401	25	1	an	an	DET
bracis-28401	25	2	analyst	analyst	NOUN
bracis-28401	25	3	must	must	AUX
bracis-28401	25	4	consider	consider	VERB
bracis-28401	25	5	multiple	multiple	ADJ
bracis-28401	25	6	variables	variable	NOUN
bracis-28401	25	7	when	when	SCONJ
bracis-28401	25	8	analyzing	analyze	VERB
bracis-28401	25	9	a	a	DET
bracis-28401	25	10	coded	code	VERB
bracis-28401	25	11	function	function	NOUN
bracis-28401	25	12	,	,	PUNCT
bracis-28401	25	13	including	include	VERB
bracis-28401	25	14	the	the	DET
bracis-28401	25	15	number	number	NOUN
bracis-28401	25	16	of	of	ADP
bracis-28401	25	17	recursive	recursive	ADJ
bracis-28401	25	18	calls	call	NOUN
bracis-28401	25	19	,	,	PUNCT
bracis-28401	25	20	the	the	DET
bracis-28401	25	21	size	size	NOUN
bracis-28401	25	22	of	of	ADP
bracis-28401	25	23	iteration	iteration	NOUN
bracis-28401	25	24	loops	loop	NOUN
bracis-28401	25	25	,	,	PUNCT
bracis-28401	25	26	and	and	CCONJ
bracis-28401	25	27	the	the	DET
bracis-28401	25	28	number	number	NOUN
bracis-28401	25	29	of	of	ADP
bracis-28401	25	30	nested	nested	ADJ
bracis-28401	25	31	loops	loop	NOUN
bracis-28401	25	32	.	.	PUNCT
bracis-28401	26	1	also	also	ADV
bracis-28401	26	2	,	,	PUNCT
bracis-28401	26	3	analysts	analyst	NOUN
bracis-28401	26	4	must	must	AUX
bracis-28401	26	5	consider	consider	VERB
bracis-28401	26	6	how	how	SCONJ
bracis-28401	26	7	these	these	DET
bracis-28401	26	8	variables	variable	NOUN
bracis-28401	26	9	relate	relate	VERB
bracis-28401	26	10	and	and	CCONJ
bracis-28401	26	11	how	how	SCONJ
bracis-28401	26	12	the	the	DET
bracis-28401	26	13	computer	computer	NOUN
bracis-28401	26	14	program	program	NOUN
bracis-28401	26	15	uses	use	VERB
bracis-28401	26	16	computational	computational	ADJ
bracis-28401	26	17	resources	resource	NOUN
bracis-28401	26	18	.	.	PUNCT
bracis-28401	27	1	consequently	consequently	ADV
bracis-28401	27	2	,	,	PUNCT
bracis-28401	27	3	experts	expert	NOUN
bracis-28401	27	4	can	can	AUX
bracis-28401	27	5	misevaluate	misevaluate	VERB
bracis-28401	27	6	the	the	DET
bracis-28401	27	7	running	run	VERB
bracis-28401	27	8	-	-	PUNCT
bracis-28401	27	9	time	time	NOUN
bracis-28401	27	10	function	function	NOUN
bracis-28401	27	11	,	,	PUNCT
bracis-28401	27	12	promoting	promote	VERB
bracis-28401	27	13	a	a	DET
bracis-28401	27	14	search	search	NOUN
bracis-28401	27	15	for	for	ADP
bracis-28401	27	16	tools	tool	NOUN
bracis-28401	27	17	and	and	CCONJ
bracis-28401	27	18	frameworks	framework	NOUN
bracis-28401	27	19	to	to	PART
bracis-28401	27	20	aid	aid	VERB
bracis-28401	27	21	in	in	ADP
bracis-28401	27	22	the	the	DET
bracis-28401	27	23	complexity	complexity	NOUN
bracis-28401	27	24	analysis	analysis	NOUN
bracis-28401	27	25	process	process	NOUN
bracis-28401	27	26	.	.	PUNCT
bracis-28401	28	1	alan	alan	PROPN
bracis-28401	28	2	turing	turing	PROPN
bracis-28401	28	3	proved	prove	VERB
bracis-28401	28	4	through	through	ADP
bracis-28401	28	5	the	the	DET
bracis-28401	28	6	halting	halting	ADJ
bracis-28401	28	7	problem	problem	NOUN
bracis-28401	28	8	that	that	SCONJ
bracis-28401	28	9	estimating	estimate	VERB
bracis-28401	28	10	the	the	DET
bracis-28401	28	11	code	code	NOUN
bracis-28401	28	12	complexity	complexity	NOUN
bracis-28401	28	13	is	be	AUX
bracis-28401	28	14	mathematically	mathematically	ADV
bracis-28401	28	15	impossible	impossible	ADJ
bracis-28401	28	16	[	[	X
bracis-28401	28	17	12	12	NUM
bracis-28401	28	18	]	]	PUNCT
bracis-28401	28	19	.	.	PUNCT
bracis-28401	29	1	thus	thus	ADV
bracis-28401	29	2	,	,	PUNCT
bracis-28401	29	3	recent	recent	ADJ
bracis-28401	29	4	research	research	NOUN
bracis-28401	29	5	applied	apply	VERB
bracis-28401	29	6	machine	machine	NOUN
bracis-28401	29	7	learning	learn	VERB
bracis-28401	29	8	techniques	technique	NOUN
bracis-28401	29	9	and	and	CCONJ
bracis-28401	29	10	mathematical	mathematical	ADJ
bracis-28401	29	11	models	model	NOUN
bracis-28401	29	12	to	to	PART
bracis-28401	29	13	estimate	estimate	VERB
bracis-28401	29	14	running	running	ADJ
bracis-28401	29	15	-	-	PUNCT
bracis-28401	29	16	time	time	NOUN
bracis-28401	29	17	complexity	complexity	NOUN
bracis-28401	29	18	functions	function	NOUN
bracis-28401	29	19	[	[	X
bracis-28401	29	20	9	9	NUM
bracis-28401	29	21	,	,	PUNCT
bracis-28401	29	22	18	18	NUM
bracis-28401	29	23	]	]	PUNCT
bracis-28401	29	24	.	.	PUNCT
bracis-28401	30	1	with	with	ADP
bracis-28401	30	2	such	such	ADJ
bracis-28401	30	3	approximation	approximation	NOUN
bracis-28401	30	4	values	value	NOUN
bracis-28401	30	5	,	,	PUNCT
bracis-28401	30	6	developers	developer	NOUN
bracis-28401	30	7	could	could	AUX
bracis-28401	30	8	get	get	VERB
bracis-28401	30	9	real	real	ADJ
bracis-28401	30	10	-	-	PUNCT
bracis-28401	30	11	time	time	NOUN
bracis-28401	30	12	feedback	feedback	NOUN
bracis-28401	30	13	on	on	ADP
bracis-28401	30	14	the	the	DET
bracis-28401	30	15	efficiency	efficiency	NOUN
bracis-28401	30	16	of	of	ADP
bracis-28401	30	17	their	their	PRON
bracis-28401	30	18	code	code	NOUN
bracis-28401	30	19	.	.	PUNCT
bracis-28401	31	1	however	however	ADV
bracis-28401	31	2	,	,	PUNCT
bracis-28401	31	3	a	a	DET
bracis-28401	31	4	relevant	relevant	ADJ
bracis-28401	31	5	barrier	barrier	NOUN
bracis-28401	31	6	that	that	PRON
bracis-28401	31	7	hinders	hinder	VERB
bracis-28401	31	8	the	the	DET
bracis-28401	31	9	evolution	evolution	NOUN
bracis-28401	31	10	and	and	CCONJ
bracis-28401	31	11	adoption	adoption	NOUN
bracis-28401	31	12	of	of	ADP
bracis-28401	31	13	such	such	ADJ
bracis-28401	31	14	models	model	NOUN
bracis-28401	31	15	is	be	AUX
bracis-28401	31	16	the	the	DET
bracis-28401	31	17	lack	lack	NOUN
bracis-28401	31	18	of	of	ADP
bracis-28401	31	19	datasets	dataset	NOUN
bracis-28401	31	20	that	that	PRON
bracis-28401	31	21	correlate	correlate	VERB
bracis-28401	31	22	coding	code	VERB
bracis-28401	31	23	characteristics	characteristic	NOUN
bracis-28401	31	24	to	to	ADP
bracis-28401	31	25	the	the	DET
bracis-28401	31	26	respective	respective	ADJ
bracis-28401	31	27	runtime	runtime	NOUN
bracis-28401	31	28	complexity	complexity	NOUN
bracis-28401	31	29	class	class	NOUN
bracis-28401	31	30	.	.	PUNCT
bracis-28401	32	1	this	this	DET
bracis-28401	32	2	research	research	NOUN
bracis-28401	32	3	aims	aim	VERB
bracis-28401	32	4	to	to	PART
bracis-28401	32	5	fill	fill	VERB
bracis-28401	32	6	this	this	DET
bracis-28401	32	7	gap	gap	NOUN
bracis-28401	32	8	by	by	ADP
bracis-28401	32	9	developing	develop	VERB
bracis-28401	32	10	a	a	DET
bracis-28401	32	11	learning	learning	NOUN
bracis-28401	32	12	method	method	NOUN
bracis-28401	32	13	to	to	PART
bracis-28401	32	14	predict	predict	VERB
bracis-28401	32	15	the	the	DET
bracis-28401	32	16	runtime	runtime	NOUN
bracis-28401	32	17	complexity	complexity	NOUN
bracis-28401	32	18	of	of	ADP
bracis-28401	32	19	a	a	DET
bracis-28401	32	20	program	program	NOUN
bracis-28401	32	21	code	code	NOUN
bracis-28401	32	22	.	.	PUNCT
bracis-28401	33	1	to	to	PART
bracis-28401	33	2	achieve	achieve	VERB
bracis-28401	33	3	this	this	DET
bracis-28401	33	4	objective	objective	NOUN
bracis-28401	33	5	,	,	PUNCT
bracis-28401	33	6	we	we	PRON
bracis-28401	33	7	built	build	VERB
bracis-28401	33	8	a	a	DET
bracis-28401	33	9	representative	representative	NOUN
bracis-28401	33	10	dataset	dataset	NOUN
bracis-28401	33	11	with	with	ADP
bracis-28401	33	12	program	program	NOUN
bracis-28401	33	13	codes	code	NOUN
bracis-28401	33	14	,	,	PUNCT
bracis-28401	33	15	related	related	ADJ
bracis-28401	33	16	characteristics	characteristic	NOUN
bracis-28401	33	17	and	and	CCONJ
bracis-28401	33	18	complexities	complexity	NOUN
bracis-28401	33	19	,	,	PUNCT
bracis-28401	33	20	and	and	CCONJ
bracis-28401	33	21	compared	compare	VERB
bracis-28401	33	22	machine	machine	NOUN
bracis-28401	33	23	learning	learning	NOUN
bracis-28401	33	24	approaches	approach	NOUN
bracis-28401	33	25	according	accord	VERB
bracis-28401	33	26	to	to	ADP
bracis-28401	33	27	their	their	PRON
bracis-28401	33	28	accuracy	accuracy	NOUN
bracis-28401	33	29	in	in	ADP
bracis-28401	33	30	predicting	predict	VERB
bracis-28401	33	31	efficiency	efficiency	NOUN
bracis-28401	33	32	(	(	PUNCT
bracis-28401	33	33	if	if	SCONJ
bracis-28401	33	34	the	the	DET
bracis-28401	33	35	code	code	NOUN
bracis-28401	33	36	is	be	AUX
bracis-28401	33	37	efficient	efficient	ADJ
bracis-28401	33	38	or	or	CCONJ
bracis-28401	33	39	not	not	PART
bracis-28401	33	40	)	)	PUNCT
bracis-28401	33	41	and	and	CCONJ
bracis-28401	33	42	the	the	DET
bracis-28401	33	43	runtime	runtime	NOUN
bracis-28401	33	44	complexity	complexity	NOUN
bracis-28401	33	45	of	of	ADP
bracis-28401	33	46	program	program	NOUN
bracis-28401	33	47	codes	code	NOUN
bracis-28401	33	48	.	.	PUNCT
bracis-28401	34	1	the	the	DET
bracis-28401	34	2	contributions	contribution	NOUN
bracis-28401	34	3	of	of	ADP
bracis-28401	34	4	this	this	DET
bracis-28401	34	5	paper	paper	NOUN
bracis-28401	34	6	are	be	AUX
bracis-28401	34	7	twofold	twofold	ADJ
bracis-28401	34	8	:	:	PUNCT
bracis-28401	34	9	first	first	ADV
bracis-28401	34	10	,	,	PUNCT
bracis-28401	34	11	it	it	PRON
bracis-28401	34	12	makes	make	VERB
bracis-28401	34	13	available	available	ADJ
bracis-28401	34	14	to	to	ADP
bracis-28401	34	15	the	the	DET
bracis-28401	34	16	machine	machine	NOUN
bracis-28401	34	17	learning	learn	VERB
bracis-28401	34	18	community	community	NOUN
bracis-28401	34	19	a	a	DET
bracis-28401	34	20	dataset	dataset	NOUN
bracis-28401	34	21	containing	contain	VERB
bracis-28401	34	22	394	394	NUM
bracis-28401	34	23	java	java	PROPN
bracis-28401	34	24	code	code	NOUN
bracis-28401	34	25	files	file	NOUN
bracis-28401	34	26	grouped	group	VERB
bracis-28401	34	27	into	into	ADP
bracis-28401	34	28	eight	eight	NUM
bracis-28401	34	29	distinct	distinct	ADJ
bracis-28401	34	30	complexity	complexity	NOUN
bracis-28401	34	31	classes	class	NOUN
bracis-28401	34	32	and	and	CCONJ
bracis-28401	34	33	each	each	DET
bracis-28401	34	34	code	code	NOUN
bracis-28401	34	35	having	have	VERB
bracis-28401	34	36	16	16	NUM
bracis-28401	34	37	metadata	metadata	NOUN
bracis-28401	34	38	information	information	NOUN
bracis-28401	34	39	;	;	PUNCT
bracis-28401	34	40	second	second	X
bracis-28401	34	41	,	,	PUNCT
bracis-28401	34	42	it	it	PRON
bracis-28401	34	43	shows	show	VERB
bracis-28401	34	44	that	that	SCONJ
bracis-28401	34	45	a	a	DET
bracis-28401	34	46	random	random	ADJ
bracis-28401	34	47	forest	forest	NOUN
bracis-28401	34	48	model	model	NOUN
bracis-28401	34	49	trained	train	VERB
bracis-28401	34	50	with	with	ADP
bracis-28401	34	51	a	a	DET
bracis-28401	34	52	dataset	dataset	NOUN
bracis-28401	34	53	merged	merge	VERB
bracis-28401	34	54	from	from	ADP
bracis-28401	34	55	the	the	DET
bracis-28401	34	56	published	publish	VERB
bracis-28401	34	57	work	work	NOUN
bracis-28401	34	58	of	of	ADP
bracis-28401	34	59	sikka	sikka	PROPN
bracis-28401	34	60	et	et	PROPN
bracis-28401	34	61	al	al	PROPN
bracis-28401	34	62	.	.	PUNCT
bracis-28401	35	1	[	[	X
bracis-28401	35	2	18	18	NUM
bracis-28401	35	3	]	]	PUNCT
bracis-28401	35	4	and	and	CCONJ
bracis-28401	35	5	web	web	NOUN
bracis-28401	35	6	crawled	crawl	VERB
bracis-28401	35	7	data	datum	NOUN
bracis-28401	35	8	can	can	AUX
bracis-28401	35	9	achieve	achieve	VERB
bracis-28401	35	10	an	an	DET
bracis-28401	35	11	accuracy	accuracy	NOUN
bracis-28401	35	12	of	of	ADP
bracis-28401	35	13	90.34	90.34	NUM
bracis-28401	35	14	%	%	NOUN
bracis-28401	35	15	when	when	SCONJ
bracis-28401	35	16	predicting	predict	VERB
bracis-28401	35	17	code	code	NOUN
bracis-28401	35	18	efficiency	efficiency	NOUN
bracis-28401	35	19	and	and	CCONJ
bracis-28401	35	20	89.26	89.26	NUM
bracis-28401	35	21	%	%	NOUN
bracis-28401	35	22	when	when	SCONJ
bracis-28401	35	23	predicting	predict	VERB
bracis-28401	35	24	complexity	complexity	NOUN
bracis-28401	35	25	classes	class	NOUN
bracis-28401	35	26	.	.	PUNCT
bracis-28401	36	1	the	the	DET
bracis-28401	36	2	remainder	remainder	NOUN
bracis-28401	36	3	of	of	ADP
bracis-28401	36	4	this	this	DET
bracis-28401	36	5	text	text	NOUN
bracis-28401	36	6	is	be	AUX
bracis-28401	36	7	organized	organize	VERB
bracis-28401	36	8	as	as	SCONJ
bracis-28401	36	9	follows	follow	VERB
bracis-28401	36	10	,	,	PUNCT
bracis-28401	36	11	sect	sect	NOUN
bracis-28401	36	12	.	.	PUNCT
bracis-28401	36	13	 	 	SPACE
bracis-28401	37	1	2	2	NUM
bracis-28401	37	2	discusses	discuss	VERB
bracis-28401	37	3	the	the	DET
bracis-28401	37	4	related	related	ADJ
bracis-28401	37	5	work	work	NOUN
bracis-28401	37	6	and	and	CCONJ
bracis-28401	37	7	current	current	ADJ
bracis-28401	37	8	limitations	limitation	NOUN
bracis-28401	37	9	.	.	PUNCT
bracis-28401	38	1	then	then	ADV
bracis-28401	38	2	,	,	PUNCT
bracis-28401	38	3	sect	sect	NOUN
bracis-28401	38	4	.	.	PUNCT
bracis-28401	38	5	 	 	SPACE
bracis-28401	38	6	3	3	NUM
bracis-28401	38	7	describe	describe	VERB
bracis-28401	38	8	the	the	DET
bracis-28401	38	9	methodology	methodology	NOUN
bracis-28401	38	10	followed	follow	VERB
bracis-28401	38	11	to	to	PART
bracis-28401	38	12	build	build	VERB
bracis-28401	38	13	datasets	dataset	NOUN
bracis-28401	38	14	and	and	CCONJ
bracis-28401	38	15	develop	develop	VERB
bracis-28401	38	16	the	the	DET
bracis-28401	38	17	machine	machine	NOUN
bracis-28401	38	18	learning	learning	NOUN
bracis-28401	38	19	models	model	NOUN
bracis-28401	38	20	.	.	PUNCT
bracis-28401	39	1	next	next	ADJ
bracis-28401	39	2	,	,	PUNCT
bracis-28401	39	3	sect	sect	NOUN
bracis-28401	39	4	.	.	PUNCT
bracis-28401	39	5	 	 	SPACE
bracis-28401	40	1	4	4	NUM
bracis-28401	40	2	presents	present	VERB
bracis-28401	40	3	the	the	DET
bracis-28401	40	4	complexity	complexity	NOUN
bracis-28401	40	5	prediction	prediction	NOUN
bracis-28401	40	6	results	result	NOUN
bracis-28401	40	7	obtained	obtain	VERB
bracis-28401	40	8	with	with	ADP
bracis-28401	40	9	trained	train	VERB
bracis-28401	40	10	models	model	NOUN
bracis-28401	40	11	and	and	CCONJ
bracis-28401	40	12	sect	sect	NOUN
bracis-28401	40	13	.	.	PUNCT
bracis-28401	40	14	 	 	SPACE
bracis-28401	41	1	5	5	NUM
bracis-28401	41	2	discusses	discuss	VERB
bracis-28401	41	3	the	the	DET
bracis-28401	41	4	limitations	limitation	NOUN
bracis-28401	41	5	of	of	ADP
bracis-28401	41	6	classifications	classification	NOUN
bracis-28401	41	7	.	.	PUNCT
bracis-28401	42	1	finally	finally	ADV
bracis-28401	42	2	,	,	PUNCT
bracis-28401	42	3	the	the	DET
bracis-28401	42	4	sect	sect	NOUN
bracis-28401	42	5	.	.	PUNCT
bracis-28401	42	6	 	 	SPACE
bracis-28401	43	1	6	6	NUM
bracis-28401	43	2	presents	present	VERB
bracis-28401	43	3	this	this	DET
bracis-28401	43	4	work	work	NOUN
bracis-28401	43	5	’s	’s	PART
bracis-28401	43	6	conclusions	conclusion	NOUN
bracis-28401	43	7	and	and	CCONJ
bracis-28401	43	8	future	future	ADJ
bracis-28401	43	9	works	work	NOUN
bracis-28401	43	10	.	.	PUNCT
bracis-28401	44	1	2	2	NUM
bracis-28401	44	2	related	relate	VERB
bracis-28401	44	3	work	work	NOUN
bracis-28401	44	4	given	give	VERB
bracis-28401	44	5	the	the	DET
bracis-28401	44	6	limitations	limitation	NOUN
bracis-28401	44	7	of	of	ADP
bracis-28401	44	8	writing	write	VERB
bracis-28401	44	9	a	a	DET
bracis-28401	44	10	computer	computer	NOUN
bracis-28401	44	11	program	program	NOUN
bracis-28401	44	12	to	to	PART
bracis-28401	44	13	determine	determine	VERB
bracis-28401	44	14	the	the	DET
bracis-28401	44	15	running	running	NOUN
bracis-28401	44	16	time	time	NOUN
bracis-28401	44	17	of	of	ADP
bracis-28401	44	18	program	program	NOUN
bracis-28401	44	19	source	source	NOUN
bracis-28401	44	20	codes	code	NOUN
bracis-28401	44	21	,	,	PUNCT
bracis-28401	44	22	a	a	DET
bracis-28401	44	23	few	few	ADJ
bracis-28401	44	24	works	work	NOUN
bracis-28401	44	25	appear	appear	VERB
bracis-28401	44	26	in	in	ADP
bracis-28401	44	27	the	the	DET
bracis-28401	44	28	literature	literature	NOUN
bracis-28401	44	29	to	to	PART
bracis-28401	44	30	address	address	VERB
bracis-28401	44	31	this	this	DET
bracis-28401	44	32	problem	problem	NOUN
bracis-28401	44	33	.	.	PUNCT
bracis-28401	45	1	however	however	ADV
bracis-28401	45	2	,	,	PUNCT
bracis-28401	45	3	the	the	DET
bracis-28401	45	4	recent	recent	ADJ
bracis-28401	45	5	advances	advance	NOUN
bracis-28401	45	6	in	in	ADP
bracis-28401	45	7	artificial	artificial	ADJ
bracis-28401	45	8	intelligence	intelligence	NOUN
bracis-28401	45	9	propelled	propel	VERB
bracis-28401	45	10	the	the	DET
bracis-28401	45	11	development	development	NOUN
bracis-28401	45	12	of	of	ADP
bracis-28401	45	13	models	model	NOUN
bracis-28401	45	14	that	that	PRON
bracis-28401	45	15	estimate	estimate	VERB
bracis-28401	45	16	code	code	NOUN
bracis-28401	45	17	complexity	complexity	NOUN
bracis-28401	45	18	.	.	PUNCT
bracis-28401	46	1	the	the	DET
bracis-28401	46	2	seminal	seminal	ADJ
bracis-28401	46	3	work	work	NOUN
bracis-28401	46	4	of	of	ADP
bracis-28401	46	5	hutter	hutter	NOUN
bracis-28401	46	6	et	et	PROPN
bracis-28401	46	7	al	al	PROPN
bracis-28401	46	8	.	.	PUNCT
bracis-28401	47	1	[	[	X
bracis-28401	47	2	9	9	NUM
bracis-28401	47	3	]	]	PUNCT
bracis-28401	47	4	assesses	assesse	NOUN
bracis-28401	47	5	machine	machine	NOUN
bracis-28401	47	6	learning	learn	VERB
bracis-28401	47	7	approaches	approach	NOUN
bracis-28401	47	8	to	to	PART
bracis-28401	47	9	predict	predict	VERB
bracis-28401	47	10	the	the	DET
bracis-28401	47	11	performance	performance	NOUN
bracis-28401	47	12	of	of	ADP
bracis-28401	47	13	algorithms	algorithm	NOUN
bracis-28401	47	14	.	.	PUNCT
bracis-28401	48	1	the	the	DET
bracis-28401	48	2	results	result	NOUN
bracis-28401	48	3	show	show	VERB
bracis-28401	48	4	that	that	SCONJ
bracis-28401	48	5	the	the	DET
bracis-28401	48	6	proposed	propose	VERB
bracis-28401	48	7	approaches	approach	NOUN
bracis-28401	48	8	based	base	VERB
bracis-28401	48	9	on	on	ADP
bracis-28401	48	10	random	random	ADJ
bracis-28401	48	11	forests	forest	NOUN
bracis-28401	48	12	and	and	CCONJ
bracis-28401	48	13	approximate	approximate	ADJ
bracis-28401	48	14	gaussian	gaussian	NOUN
bracis-28401	48	15	processes	process	NOUN
bracis-28401	48	16	are	be	AUX
bracis-28401	48	17	the	the	DET
bracis-28401	48	18	ones	one	NOUN
bracis-28401	48	19	that	that	PRON
bracis-28401	48	20	better	well	ADV
bracis-28401	48	21	predict	predict	VERB
bracis-28401	48	22	the	the	DET
bracis-28401	48	23	performance	performance	NOUN
bracis-28401	48	24	of	of	ADP
bracis-28401	48	25	parameterized	parameterized	ADJ
bracis-28401	48	26	algorithms	algorithm	NOUN
bracis-28401	48	27	used	use	VERB
bracis-28401	48	28	to	to	PART
bracis-28401	48	29	solve	solve	VERB
bracis-28401	48	30	np	np	ADV
bracis-28401	48	31	-	-	PUNCT
bracis-28401	48	32	hard	hard	ADJ
bracis-28401	48	33	problems	problem	NOUN
bracis-28401	48	34	.	.	PUNCT
bracis-28401	49	1	the	the	DET
bracis-28401	49	2	correlation	correlation	NOUN
bracis-28401	49	3	coefficients	coefficient	NOUN
bracis-28401	49	4	of	of	ADP
bracis-28401	49	5	predictions	prediction	NOUN
bracis-28401	49	6	reached	reach	VERB
bracis-28401	49	7	values	value	NOUN
bracis-28401	49	8	superior	superior	ADJ
bracis-28401	49	9	to	to	ADP
bracis-28401	49	10	0.9	0.9	NUM
bracis-28401	49	11	.	.	PUNCT
bracis-28401	50	1	although	although	SCONJ
bracis-28401	50	2	the	the	DET
bracis-28401	50	3	research	research	NOUN
bracis-28401	50	4	of	of	ADP
bracis-28401	50	5	hutter	hutter	NOUN
bracis-28401	50	6	et	et	PROPN
bracis-28401	50	7	al	al	PROPN
bracis-28401	50	8	.	.	PROPN
bracis-28401	50	9	provided	provide	VERB
bracis-28401	50	10	relevant	relevant	ADJ
bracis-28401	50	11	results	result	NOUN
bracis-28401	50	12	,	,	PUNCT
bracis-28401	50	13	our	our	PRON
bracis-28401	50	14	focus	focus	NOUN
bracis-28401	50	15	differs	differ	VERB
bracis-28401	50	16	from	from	ADP
bracis-28401	50	17	theirs	theirs	PRON
bracis-28401	50	18	because	because	SCONJ
bracis-28401	50	19	we	we	PRON
bracis-28401	50	20	wish	wish	VERB
bracis-28401	50	21	to	to	PART
bracis-28401	50	22	estimate	estimate	VERB
bracis-28401	50	23	the	the	DET
bracis-28401	50	24	runtime	runtime	NOUN
bracis-28401	50	25	complexity	complexity	NOUN
bracis-28401	50	26	regarding	regard	VERB
bracis-28401	50	27	asymptotic	asymptotic	ADJ
bracis-28401	50	28	order	order	NOUN
bracis-28401	50	29	.	.	PUNCT
bracis-28401	51	1	the	the	DET
bracis-28401	51	2	research	research	NOUN
bracis-28401	51	3	work	work	NOUN
bracis-28401	51	4	of	of	ADP
bracis-28401	51	5	sikka	sikka	PROPN
bracis-28401	51	6	et	et	PROPN
bracis-28401	51	7	al	al	PROPN
bracis-28401	51	8	.	.	PUNCT
bracis-28401	52	1	[	[	X
bracis-28401	52	2	18	18	NUM
bracis-28401	52	3	]	]	PUNCT
bracis-28401	52	4	addressed	address	VERB
bracis-28401	52	5	the	the	DET
bracis-28401	52	6	runtime	runtime	NOUN
bracis-28401	52	7	complexity	complexity	NOUN
bracis-28401	52	8	estimation	estimation	NOUN
bracis-28401	52	9	problem	problem	NOUN
bracis-28401	52	10	using	use	VERB
bracis-28401	52	11	machine	machine	NOUN
bracis-28401	52	12	learning	learning	NOUN
bracis-28401	52	13	models	model	NOUN
bracis-28401	52	14	.	.	PUNCT
bracis-28401	53	1	the	the	DET
bracis-28401	53	2	paper	paper	NOUN
bracis-28401	53	3	has	have	VERB
bracis-28401	53	4	two	two	NUM
bracis-28401	53	5	main	main	ADJ
bracis-28401	53	6	contributions	contribution	NOUN
bracis-28401	53	7	.	.	PUNCT
bracis-28401	54	1	first	first	ADV
bracis-28401	54	2	,	,	PUNCT
bracis-28401	54	3	it	it	PRON
bracis-28401	54	4	publishes	publish	VERB
bracis-28401	54	5	the	the	DET
bracis-28401	54	6	code	code	NOUN
bracis-28401	54	7	runtime	runtime	NOUN
bracis-28401	54	8	complexity	complexity	NOUN
bracis-28401	54	9	dataset	dataset	NOUN
bracis-28401	54	10	(	(	PUNCT
bracis-28401	54	11	corcod	corcod	NOUN
bracis-28401	54	12	)	)	PUNCT
bracis-28401	54	13	composed	compose	VERB
bracis-28401	54	14	of	of	ADP
bracis-28401	54	15	932	932	NUM
bracis-28401	54	16	code	code	NOUN
bracis-28401	54	17	files	file	NOUN
bracis-28401	54	18	belonging	belong	VERB
bracis-28401	54	19	to	to	ADP
bracis-28401	54	20	5	5	NUM
bracis-28401	54	21	different	different	ADJ
bracis-28401	54	22	classes	class	NOUN
bracis-28401	54	23	of	of	ADP
bracis-28401	54	24	complexities	complexity	NOUN
bracis-28401	54	25	,	,	PUNCT
bracis-28401	54	26	namely	namely	ADV
bracis-28401	54	27	constant	constant	ADJ
bracis-28401	54	28	-	-	PUNCT
bracis-28401	54	29	time	time	NOUN
bracis-28401	54	30	,	,	PUNCT
bracis-28401	54	31	logarithmic	logarithmic	ADJ
bracis-28401	54	32	-	-	PUNCT
bracis-28401	54	33	time	time	NOUN
bracis-28401	54	34	,	,	PUNCT
bracis-28401	54	35	linear	linear	ADJ
bracis-28401	54	36	-	-	PUNCT
bracis-28401	54	37	time	time	NOUN
bracis-28401	54	38	,	,	PUNCT
bracis-28401	54	39	linearithmic	linearithmic	ADJ
bracis-28401	54	40	-	-	PUNCT
bracis-28401	54	41	time	time	NOUN
bracis-28401	54	42	,	,	PUNCT
bracis-28401	54	43	and	and	CCONJ
bracis-28401	54	44	quadratic	quadratic	ADJ
bracis-28401	54	45	-	-	PUNCT
bracis-28401	54	46	time	time	NOUN
bracis-28401	54	47	.	.	PUNCT
bracis-28401	55	1	second	second	ADJ
bracis-28401	55	2	,	,	PUNCT
bracis-28401	55	3	it	it	PRON
bracis-28401	55	4	shows	show	VERB
bracis-28401	55	5	that	that	SCONJ
bracis-28401	55	6	the	the	DET
bracis-28401	55	7	random	random	ADJ
bracis-28401	55	8	forest	forest	NOUN
bracis-28401	55	9	model	model	NOUN
bracis-28401	55	10	achieved	achieve	VERB
bracis-28401	55	11	the	the	DET
bracis-28401	55	12	best	good	ADJ
bracis-28401	55	13	results	result	NOUN
bracis-28401	55	14	for	for	ADP
bracis-28401	55	15	predicting	predict	VERB
bracis-28401	55	16	code	code	NOUN
bracis-28401	55	17	complexity	complexity	NOUN
bracis-28401	55	18	,	,	PUNCT
bracis-28401	55	19	with	with	ADP
bracis-28401	55	20	an	an	DET
bracis-28401	55	21	accuracy	accuracy	NOUN
bracis-28401	55	22	of	of	ADP
bracis-28401	55	23	71.84	71.84	NUM
bracis-28401	55	24	%	%	NOUN
bracis-28401	55	25	using	use	VERB
bracis-28401	55	26	code	code	NOUN
bracis-28401	55	27	features	feature	NOUN
bracis-28401	55	28	as	as	ADP
bracis-28401	55	29	attributes	attribute	NOUN
bracis-28401	55	30	and	and	CCONJ
bracis-28401	55	31	83.57	83.57	NUM
bracis-28401	55	32	%	%	NOUN
bracis-28401	55	33	when	when	SCONJ
bracis-28401	55	34	abstract	abstract	ADJ
bracis-28401	55	35	syntax	syntax	NOUN
bracis-28401	55	36	tree	tree	NOUN
bracis-28401	55	37	(	(	PUNCT
bracis-28401	55	38	ast	ast	PROPN
bracis-28401	55	39	)	)	PUNCT
bracis-28401	55	40	applies	apply	VERB
bracis-28401	55	41	to	to	PART
bracis-28401	55	42	generate	generate	VERB
bracis-28401	55	43	code	code	NOUN
bracis-28401	55	44	embedding	embed	VERB
bracis-28401	55	45	used	use	VERB
bracis-28401	55	46	in	in	ADP
bracis-28401	55	47	training	training	NOUN
bracis-28401	55	48	.	.	PUNCT
bracis-28401	56	1	although	although	SCONJ
bracis-28401	56	2	the	the	DET
bracis-28401	56	3	paper	paper	NOUN
bracis-28401	56	4	contributes	contribute	VERB
bracis-28401	56	5	a	a	DET
bracis-28401	56	6	significant	significant	ADJ
bracis-28401	56	7	step	step	NOUN
bracis-28401	56	8	for	for	ADP
bracis-28401	56	9	future	future	ADJ
bracis-28401	56	10	research	research	NOUN
bracis-28401	56	11	,	,	PUNCT
bracis-28401	56	12	we	we	PRON
bracis-28401	56	13	argue	argue	VERB
bracis-28401	56	14	that	that	SCONJ
bracis-28401	56	15	the	the	DET
bracis-28401	56	16	dataset	dataset	NOUN
bracis-28401	56	17	does	do	AUX
bracis-28401	56	18	not	not	PART
bracis-28401	56	19	have	have	VERB
bracis-28401	56	20	entries	entry	NOUN
bracis-28401	56	21	for	for	ADP
bracis-28401	56	22	inefficient	inefficient	ADJ
bracis-28401	56	23	codes	code	NOUN
bracis-28401	56	24	.	.	PUNCT
bracis-28401	57	1	thus	thus	ADV
bracis-28401	57	2	,	,	PUNCT
bracis-28401	57	3	we	we	PRON
bracis-28401	57	4	address	address	VERB
bracis-28401	57	5	this	this	DET
bracis-28401	57	6	problem	problem	NOUN
bracis-28401	57	7	by	by	ADP
bracis-28401	57	8	crawling	crawl	VERB
bracis-28401	57	9	a	a	DET
bracis-28401	57	10	public	public	ADJ
bracis-28401	57	11	website	website	NOUN
bracis-28401	57	12	to	to	PART
bracis-28401	57	13	publish	publish	VERB
bracis-28401	57	14	a	a	DET
bracis-28401	57	15	more	more	ADV
bracis-28401	57	16	comprehensive	comprehensive	ADJ
bracis-28401	57	17	dataset	dataset	NOUN
bracis-28401	57	18	;	;	PUNCT
bracis-28401	57	19	also	also	ADV
bracis-28401	57	20	,	,	PUNCT
bracis-28401	57	21	we	we	PRON
bracis-28401	57	22	evaluated	evaluate	VERB
bracis-28401	57	23	more	more	ADJ
bracis-28401	57	24	recent	recent	ADJ
bracis-28401	57	25	models	model	NOUN
bracis-28401	57	26	,	,	PUNCT
bracis-28401	57	27	such	such	ADJ
bracis-28401	57	28	as	as	ADP
bracis-28401	57	29	the	the	DET
bracis-28401	57	30	extreme	extreme	ADJ
bracis-28401	57	31	gradient	gradient	NOUN
bracis-28401	57	32	boosting	boost	VERB
bracis-28401	57	33	trees	tree	NOUN
bracis-28401	57	34	(	(	PUNCT
bracis-28401	57	35	xgbt	xgbt	NOUN
bracis-28401	57	36	)	)	PUNCT
bracis-28401	57	37	and	and	CCONJ
bracis-28401	57	38	artificial	artificial	ADJ
bracis-28401	57	39	neural	neural	ADJ
bracis-28401	57	40	networks	network	NOUN
bracis-28401	57	41	(	(	PUNCT
bracis-28401	57	42	ann	ann	PROPN
bracis-28401	57	43	)	)	PUNCT
bracis-28401	57	44	.	.	PUNCT
bracis-28401	58	1	the	the	DET
bracis-28401	58	2	efforts	effort	NOUN
bracis-28401	58	3	published	publish	VERB
bracis-28401	58	4	by	by	ADP
bracis-28401	58	5	sepideh	sepideh	NOUN
bracis-28401	58	6	seifzadeh	seifzadeh	NOUN
bracis-28401	58	7	in	in	ADP
bracis-28401	58	8	a	a	DET
bracis-28401	58	9	public	public	ADJ
bracis-28401	58	10	blog	blog	NOUN
bracis-28401	58	11	[	[	X
bracis-28401	58	12	17	17	NUM
bracis-28401	58	13	]	]	PUNCT
bracis-28401	58	14	appear	appear	VERB
bracis-28401	58	15	to	to	PART
bracis-28401	58	16	be	be	AUX
bracis-28401	58	17	the	the	DET
bracis-28401	58	18	results	result	NOUN
bracis-28401	58	19	of	of	ADP
bracis-28401	58	20	ongoing	ongoing	ADJ
bracis-28401	58	21	research	research	NOUN
bracis-28401	58	22	at	at	ADP
bracis-28401	58	23	ibm	ibm	PROPN
bracis-28401	58	24	.	.	PUNCT
bracis-28401	59	1	the	the	DET
bracis-28401	59	2	publication	publication	NOUN
bracis-28401	59	3	has	have	VERB
bracis-28401	59	4	two	two	NUM
bracis-28401	59	5	significant	significant	ADJ
bracis-28401	59	6	highlights	highlight	NOUN
bracis-28401	59	7	:	:	PUNCT
bracis-28401	59	8	first	first	ADV
bracis-28401	59	9	,	,	PUNCT
bracis-28401	59	10	the	the	DET
bracis-28401	59	11	developed	develop	VERB
bracis-28401	59	12	models	model	NOUN
bracis-28401	59	13	use	use	VERB
bracis-28401	59	14	the	the	DET
bracis-28401	59	15	codenet	codenet	NOUN
bracis-28401	59	16	dataset	dataset	VERB
bracis-28401	59	17	with	with	ADP
bracis-28401	59	18	around	around	ADP
bracis-28401	59	19	14	14	NUM
bracis-28401	59	20	m	m	NOUN
bracis-28401	59	21	code	code	NOUN
bracis-28401	59	22	samples	sample	NOUN
bracis-28401	59	23	for	for	ADP
bracis-28401	59	24	roughly	roughly	ADV
bracis-28401	59	25	4k	4k	NUM
bracis-28401	59	26	programming	programming	NOUN
bracis-28401	59	27	problems	problem	NOUN
bracis-28401	59	28	;	;	PUNCT
bracis-28401	59	29	second	second	X
bracis-28401	59	30	,	,	PUNCT
bracis-28401	59	31	they	they	PRON
bracis-28401	59	32	trained	train	VERB
bracis-28401	59	33	an	an	DET
bracis-28401	59	34	ann	ann	NOUN
bracis-28401	59	35	and	and	CCONJ
bracis-28401	59	36	a	a	DET
bracis-28401	59	37	light	light	ADJ
bracis-28401	59	38	gradient	gradient	NOUN
bracis-28401	59	39	boosting	boost	VERB
bracis-28401	59	40	machine	machine	NOUN
bracis-28401	59	41	(	(	PUNCT
bracis-28401	59	42	lgbm	lgbm	NOUN
bracis-28401	59	43	)	)	PUNCT
bracis-28401	59	44	using	use	VERB
bracis-28401	59	45	both	both	PRON
bracis-28401	59	46	code	code	NOUN
bracis-28401	59	47	features	feature	NOUN
bracis-28401	59	48	and	and	CCONJ
bracis-28401	59	49	code	code	NOUN
bracis-28401	59	50	graph	graph	NOUN
bracis-28401	59	51	representation	representation	NOUN
bracis-28401	59	52	to	to	PART
bracis-28401	59	53	predict	predict	VERB
bracis-28401	59	54	six	six	NUM
bracis-28401	59	55	classes	class	NOUN
bracis-28401	59	56	of	of	ADP
bracis-28401	59	57	runtime	runtime	NOUN
bracis-28401	59	58	complexity	complexity	NOUN
bracis-28401	59	59	near	near	ADP
bracis-28401	59	60	-	-	PUNCT
bracis-28401	59	61	constant	constant	ADJ
bracis-28401	59	62	,	,	PUNCT
bracis-28401	59	63	linear	linear	ADJ
bracis-28401	59	64	,	,	PUNCT
bracis-28401	59	65	log	log	NOUN
bracis-28401	59	66	-	-	PUNCT
bracis-28401	59	67	linear	linear	NOUN
bracis-28401	59	68	,	,	PUNCT
bracis-28401	59	69	polynomial	polynomial	ADJ
bracis-28401	59	70	,	,	PUNCT
bracis-28401	59	71	exponential	exponential	NOUN
bracis-28401	59	72	,	,	PUNCT
bracis-28401	59	73	and	and	CCONJ
bracis-28401	59	74	factorial	factorial	NOUN
bracis-28401	59	75	.	.	PUNCT
bracis-28401	60	1	the	the	DET
bracis-28401	60	2	preliminary	preliminary	ADJ
bracis-28401	60	3	results	result	NOUN
bracis-28401	60	4	show	show	VERB
bracis-28401	60	5	up	up	ADP
bracis-28401	60	6	to	to	ADP
bracis-28401	60	7	\(80\%\	\(80\%\	NOUN
bracis-28401	60	8	)	)	PUNCT
bracis-28401	60	9	of	of	ADP
bracis-28401	60	10	accuracy	accuracy	NOUN
bracis-28401	60	11	in	in	ADP
bracis-28401	60	12	predictions	prediction	NOUN
bracis-28401	60	13	,	,	PUNCT
bracis-28401	60	14	which	which	PRON
bracis-28401	60	15	supports	support	VERB
bracis-28401	60	16	machine	machine	NOUN
bracis-28401	60	17	learning	learn	VERB
bracis-28401	60	18	for	for	ADP
bracis-28401	60	19	addressing	address	VERB
bracis-28401	60	20	the	the	DET
bracis-28401	60	21	problem	problem	NOUN
bracis-28401	60	22	of	of	ADP
bracis-28401	60	23	runtime	runtime	NOUN
bracis-28401	60	24	complexity	complexity	NOUN
bracis-28401	60	25	estimation	estimation	NOUN
bracis-28401	60	26	.	.	PUNCT
bracis-28401	61	1	despite	despite	SCONJ
bracis-28401	61	2	the	the	DET
bracis-28401	61	3	promising	promising	ADJ
bracis-28401	61	4	results	result	NOUN
bracis-28401	61	5	,	,	PUNCT
bracis-28401	61	6	the	the	DET
bracis-28401	61	7	problem	problem	NOUN
bracis-28401	61	8	remains	remain	VERB
bracis-28401	61	9	open	open	ADJ
bracis-28401	61	10	,	,	PUNCT
bracis-28401	61	11	with	with	ADP
bracis-28401	61	12	space	space	NOUN
bracis-28401	61	13	for	for	ADP
bracis-28401	61	14	improvements	improvement	NOUN
bracis-28401	61	15	;	;	PUNCT
bracis-28401	61	16	also	also	ADV
bracis-28401	61	17	,	,	PUNCT
bracis-28401	61	18	we	we	PRON
bracis-28401	61	19	accessed	access	VERB
bracis-28401	61	20	the	the	DET
bracis-28401	61	21	codenet	codenet	NOUN
bracis-28401	61	22	used	use	VERB
bracis-28401	61	23	in	in	ADP
bracis-28401	61	24	the	the	DET
bracis-28401	61	25	results	result	NOUN
bracis-28401	61	26	and	and	CCONJ
bracis-28401	61	27	do	do	AUX
bracis-28401	61	28	not	not	PART
bracis-28401	61	29	find	find	VERB
bracis-28401	61	30	the	the	DET
bracis-28401	61	31	tags	tag	NOUN
bracis-28401	61	32	that	that	PRON
bracis-28401	61	33	classify	classify	VERB
bracis-28401	61	34	codes	code	NOUN
bracis-28401	61	35	according	accord	VERB
bracis-28401	61	36	to	to	ADP
bracis-28401	61	37	complexity	complexity	NOUN
bracis-28401	61	38	classes	class	NOUN
bracis-28401	61	39	,	,	PUNCT
bracis-28401	61	40	we	we	PRON
bracis-28401	61	41	suppose	suppose	VERB
bracis-28401	61	42	authors	author	NOUN
bracis-28401	61	43	manually	manually	ADV
bracis-28401	61	44	tagged	tag	VERB
bracis-28401	61	45	the	the	DET
bracis-28401	61	46	dataset	dataset	NOUN
bracis-28401	61	47	,	,	PUNCT
bracis-28401	61	48	but	but	CCONJ
bracis-28401	61	49	it	it	PRON
bracis-28401	61	50	is	be	AUX
bracis-28401	61	51	not	not	PART
bracis-28401	61	52	clear	clear	ADJ
bracis-28401	61	53	in	in	ADP
bracis-28401	61	54	the	the	DET
bracis-28401	61	55	published	publish	VERB
bracis-28401	61	56	article	article	NOUN
bracis-28401	61	57	.	.	PUNCT
bracis-28401	62	1	3	3	NUM
bracis-28401	62	2	material	material	NOUN
bracis-28401	62	3	and	and	CCONJ
bracis-28401	62	4	 	 	SPACE
bracis-28401	62	5	methods	method	NOUN
bracis-28401	62	6	this	this	DET
bracis-28401	62	7	section	section	NOUN
bracis-28401	62	8	presents	present	VERB
bracis-28401	62	9	the	the	DET
bracis-28401	62	10	materials	material	NOUN
bracis-28401	62	11	and	and	CCONJ
bracis-28401	62	12	methodology	methodology	NOUN
bracis-28401	62	13	used	use	VERB
bracis-28401	62	14	to	to	PART
bracis-28401	62	15	compare	compare	VERB
bracis-28401	62	16	approaches	approach	NOUN
bracis-28401	62	17	to	to	PART
bracis-28401	62	18	estimate	estimate	VERB
bracis-28401	62	19	code	code	NOUN
bracis-28401	62	20	running	running	NOUN
bracis-28401	62	21	time	time	NOUN
bracis-28401	62	22	complexity	complexity	NOUN
bracis-28401	62	23	.	.	PUNCT
bracis-28401	63	1	section	section	NOUN
bracis-28401	63	2	 	 	SPACE
bracis-28401	63	3	3.1	3.1	NUM
bracis-28401	63	4	explains	explain	VERB
bracis-28401	63	5	the	the	DET
bracis-28401	63	6	steps	step	NOUN
bracis-28401	63	7	taken	take	VERB
bracis-28401	63	8	to	to	PART
bracis-28401	63	9	consolidate	consolidate	VERB
bracis-28401	63	10	a	a	DET
bracis-28401	63	11	dataset	dataset	NOUN
bracis-28401	63	12	with	with	ADP
bracis-28401	63	13	representativeness	representativeness	NOUN
bracis-28401	63	14	for	for	ADP
bracis-28401	63	15	training	training	NOUN
bracis-28401	63	16	machine	machine	NOUN
bracis-28401	63	17	learning	learning	NOUN
bracis-28401	63	18	models	model	NOUN
bracis-28401	63	19	,	,	PUNCT
bracis-28401	63	20	including	include	VERB
bracis-28401	63	21	a	a	DET
bracis-28401	63	22	discussion	discussion	NOUN
bracis-28401	63	23	regarding	regard	VERB
bracis-28401	63	24	dataset	dataset	ADJ
bracis-28401	63	25	balancing	balancing	NOUN
bracis-28401	63	26	.	.	PUNCT
bracis-28401	64	1	section	section	NOUN
bracis-28401	64	2	 	 	SPACE
bracis-28401	64	3	3.2	3.2	NUM
bracis-28401	64	4	explains	explain	VERB
bracis-28401	64	5	how	how	SCONJ
bracis-28401	64	6	we	we	PRON
bracis-28401	64	7	extracted	extract	VERB
bracis-28401	64	8	attributes	attribute	NOUN
bracis-28401	64	9	from	from	ADP
bracis-28401	64	10	codes	code	NOUN
bracis-28401	64	11	and	and	CCONJ
bracis-28401	64	12	the	the	DET
bracis-28401	64	13	assumptions	assumption	NOUN
bracis-28401	64	14	leveraged	leverage	VERB
bracis-28401	64	15	for	for	ADP
bracis-28401	64	16	complexity	complexity	NOUN
bracis-28401	64	17	classification	classification	NOUN
bracis-28401	64	18	,	,	PUNCT
bracis-28401	64	19	as	as	SCONJ
bracis-28401	64	20	also	also	ADV
bracis-28401	64	21	discusses	discuss	VERB
bracis-28401	64	22	the	the	DET
bracis-28401	64	23	process	process	NOUN
bracis-28401	64	24	used	use	VERB
bracis-28401	64	25	to	to	PART
bracis-28401	64	26	select	select	VERB
bracis-28401	64	27	features	feature	NOUN
bracis-28401	64	28	for	for	ADP
bracis-28401	64	29	the	the	DET
bracis-28401	64	30	machine	machine	NOUN
bracis-28401	64	31	learning	learning	NOUN
bracis-28401	64	32	models	model	NOUN
bracis-28401	64	33	.	.	PUNCT
bracis-28401	65	1	finally	finally	ADV
bracis-28401	65	2	,	,	PUNCT
bracis-28401	65	3	sect	sect	NOUN
bracis-28401	65	4	.	.	PUNCT
bracis-28401	65	5	 	 	SPACE
bracis-28401	66	1	3.3	3.3	NUM
bracis-28401	66	2	presents	present	VERB
bracis-28401	66	3	the	the	DET
bracis-28401	66	4	machine	machine	NOUN
bracis-28401	66	5	learning	learning	NOUN
bracis-28401	66	6	models	model	NOUN
bracis-28401	66	7	used	use	VERB
bracis-28401	66	8	to	to	PART
bracis-28401	66	9	predict	predict	VERB
bracis-28401	66	10	the	the	DET
bracis-28401	66	11	codes	code	NOUN
bracis-28401	66	12	’	'	PUNCT
bracis-28401	66	13	complexity	complexity	NOUN
bracis-28401	66	14	and	and	CCONJ
bracis-28401	66	15	process	process	NOUN
bracis-28401	66	16	used	use	VERB
bracis-28401	66	17	for	for	ADP
bracis-28401	66	18	comparisons	comparison	NOUN
bracis-28401	66	19	.	.	PUNCT
bracis-28401	67	1	all	all	DET
bracis-28401	67	2	the	the	DET
bracis-28401	67	3	source	source	NOUN
bracis-28401	67	4	codes	code	NOUN
bracis-28401	67	5	we	we	PRON
bracis-28401	67	6	used	use	VERB
bracis-28401	67	7	in	in	ADP
bracis-28401	67	8	this	this	DET
bracis-28401	67	9	paper	paper	NOUN
bracis-28401	67	10	are	be	AUX
bracis-28401	67	11	available	available	ADJ
bracis-28401	67	12	on	on	ADP
bracis-28401	67	13	githubfootnote	githubfootnote	PROPN
bracis-28401	67	14	1	1	NUM
bracis-28401	67	15	.	.	SYM
bracis-28401	67	16	3.1	3.1	NUM
bracis-28401	67	17	dataset	dataset	NOUN
bracis-28401	67	18	consolidation	consolidation	NOUN
bracis-28401	67	19	the	the	DET
bracis-28401	67	20	first	first	ADJ
bracis-28401	67	21	step	step	NOUN
bracis-28401	67	22	toward	toward	ADP
bracis-28401	67	23	developing	develop	VERB
bracis-28401	67	24	this	this	DET
bracis-28401	67	25	research	research	NOUN
bracis-28401	67	26	project	project	NOUN
bracis-28401	67	27	is	be	AUX
bracis-28401	67	28	dataset	dataset	ADJ
bracis-28401	67	29	consolidation	consolidation	NOUN
bracis-28401	67	30	.	.	PUNCT
bracis-28401	68	1	this	this	DET
bracis-28401	68	2	work	work	NOUN
bracis-28401	68	3	relies	rely	VERB
bracis-28401	68	4	on	on	ADP
bracis-28401	68	5	three	three	NUM
bracis-28401	68	6	datasets	dataset	NOUN
bracis-28401	68	7	.	.	PUNCT
bracis-28401	69	1	the	the	DET
bracis-28401	69	2	first	first	ADJ
bracis-28401	69	3	one	one	NUM
bracis-28401	69	4	is	be	AUX
bracis-28401	69	5	the	the	DET
bracis-28401	69	6	reference	reference	NOUN
bracis-28401	69	7	dataset	dataset	NOUN
bracis-28401	69	8	published	publish	VERB
bracis-28401	69	9	in	in	ADP
bracis-28401	69	10	the	the	DET
bracis-28401	69	11	work	work	NOUN
bracis-28401	69	12	of	of	ADP
bracis-28401	69	13	sikka	sikka	PROPN
bracis-28401	69	14	et	et	PROPN
bracis-28401	69	15	al	al	PROPN
bracis-28401	69	16	.	.	PUNCT
bracis-28401	70	1	[	[	X
bracis-28401	70	2	18	18	NUM
bracis-28401	70	3	]	]	PUNCT
bracis-28401	70	4	,	,	PUNCT
bracis-28401	70	5	which	which	PRON
bracis-28401	70	6	consists	consist	VERB
bracis-28401	70	7	of	of	ADP
bracis-28401	70	8	931	931	NUM
bracis-28401	70	9	java	java	PROPN
bracis-28401	70	10	code	code	NOUN
bracis-28401	70	11	files	file	NOUN
bracis-28401	70	12	,	,	PUNCT
bracis-28401	70	13	with	with	ADP
bracis-28401	70	14	14	14	NUM
bracis-28401	70	15	metadata	metadata	NOUN
bracis-28401	70	16	information	information	NOUN
bracis-28401	70	17	relative	relative	ADJ
bracis-28401	70	18	to	to	ADP
bracis-28401	70	19	the	the	DET
bracis-28401	70	20	codes	code	NOUN
bracis-28401	70	21	and	and	CCONJ
bracis-28401	70	22	their	their	PRON
bracis-28401	70	23	respective	respective	ADJ
bracis-28401	70	24	complexity	complexity	NOUN
bracis-28401	70	25	.	.	PUNCT
bracis-28401	71	1	considering	consider	VERB
bracis-28401	71	2	that	that	SCONJ
bracis-28401	71	3	such	such	DET
bracis-28401	71	4	a	a	DET
bracis-28401	71	5	dataset	dataset	NOUN
bracis-28401	71	6	does	do	AUX
bracis-28401	71	7	not	not	PART
bracis-28401	71	8	contain	contain	VERB
bracis-28401	71	9	codes	code	NOUN
bracis-28401	71	10	with	with	ADP
bracis-28401	71	11	intractable	intractable	ADJ
bracis-28401	71	12	complexity	complexity	NOUN
bracis-28401	71	13	,	,	PUNCT
bracis-28401	71	14	this	this	DET
bracis-28401	71	15	work	work	NOUN
bracis-28401	71	16	builds	build	VERB
bracis-28401	71	17	a	a	DET
bracis-28401	71	18	second	second	ADJ
bracis-28401	71	19	one	one	NUM
bracis-28401	71	20	with	with	ADP
bracis-28401	71	21	data	datum	NOUN
bracis-28401	71	22	from	from	ADP
bracis-28401	71	23	a	a	DET
bracis-28401	71	24	publicly	publicly	ADV
bracis-28401	71	25	available	available	ADJ
bracis-28401	71	26	website	website	NOUN
bracis-28401	71	27	,	,	PUNCT
bracis-28401	71	28	which	which	PRON
bracis-28401	71	29	we	we	PRON
bracis-28401	71	30	call	call	VERB
bracis-28401	71	31	crawled	crawl	VERB
bracis-28401	71	32	dataset	dataset	NOUN
bracis-28401	71	33	(	(	PUNCT
bracis-28401	71	34	394	394	NUM
bracis-28401	71	35	entries	entry	NOUN
bracis-28401	71	36	)	)	PUNCT
bracis-28401	71	37	.	.	PUNCT
bracis-28401	72	1	the	the	DET
bracis-28401	72	2	third	third	ADJ
bracis-28401	72	3	one	one	NOUN
bracis-28401	72	4	,	,	PUNCT
bracis-28401	72	5	the	the	DET
bracis-28401	72	6	merged	merge	VERB
bracis-28401	72	7	dataset	dataset	NOUN
bracis-28401	72	8	(	(	PUNCT
bracis-28401	72	9	1325	1325	NUM
bracis-28401	72	10	entries	entry	NOUN
bracis-28401	72	11	)	)	PUNCT
bracis-28401	72	12	,	,	PUNCT
bracis-28401	72	13	results	result	VERB
bracis-28401	72	14	from	from	ADP
bracis-28401	72	15	merging	merge	VERB
bracis-28401	72	16	the	the	DET
bracis-28401	72	17	reference	reference	NOUN
bracis-28401	72	18	and	and	CCONJ
bracis-28401	72	19	the	the	DET
bracis-28401	72	20	crawled	crawl	VERB
bracis-28401	72	21	datasets	dataset	NOUN
bracis-28401	72	22	.	.	PUNCT
bracis-28401	73	1	we	we	PRON
bracis-28401	73	2	developed	develop	VERB
bracis-28401	73	3	a	a	DET
bracis-28401	73	4	web	web	NOUN
bracis-28401	73	5	crawler	crawler	NOUN
bracis-28401	73	6	to	to	PART
bracis-28401	73	7	extract	extract	VERB
bracis-28401	73	8	the	the	DET
bracis-28401	73	9	information	information	NOUN
bracis-28401	73	10	from	from	ADP
bracis-28401	73	11	the	the	DET
bracis-28401	73	12	platform	platform	NOUN
bracis-28401	73	13	geekforgeeks.org	geekforgeeks.org	PROPN
bracis-28401	73	14	,	,	PUNCT
bracis-28401	73	15	which	which	PRON
bracis-28401	73	16	contains	contain	VERB
bracis-28401	73	17	a	a	DET
bracis-28401	73	18	specific	specific	ADJ
bracis-28401	73	19	section	section	NOUN
bracis-28401	73	20	to	to	PART
bracis-28401	73	21	discuss	discuss	VERB
bracis-28401	73	22	fundamentals	fundamental	NOUN
bracis-28401	73	23	of	of	ADP
bracis-28401	73	24	algorithmsfootnote	algorithmsfootnote	NOUN
bracis-28401	73	25	2	2	NUM
bracis-28401	73	26	.	.	PUNCT
bracis-28401	73	27	such	such	ADJ
bracis-28401	73	28	section	section	NOUN
bracis-28401	73	29	discusses	discuss	VERB
bracis-28401	73	30	several	several	ADJ
bracis-28401	73	31	algorithms	algorithm	NOUN
bracis-28401	73	32	,	,	PUNCT
bracis-28401	73	33	their	their	PRON
bracis-28401	73	34	respective	respective	ADJ
bracis-28401	73	35	codes	code	NOUN
bracis-28401	73	36	,	,	PUNCT
bracis-28401	73	37	and	and	CCONJ
bracis-28401	73	38	complexities	complexity	NOUN
bracis-28401	73	39	.	.	PUNCT
bracis-28401	74	1	the	the	DET
bracis-28401	74	2	crawler	crawler	NOUN
bracis-28401	74	3	consists	consist	VERB
bracis-28401	74	4	of	of	ADP
bracis-28401	74	5	a	a	DET
bracis-28401	74	6	python	python	NOUN
bracis-28401	74	7	script	script	NOUN
bracis-28401	74	8	that	that	PRON
bracis-28401	74	9	uses	use	VERB
bracis-28401	74	10	the	the	DET
bracis-28401	74	11	selenium	selenium	NOUN
bracis-28401	74	12	library	library	NOUN
bracis-28401	74	13	to	to	PART
bracis-28401	74	14	scratch	scratch	VERB
bracis-28401	74	15	the	the	DET
bracis-28401	74	16	website	website	NOUN
bracis-28401	74	17	and	and	CCONJ
bracis-28401	74	18	extract	extract	VERB
bracis-28401	74	19	codes	code	NOUN
bracis-28401	74	20	and	and	CCONJ
bracis-28401	74	21	complexity	complexity	NOUN
bracis-28401	74	22	information	information	NOUN
bracis-28401	74	23	and	and	CCONJ
bracis-28401	74	24	runs	run	NOUN
bracis-28401	74	25	as	as	SCONJ
bracis-28401	74	26	follows	follow	VERB
bracis-28401	74	27	.	.	PUNCT
bracis-28401	75	1	first	first	ADV
bracis-28401	75	2	,	,	PUNCT
bracis-28401	75	3	it	it	PRON
bracis-28401	75	4	accesses	access	VERB
bracis-28401	75	5	the	the	DET
bracis-28401	75	6	main	main	ADJ
bracis-28401	75	7	page	page	NOUN
bracis-28401	75	8	,	,	PUNCT
bracis-28401	75	9	which	which	PRON
bracis-28401	75	10	contains	contain	VERB
bracis-28401	75	11	a	a	DET
bracis-28401	75	12	list	list	NOUN
bracis-28401	75	13	of	of	ADP
bracis-28401	75	14	topics	topic	NOUN
bracis-28401	75	15	related	relate	VERB
bracis-28401	75	16	to	to	ADP
bracis-28401	75	17	the	the	DET
bracis-28401	75	18	fundamentals	fundamental	NOUN
bracis-28401	75	19	of	of	ADP
bracis-28401	75	20	algorithms	algorithm	NOUN
bracis-28401	75	21	.	.	PUNCT
bracis-28401	76	1	then	then	ADV
bracis-28401	76	2	,	,	PUNCT
bracis-28401	76	3	the	the	DET
bracis-28401	76	4	crawler	crawler	NOUN
bracis-28401	76	5	runs	run	VERB
bracis-28401	76	6	a	a	DET
bracis-28401	76	7	login	login	NOUN
bracis-28401	76	8	process	process	NOUN
bracis-28401	76	9	and	and	CCONJ
bracis-28401	76	10	computes	compute	VERB
bracis-28401	76	11	the	the	DET
bracis-28401	76	12	list	list	NOUN
bracis-28401	76	13	of	of	ADP
bracis-28401	76	14	links	link	NOUN
bracis-28401	76	15	to	to	PART
bracis-28401	76	16	be	be	AUX
bracis-28401	76	17	visited	visit	VERB
bracis-28401	76	18	on	on	ADP
bracis-28401	76	19	the	the	DET
bracis-28401	76	20	page	page	NOUN
bracis-28401	76	21	.	.	PUNCT
bracis-28401	77	1	next	next	ADV
bracis-28401	77	2	,	,	PUNCT
bracis-28401	77	3	each	each	DET
bracis-28401	77	4	page	page	NOUN
bracis-28401	77	5	in	in	ADP
bracis-28401	77	6	the	the	DET
bracis-28401	77	7	link	link	NOUN
bracis-28401	77	8	list	list	NOUN
bracis-28401	77	9	is	be	AUX
bracis-28401	77	10	accessed	access	VERB
bracis-28401	77	11	to	to	PART
bracis-28401	77	12	verify	verify	VERB
bracis-28401	77	13	if	if	SCONJ
bracis-28401	77	14	it	it	PRON
bracis-28401	77	15	contains	contain	VERB
bracis-28401	77	16	content	content	NOUN
bracis-28401	77	17	relevant	relevant	ADJ
bracis-28401	77	18	to	to	ADP
bracis-28401	77	19	complexity	complexity	NOUN
bracis-28401	77	20	prediction	prediction	NOUN
bracis-28401	77	21	.	.	PUNCT
bracis-28401	78	1	in	in	ADP
bracis-28401	78	2	other	other	ADJ
bracis-28401	78	3	words	word	NOUN
bracis-28401	78	4	,	,	PUNCT
bracis-28401	78	5	the	the	DET
bracis-28401	78	6	crawler	crawler	NOUN
bracis-28401	78	7	searches	search	NOUN
bracis-28401	78	8	if	if	SCONJ
bracis-28401	78	9	the	the	DET
bracis-28401	78	10	page	page	NOUN
bracis-28401	78	11	has	have	VERB
bracis-28401	78	12	algorithms	algorithm	NOUN
bracis-28401	78	13	’	'	PUNCT
bracis-28401	78	14	source	source	NOUN
bracis-28401	78	15	codes	code	NOUN
bracis-28401	78	16	and	and	CCONJ
bracis-28401	78	17	runtime	runtime	NOUN
bracis-28401	78	18	complexity	complexity	NOUN
bracis-28401	78	19	information	information	NOUN
bracis-28401	78	20	.	.	PUNCT
bracis-28401	79	1	considering	consider	VERB
bracis-28401	79	2	that	that	SCONJ
bracis-28401	79	3	the	the	DET
bracis-28401	79	4	focus	focus	NOUN
bracis-28401	79	5	of	of	ADP
bracis-28401	79	6	this	this	DET
bracis-28401	79	7	research	research	NOUN
bracis-28401	79	8	is	be	AUX
bracis-28401	79	9	to	to	PART
bracis-28401	79	10	extend	extend	VERB
bracis-28401	79	11	the	the	DET
bracis-28401	79	12	reference	reference	NOUN
bracis-28401	79	13	dataset	dataset	NOUN
bracis-28401	79	14	,	,	PUNCT
bracis-28401	79	15	the	the	DET
bracis-28401	79	16	crawler	crawler	NOUN
bracis-28401	79	17	always	always	ADV
bracis-28401	79	18	selects	select	VERB
bracis-28401	79	19	java	java	PROPN
bracis-28401	79	20	programming	programming	NOUN
bracis-28401	79	21	language	language	NOUN
bracis-28401	79	22	.	.	PUNCT
bracis-28401	80	1	also	also	ADV
bracis-28401	80	2	,	,	PUNCT
bracis-28401	80	3	the	the	DET
bracis-28401	80	4	page	page	NOUN
bracis-28401	80	5	should	should	AUX
bracis-28401	80	6	provide	provide	VERB
bracis-28401	80	7	text	text	NOUN
bracis-28401	80	8	describing	describe	VERB
bracis-28401	80	9	the	the	DET
bracis-28401	80	10	time	time	NOUN
bracis-28401	80	11	complexity	complexity	NOUN
bracis-28401	80	12	of	of	ADP
bracis-28401	80	13	the	the	DET
bracis-28401	80	14	code	code	NOUN
bracis-28401	80	15	in	in	ADP
bracis-28401	80	16	any	any	DET
bracis-28401	80	17	place	place	NOUN
bracis-28401	80	18	near	near	ADP
bracis-28401	80	19	it	it	PRON
bracis-28401	80	20	.	.	PUNCT
bracis-28401	81	1	as	as	ADV
bracis-28401	81	2	soon	soon	ADV
bracis-28401	81	3	as	as	SCONJ
bracis-28401	81	4	the	the	DET
bracis-28401	81	5	crawler	crawler	NOUN
bracis-28401	81	6	identifies	identify	VERB
bracis-28401	81	7	that	that	SCONJ
bracis-28401	81	8	the	the	DET
bracis-28401	81	9	page	page	NOUN
bracis-28401	81	10	contains	contain	VERB
bracis-28401	81	11	the	the	DET
bracis-28401	81	12	relevant	relevant	ADJ
bracis-28401	81	13	content	content	NOUN
bracis-28401	81	14	,	,	PUNCT
bracis-28401	81	15	it	it	PRON
bracis-28401	81	16	copies	copy	VERB
bracis-28401	81	17	each	each	DET
bracis-28401	81	18	code	code	NOUN
bracis-28401	81	19	and	and	CCONJ
bracis-28401	81	20	searches	search	NOUN
bracis-28401	81	21	for	for	ADP
bracis-28401	81	22	the	the	DET
bracis-28401	81	23	nearest	near	ADJ
bracis-28401	81	24	complexity	complexity	NOUN
bracis-28401	81	25	information	information	NOUN
bracis-28401	81	26	.	.	PUNCT
bracis-28401	82	1	it	it	PRON
bracis-28401	82	2	is	be	AUX
bracis-28401	82	3	essential	essential	ADJ
bracis-28401	82	4	to	to	PART
bracis-28401	82	5	highlight	highlight	VERB
bracis-28401	82	6	that	that	SCONJ
bracis-28401	82	7	many	many	ADJ
bracis-28401	82	8	pages	page	NOUN
bracis-28401	82	9	have	have	VERB
bracis-28401	82	10	multiple	multiple	ADJ
bracis-28401	82	11	program	program	NOUN
bracis-28401	82	12	codes	code	NOUN
bracis-28401	82	13	;	;	PUNCT
bracis-28401	82	14	thus	thus	ADV
bracis-28401	82	15	,	,	PUNCT
bracis-28401	82	16	we	we	PRON
bracis-28401	82	17	save	save	VERB
bracis-28401	82	18	each	each	DET
bracis-28401	82	19	one	one	NOUN
bracis-28401	82	20	and	and	CCONJ
bracis-28401	82	21	associate	associate	VERB
bracis-28401	82	22	it	it	PRON
bracis-28401	82	23	with	with	ADP
bracis-28401	82	24	the	the	DET
bracis-28401	82	25	runtime	runtime	NOUN
bracis-28401	82	26	complexity	complexity	NOUN
bracis-28401	82	27	information	information	NOUN
bracis-28401	82	28	closer	close	ADV
bracis-28401	82	29	to	to	ADP
bracis-28401	82	30	the	the	DET
bracis-28401	82	31	point	point	NOUN
bracis-28401	82	32	where	where	SCONJ
bracis-28401	82	33	the	the	DET
bracis-28401	82	34	program	program	NOUN
bracis-28401	82	35	code	code	NOUN
bracis-28401	82	36	is	be	AUX
bracis-28401	82	37	exhibited	exhibit	VERB
bracis-28401	82	38	.	.	PUNCT
bracis-28401	83	1	such	such	ADJ
bracis-28401	83	2	nearest	near	ADJ
bracis-28401	83	3	assumption	assumption	NOUN
bracis-28401	83	4	involves	involve	VERB
bracis-28401	83	5	a	a	DET
bracis-28401	83	6	risk	risk	NOUN
bracis-28401	83	7	of	of	ADP
bracis-28401	83	8	misclassification	misclassification	NOUN
bracis-28401	83	9	,	,	PUNCT
bracis-28401	83	10	as	as	SCONJ
bracis-28401	83	11	the	the	DET
bracis-28401	83	12	pages	page	NOUN
bracis-28401	83	13	from	from	ADP
bracis-28401	83	14	the	the	DET
bracis-28401	83	15	website	website	NOUN
bracis-28401	83	16	do	do	AUX
bracis-28401	83	17	not	not	PART
bracis-28401	83	18	follow	follow	VERB
bracis-28401	83	19	a	a	DET
bracis-28401	83	20	static	static	ADJ
bracis-28401	83	21	standard	standard	NOUN
bracis-28401	83	22	;	;	PUNCT
bracis-28401	83	23	however	however	ADV
bracis-28401	83	24	,	,	PUNCT
bracis-28401	83	25	we	we	PRON
bracis-28401	83	26	understand	understand	VERB
bracis-28401	83	27	that	that	SCONJ
bracis-28401	83	28	this	this	PRON
bracis-28401	83	29	is	be	AUX
bracis-28401	83	30	the	the	DET
bracis-28401	83	31	best	good	ADJ
bracis-28401	83	32	effort	effort	NOUN
bracis-28401	83	33	for	for	ADP
bracis-28401	83	34	automated	automate	VERB
bracis-28401	83	35	computing	computing	NOUN
bracis-28401	83	36	of	of	ADP
bracis-28401	83	37	a	a	DET
bracis-28401	83	38	dataset	dataset	NOUN
bracis-28401	83	39	.	.	PUNCT
bracis-28401	84	1	the	the	DET
bracis-28401	84	2	crawler	crawler	NOUN
bracis-28401	84	3	process	process	NOUN
bracis-28401	84	4	resulted	result	VERB
bracis-28401	84	5	in	in	ADP
bracis-28401	84	6	a	a	DET
bracis-28401	84	7	dataset	dataset	NOUN
bracis-28401	84	8	with	with	ADP
bracis-28401	84	9	394	394	NUM
bracis-28401	84	10	program	program	NOUN
bracis-28401	84	11	codes	code	NOUN
bracis-28401	84	12	and	and	CCONJ
bracis-28401	84	13	78	78	NUM
bracis-28401	84	14	distinct	distinct	ADJ
bracis-28401	84	15	complexity	complexity	NOUN
bracis-28401	84	16	classes	class	NOUN
bracis-28401	84	17	.	.	PUNCT
bracis-28401	85	1	many	many	ADJ
bracis-28401	85	2	classes	class	NOUN
bracis-28401	85	3	extracted	extract	VERB
bracis-28401	85	4	from	from	ADP
bracis-28401	85	5	the	the	DET
bracis-28401	85	6	web	web	NOUN
bracis-28401	85	7	pages	page	NOUN
bracis-28401	85	8	do	do	AUX
bracis-28401	85	9	not	not	PART
bracis-28401	85	10	follow	follow	VERB
bracis-28401	85	11	the	the	DET
bracis-28401	85	12	general	general	ADJ
bracis-28401	85	13	form	form	NOUN
bracis-28401	85	14	of	of	ADP
bracis-28401	85	15	asymptotic	asymptotic	ADJ
bracis-28401	85	16	classes	class	NOUN
bracis-28401	85	17	;	;	PUNCT
bracis-28401	85	18	for	for	ADP
bracis-28401	85	19	example	example	NOUN
bracis-28401	85	20	,	,	PUNCT
bracis-28401	85	21	the	the	DET
bracis-28401	85	22	classes	class	NOUN
bracis-28401	85	23	o(n|n|	o(n|n|	NUM
bracis-28401	85	24	)	)	PUNCT
bracis-28401	85	25	(	(	PUNCT
bracis-28401	85	26	algorithm	algorithm	NOUN
bracis-28401	85	27	:	:	PUNCT
bracis-28401	85	28	compute	compute	VERB
bracis-28401	85	29	the	the	DET
bracis-28401	85	30	sum	sum	NOUN
bracis-28401	85	31	of	of	ADP
bracis-28401	85	32	digits	digit	NOUN
bracis-28401	85	33	in	in	ADP
bracis-28401	85	34	all	all	DET
bracis-28401	85	35	numbers	number	NOUN
bracis-28401	85	36	from	from	ADP
bracis-28401	85	37	1	1	NUM
bracis-28401	85	38	to	to	ADP
bracis-28401	85	39	n	n	CCONJ
bracis-28401	85	40	)	)	PUNCT
bracis-28401	85	41	and	and	CCONJ
bracis-28401	85	42	\(o(m^2k	\(o(m^2k	NOUN
bracis-28401	86	1	+	+	CCONJ
bracis-28401	86	2	k^3	k^3	PROPN
bracis-28401	86	3	log	log	VERB
bracis-28401	86	4	n)\	n)\	NUM
bracis-28401	86	5	)	)	PUNCT
bracis-28401	86	6	(	(	PUNCT
bracis-28401	86	7	algorithm	algorithm	NOUN
bracis-28401	86	8	:	:	PUNCT
bracis-28401	86	9	count	count	VERB
bracis-28401	86	10	ways	way	NOUN
bracis-28401	86	11	to	to	PART
bracis-28401	86	12	reach	reach	VERB
bracis-28401	86	13	the	the	DET
bracis-28401	86	14	nth	nth	NOUN
bracis-28401	86	15	stair	stair	NOUN
bracis-28401	86	16	)	)	PUNCT
bracis-28401	86	17	do	do	AUX
bracis-28401	86	18	not	not	PART
bracis-28401	86	19	match	match	VERB
bracis-28401	86	20	any	any	DET
bracis-28401	86	21	general	general	ADJ
bracis-28401	86	22	case	case	NOUN
bracis-28401	86	23	;	;	PUNCT
bracis-28401	86	24	for	for	ADP
bracis-28401	86	25	those	those	DET
bracis-28401	86	26	cases	case	NOUN
bracis-28401	86	27	,	,	PUNCT
bracis-28401	86	28	we	we	PRON
bracis-28401	86	29	manually	manually	ADV
bracis-28401	86	30	evaluated	evaluate	VERB
bracis-28401	86	31	each	each	DET
bracis-28401	86	32	entry	entry	NOUN
bracis-28401	86	33	and	and	CCONJ
bracis-28401	86	34	defined	define	VERB
bracis-28401	86	35	their	their	PRON
bracis-28401	86	36	value	value	NOUN
bracis-28401	86	37	according	accord	VERB
bracis-28401	86	38	to	to	ADP
bracis-28401	86	39	the	the	DET
bracis-28401	86	40	closest	close	ADJ
bracis-28401	86	41	dominant	dominant	ADJ
bracis-28401	86	42	class	class	NOUN
bracis-28401	86	43	.	.	PUNCT
bracis-28401	87	1	to	to	PART
bracis-28401	87	2	produce	produce	VERB
bracis-28401	87	3	a	a	DET
bracis-28401	87	4	feasible	feasible	ADJ
bracis-28401	87	5	scenario	scenario	NOUN
bracis-28401	87	6	,	,	PUNCT
bracis-28401	87	7	instead	instead	ADV
bracis-28401	87	8	of	of	ADP
bracis-28401	87	9	78	78	NUM
bracis-28401	87	10	complexities	complexity	NOUN
bracis-28401	87	11	classes	class	NOUN
bracis-28401	87	12	,	,	PUNCT
bracis-28401	87	13	we	we	PRON
bracis-28401	87	14	reduced	reduce	VERB
bracis-28401	87	15	the	the	DET
bracis-28401	87	16	classification	classification	NOUN
bracis-28401	87	17	scope	scope	NOUN
bracis-28401	87	18	to	to	ADP
bracis-28401	87	19	eight	eight	NUM
bracis-28401	87	20	categories	category	NOUN
bracis-28401	87	21	:	:	PUNCT
bracis-28401	87	22	constant	constant	ADJ
bracis-28401	87	23	,	,	PUNCT
bracis-28401	87	24	logarithmic	logarithmic	ADJ
bracis-28401	87	25	(	(	PUNCT
bracis-28401	87	26	includes	include	VERB
bracis-28401	87	27	double	double	ADJ
bracis-28401	87	28	logarithmic	logarithmic	ADJ
bracis-28401	87	29	and	and	CCONJ
bracis-28401	87	30	polylogarithmic	polylogarithmic	ADJ
bracis-28401	87	31	)	)	PUNCT
bracis-28401	87	32	,	,	PUNCT
bracis-28401	87	33	sublinear	sublinear	NOUN
bracis-28401	87	34	(	(	PUNCT
bracis-28401	87	35	fractional	fractional	ADJ
bracis-28401	87	36	power	power	NOUN
bracis-28401	87	37	)	)	PUNCT
bracis-28401	87	38	,	,	PUNCT
bracis-28401	87	39	linear	linear	ADJ
bracis-28401	87	40	,	,	PUNCT
bracis-28401	87	41	linearithmic	linearithmic	ADJ
bracis-28401	87	42	,	,	PUNCT
bracis-28401	87	43	quadratic	quadratic	ADJ
bracis-28401	87	44	,	,	PUNCT
bracis-28401	87	45	polynomial	polynomial	ADJ
bracis-28401	87	46	,	,	PUNCT
bracis-28401	87	47	and	and	CCONJ
bracis-28401	87	48	exponential	exponential	NOUN
bracis-28401	87	49	(	(	PUNCT
bracis-28401	87	50	we	we	PRON
bracis-28401	87	51	also	also	ADV
bracis-28401	87	52	consider	consider	VERB
bracis-28401	87	53	factorial	factorial	ADJ
bracis-28401	87	54	as	as	ADP
bracis-28401	87	55	exponential	exponential	NOUN
bracis-28401	87	56	)	)	PUNCT
bracis-28401	87	57	.	.	PUNCT
bracis-28401	88	1	in	in	ADP
bracis-28401	88	2	addition	addition	NOUN
bracis-28401	88	3	,	,	PUNCT
bracis-28401	88	4	we	we	PRON
bracis-28401	88	5	split	split	VERB
bracis-28401	88	6	the	the	DET
bracis-28401	88	7	program	program	NOUN
bracis-28401	88	8	codes	code	NOUN
bracis-28401	88	9	into	into	ADP
bracis-28401	88	10	two	two	NUM
bracis-28401	88	11	major	major	ADJ
bracis-28401	88	12	categories	category	NOUN
bracis-28401	88	13	:	:	PUNCT
bracis-28401	88	14	the	the	DET
bracis-28401	88	15	program	program	NOUN
bracis-28401	88	16	codes	code	NOUN
bracis-28401	88	17	that	that	PRON
bracis-28401	88	18	are	be	AUX
bracis-28401	88	19	efficient	efficient	ADJ
bracis-28401	88	20	(	(	PUNCT
bracis-28401	88	21	constant	constant	ADJ
bracis-28401	88	22	,	,	PUNCT
bracis-28401	88	23	logarithmic	logarithmic	ADJ
bracis-28401	88	24	,	,	PUNCT
bracis-28401	88	25	sublinear	sublinear	NOUN
bracis-28401	88	26	,	,	PUNCT
bracis-28401	88	27	linear	linear	ADJ
bracis-28401	88	28	,	,	PUNCT
bracis-28401	88	29	and	and	CCONJ
bracis-28401	88	30	linearithmic	linearithmic	ADJ
bracis-28401	88	31	)	)	PUNCT
bracis-28401	88	32	and	and	CCONJ
bracis-28401	88	33	the	the	DET
bracis-28401	88	34	inefficient	inefficient	ADJ
bracis-28401	88	35	ones	one	NOUN
bracis-28401	88	36	(	(	PUNCT
bracis-28401	88	37	quadratic	quadratic	ADJ
bracis-28401	88	38	,	,	PUNCT
bracis-28401	88	39	polynomial	polynomial	ADJ
bracis-28401	88	40	,	,	PUNCT
bracis-28401	88	41	and	and	CCONJ
bracis-28401	88	42	exponential	exponential	NOUN
bracis-28401	88	43	)	)	PUNCT
bracis-28401	88	44	.	.	PUNCT
bracis-28401	89	1	we	we	PRON
bracis-28401	89	2	assume	assume	VERB
bracis-28401	89	3	as	as	ADP
bracis-28401	89	4	polynomial	polynomial	ADJ
bracis-28401	89	5	time	time	NOUN
bracis-28401	89	6	,	,	PUNCT
bracis-28401	89	7	the	the	DET
bracis-28401	89	8	asymptotic	asymptotic	ADJ
bracis-28401	89	9	functions	function	NOUN
bracis-28401	89	10	that	that	PRON
bracis-28401	89	11	are	be	AUX
bracis-28401	89	12	equal	equal	ADJ
bracis-28401	89	13	to	to	ADP
bracis-28401	89	14	or	or	CCONJ
bracis-28401	89	15	greater	great	ADJ
bracis-28401	89	16	than	than	ADP
bracis-28401	89	17	\(o(n^3)\	\(o(n^3)\	PROPN
bracis-28401	89	18	)	)	PUNCT
bracis-28401	89	19	.	.	PUNCT
bracis-28401	90	1	we	we	PRON
bracis-28401	90	2	understand	understand	VERB
bracis-28401	90	3	this	this	PRON
bracis-28401	90	4	is	be	AUX
bracis-28401	90	5	a	a	DET
bracis-28401	90	6	questionable	questionable	ADJ
bracis-28401	90	7	assumption	assumption	NOUN
bracis-28401	90	8	,	,	PUNCT
bracis-28401	90	9	as	as	SCONJ
bracis-28401	90	10	according	accord	VERB
bracis-28401	90	11	to	to	ADP
bracis-28401	90	12	[	[	X
bracis-28401	90	13	10	10	NUM
bracis-28401	90	14	]	]	PUNCT
bracis-28401	90	15	,	,	PUNCT
bracis-28401	90	16	polynomial	polynomial	ADJ
bracis-28401	90	17	time	time	NOUN
bracis-28401	90	18	functions	function	NOUN
bracis-28401	90	19	have	have	VERB
bracis-28401	90	20	the	the	DET
bracis-28401	90	21	form	form	NOUN
bracis-28401	90	22	of	of	ADP
bracis-28401	90	23	\(n^c\	\(n^c\	NOUN
bracis-28401	90	24	)	)	PUNCT
bracis-28401	90	25	for	for	ADP
bracis-28401	90	26	every	every	DET
bracis-28401	90	27	c	c	NOUN
bracis-28401	90	28	greater	great	ADJ
bracis-28401	90	29	than	than	ADP
bracis-28401	90	30	1	1	NUM
bracis-28401	90	31	.	.	PUNCT
bracis-28401	91	1	however	however	ADV
bracis-28401	91	2	,	,	PUNCT
bracis-28401	91	3	we	we	PRON
bracis-28401	91	4	argue	argue	VERB
bracis-28401	91	5	that	that	SCONJ
bracis-28401	91	6	algorithms	algorithm	NOUN
bracis-28401	91	7	that	that	PRON
bracis-28401	91	8	run	run	VERB
bracis-28401	91	9	in	in	ADP
bracis-28401	91	10	\(o(n^3)\	\(o(n^3)\	NOUN
bracis-28401	91	11	)	)	PUNCT
bracis-28401	91	12	are	be	AUX
bracis-28401	91	13	much	much	ADV
bracis-28401	91	14	more	more	ADV
bracis-28401	91	15	inefficient	inefficient	ADJ
bracis-28401	91	16	than	than	ADP
bracis-28401	91	17	the	the	DET
bracis-28401	91	18	ones	one	NOUN
bracis-28401	91	19	that	that	PRON
bracis-28401	91	20	run	run	VERB
bracis-28401	91	21	in	in	ADP
bracis-28401	91	22	\(o(n^2)\	\(o(n^2)\	ADJ
bracis-28401	91	23	)	)	PUNCT
bracis-28401	91	24	time	time	NOUN
bracis-28401	91	25	,	,	PUNCT
bracis-28401	91	26	and	and	CCONJ
bracis-28401	91	27	thus	thus	ADV
bracis-28401	91	28	,	,	PUNCT
bracis-28401	91	29	supposing	suppose	VERB
bracis-28401	91	30	\(o(n^3)\	\(o(n^3)\	NOUN
bracis-28401	91	31	)	)	PUNCT
bracis-28401	91	32	is	be	AUX
bracis-28401	91	33	distinct	distinct	ADJ
bracis-28401	91	34	from	from	ADP
bracis-28401	91	35	\(o(n^2)\	\(o(n^2)\	PROPN
bracis-28401	91	36	)	)	PUNCT
bracis-28401	91	37	is	be	AUX
bracis-28401	91	38	quite	quite	ADV
bracis-28401	91	39	reasonable	reasonable	ADJ
bracis-28401	91	40	.	.	PUNCT
bracis-28401	92	1	figure	figure	NOUN
bracis-28401	92	2	 	 	SPACE
bracis-28401	92	3	1	1	NUM
bracis-28401	92	4	depicts	depict	VERB
bracis-28401	92	5	the	the	DET
bracis-28401	92	6	resultant	resultant	NOUN
bracis-28401	92	7	distribution	distribution	NOUN
bracis-28401	92	8	of	of	ADP
bracis-28401	92	9	complexity	complexity	NOUN
bracis-28401	92	10	classes	class	NOUN
bracis-28401	92	11	in	in	ADP
bracis-28401	92	12	crawled	crawl	VERB
bracis-28401	92	13	and	and	CCONJ
bracis-28401	92	14	reference	reference	NOUN
bracis-28401	92	15	datasets	dataset	NOUN
bracis-28401	92	16	.	.	PUNCT
bracis-28401	93	1	fig	fig	NOUN
bracis-28401	93	2	.	.	PUNCT
bracis-28401	94	1	1	1	X
bracis-28401	94	2	.	.	X
bracis-28401	94	3	distribution	distribution	NOUN
bracis-28401	94	4	of	of	ADP
bracis-28401	94	5	complexity	complexity	NOUN
bracis-28401	94	6	classes	class	NOUN
bracis-28401	94	7	in	in	ADP
bracis-28401	94	8	the	the	DET
bracis-28401	94	9	available	available	ADJ
bracis-28401	94	10	datasets	dataset	NOUN
bracis-28401	94	11	full	full	ADJ
bracis-28401	94	12	size	size	NOUN
bracis-28401	94	13	image	image	NOUN
bracis-28401	94	14	as	as	SCONJ
bracis-28401	94	15	shown	show	VERB
bracis-28401	94	16	in	in	ADP
bracis-28401	94	17	fig	fig	NOUN
bracis-28401	94	18	.	.	PUNCT
bracis-28401	94	19	 	 	SPACE
bracis-28401	94	20	1b	1b	NUM
bracis-28401	94	21	,	,	PUNCT
bracis-28401	94	22	the	the	DET
bracis-28401	94	23	reference	reference	NOUN
bracis-28401	94	24	dataset	dataset	NOUN
bracis-28401	94	25	does	do	AUX
bracis-28401	94	26	not	not	PART
bracis-28401	94	27	contain	contain	VERB
bracis-28401	94	28	the	the	DET
bracis-28401	94	29	exponential	exponential	ADJ
bracis-28401	94	30	time	time	NOUN
bracis-28401	94	31	and	and	CCONJ
bracis-28401	94	32	the	the	DET
bracis-28401	94	33	polynomial	polynomial	ADJ
bracis-28401	94	34	time	time	NOUN
bracis-28401	94	35	codes	code	NOUN
bracis-28401	94	36	,	,	PUNCT
bracis-28401	94	37	which	which	PRON
bracis-28401	94	38	severally	severally	ADV
bracis-28401	94	39	reduces	reduce	VERB
bracis-28401	94	40	the	the	DET
bracis-28401	94	41	size	size	NOUN
bracis-28401	94	42	of	of	ADP
bracis-28401	94	43	the	the	DET
bracis-28401	94	44	inefficient	inefficient	ADJ
bracis-28401	94	45	class	class	NOUN
bracis-28401	94	46	.	.	PUNCT
bracis-28401	95	1	also	also	ADV
bracis-28401	95	2	,	,	PUNCT
bracis-28401	95	3	as	as	SCONJ
bracis-28401	95	4	one	one	PRON
bracis-28401	95	5	can	can	AUX
bracis-28401	95	6	notice	notice	VERB
bracis-28401	95	7	,	,	PUNCT
bracis-28401	95	8	both	both	DET
bracis-28401	95	9	datasets	dataset	NOUN
bracis-28401	95	10	are	be	AUX
bracis-28401	95	11	imbalanced	imbalance	VERB
bracis-28401	95	12	:	:	PUNCT
bracis-28401	95	13	in	in	ADP
bracis-28401	95	14	the	the	DET
bracis-28401	95	15	crawled	crawl	VERB
bracis-28401	95	16	dataset	dataset	NOUN
bracis-28401	95	17	(	(	PUNCT
bracis-28401	95	18	fig	fig	NOUN
bracis-28401	95	19	.	.	PUNCT
bracis-28401	95	20	 	 	SPACE
bracis-28401	95	21	1a	1a	NOUN
bracis-28401	95	22	)	)	PUNCT
bracis-28401	95	23	the	the	DET
bracis-28401	95	24	smaller	small	ADJ
bracis-28401	95	25	class	class	NOUN
bracis-28401	95	26	(	(	PUNCT
bracis-28401	95	27	sublinear	sublinear	NOUN
bracis-28401	95	28	)	)	PUNCT
bracis-28401	95	29	contains	contain	VERB
bracis-28401	95	30	five	five	NUM
bracis-28401	95	31	entries	entry	NOUN
bracis-28401	95	32	while	while	SCONJ
bracis-28401	95	33	the	the	DET
bracis-28401	95	34	larger	large	ADJ
bracis-28401	95	35	class	class	NOUN
bracis-28401	95	36	(	(	PUNCT
bracis-28401	95	37	linear	linear	NOUN
bracis-28401	95	38	)	)	PUNCT
bracis-28401	95	39	contains	contain	VERB
bracis-28401	95	40	125	125	NUM
bracis-28401	95	41	entries	entry	NOUN
bracis-28401	95	42	;	;	PUNCT
bracis-28401	95	43	in	in	ADP
bracis-28401	95	44	the	the	DET
bracis-28401	95	45	reference	reference	NOUN
bracis-28401	95	46	dataset	dataset	VERB
bracis-28401	95	47	the	the	DET
bracis-28401	95	48	smaller	small	ADJ
bracis-28401	95	49	class	class	NOUN
bracis-28401	95	50	(	(	PUNCT
bracis-28401	95	51	logarithmic	logarithmic	NOUN
bracis-28401	95	52	)	)	PUNCT
bracis-28401	95	53	contains	contain	VERB
bracis-28401	95	54	55	55	NUM
bracis-28401	95	55	entries	entry	NOUN
bracis-28401	95	56	while	while	SCONJ
bracis-28401	95	57	the	the	DET
bracis-28401	95	58	larger	large	ADJ
bracis-28401	95	59	class	class	NOUN
bracis-28401	95	60	(	(	PUNCT
bracis-28401	95	61	also	also	ADV
bracis-28401	95	62	the	the	DET
bracis-28401	95	63	linear	linear	NOUN
bracis-28401	95	64	)	)	PUNCT
bracis-28401	95	65	contains	contain	VERB
bracis-28401	95	66	383	383	NUM
bracis-28401	95	67	entries	entry	NOUN
bracis-28401	95	68	.	.	PUNCT
bracis-28401	96	1	such	such	ADJ
bracis-28401	96	2	unbalancing	unbalancing	NOUN
bracis-28401	96	3	also	also	ADV
bracis-28401	96	4	impacts	impact	VERB
bracis-28401	96	5	the	the	DET
bracis-28401	96	6	classes	class	NOUN
bracis-28401	96	7	distribution	distribution	NOUN
bracis-28401	96	8	in	in	ADP
bracis-28401	96	9	the	the	DET
bracis-28401	96	10	merged	merge	VERB
bracis-28401	96	11	dataset	dataset	NOUN
bracis-28401	96	12	(	(	PUNCT
bracis-28401	96	13	fig	fig	NOUN
bracis-28401	96	14	.	.	PUNCT
bracis-28401	96	15	 	 	SPACE
bracis-28401	96	16	1c	1c	NOUN
bracis-28401	96	17	)	)	PUNCT
bracis-28401	96	18	,	,	PUNCT
bracis-28401	96	19	making	make	VERB
bracis-28401	96	20	the	the	DET
bracis-28401	96	21	linear	linear	ADJ
bracis-28401	96	22	and	and	CCONJ
bracis-28401	96	23	quadratic	quadratic	ADJ
bracis-28401	96	24	classes	class	NOUN
bracis-28401	96	25	more	more	ADV
bracis-28401	96	26	representative	representative	ADJ
bracis-28401	96	27	.	.	PUNCT
bracis-28401	97	1	regarding	regard	VERB
bracis-28401	97	2	efficiency	efficiency	NOUN
bracis-28401	97	3	,	,	PUNCT
bracis-28401	97	4	the	the	DET
bracis-28401	97	5	distribution	distribution	NOUN
bracis-28401	97	6	in	in	ADP
bracis-28401	97	7	each	each	DET
bracis-28401	97	8	dataset	dataset	NOUN
bracis-28401	97	9	is	be	AUX
bracis-28401	97	10	as	as	SCONJ
bracis-28401	97	11	follows	follow	VERB
bracis-28401	97	12	:	:	PUNCT
bracis-28401	97	13	63.70	63.70	NUM
bracis-28401	97	14	%	%	NOUN
bracis-28401	97	15	of	of	ADP
bracis-28401	97	16	codes	code	NOUN
bracis-28401	97	17	are	be	AUX
bracis-28401	97	18	from	from	ADP
bracis-28401	97	19	efficient	efficient	ADJ
bracis-28401	97	20	classes	class	NOUN
bracis-28401	97	21	in	in	ADP
bracis-28401	97	22	the	the	DET
bracis-28401	97	23	crawled	crawl	VERB
bracis-28401	97	24	dataset	dataset	NOUN
bracis-28401	97	25	,	,	PUNCT
bracis-28401	97	26	78.51	78.51	NUM
bracis-28401	97	27	%	%	NOUN
bracis-28401	97	28	in	in	ADP
bracis-28401	97	29	the	the	DET
bracis-28401	97	30	reference	reference	NOUN
bracis-28401	97	31	dataset	dataset	NOUN
bracis-28401	97	32	,	,	PUNCT
bracis-28401	97	33	and	and	CCONJ
bracis-28401	97	34	74.18	74.18	NUM
bracis-28401	97	35	%	%	NOUN
bracis-28401	97	36	in	in	ADP
bracis-28401	97	37	the	the	DET
bracis-28401	97	38	merged	merge	VERB
bracis-28401	97	39	dataset	dataset	NOUN
bracis-28401	97	40	.	.	PUNCT
bracis-28401	98	1	considering	consider	VERB
bracis-28401	98	2	that	that	SCONJ
bracis-28401	98	3	an	an	DET
bracis-28401	98	4	imbalanced	imbalanced	ADJ
bracis-28401	98	5	dataset	dataset	NOUN
bracis-28401	98	6	can	can	AUX
bracis-28401	98	7	impact	impact	VERB
bracis-28401	98	8	the	the	DET
bracis-28401	98	9	abstraction	abstraction	NOUN
bracis-28401	98	10	capability	capability	NOUN
bracis-28401	98	11	of	of	ADP
bracis-28401	98	12	machine	machine	NOUN
bracis-28401	98	13	learning	learning	NOUN
bracis-28401	98	14	models	model	NOUN
bracis-28401	98	15	[	[	X
bracis-28401	98	16	14	14	NUM
bracis-28401	98	17	]	]	PUNCT
bracis-28401	98	18	and	and	CCONJ
bracis-28401	98	19	that	that	SCONJ
bracis-28401	98	20	our	our	PRON
bracis-28401	98	21	dataset	dataset	NOUN
bracis-28401	98	22	can	can	AUX
bracis-28401	98	23	be	be	AUX
bracis-28401	98	24	considered	consider	VERB
bracis-28401	98	25	small	small	ADJ
bracis-28401	98	26	compared	compare	VERB
bracis-28401	98	27	to	to	ADP
bracis-28401	98	28	what	what	PRON
bracis-28401	98	29	is	be	AUX
bracis-28401	98	30	considered	consider	VERB
bracis-28401	98	31	in	in	ADP
bracis-28401	98	32	current	current	ADJ
bracis-28401	98	33	state	state	NOUN
bracis-28401	98	34	-	-	PUNCT
bracis-28401	98	35	of	of	ADP
bracis-28401	98	36	-	-	PUNCT
bracis-28401	98	37	the	the	DET
bracis-28401	98	38	-	-	PUNCT
bracis-28401	98	39	art	art	NOUN
bracis-28401	98	40	,	,	PUNCT
bracis-28401	98	41	we	we	PRON
bracis-28401	98	42	rely	rely	VERB
bracis-28401	98	43	on	on	ADP
bracis-28401	98	44	the	the	DET
bracis-28401	98	45	smote	smote	ADJ
bracis-28401	98	46	tool	tool	NOUN
bracis-28401	98	47	to	to	PART
bracis-28401	98	48	balance	balance	VERB
bracis-28401	98	49	the	the	DET
bracis-28401	98	50	data	datum	NOUN
bracis-28401	98	51	on	on	ADP
bracis-28401	98	52	each	each	DET
bracis-28401	98	53	dataset	dataset	NOUN
bracis-28401	98	54	.	.	PUNCT
bracis-28401	99	1	the	the	DET
bracis-28401	99	2	smote	smote	ADJ
bracis-28401	99	3	(	(	PUNCT
bracis-28401	99	4	synthetic	synthetic	ADJ
bracis-28401	99	5	minority	minority	NOUN
bracis-28401	99	6	oversampling	oversample	VERB
bracis-28401	99	7	technique	technique	NOUN
bracis-28401	99	8	)	)	PUNCT
bracis-28401	100	1	[	[	X
bracis-28401	100	2	4	4	X
bracis-28401	100	3	]	]	PUNCT
bracis-28401	100	4	is	be	AUX
bracis-28401	100	5	a	a	DET
bracis-28401	100	6	well	well	ADV
bracis-28401	100	7	-	-	PUNCT
bracis-28401	100	8	known	know	VERB
bracis-28401	100	9	algorithm	algorithm	NOUN
bracis-28401	100	10	for	for	ADP
bracis-28401	100	11	solving	solve	VERB
bracis-28401	100	12	imbalanced	imbalanced	ADJ
bracis-28401	100	13	classification	classification	NOUN
bracis-28401	100	14	problems	problem	NOUN
bracis-28401	100	15	.	.	PUNCT
bracis-28401	101	1	the	the	DET
bracis-28401	101	2	general	general	ADJ
bracis-28401	101	3	idea	idea	NOUN
bracis-28401	101	4	of	of	ADP
bracis-28401	101	5	this	this	DET
bracis-28401	101	6	method	method	NOUN
bracis-28401	101	7	is	be	AUX
bracis-28401	101	8	to	to	PART
bracis-28401	101	9	artificially	artificially	ADV
bracis-28401	101	10	generate	generate	VERB
bracis-28401	101	11	new	new	ADJ
bracis-28401	101	12	samples	sample	NOUN
bracis-28401	101	13	of	of	ADP
bracis-28401	101	14	the	the	DET
bracis-28401	101	15	minority	minority	NOUN
bracis-28401	101	16	class	class	NOUN
bracis-28401	101	17	using	use	VERB
bracis-28401	101	18	the	the	DET
bracis-28401	101	19	nearest	near	ADJ
bracis-28401	101	20	neighbors	neighbor	NOUN
bracis-28401	101	21	of	of	ADP
bracis-28401	101	22	these	these	DET
bracis-28401	101	23	cases	case	NOUN
bracis-28401	101	24	.	.	PUNCT
bracis-28401	102	1	such	such	ADJ
bracis-28401	102	2	synthetic	synthetic	ADJ
bracis-28401	102	3	data	datum	NOUN
bracis-28401	102	4	would	would	AUX
bracis-28401	102	5	be	be	AUX
bracis-28401	102	6	generated	generate	VERB
bracis-28401	102	7	between	between	ADP
bracis-28401	102	8	the	the	DET
bracis-28401	102	9	random	random	ADJ
bracis-28401	102	10	data	datum	NOUN
bracis-28401	102	11	and	and	CCONJ
bracis-28401	102	12	the	the	DET
bracis-28401	102	13	randomly	randomly	ADV
bracis-28401	102	14	selected	select	VERB
bracis-28401	102	15	k	k	ADV
bracis-28401	102	16	-	-	PUNCT
bracis-28401	102	17	nearest	near	ADJ
bracis-28401	102	18	neighbor	neighbor	NOUN
bracis-28401	102	19	;	;	PUNCT
bracis-28401	102	20	the	the	DET
bracis-28401	102	21	procedure	procedure	NOUN
bracis-28401	102	22	is	be	AUX
bracis-28401	102	23	then	then	ADV
bracis-28401	102	24	repeated	repeat	VERB
bracis-28401	102	25	until	until	SCONJ
bracis-28401	102	26	the	the	DET
bracis-28401	102	27	minority	minority	NOUN
bracis-28401	102	28	class	class	NOUN
bracis-28401	102	29	has	have	VERB
bracis-28401	102	30	a	a	DET
bracis-28401	102	31	size	size	NOUN
bracis-28401	102	32	equal	equal	ADJ
bracis-28401	102	33	to	to	ADP
bracis-28401	102	34	or	or	CCONJ
bracis-28401	102	35	close	close	ADV
bracis-28401	102	36	to	to	ADP
bracis-28401	102	37	the	the	DET
bracis-28401	102	38	majority	majority	NOUN
bracis-28401	102	39	.	.	PUNCT
bracis-28401	103	1	due	due	ADP
bracis-28401	103	2	to	to	ADP
bracis-28401	103	3	applying	apply	VERB
bracis-28401	103	4	smote	smote	NOUN
bracis-28401	103	5	,	,	PUNCT
bracis-28401	103	6	all	all	DET
bracis-28401	103	7	the	the	DET
bracis-28401	103	8	resultant	resultant	NOUN
bracis-28401	103	9	complexity	complexity	NOUN
bracis-28401	103	10	classes	class	NOUN
bracis-28401	103	11	hold	hold	VERB
bracis-28401	103	12	a	a	DET
bracis-28401	103	13	similar	similar	ADJ
bracis-28401	103	14	number	number	NOUN
bracis-28401	103	15	of	of	ADP
bracis-28401	103	16	occurrences	occurrence	NOUN
bracis-28401	103	17	.	.	PUNCT
bracis-28401	104	1	3.2	3.2	NUM
bracis-28401	104	2	features	feature	VERB
bracis-28401	104	3	extraction	extraction	NOUN
bracis-28401	104	4	and	and	CCONJ
bracis-28401	104	5	 	 	SPACE
bracis-28401	104	6	selection	selection	NOUN
bracis-28401	104	7	we	we	PRON
bracis-28401	104	8	wrote	write	VERB
bracis-28401	104	9	the	the	DET
bracis-28401	104	10	code	code	NOUN
bracis-28401	104	11	features	feature	VERB
bracis-28401	104	12	extraction	extraction	NOUN
bracis-28401	104	13	program	program	NOUN
bracis-28401	104	14	in	in	ADP
bracis-28401	104	15	python	python	NOUN
bracis-28401	104	16	(	(	PUNCT
bracis-28401	104	17	“	"	PUNCT
bracis-28401	104	18	crawler.py	crawler.py	X
bracis-28401	104	19	file	file	NOUN
bracis-28401	104	20	on	on	ADP
bracis-28401	104	21	the	the	DET
bracis-28401	104	22	repository	repository	NOUN
bracis-28401	104	23	”	"	PUNCT
bracis-28401	104	24	)	)	PUNCT
bracis-28401	104	25	and	and	CCONJ
bracis-28401	104	26	relied	rely	VERB
bracis-28401	104	27	on	on	ADP
bracis-28401	104	28	the	the	DET
bracis-28401	104	29	javalang	javalang	PROPN
bracis-28401	104	30	library	library	PROPN
bracis-28401	104	31	to	to	PART
bracis-28401	104	32	extract	extract	VERB
bracis-28401	104	33	the	the	DET
bracis-28401	104	34	features	feature	NOUN
bracis-28401	104	35	described	describe	VERB
bracis-28401	104	36	in	in	ADP
bracis-28401	104	37	table	table	NOUN
bracis-28401	104	38	 	 	SPACE
bracis-28401	104	39	1	1	NUM
bracis-28401	104	40	for	for	ADP
bracis-28401	104	41	each	each	DET
bracis-28401	104	42	java	java	PROPN
bracis-28401	104	43	code	code	PROPN
bracis-28401	104	44	in	in	ADP
bracis-28401	104	45	the	the	DET
bracis-28401	104	46	datasets	dataset	NOUN
bracis-28401	104	47	.	.	PUNCT
bracis-28401	105	1	the	the	DET
bracis-28401	105	2	second	second	ADJ
bracis-28401	105	3	column	column	NOUN
bracis-28401	105	4	in	in	ADP
bracis-28401	105	5	the	the	DET
bracis-28401	105	6	table	table	NOUN
bracis-28401	105	7	describes	describe	VERB
bracis-28401	105	8	if	if	SCONJ
bracis-28401	105	9	the	the	DET
bracis-28401	105	10	former	former	ADJ
bracis-28401	105	11	work	work	NOUN
bracis-28401	105	12	of	of	ADP
bracis-28401	105	13	sikka	sikka	PROPN
bracis-28401	105	14	et	et	PROPN
bracis-28401	105	15	al	al	PROPN
bracis-28401	105	16	.	.	PUNCT
bracis-28401	106	1	[	[	X
bracis-28401	106	2	18	18	NUM
bracis-28401	106	3	]	]	PUNCT
bracis-28401	106	4	relies	rely	VERB
bracis-28401	106	5	on	on	ADP
bracis-28401	106	6	the	the	DET
bracis-28401	106	7	feature	feature	NOUN
bracis-28401	106	8	for	for	ADP
bracis-28401	106	9	their	their	PRON
bracis-28401	106	10	prediction	prediction	NOUN
bracis-28401	106	11	.	.	PUNCT
bracis-28401	107	1	for	for	ADP
bracis-28401	107	2	the	the	DET
bracis-28401	107	3	cases	case	NOUN
bracis-28401	107	4	where	where	SCONJ
bracis-28401	107	5	column	column	NOUN
bracis-28401	107	6	values	value	NOUN
bracis-28401	107	7	are	be	AUX
bracis-28401	107	8	with	with	ADP
bracis-28401	107	9	“	"	PUNCT
bracis-28401	107	10	no	no	INTJ
bracis-28401	107	11	*	*	PUNCT
bracis-28401	107	12	”	"	PUNCT
bracis-28401	107	13	,	,	PUNCT
bracis-28401	107	14	the	the	DET
bracis-28401	107	15	feature	feature	NOUN
bracis-28401	107	16	was	be	AUX
bracis-28401	107	17	only	only	ADV
bracis-28401	107	18	used	use	VERB
bracis-28401	107	19	in	in	ADP
bracis-28401	107	20	[	[	X
bracis-28401	107	21	18	18	NUM
bracis-28401	107	22	]	]	PUNCT
bracis-28401	107	23	for	for	ADP
bracis-28401	107	24	the	the	DET
bracis-28401	107	25	manual	manual	ADJ
bracis-28401	107	26	classification	classification	NOUN
bracis-28401	107	27	of	of	ADP
bracis-28401	107	28	algorithms	algorithm	NOUN
bracis-28401	107	29	and	and	CCONJ
bracis-28401	107	30	not	not	PART
bracis-28401	107	31	for	for	ADP
bracis-28401	107	32	the	the	DET
bracis-28401	107	33	machine	machine	NOUN
bracis-28401	107	34	learning	learning	NOUN
bracis-28401	107	35	models	model	NOUN
bracis-28401	107	36	.	.	PUNCT
bracis-28401	108	1	for	for	ADP
bracis-28401	108	2	the	the	DET
bracis-28401	108	3	case	case	NOUN
bracis-28401	108	4	of	of	ADP
bracis-28401	108	5	recursive	recursive	ADJ
bracis-28401	108	6	calls	call	NOUN
bracis-28401	108	7	,	,	PUNCT
bracis-28401	108	8	we	we	PRON
bracis-28401	108	9	measured	measure	VERB
bracis-28401	108	10	the	the	DET
bracis-28401	108	11	number	number	NOUN
bracis-28401	108	12	of	of	ADP
bracis-28401	108	13	recursive	recursive	ADJ
bracis-28401	108	14	calls	call	NOUN
bracis-28401	108	15	in	in	ADP
bracis-28401	108	16	the	the	DET
bracis-28401	108	17	code	code	NOUN
bracis-28401	108	18	instead	instead	ADV
bracis-28401	108	19	of	of	ADP
bracis-28401	108	20	if	if	SCONJ
bracis-28401	108	21	there	there	PRON
bracis-28401	108	22	is	be	VERB
bracis-28401	108	23	a	a	DET
bracis-28401	108	24	recursive	recursive	ADJ
bracis-28401	108	25	call	call	NOUN
bracis-28401	108	26	in	in	ADP
bracis-28401	108	27	the	the	DET
bracis-28401	108	28	code	code	NOUN
bracis-28401	108	29	.	.	PUNCT
bracis-28401	109	1	table	table	NOUN
bracis-28401	109	2	1	1	NUM
bracis-28401	109	3	.	.	PUNCT
bracis-28401	110	1	features	feature	NOUN
bracis-28401	110	2	extracted	extract	VERB
bracis-28401	110	3	from	from	ADP
bracis-28401	110	4	codes	code	NOUN
bracis-28401	110	5	and	and	CCONJ
bracis-28401	110	6	respective	respective	ADJ
bracis-28401	110	7	descriptionsfull	descriptionsfull	NOUN
bracis-28401	110	8	size	size	NOUN
bracis-28401	110	9	table	table	NOUN
bracis-28401	110	10	as	as	SCONJ
bracis-28401	110	11	we	we	PRON
bracis-28401	110	12	established	establish	VERB
bracis-28401	110	13	the	the	DET
bracis-28401	110	14	set	set	NOUN
bracis-28401	110	15	of	of	ADP
bracis-28401	110	16	complexity	complexity	NOUN
bracis-28401	110	17	classes	class	NOUN
bracis-28401	110	18	and	and	CCONJ
bracis-28401	110	19	balanced	balance	VERB
bracis-28401	110	20	the	the	DET
bracis-28401	110	21	datasets	dataset	NOUN
bracis-28401	110	22	,	,	PUNCT
bracis-28401	110	23	the	the	DET
bracis-28401	110	24	next	next	ADJ
bracis-28401	110	25	step	step	NOUN
bracis-28401	110	26	is	be	AUX
bracis-28401	110	27	to	to	PART
bracis-28401	110	28	perform	perform	VERB
bracis-28401	110	29	a	a	DET
bracis-28401	110	30	feature	feature	NOUN
bracis-28401	110	31	selection	selection	NOUN
bracis-28401	110	32	to	to	PART
bracis-28401	110	33	determine	determine	VERB
bracis-28401	110	34	the	the	DET
bracis-28401	110	35	most	most	ADV
bracis-28401	110	36	relevant	relevant	ADJ
bracis-28401	110	37	characteristics	characteristic	NOUN
bracis-28401	110	38	to	to	PART
bracis-28401	110	39	distinguish	distinguish	VERB
bracis-28401	110	40	the	the	DET
bracis-28401	110	41	codes	code	NOUN
bracis-28401	110	42	according	accord	VERB
bracis-28401	110	43	to	to	ADP
bracis-28401	110	44	their	their	PRON
bracis-28401	110	45	complexity	complexity	NOUN
bracis-28401	110	46	classes	class	NOUN
bracis-28401	110	47	.	.	PUNCT
bracis-28401	111	1	multiple	multiple	ADJ
bracis-28401	111	2	approaches	approach	NOUN
bracis-28401	111	3	exist	exist	VERB
bracis-28401	111	4	for	for	ADP
bracis-28401	111	5	determining	determine	VERB
bracis-28401	111	6	the	the	DET
bracis-28401	111	7	most	most	ADV
bracis-28401	111	8	relevant	relevant	ADJ
bracis-28401	111	9	features	feature	NOUN
bracis-28401	111	10	of	of	ADP
bracis-28401	111	11	random	random	ADJ
bracis-28401	111	12	forest	forest	NOUN
bracis-28401	111	13	models	model	NOUN
bracis-28401	111	14	.	.	PUNCT
bracis-28401	112	1	according	accord	VERB
bracis-28401	112	2	to	to	ADP
bracis-28401	112	3	speiser	speiser	NOUN
bracis-28401	112	4	et	et	PROPN
bracis-28401	112	5	al	al	PROPN
bracis-28401	112	6	.	.	PUNCT
bracis-28401	113	1	[	[	X
bracis-28401	113	2	19	19	NUM
bracis-28401	113	3	]	]	PUNCT
bracis-28401	113	4	for	for	ADP
bracis-28401	113	5	datasets	dataset	NOUN
bracis-28401	113	6	with	with	ADP
bracis-28401	113	7	many	many	ADJ
bracis-28401	113	8	predictors	predictor	NOUN
bracis-28401	113	9	,	,	PUNCT
bracis-28401	113	10	the	the	DET
bracis-28401	113	11	methods	method	NOUN
bracis-28401	113	12	implemented	implement	VERB
bracis-28401	113	13	in	in	ADP
bracis-28401	113	14	the	the	DET
bracis-28401	113	15	r	r	NOUN
bracis-28401	113	16	packages	package	NOUN
bracis-28401	113	17	varselrf	varselrf	NOUN
bracis-28401	113	18	and	and	CCONJ
bracis-28401	113	19	boruta	boruta	VERB
bracis-28401	114	1	[	[	X
bracis-28401	114	2	11	11	NUM
bracis-28401	114	3	]	]	PUNCT
bracis-28401	114	4	are	be	AUX
bracis-28401	114	5	preferable	preferable	ADJ
bracis-28401	114	6	due	due	ADJ
bracis-28401	114	7	to	to	ADP
bracis-28401	114	8	computational	computational	ADJ
bracis-28401	114	9	efficiency	efficiency	NOUN
bracis-28401	114	10	.	.	PUNCT
bracis-28401	115	1	thus	thus	ADV
bracis-28401	115	2	,	,	PUNCT
bracis-28401	115	3	in	in	ADP
bracis-28401	115	4	this	this	DET
bracis-28401	115	5	work	work	NOUN
bracis-28401	115	6	,	,	PUNCT
bracis-28401	115	7	we	we	PRON
bracis-28401	115	8	rely	rely	VERB
bracis-28401	115	9	on	on	ADP
bracis-28401	115	10	the	the	DET
bracis-28401	115	11	boruta	boruta	NOUN
bracis-28401	115	12	package	package	NOUN
bracis-28401	115	13	to	to	PART
bracis-28401	115	14	define	define	VERB
bracis-28401	115	15	which	which	DET
bracis-28401	115	16	code	code	NOUN
bracis-28401	115	17	attributes	attribute	NOUN
bracis-28401	115	18	are	be	AUX
bracis-28401	115	19	more	more	ADV
bracis-28401	115	20	relevant	relevant	ADJ
bracis-28401	115	21	to	to	PART
bracis-28401	115	22	predict	predict	VERB
bracis-28401	115	23	the	the	DET
bracis-28401	115	24	complexity	complexity	NOUN
bracis-28401	115	25	classes	class	NOUN
bracis-28401	115	26	and	and	CCONJ
bracis-28401	115	27	the	the	DET
bracis-28401	115	28	efficiency	efficiency	NOUN
bracis-28401	115	29	of	of	ADP
bracis-28401	115	30	a	a	DET
bracis-28401	115	31	given	give	VERB
bracis-28401	115	32	code	code	NOUN
bracis-28401	115	33	(	(	PUNCT
bracis-28401	115	34	please	please	INTJ
bracis-28401	115	35	read	read	VERB
bracis-28401	115	36	the	the	DET
bracis-28401	115	37	“	"	PUNCT
bracis-28401	115	38	classificators.r	classificators.r	PROPN
bracis-28401	115	39	”	"	PUNCT
bracis-28401	115	40	file	file	NOUN
bracis-28401	115	41	in	in	ADP
bracis-28401	115	42	the	the	DET
bracis-28401	115	43	repository	repository	NOUN
bracis-28401	115	44	)	)	PUNCT
bracis-28401	115	45	.	.	PUNCT
bracis-28401	116	1	boruta	boruta	PROPN
bracis-28401	116	2	is	be	AUX
bracis-28401	116	3	a	a	DET
bracis-28401	116	4	feature	feature	NOUN
bracis-28401	116	5	selection	selection	NOUN
bracis-28401	116	6	algorithm	algorithm	NOUN
bracis-28401	116	7	that	that	PRON
bracis-28401	116	8	relies	rely	VERB
bracis-28401	116	9	on	on	ADP
bracis-28401	116	10	random	random	ADJ
bracis-28401	116	11	forest	forest	NOUN
bracis-28401	116	12	to	to	PART
bracis-28401	116	13	output	output	VERB
bracis-28401	116	14	a	a	DET
bracis-28401	116	15	variable	variable	ADJ
bracis-28401	116	16	importance	importance	NOUN
bracis-28401	116	17	measure	measure	NOUN
bracis-28401	116	18	(	(	PUNCT
bracis-28401	116	19	vim	vim	NOUN
bracis-28401	116	20	)	)	PUNCT
bracis-28401	116	21	;	;	PUNCT
bracis-28401	116	22	the	the	DET
bracis-28401	116	23	method	method	NOUN
bracis-28401	116	24	’s	’s	PART
bracis-28401	116	25	rationality	rationality	NOUN
bracis-28401	116	26	consists	consist	VERB
bracis-28401	116	27	of	of	ADP
bracis-28401	116	28	progressively	progressively	ADV
bracis-28401	116	29	eliminating	eliminate	VERB
bracis-28401	116	30	irrelevant	irrelevant	ADJ
bracis-28401	116	31	features	feature	NOUN
bracis-28401	116	32	by	by	ADP
bracis-28401	116	33	comparing	compare	VERB
bracis-28401	116	34	original	original	ADJ
bracis-28401	116	35	attributes	attribute	NOUN
bracis-28401	116	36	’	'	PUNCT
bracis-28401	116	37	importance	importance	NOUN
bracis-28401	116	38	with	with	ADP
bracis-28401	116	39	importance	importance	NOUN
bracis-28401	116	40	achievable	achievable	ADJ
bracis-28401	116	41	at	at	ADP
bracis-28401	116	42	random	random	ADJ
bracis-28401	116	43	until	until	SCONJ
bracis-28401	116	44	the	the	DET
bracis-28401	116	45	test	test	NOUN
bracis-28401	116	46	is	be	AUX
bracis-28401	116	47	stable	stable	ADJ
bracis-28401	116	48	.	.	PUNCT
bracis-28401	117	1	table	table	NOUN
bracis-28401	117	2	 	 	SPACE
bracis-28401	117	3	2	2	NUM
bracis-28401	117	4	depicts	depict	VERB
bracis-28401	117	5	the	the	DET
bracis-28401	117	6	resultant	resultant	NOUN
bracis-28401	117	7	feature	feature	NOUN
bracis-28401	117	8	functions	function	NOUN
bracis-28401	117	9	from	from	ADP
bracis-28401	117	10	boruta	boruta	NOUN
bracis-28401	117	11	process	process	NOUN
bracis-28401	117	12	.	.	PUNCT
bracis-28401	118	1	table	table	NOUN
bracis-28401	118	2	2	2	NUM
bracis-28401	118	3	.	.	PUNCT
bracis-28401	119	1	features	feature	NOUN
bracis-28401	119	2	resultant	resultant	VERB
bracis-28401	119	3	from	from	ADP
bracis-28401	119	4	boruta	boruta	NOUN
bracis-28401	119	5	feature	feature	NOUN
bracis-28401	119	6	selection	selection	NOUN
bracis-28401	119	7	process	process	NOUN
bracis-28401	119	8	in	in	ADP
bracis-28401	119	9	each	each	DET
bracis-28401	119	10	dataset	dataset	NOUN
bracis-28401	119	11	according	accord	VERB
bracis-28401	119	12	to	to	ADP
bracis-28401	119	13	the	the	DET
bracis-28401	119	14	dependent	dependent	ADJ
bracis-28401	119	15	variablefull	variablefull	NOUN
bracis-28401	119	16	size	size	NOUN
bracis-28401	119	17	table	table	NOUN
bracis-28401	119	18	an	an	DET
bracis-28401	119	19	analysis	analysis	NOUN
bracis-28401	119	20	of	of	ADP
bracis-28401	119	21	the	the	DET
bracis-28401	119	22	feature	feature	NOUN
bracis-28401	119	23	selection	selection	NOUN
bracis-28401	119	24	results	result	NOUN
bracis-28401	119	25	depicted	depict	VERB
bracis-28401	119	26	in	in	ADP
bracis-28401	119	27	table	table	NOUN
bracis-28401	119	28	 	 	SPACE
bracis-28401	119	29	2	2	NUM
bracis-28401	119	30	permits	permit	VERB
bracis-28401	119	31	some	some	DET
bracis-28401	119	32	relevant	relevant	ADJ
bracis-28401	119	33	considerations	consideration	NOUN
bracis-28401	119	34	:	:	PUNCT
bracis-28401	119	35	(	(	PUNCT
bracis-28401	119	36	i	i	NOUN
bracis-28401	119	37	)	)	PUNCT
bracis-28401	119	38	the	the	DET
bracis-28401	119	39	efficiency	efficiency	NOUN
bracis-28401	119	40	estimation	estimation	NOUN
bracis-28401	119	41	requires	require	VERB
bracis-28401	119	42	fewer	few	ADJ
bracis-28401	119	43	features	feature	NOUN
bracis-28401	119	44	than	than	ADP
bracis-28401	119	45	the	the	DET
bracis-28401	119	46	complexity	complexity	NOUN
bracis-28401	119	47	class	class	NOUN
bracis-28401	119	48	estimation	estimation	NOUN
bracis-28401	119	49	;	;	PUNCT
bracis-28401	119	50	(	(	PUNCT
bracis-28401	119	51	ii	ii	NOUN
bracis-28401	119	52	)	)	PUNCT
bracis-28401	119	53	the	the	DET
bracis-28401	119	54	crawled	crawl	VERB
bracis-28401	119	55	dataset	dataset	NOUN
bracis-28401	119	56	also	also	ADV
bracis-28401	119	57	uses	use	VERB
bracis-28401	119	58	fewer	few	ADJ
bracis-28401	119	59	features	feature	NOUN
bracis-28401	119	60	for	for	ADP
bracis-28401	119	61	both	both	DET
bracis-28401	119	62	predicting	predict	VERB
bracis-28401	119	63	efficiency	efficiency	NOUN
bracis-28401	119	64	and	and	CCONJ
bracis-28401	119	65	complexity	complexity	NOUN
bracis-28401	119	66	classes	class	NOUN
bracis-28401	119	67	and	and	CCONJ
bracis-28401	119	68	;	;	PUNCT
bracis-28401	119	69	(	(	PUNCT
bracis-28401	119	70	iii	iii	X
bracis-28401	119	71	)	)	PUNCT
bracis-28401	119	72	the	the	DET
bracis-28401	119	73	number	number	NOUN
bracis-28401	119	74	of	of	ADP
bracis-28401	119	75	switches	switch	NOUN
bracis-28401	119	76	(	(	PUNCT
bracis-28401	119	77	attribute	attribute	NOUN
bracis-28401	119	78	number	number	NOUN
bracis-28401	119	79	3	3	NUM
bracis-28401	119	80	)	)	PUNCT
bracis-28401	119	81	in	in	ADP
bracis-28401	119	82	codes	code	NOUN
bracis-28401	119	83	is	be	AUX
bracis-28401	119	84	irrelevant	irrelevant	ADJ
bracis-28401	119	85	for	for	ADP
bracis-28401	119	86	the	the	DET
bracis-28401	119	87	predictions	prediction	NOUN
bracis-28401	119	88	.	.	PUNCT
bracis-28401	120	1	3.3	3.3	NUM
bracis-28401	120	2	model	model	NOUN
bracis-28401	120	3	training	training	NOUN
bracis-28401	120	4	and	and	CCONJ
bracis-28401	120	5	 	 	SPACE
bracis-28401	120	6	validation	validation	NOUN
bracis-28401	120	7	the	the	DET
bracis-28401	120	8	last	last	ADJ
bracis-28401	120	9	step	step	NOUN
bracis-28401	120	10	of	of	ADP
bracis-28401	120	11	this	this	DET
bracis-28401	120	12	research	research	NOUN
bracis-28401	120	13	consists	consist	VERB
bracis-28401	120	14	of	of	ADP
bracis-28401	120	15	comparing	compare	VERB
bracis-28401	120	16	supervised	supervised	ADJ
bracis-28401	120	17	machine	machine	NOUN
bracis-28401	120	18	learning	learning	NOUN
bracis-28401	120	19	models	model	NOUN
bracis-28401	120	20	according	accord	VERB
bracis-28401	120	21	to	to	ADP
bracis-28401	120	22	their	their	PRON
bracis-28401	120	23	ability	ability	NOUN
bracis-28401	120	24	to	to	PART
bracis-28401	120	25	predict	predict	VERB
bracis-28401	120	26	the	the	DET
bracis-28401	120	27	running	running	ADJ
bracis-28401	120	28	-	-	PUNCT
bracis-28401	120	29	time	time	NOUN
bracis-28401	120	30	complexity	complexity	NOUN
bracis-28401	120	31	class	class	NOUN
bracis-28401	120	32	of	of	ADP
bracis-28401	120	33	a	a	DET
bracis-28401	120	34	program	program	NOUN
bracis-28401	120	35	code	code	NOUN
bracis-28401	120	36	.	.	PUNCT
bracis-28401	121	1	to	to	ADP
bracis-28401	121	2	this	this	DET
bracis-28401	121	3	end	end	NOUN
bracis-28401	121	4	,	,	PUNCT
bracis-28401	121	5	we	we	PRON
bracis-28401	121	6	first	first	ADV
bracis-28401	121	7	use	use	VERB
bracis-28401	121	8	the	the	DET
bracis-28401	121	9	merged	merge	VERB
bracis-28401	121	10	dataset	dataset	NOUN
bracis-28401	121	11	to	to	PART
bracis-28401	121	12	find	find	VERB
bracis-28401	121	13	out	out	ADP
bracis-28401	121	14	which	which	DET
bracis-28401	121	15	method	method	NOUN
bracis-28401	121	16	have	have	VERB
bracis-28401	121	17	the	the	DET
bracis-28401	121	18	best	good	ADJ
bracis-28401	121	19	accuracy	accuracy	NOUN
bracis-28401	121	20	to	to	PART
bracis-28401	121	21	predict	predict	VERB
bracis-28401	121	22	both	both	DET
bracis-28401	121	23	efficiency	efficiency	NOUN
bracis-28401	121	24	(	(	PUNCT
bracis-28401	121	25	two	two	NUM
bracis-28401	121	26	-	-	PUNCT
bracis-28401	121	27	class	class	NOUN
bracis-28401	121	28	prediction	prediction	NOUN
bracis-28401	121	29	problem	problem	NOUN
bracis-28401	121	30	)	)	PUNCT
bracis-28401	121	31	and	and	CCONJ
bracis-28401	121	32	complexity	complexity	NOUN
bracis-28401	121	33	class	class	NOUN
bracis-28401	121	34	(	(	PUNCT
bracis-28401	121	35	multiclass	multiclass	ADJ
bracis-28401	121	36	prediction	prediction	NOUN
bracis-28401	121	37	)	)	PUNCT
bracis-28401	121	38	.	.	PUNCT
bracis-28401	122	1	considering	consider	VERB
bracis-28401	122	2	the	the	DET
bracis-28401	122	3	results	result	NOUN
bracis-28401	122	4	provided	provide	VERB
bracis-28401	122	5	by	by	ADP
bracis-28401	122	6	the	the	DET
bracis-28401	122	7	work	work	NOUN
bracis-28401	122	8	of	of	ADP
bracis-28401	122	9	[	[	X
bracis-28401	122	10	18	18	NUM
bracis-28401	122	11	]	]	PUNCT
bracis-28401	122	12	,	,	PUNCT
bracis-28401	122	13	which	which	PRON
bracis-28401	122	14	found	find	VERB
bracis-28401	122	15	that	that	SCONJ
bracis-28401	122	16	random	random	ADJ
bracis-28401	122	17	forest	forest	NOUN
bracis-28401	122	18	had	have	VERB
bracis-28401	122	19	the	the	DET
bracis-28401	122	20	best	good	ADJ
bracis-28401	122	21	accuracy	accuracy	NOUN
bracis-28401	122	22	among	among	ADP
bracis-28401	122	23	eight	eight	NUM
bracis-28401	122	24	classification	classification	NOUN
bracis-28401	122	25	algorithms	algorithm	NOUN
bracis-28401	122	26	,	,	PUNCT
bracis-28401	122	27	we	we	PRON
bracis-28401	122	28	included	include	VERB
bracis-28401	122	29	extreme	extreme	ADJ
bracis-28401	122	30	gradient	gradient	NOUN
bracis-28401	122	31	boosting	boost	VERB
bracis-28401	122	32	trees	tree	NOUN
bracis-28401	122	33	(	(	PUNCT
bracis-28401	122	34	xgbt	xgbt	PROPN
bracis-28401	122	35	)	)	PUNCT
bracis-28401	122	36	and	and	CCONJ
bracis-28401	122	37	ann	ann	PROPN
bracis-28401	122	38	in	in	ADP
bracis-28401	122	39	the	the	DET
bracis-28401	122	40	comparisons	comparison	NOUN
bracis-28401	122	41	because	because	SCONJ
bracis-28401	122	42	the	the	DET
bracis-28401	122	43	previous	previous	ADJ
bracis-28401	122	44	work	work	NOUN
bracis-28401	122	45	do	do	AUX
bracis-28401	122	46	not	not	PART
bracis-28401	122	47	considered	consider	VERB
bracis-28401	122	48	that	that	SCONJ
bracis-28401	122	49	approaches	approach	NOUN
bracis-28401	122	50	.	.	PUNCT
bracis-28401	123	1	we	we	PRON
bracis-28401	123	2	conducted	conduct	VERB
bracis-28401	123	3	the	the	DET
bracis-28401	123	4	implementations	implementation	NOUN
bracis-28401	123	5	of	of	ADP
bracis-28401	123	6	random	random	ADJ
bracis-28401	123	7	forest	forest	NOUN
bracis-28401	123	8	both	both	CCONJ
bracis-28401	123	9	in	in	ADP
bracis-28401	123	10	r	r	NOUN
bracis-28401	123	11	and	and	CCONJ
bracis-28401	123	12	in	in	ADP
bracis-28401	123	13	python	python	NOUN
bracis-28401	123	14	(	(	PUNCT
bracis-28401	123	15	files	file	NOUN
bracis-28401	123	16	“	"	PUNCT
bracis-28401	123	17	classificators.r	classificators.r	PROPN
bracis-28401	123	18	”	"	PUNCT
bracis-28401	123	19	and	and	CCONJ
bracis-28401	123	20	“	"	PUNCT
bracis-28401	123	21	classificators.py	classificators.py	PROPN
bracis-28401	123	22	”	"	PUNCT
bracis-28401	123	23	,	,	PUNCT
bracis-28401	123	24	respectively	respectively	ADV
bracis-28401	123	25	)	)	PUNCT
bracis-28401	123	26	and	and	CCONJ
bracis-28401	123	27	the	the	DET
bracis-28401	123	28	other	other	ADJ
bracis-28401	123	29	models	model	NOUN
bracis-28401	123	30	only	only	ADV
bracis-28401	123	31	in	in	ADP
bracis-28401	123	32	python	python	PROPN
bracis-28401	123	33	.	.	PUNCT
bracis-28401	124	1	xgbt	xgbt	PROPN
bracis-28401	124	2	is	be	AUX
bracis-28401	124	3	an	an	DET
bracis-28401	124	4	effective	effective	ADJ
bracis-28401	124	5	and	and	CCONJ
bracis-28401	124	6	scalable	scalable	ADJ
bracis-28401	124	7	tree	tree	NOUN
bracis-28401	124	8	-	-	PUNCT
bracis-28401	124	9	boosting	boost	VERB
bracis-28401	124	10	system	system	NOUN
bracis-28401	124	11	that	that	PRON
bracis-28401	124	12	combines	combine	VERB
bracis-28401	124	13	novel	novel	ADJ
bracis-28401	124	14	sparsity	sparsity	NOUN
bracis-28401	124	15	-	-	PUNCT
bracis-28401	124	16	aware	aware	ADJ
bracis-28401	124	17	algorithms	algorithm	NOUN
bracis-28401	124	18	and	and	CCONJ
bracis-28401	124	19	weighted	weight	VERB
bracis-28401	124	20	quantile	quantile	ADJ
bracis-28401	124	21	sketch	sketch	NOUN
bracis-28401	124	22	for	for	ADP
bracis-28401	124	23	approximate	approximate	ADJ
bracis-28401	124	24	tree	tree	NOUN
bracis-28401	124	25	learning	learning	NOUN
bracis-28401	124	26	 	 	SPACE
bracis-28401	125	1	[	[	X
bracis-28401	125	2	5	5	NUM
bracis-28401	125	3	]	]	PUNCT
bracis-28401	125	4	.	.	PUNCT
bracis-28401	126	1	this	this	DET
bracis-28401	126	2	system	system	NOUN
bracis-28401	126	3	is	be	AUX
bracis-28401	126	4	an	an	DET
bracis-28401	126	5	optimized	optimize	VERB
bracis-28401	126	6	version	version	NOUN
bracis-28401	126	7	of	of	ADP
bracis-28401	126	8	the	the	DET
bracis-28401	126	9	gradient	gradient	NOUN
bracis-28401	126	10	boosting	boost	VERB
bracis-28401	126	11	machine	machine	NOUN
bracis-28401	126	12	algorithm	algorithm	NOUN
bracis-28401	126	13	(	(	PUNCT
bracis-28401	126	14	gbdt	gbdt	PROPN
bracis-28401	126	15	)	)	PUNCT
bracis-28401	126	16	,	,	PUNCT
bracis-28401	126	17	created	create	VERB
bracis-28401	126	18	by	by	ADP
bracis-28401	126	19	friedman	friedman	PROPN
bracis-28401	126	20	 	 	SPACE
bracis-28401	127	1	[	[	X
bracis-28401	127	2	7	7	NUM
bracis-28401	127	3	]	]	PUNCT
bracis-28401	127	4	,	,	PUNCT
bracis-28401	127	5	which	which	PRON
bracis-28401	127	6	uses	use	VERB
bracis-28401	127	7	decision	decision	NOUN
bracis-28401	127	8	trees	tree	NOUN
bracis-28401	127	9	for	for	ADP
bracis-28401	127	10	classification	classification	NOUN
bracis-28401	127	11	.	.	PUNCT
bracis-28401	128	1	the	the	DET
bracis-28401	128	2	traditional	traditional	ADJ
bracis-28401	128	3	gbdt	gbdt	NOUN
bracis-28401	128	4	approach	approach	NOUN
bracis-28401	128	5	only	only	ADV
bracis-28401	128	6	deals	deal	NOUN
bracis-28401	128	7	with	with	ADP
bracis-28401	128	8	the	the	DET
bracis-28401	128	9	first	first	ADJ
bracis-28401	128	10	derivative	derivative	NOUN
bracis-28401	128	11	in	in	ADP
bracis-28401	128	12	learning	learning	NOUN
bracis-28401	128	13	;	;	PUNCT
bracis-28401	128	14	xgboost	xgboost	X
bracis-28401	128	15	improves	improve	VERB
bracis-28401	128	16	the	the	DET
bracis-28401	128	17	loss	loss	NOUN
bracis-28401	128	18	function	function	NOUN
bracis-28401	128	19	with	with	ADP
bracis-28401	128	20	taylor	taylor	PROPN
bracis-28401	128	21	expansion	expansion	NOUN
bracis-28401	128	22	,	,	PUNCT
bracis-28401	128	23	reducing	reduce	VERB
bracis-28401	128	24	modeling	modeling	NOUN
bracis-28401	128	25	complexities	complexity	NOUN
bracis-28401	128	26	and	and	CCONJ
bracis-28401	128	27	the	the	DET
bracis-28401	128	28	likelihood	likelihood	NOUN
bracis-28401	128	29	of	of	ADP
bracis-28401	128	30	model	model	NOUN
bracis-28401	128	31	over	over	ADP
bracis-28401	128	32	-	-	PUNCT
bracis-28401	128	33	fitness	fitness	NOUN
bracis-28401	128	34	 	 	SPACE
bracis-28401	129	1	[	[	X
bracis-28401	129	2	3	3	NUM
bracis-28401	129	3	]	]	PUNCT
bracis-28401	129	4	.	.	PUNCT
bracis-28401	130	1	regarding	regard	VERB
bracis-28401	130	2	anns	ann	NOUN
bracis-28401	130	3	,	,	PUNCT
bracis-28401	130	4	each	each	DET
bracis-28401	130	5	implementation	implementation	NOUN
bracis-28401	130	6	requires	require	VERB
bracis-28401	130	7	several	several	ADJ
bracis-28401	130	8	configuration	configuration	NOUN
bracis-28401	130	9	parameters	parameter	NOUN
bracis-28401	130	10	,	,	PUNCT
bracis-28401	130	11	which	which	PRON
bracis-28401	130	12	we	we	PRON
bracis-28401	130	13	discuss	discuss	VERB
bracis-28401	130	14	in	in	ADP
bracis-28401	130	15	the	the	DET
bracis-28401	130	16	following	following	NOUN
bracis-28401	130	17	.	.	PUNCT
bracis-28401	131	1	we	we	PRON
bracis-28401	131	2	normalized	normalize	VERB
bracis-28401	131	3	data	datum	NOUN
bracis-28401	131	4	using	use	VERB
bracis-28401	131	5	the	the	DET
bracis-28401	131	6	standardscaler	standardscaler	NOUN
bracis-28401	131	7	function	function	NOUN
bracis-28401	131	8	from	from	ADP
bracis-28401	131	9	scikit	scikit	NOUN
bracis-28401	131	10	-	-	PUNCT
bracis-28401	131	11	learn	learn	VERB
bracis-28401	131	12	[	[	X
bracis-28401	131	13	13	13	NUM
bracis-28401	131	14	]	]	PUNCT
bracis-28401	131	15	to	to	PART
bracis-28401	131	16	scale	scale	VERB
bracis-28401	131	17	the	the	DET
bracis-28401	131	18	features	feature	NOUN
bracis-28401	131	19	so	so	SCONJ
bracis-28401	131	20	that	that	SCONJ
bracis-28401	131	21	they	they	PRON
bracis-28401	131	22	have	have	VERB
bracis-28401	131	23	a	a	DET
bracis-28401	131	24	mean	mean	NOUN
bracis-28401	131	25	of	of	ADP
bracis-28401	131	26	0	0	NUM
bracis-28401	131	27	and	and	CCONJ
bracis-28401	131	28	a	a	DET
bracis-28401	131	29	standard	standard	ADJ
bracis-28401	131	30	deviation	deviation	NOUN
bracis-28401	131	31	of	of	ADP
bracis-28401	131	32	1	1	NUM
bracis-28401	131	33	.	.	PUNCT
bracis-28401	132	1	such	such	ADJ
bracis-28401	132	2	scaling	scaling	NOUN
bracis-28401	132	3	is	be	AUX
bracis-28401	132	4	a	a	DET
bracis-28401	132	5	typical	typical	ADJ
bracis-28401	132	6	pre	pre	ADJ
bracis-28401	132	7	-	-	ADJ
bracis-28401	132	8	processing	processing	ADJ
bracis-28401	132	9	step	step	NOUN
bracis-28401	132	10	to	to	PART
bracis-28401	132	11	improve	improve	VERB
bracis-28401	132	12	model	model	NOUN
bracis-28401	132	13	performance	performance	NOUN
bracis-28401	132	14	[	[	X
bracis-28401	132	15	20	20	NUM
bracis-28401	132	16	]	]	PUNCT
bracis-28401	132	17	.	.	PUNCT
bracis-28401	133	1	we	we	PRON
bracis-28401	133	2	then	then	ADV
bracis-28401	133	3	established	establish	VERB
bracis-28401	133	4	the	the	DET
bracis-28401	133	5	hyperparameters	hyperparameter	NOUN
bracis-28401	133	6	based	base	VERB
bracis-28401	133	7	on	on	ADP
bracis-28401	133	8	the	the	DET
bracis-28401	133	9	best	good	ADJ
bracis-28401	133	10	random	random	ADJ
bracis-28401	133	11	search	search	NOUN
bracis-28401	133	12	results	result	NOUN
bracis-28401	133	13	,	,	PUNCT
bracis-28401	133	14	which	which	PRON
bracis-28401	133	15	have	have	AUX
bracis-28401	133	16	been	be	AUX
bracis-28401	133	17	proven	prove	VERB
bracis-28401	133	18	more	more	ADV
bracis-28401	133	19	efficient	efficient	ADJ
bracis-28401	133	20	for	for	ADP
bracis-28401	133	21	hyper	hyper	ADJ
bracis-28401	133	22	parametrization	parametrization	NOUN
bracis-28401	133	23	than	than	ADP
bracis-28401	133	24	trials	trial	NOUN
bracis-28401	133	25	on	on	ADP
bracis-28401	133	26	a	a	DET
bracis-28401	133	27	grid	grid	NOUN
bracis-28401	133	28	 	 	SPACE
bracis-28401	134	1	[	[	X
bracis-28401	134	2	1	1	NUM
bracis-28401	134	3	]	]	PUNCT
bracis-28401	134	4	.	.	PUNCT
bracis-28401	135	1	when	when	SCONJ
bracis-28401	135	2	the	the	DET
bracis-28401	135	3	corresponding	corresponding	ADJ
bracis-28401	135	4	dropout	dropout	NOUN
bracis-28401	135	5	rate	rate	NOUN
bracis-28401	135	6	exceeds	exceed	NOUN
bracis-28401	135	7	zero	zero	NUM
bracis-28401	135	8	,	,	PUNCT
bracis-28401	135	9	a	a	DET
bracis-28401	135	10	dropout	dropout	NOUN
bracis-28401	135	11	layer	layer	NOUN
bracis-28401	135	12	is	be	AUX
bracis-28401	135	13	added	add	VERB
bracis-28401	135	14	after	after	ADP
bracis-28401	135	15	the	the	DET
bracis-28401	135	16	dense	dense	ADJ
bracis-28401	135	17	layer	layer	NOUN
bracis-28401	135	18	to	to	PART
bracis-28401	135	19	prevent	prevent	VERB
bracis-28401	135	20	overfitting	overfitting	NOUN
bracis-28401	135	21	.	.	PUNCT
bracis-28401	136	1	the	the	DET
bracis-28401	136	2	same	same	ADJ
bracis-28401	136	3	applies	apply	VERB
bracis-28401	136	4	to	to	ADP
bracis-28401	136	5	the	the	DET
bracis-28401	136	6	batch	batch	NOUN
bracis-28401	136	7	normalization	normalization	NOUN
bracis-28401	136	8	flag	flag	NOUN
bracis-28401	136	9	:	:	PUNCT
bracis-28401	136	10	when	when	SCONJ
bracis-28401	136	11	it	it	PRON
bracis-28401	136	12	is	be	AUX
bracis-28401	136	13	true	true	ADJ
bracis-28401	136	14	,	,	PUNCT
bracis-28401	136	15	it	it	PRON
bracis-28401	136	16	adds	add	VERB
bracis-28401	136	17	a	a	DET
bracis-28401	136	18	batchnormalization	batchnormalization	NOUN
bracis-28401	136	19	layer	layer	NOUN
bracis-28401	136	20	after	after	ADP
bracis-28401	136	21	the	the	DET
bracis-28401	136	22	dense	dense	ADJ
bracis-28401	136	23	layer	layer	NOUN
bracis-28401	136	24	to	to	PART
bracis-28401	136	25	normalize	normalize	VERB
bracis-28401	136	26	the	the	DET
bracis-28401	136	27	inputs	input	NOUN
bracis-28401	136	28	and	and	CCONJ
bracis-28401	136	29	improve	improve	VERB
bracis-28401	136	30	the	the	DET
bracis-28401	136	31	convergence	convergence	NOUN
bracis-28401	136	32	of	of	ADP
bracis-28401	136	33	the	the	DET
bracis-28401	136	34	model	model	NOUN
bracis-28401	136	35	 	 	SPACE
bracis-28401	137	1	[	[	X
bracis-28401	137	2	8	8	NUM
bracis-28401	137	3	]	]	PUNCT
bracis-28401	137	4	.	.	PUNCT
bracis-28401	138	1	lastly	lastly	ADV
bracis-28401	138	2	,	,	PUNCT
bracis-28401	138	3	the	the	DET
bracis-28401	138	4	model	model	NOUN
bracis-28401	138	5	is	be	AUX
bracis-28401	138	6	optimized	optimize	VERB
bracis-28401	138	7	through	through	ADP
bracis-28401	138	8	adam	adam	PROPN
bracis-28401	138	9	,	,	PUNCT
bracis-28401	138	10	defined	define	VERB
bracis-28401	138	11	by	by	ADP
bracis-28401	138	12	the	the	DET
bracis-28401	138	13	random	random	ADJ
bracis-28401	138	14	search	search	NOUN
bracis-28401	138	15	,	,	PUNCT
bracis-28401	138	16	and	and	CCONJ
bracis-28401	138	17	trained	train	VERB
bracis-28401	138	18	for	for	ADP
bracis-28401	138	19	500	500	NUM
bracis-28401	138	20	epochs	epoch	NOUN
bracis-28401	138	21	with	with	ADP
bracis-28401	138	22	a	a	DET
bracis-28401	138	23	batch	batch	NOUN
bracis-28401	138	24	size	size	NOUN
bracis-28401	138	25	equal	equal	ADJ
bracis-28401	138	26	to	to	ADP
bracis-28401	138	27	64	64	NUM
bracis-28401	138	28	.	.	PUNCT
bracis-28401	139	1	we	we	PRON
bracis-28401	139	2	used	use	VERB
bracis-28401	139	3	the	the	DET
bracis-28401	139	4	train_test_split	train_test_split	ADJ
bracis-28401	139	5	function	function	NOUN
bracis-28401	139	6	from	from	ADP
bracis-28401	139	7	scikit	scikit	NOUN
bracis-28401	139	8	-	-	PUNCT
bracis-28401	139	9	learn	learn	VERB
bracis-28401	139	10	[	[	X
bracis-28401	139	11	13	13	NUM
bracis-28401	139	12	]	]	PUNCT
bracis-28401	139	13	to	to	PART
bracis-28401	139	14	split	split	VERB
bracis-28401	139	15	the	the	DET
bracis-28401	139	16	balanced	balanced	ADJ
bracis-28401	139	17	dataset	dataset	NOUN
bracis-28401	139	18	into	into	ADP
bracis-28401	139	19	trainand	trainand	NOUN
bracis-28401	139	20	test	test	NOUN
bracis-28401	139	21	-	-	PUNCT
bracis-28401	139	22	data	data	NOUN
bracis-28401	139	23	.	.	PUNCT
bracis-28401	140	1	to	to	PART
bracis-28401	140	2	prevent	prevent	VERB
bracis-28401	140	3	overfitting	overfitte	VERB
bracis-28401	140	4	issues	issue	NOUN
bracis-28401	140	5	,	,	PUNCT
bracis-28401	140	6	we	we	PRON
bracis-28401	140	7	chose	choose	VERB
bracis-28401	140	8	to	to	PART
bracis-28401	140	9	maintain	maintain	VERB
bracis-28401	140	10	most	most	ADJ
bracis-28401	140	11	of	of	ADP
bracis-28401	140	12	the	the	DET
bracis-28401	140	13	function	function	NOUN
bracis-28401	140	14	parameters	parameter	NOUN
bracis-28401	140	15	as	as	ADP
bracis-28401	140	16	standard	standard	ADJ
bracis-28401	140	17	as	as	ADP
bracis-28401	140	18	possible	possible	ADJ
bracis-28401	140	19	.	.	PUNCT
bracis-28401	141	1	that	that	DET
bracis-28401	141	2	way	way	NOUN
bracis-28401	141	3	,	,	PUNCT
bracis-28401	141	4	we	we	PRON
bracis-28401	141	5	altered	alter	VERB
bracis-28401	141	6	only	only	ADV
bracis-28401	141	7	the	the	DET
bracis-28401	141	8	stratify	stratify	NOUN
bracis-28401	141	9	.	.	PUNCT
bracis-28401	142	1	when	when	SCONJ
bracis-28401	142	2	different	different	ADJ
bracis-28401	142	3	from	from	ADP
bracis-28401	142	4	none	none	NOUN
bracis-28401	142	5	,	,	PUNCT
bracis-28401	142	6	the	the	DET
bracis-28401	142	7	samples	sample	NOUN
bracis-28401	142	8	are	be	AUX
bracis-28401	142	9	stratified	stratify	VERB
bracis-28401	142	10	through	through	ADP
bracis-28401	142	11	stratifiedkfold	stratifiedkfold	ADJ
bracis-28401	142	12	,	,	PUNCT
bracis-28401	142	13	so	so	SCONJ
bracis-28401	142	14	that	that	SCONJ
bracis-28401	142	15	each	each	DET
bracis-28401	142	16	set	set	NOUN
bracis-28401	142	17	contains	contain	VERB
bracis-28401	142	18	approximately	approximately	ADV
bracis-28401	142	19	the	the	DET
bracis-28401	142	20	same	same	ADJ
bracis-28401	142	21	percentage	percentage	NOUN
bracis-28401	142	22	of	of	ADP
bracis-28401	142	23	samples	sample	NOUN
bracis-28401	142	24	of	of	ADP
bracis-28401	142	25	each	each	DET
bracis-28401	142	26	target	target	NOUN
bracis-28401	142	27	class	class	NOUN
bracis-28401	142	28	as	as	ADP
bracis-28401	142	29	the	the	DET
bracis-28401	142	30	complete	complete	ADJ
bracis-28401	142	31	set	set	NOUN
bracis-28401	142	32	.	.	PUNCT
bracis-28401	143	1	stratification	stratification	NOUN
bracis-28401	143	2	has	have	AUX
bracis-28401	143	3	been	be	AUX
bracis-28401	143	4	found	find	VERB
bracis-28401	143	5	to	to	PART
bracis-28401	143	6	improve	improve	VERB
bracis-28401	143	7	upon	upon	SCONJ
bracis-28401	143	8	standard	standard	ADJ
bracis-28401	143	9	cross	cross	NOUN
bracis-28401	143	10	-	-	ADJ
bracis-28401	143	11	validation	validation	ADJ
bracis-28401	143	12	both	both	PRON
bracis-28401	143	13	in	in	ADP
bracis-28401	143	14	terms	term	NOUN
bracis-28401	143	15	of	of	ADP
bracis-28401	143	16	bias	bias	NOUN
bracis-28401	143	17	and	and	CCONJ
bracis-28401	143	18	variance	variance	NOUN
bracis-28401	143	19	.	.	PUNCT
bracis-28401	144	1	the	the	DET
bracis-28401	144	2	standard	standard	ADJ
bracis-28401	144	3	method	method	NOUN
bracis-28401	144	4	of	of	ADP
bracis-28401	144	5	randomly	randomly	ADV
bracis-28401	144	6	distributing	distribute	VERB
bracis-28401	144	7	multi	multi	ADJ
bracis-28401	144	8	-	-	ADJ
bracis-28401	144	9	label	label	ADJ
bracis-28401	144	10	training	training	NOUN
bracis-28401	144	11	samples	sample	NOUN
bracis-28401	144	12	can	can	AUX
bracis-28401	144	13	create	create	VERB
bracis-28401	144	14	issues	issue	NOUN
bracis-28401	144	15	when	when	SCONJ
bracis-28401	144	16	test	test	NOUN
bracis-28401	144	17	subsets	subset	NOUN
bracis-28401	144	18	lack	lack	VERB
bracis-28401	144	19	even	even	ADV
bracis-28401	144	20	a	a	DET
bracis-28401	144	21	single	single	ADJ
bracis-28401	144	22	positive	positive	ADJ
bracis-28401	144	23	example	example	NOUN
bracis-28401	144	24	of	of	ADP
bracis-28401	144	25	a	a	DET
bracis-28401	144	26	rare	rare	ADJ
bracis-28401	144	27	label	label	NOUN
bracis-28401	144	28	.	.	PUNCT
bracis-28401	145	1	this	this	PRON
bracis-28401	145	2	,	,	PUNCT
bracis-28401	145	3	in	in	ADP
bracis-28401	145	4	turn	turn	NOUN
bracis-28401	145	5	,	,	PUNCT
bracis-28401	145	6	can	can	AUX
bracis-28401	145	7	lead	lead	VERB
bracis-28401	145	8	to	to	ADP
bracis-28401	145	9	calculation	calculation	NOUN
bracis-28401	145	10	problems	problem	NOUN
bracis-28401	145	11	for	for	ADP
bracis-28401	145	12	various	various	ADJ
bracis-28401	145	13	multi	multi	ADJ
bracis-28401	145	14	-	-	ADJ
bracis-28401	145	15	label	label	ADJ
bracis-28401	145	16	evaluation	evaluation	NOUN
bracis-28401	145	17	measures	measure	NOUN
bracis-28401	145	18	[	[	X
bracis-28401	145	19	16	16	NUM
bracis-28401	145	20	]	]	PUNCT
bracis-28401	145	21	.	.	PUNCT
bracis-28401	146	1	after	after	SCONJ
bracis-28401	146	2	we	we	PRON
bracis-28401	146	3	established	establish	VERB
bracis-28401	146	4	that	that	DET
bracis-28401	146	5	random	random	ADJ
bracis-28401	146	6	forest	forest	NOUN
bracis-28401	146	7	is	be	AUX
bracis-28401	146	8	the	the	DET
bracis-28401	146	9	machine	machine	NOUN
bracis-28401	146	10	learning	learn	VERB
bracis-28401	146	11	approach	approach	NOUN
bracis-28401	146	12	that	that	PRON
bracis-28401	146	13	provides	provide	VERB
bracis-28401	146	14	the	the	DET
bracis-28401	146	15	best	good	ADJ
bracis-28401	146	16	results	result	NOUN
bracis-28401	146	17	(	(	PUNCT
bracis-28401	146	18	see	see	VERB
bracis-28401	146	19	sect	sect	NOUN
bracis-28401	146	20	.	.	PUNCT
bracis-28401	146	21	 	 	SPACE
bracis-28401	147	1	4	4	NUM
bracis-28401	147	2	)	)	PUNCT
bracis-28401	147	3	,	,	PUNCT
bracis-28401	147	4	we	we	PRON
bracis-28401	147	5	conducted	conduct	VERB
bracis-28401	147	6	a	a	DET
bracis-28401	147	7	systematic	systematic	ADJ
bracis-28401	147	8	process	process	NOUN
bracis-28401	147	9	for	for	ADP
bracis-28401	147	10	learning	learning	NOUN
bracis-28401	147	11	and	and	CCONJ
bracis-28401	147	12	predicting	predict	VERB
bracis-28401	147	13	complexity	complexity	NOUN
bracis-28401	147	14	classes	class	NOUN
bracis-28401	147	15	:	:	PUNCT
bracis-28401	148	1	1	1	X
bracis-28401	148	2	.	.	X
bracis-28401	148	3	we	we	PRON
bracis-28401	148	4	used	use	VERB
bracis-28401	148	5	the	the	DET
bracis-28401	148	6	crawled	crawl	VERB
bracis-28401	148	7	dataset	dataset	NOUN
bracis-28401	148	8	for	for	ADP
bracis-28401	148	9	training	train	VERB
bracis-28401	148	10	the	the	DET
bracis-28401	148	11	models	model	NOUN
bracis-28401	148	12	with	with	ADP
bracis-28401	148	13	a	a	DET
bracis-28401	148	14	sample	sample	NOUN
bracis-28401	148	15	of	of	ADP
bracis-28401	148	16	70	70	NUM
bracis-28401	148	17	%	%	NOUN
bracis-28401	148	18	and	and	CCONJ
bracis-28401	148	19	tested	test	VERB
bracis-28401	148	20	with	with	ADP
bracis-28401	148	21	30	30	NUM
bracis-28401	148	22	%	%	NOUN
bracis-28401	148	23	remaining	remain	VERB
bracis-28401	148	24	data	datum	NOUN
bracis-28401	148	25	;	;	PUNCT
bracis-28401	148	26	2	2	X
bracis-28401	148	27	.	.	X
bracis-28401	148	28	we	we	PRON
bracis-28401	148	29	compare	compare	VERB
bracis-28401	148	30	our	our	PRON
bracis-28401	148	31	results	result	NOUN
bracis-28401	148	32	to	to	PART
bracis-28401	148	33	sikka	sikka	VERB
bracis-28401	148	34	et	et	PROPN
bracis-28401	148	35	al	al	PROPN
bracis-28401	148	36	.	.	PUNCT
bracis-28401	149	1	[	[	X
bracis-28401	149	2	18	18	NUM
bracis-28401	149	3	]	]	PUNCT
bracis-28401	149	4	by	by	ADP
bracis-28401	149	5	running	run	VERB
bracis-28401	149	6	a	a	DET
bracis-28401	149	7	cross	cross	ADJ
bracis-28401	149	8	-	-	ADJ
bracis-28401	149	9	validation	validation	ADJ
bracis-28401	149	10	process	process	NOUN
bracis-28401	149	11	with	with	ADP
bracis-28401	149	12	70	70	NUM
bracis-28401	149	13	%	%	NOUN
bracis-28401	149	14	of	of	ADP
bracis-28401	149	15	the	the	DET
bracis-28401	149	16	reference	reference	NOUN
bracis-28401	149	17	dataset	dataset	VERB
bracis-28401	149	18	and	and	CCONJ
bracis-28401	149	19	validating	validate	VERB
bracis-28401	149	20	using	use	VERB
bracis-28401	149	21	30	30	NUM
bracis-28401	149	22	%	%	NOUN
bracis-28401	149	23	of	of	ADP
bracis-28401	149	24	their	their	PRON
bracis-28401	149	25	data	datum	NOUN
bracis-28401	149	26	;	;	PUNCT
bracis-28401	149	27	3	3	X
bracis-28401	149	28	.	.	X
bracis-28401	150	1	we	we	PRON
bracis-28401	150	2	evaluated	evaluate	VERB
bracis-28401	150	3	the	the	DET
bracis-28401	150	4	generalization	generalization	NOUN
bracis-28401	150	5	capability	capability	NOUN
bracis-28401	150	6	of	of	ADP
bracis-28401	150	7	the	the	DET
bracis-28401	150	8	crawled	crawl	VERB
bracis-28401	150	9	dataset	dataset	VERB
bracis-28401	150	10	by	by	ADP
bracis-28401	150	11	training	train	VERB
bracis-28401	150	12	the	the	DET
bracis-28401	150	13	ml	ml	NOUN
bracis-28401	150	14	model	model	NOUN
bracis-28401	150	15	with	with	ADP
bracis-28401	150	16	70	70	NUM
bracis-28401	150	17	%	%	NOUN
bracis-28401	150	18	of	of	ADP
bracis-28401	150	19	the	the	DET
bracis-28401	150	20	crawled	crawl	VERB
bracis-28401	150	21	dataset	dataset	NOUN
bracis-28401	150	22	and	and	CCONJ
bracis-28401	150	23	testing	testing	NOUN
bracis-28401	150	24	with	with	ADP
bracis-28401	150	25	100	100	NUM
bracis-28401	150	26	%	%	NOUN
bracis-28401	150	27	of	of	ADP
bracis-28401	150	28	the	the	DET
bracis-28401	150	29	reference	reference	NOUN
bracis-28401	150	30	dataset	dataset	NOUN
bracis-28401	150	31	,	,	PUNCT
bracis-28401	150	32	and	and	CCONJ
bracis-28401	150	33	;	;	PUNCT
bracis-28401	150	34	4	4	X
bracis-28401	150	35	.	.	X
bracis-28401	150	36	we	we	PRON
bracis-28401	150	37	in	in	ADP
bracis-28401	150	38	-	-	PUNCT
bracis-28401	150	39	depth	depth	NOUN
bracis-28401	150	40	evaluate	evaluate	VERB
bracis-28401	150	41	the	the	DET
bracis-28401	150	42	confusion	confusion	NOUN
bracis-28401	150	43	matrix	matrix	NOUN
bracis-28401	150	44	of	of	ADP
bracis-28401	150	45	the	the	DET
bracis-28401	150	46	random	random	ADJ
bracis-28401	150	47	forest	forest	NOUN
bracis-28401	150	48	model	model	NOUN
bracis-28401	150	49	using	use	VERB
bracis-28401	150	50	70	70	NUM
bracis-28401	150	51	%	%	NOUN
bracis-28401	150	52	of	of	ADP
bracis-28401	150	53	the	the	DET
bracis-28401	150	54	merged	merge	VERB
bracis-28401	150	55	dataset	dataset	NOUN
bracis-28401	150	56	for	for	ADP
bracis-28401	150	57	training	training	NOUN
bracis-28401	150	58	and	and	CCONJ
bracis-28401	150	59	30	30	NUM
bracis-28401	150	60	%	%	NOUN
bracis-28401	150	61	for	for	ADP
bracis-28401	150	62	testing	testing	NOUN
bracis-28401	150	63	.	.	PUNCT
bracis-28401	151	1	4	4	NUM
bracis-28401	151	2	results	result	VERB
bracis-28401	151	3	this	this	DET
bracis-28401	151	4	section	section	NOUN
bracis-28401	151	5	presents	present	VERB
bracis-28401	151	6	the	the	DET
bracis-28401	151	7	results	result	NOUN
bracis-28401	151	8	for	for	ADP
bracis-28401	151	9	predicting	predict	VERB
bracis-28401	151	10	computer	computer	NOUN
bracis-28401	151	11	program	program	NOUN
bracis-28401	151	12	code	code	NOUN
bracis-28401	151	13	efficiency	efficiency	NOUN
bracis-28401	151	14	and	and	CCONJ
bracis-28401	151	15	complexity	complexity	NOUN
bracis-28401	151	16	classes	class	NOUN
bracis-28401	151	17	based	base	VERB
bracis-28401	151	18	on	on	ADP
bracis-28401	151	19	their	their	PRON
bracis-28401	151	20	attributes	attribute	NOUN
bracis-28401	151	21	.	.	PUNCT
bracis-28401	152	1	first	first	ADV
bracis-28401	152	2	,	,	PUNCT
bracis-28401	152	3	we	we	PRON
bracis-28401	152	4	compare	compare	VERB
bracis-28401	152	5	the	the	DET
bracis-28401	152	6	accuracy	accuracy	NOUN
bracis-28401	152	7	of	of	ADP
bracis-28401	152	8	predictions	prediction	NOUN
bracis-28401	152	9	for	for	ADP
bracis-28401	152	10	each	each	DET
bracis-28401	152	11	model	model	NOUN
bracis-28401	152	12	in	in	ADP
bracis-28401	152	13	the	the	DET
bracis-28401	152	14	merged	merge	VERB
bracis-28401	152	15	dataset	dataset	NOUN
bracis-28401	152	16	to	to	PART
bracis-28401	152	17	select	select	VERB
bracis-28401	152	18	the	the	DET
bracis-28401	152	19	appropriate	appropriate	ADJ
bracis-28401	152	20	approach	approach	NOUN
bracis-28401	152	21	to	to	PART
bracis-28401	152	22	perform	perform	VERB
bracis-28401	152	23	our	our	PRON
bracis-28401	152	24	in	in	ADP
bracis-28401	152	25	-	-	PUNCT
bracis-28401	152	26	depth	depth	NOUN
bracis-28401	152	27	systematic	systematic	ADJ
bracis-28401	152	28	evaluation	evaluation	NOUN
bracis-28401	152	29	process	process	NOUN
bracis-28401	152	30	.	.	PUNCT
bracis-28401	153	1	table	table	NOUN
bracis-28401	153	2	 	 	SPACE
bracis-28401	153	3	3	3	NUM
bracis-28401	153	4	depicts	depict	VERB
bracis-28401	153	5	these	these	DET
bracis-28401	153	6	comparison	comparison	NOUN
bracis-28401	153	7	results	result	NOUN
bracis-28401	153	8	;	;	PUNCT
bracis-28401	153	9	the	the	DET
bracis-28401	153	10	accuracy	accuracy	NOUN
bracis-28401	153	11	values	value	NOUN
bracis-28401	153	12	show	show	VERB
bracis-28401	153	13	that	that	SCONJ
bracis-28401	153	14	the	the	DET
bracis-28401	153	15	random	random	ADJ
bracis-28401	153	16	forest	forest	NOUN
bracis-28401	153	17	is	be	AUX
bracis-28401	153	18	the	the	DET
bracis-28401	153	19	best	good	ADJ
bracis-28401	153	20	approach	approach	NOUN
bracis-28401	153	21	among	among	ADP
bracis-28401	153	22	the	the	DET
bracis-28401	153	23	evaluated	evaluate	VERB
bracis-28401	153	24	methods	method	NOUN
bracis-28401	153	25	,	,	PUNCT
bracis-28401	153	26	predicting	predict	VERB
bracis-28401	153	27	codes	code	NOUN
bracis-28401	153	28	’	'	PUNCT
bracis-28401	153	29	efficiency	efficiency	NOUN
bracis-28401	153	30	with	with	ADP
bracis-28401	153	31	90.17	90.17	NUM
bracis-28401	153	32	%	%	NOUN
bracis-28401	153	33	accuracy	accuracy	NOUN
bracis-28401	153	34	and	and	CCONJ
bracis-28401	153	35	the	the	DET
bracis-28401	153	36	complexity	complexity	NOUN
bracis-28401	153	37	class	class	NOUN
bracis-28401	153	38	with	with	ADP
bracis-28401	153	39	89.84	89.84	NUM
bracis-28401	153	40	%	%	NOUN
bracis-28401	153	41	.	.	PUNCT
bracis-28401	154	1	the	the	DET
bracis-28401	154	2	xgbt	xgbt	PROPN
bracis-28401	154	3	provided	provide	VERB
bracis-28401	154	4	an	an	DET
bracis-28401	154	5	accuracy	accuracy	NOUN
bracis-28401	154	6	close	close	ADV
bracis-28401	154	7	to	to	ADP
bracis-28401	154	8	the	the	DET
bracis-28401	154	9	random	random	ADJ
bracis-28401	154	10	forest	forest	NOUN
bracis-28401	154	11	,	,	PUNCT
bracis-28401	154	12	and	and	CCONJ
bracis-28401	154	13	given	give	VERB
bracis-28401	154	14	the	the	DET
bracis-28401	154	15	nondeterministic	nondeterministic	ADJ
bracis-28401	154	16	behavior	behavior	NOUN
bracis-28401	154	17	of	of	ADP
bracis-28401	154	18	ann	ann	PROPN
bracis-28401	154	19	it	it	PRON
bracis-28401	154	20	resulted	result	VERB
bracis-28401	154	21	in	in	ADP
bracis-28401	154	22	a	a	DET
bracis-28401	154	23	range	range	NOUN
bracis-28401	154	24	of	of	ADP
bracis-28401	154	25	accuracy	accuracy	NOUN
bracis-28401	154	26	,	,	PUNCT
bracis-28401	154	27	also	also	ADV
bracis-28401	154	28	smaller	small	ADJ
bracis-28401	154	29	than	than	ADP
bracis-28401	154	30	the	the	DET
bracis-28401	154	31	random	random	ADJ
bracis-28401	154	32	forest	forest	NOUN
bracis-28401	154	33	.	.	PUNCT
bracis-28401	155	1	such	such	ADJ
bracis-28401	155	2	results	result	NOUN
bracis-28401	155	3	follow	follow	VERB
bracis-28401	155	4	the	the	DET
bracis-28401	155	5	findings	finding	NOUN
bracis-28401	155	6	of	of	ADP
bracis-28401	155	7	[	[	X
bracis-28401	155	8	18	18	NUM
bracis-28401	155	9	]	]	PUNCT
bracis-28401	155	10	,	,	PUNCT
bracis-28401	155	11	which	which	PRON
bracis-28401	155	12	pointed	point	VERB
bracis-28401	155	13	out	out	ADP
bracis-28401	155	14	the	the	DET
bracis-28401	155	15	random	random	ADJ
bracis-28401	155	16	forest	forest	NOUN
bracis-28401	155	17	as	as	ADP
bracis-28401	155	18	the	the	DET
bracis-28401	155	19	algorithm	algorithm	NOUN
bracis-28401	155	20	that	that	PRON
bracis-28401	155	21	resulted	result	VERB
bracis-28401	155	22	in	in	ADP
bracis-28401	155	23	better	well	ADJ
bracis-28401	155	24	accuracy	accuracy	NOUN
bracis-28401	155	25	for	for	ADP
bracis-28401	155	26	predicting	predict	VERB
bracis-28401	155	27	complexity	complexity	NOUN
bracis-28401	155	28	classes	class	NOUN
bracis-28401	155	29	(	(	PUNCT
bracis-28401	155	30	71.84	71.84	NUM
bracis-28401	155	31	%	%	NOUN
bracis-28401	155	32	)	)	PUNCT
bracis-28401	155	33	.	.	PUNCT
bracis-28401	156	1	thus	thus	ADV
bracis-28401	156	2	,	,	PUNCT
bracis-28401	156	3	we	we	PRON
bracis-28401	156	4	will	will	AUX
bracis-28401	156	5	consider	consider	VERB
bracis-28401	156	6	the	the	DET
bracis-28401	156	7	random	random	ADJ
bracis-28401	156	8	forest	forest	NOUN
bracis-28401	156	9	for	for	ADP
bracis-28401	156	10	our	our	PRON
bracis-28401	156	11	systematic	systematic	ADJ
bracis-28401	156	12	evaluation	evaluation	NOUN
bracis-28401	156	13	process	process	NOUN
bracis-28401	156	14	.	.	PUNCT
bracis-28401	157	1	table	table	NOUN
bracis-28401	157	2	3	3	NUM
bracis-28401	157	3	.	.	PUNCT
bracis-28401	157	4	comparison	comparison	NOUN
bracis-28401	157	5	of	of	ADP
bracis-28401	157	6	machine	machine	NOUN
bracis-28401	157	7	learning	learning	NOUN
bracis-28401	157	8	models	model	NOUN
bracis-28401	157	9	to	to	PART
bracis-28401	157	10	predict	predict	VERB
bracis-28401	157	11	efficiency	efficiency	NOUN
bracis-28401	157	12	and	and	CCONJ
bracis-28401	157	13	complexity	complexity	NOUN
bracis-28401	157	14	class	class	NOUN
bracis-28401	157	15	on	on	ADP
bracis-28401	157	16	the	the	DET
bracis-28401	157	17	merged	merge	VERB
bracis-28401	157	18	datasetfull	datasetfull	ADJ
bracis-28401	157	19	size	size	NOUN
bracis-28401	157	20	table	table	NOUN
bracis-28401	157	21	as	as	SCONJ
bracis-28401	157	22	we	we	PRON
bracis-28401	157	23	established	establish	VERB
bracis-28401	157	24	random	random	ADJ
bracis-28401	157	25	forest	forest	NOUN
bracis-28401	157	26	as	as	SCONJ
bracis-28401	157	27	the	the	DET
bracis-28401	157	28	reference	reference	NOUN
bracis-28401	157	29	ml	ml	AUX
bracis-28401	157	30	approach	approach	NOUN
bracis-28401	157	31	,	,	PUNCT
bracis-28401	157	32	we	we	PRON
bracis-28401	157	33	now	now	ADV
bracis-28401	157	34	assess	assess	VERB
bracis-28401	157	35	its	its	PRON
bracis-28401	157	36	accuracy	accuracy	NOUN
bracis-28401	157	37	to	to	PART
bracis-28401	157	38	predict	predict	VERB
bracis-28401	157	39	the	the	DET
bracis-28401	157	40	efficiency	efficiency	NOUN
bracis-28401	157	41	of	of	ADP
bracis-28401	157	42	codes	code	NOUN
bracis-28401	157	43	using	use	VERB
bracis-28401	157	44	our	our	PRON
bracis-28401	157	45	systematic	systematic	ADJ
bracis-28401	157	46	evaluation	evaluation	NOUN
bracis-28401	157	47	process	process	NOUN
bracis-28401	157	48	.	.	PUNCT
bracis-28401	158	1	table	table	NOUN
bracis-28401	158	2	 	 	SPACE
bracis-28401	158	3	4	4	NUM
bracis-28401	158	4	contains	contain	VERB
bracis-28401	158	5	prediction	prediction	NOUN
bracis-28401	158	6	results	result	NOUN
bracis-28401	158	7	for	for	ADP
bracis-28401	158	8	the	the	DET
bracis-28401	158	9	efficiency	efficiency	NOUN
bracis-28401	158	10	of	of	ADP
bracis-28401	158	11	available	available	ADJ
bracis-28401	158	12	algorithm	algorithm	NOUN
bracis-28401	158	13	codes	code	NOUN
bracis-28401	158	14	.	.	PUNCT
bracis-28401	159	1	two	two	NUM
bracis-28401	159	2	main	main	ADJ
bracis-28401	159	3	conclusions	conclusion	NOUN
bracis-28401	159	4	arise	arise	VERB
bracis-28401	159	5	from	from	ADP
bracis-28401	159	6	the	the	DET
bracis-28401	159	7	analysis	analysis	NOUN
bracis-28401	159	8	of	of	ADP
bracis-28401	159	9	the	the	DET
bracis-28401	159	10	use	use	NOUN
bracis-28401	159	11	of	of	ADP
bracis-28401	159	12	random	random	ADJ
bracis-28401	159	13	forest	forest	NOUN
bracis-28401	159	14	to	to	PART
bracis-28401	159	15	predict	predict	VERB
bracis-28401	159	16	the	the	DET
bracis-28401	159	17	efficiency	efficiency	NOUN
bracis-28401	159	18	of	of	ADP
bracis-28401	159	19	source	source	NOUN
bracis-28401	159	20	codes	code	NOUN
bracis-28401	159	21	:	:	PUNCT
bracis-28401	159	22	i	i	NOUN
bracis-28401	159	23	)	)	PUNCT
bracis-28401	159	24	when	when	SCONJ
bracis-28401	159	25	the	the	DET
bracis-28401	159	26	training	training	NOUN
bracis-28401	159	27	and	and	CCONJ
bracis-28401	159	28	test	test	NOUN
bracis-28401	159	29	data	datum	NOUN
bracis-28401	159	30	are	be	AUX
bracis-28401	159	31	from	from	ADP
bracis-28401	159	32	the	the	DET
bracis-28401	159	33	same	same	ADJ
bracis-28401	159	34	dataset	dataset	NOUN
bracis-28401	159	35	,	,	PUNCT
bracis-28401	159	36	the	the	DET
bracis-28401	159	37	model	model	NOUN
bracis-28401	159	38	can	can	AUX
bracis-28401	159	39	achieve	achieve	VERB
bracis-28401	159	40	up	up	ADP
bracis-28401	159	41	to	to	PART
bracis-28401	159	42	80	80	NUM
bracis-28401	159	43	%	%	NOUN
bracis-28401	159	44	of	of	ADP
bracis-28401	159	45	accuracy	accuracy	NOUN
bracis-28401	159	46	(	(	PUNCT
bracis-28401	159	47	80.13	80.13	NUM
bracis-28401	159	48	%	%	NOUN
bracis-28401	159	49	for	for	ADP
bracis-28401	159	50	crawled	crawl	VERB
bracis-28401	159	51	dataset	dataset	NOUN
bracis-28401	159	52	,	,	PUNCT
bracis-28401	159	53	93.85	93.85	NUM
bracis-28401	159	54	%	%	NOUN
bracis-28401	159	55	for	for	ADP
bracis-28401	159	56	reference	reference	NOUN
bracis-28401	159	57	dataset	dataset	NOUN
bracis-28401	159	58	,	,	PUNCT
bracis-28401	159	59	and	and	CCONJ
bracis-28401	159	60	90.17	90.17	NUM
bracis-28401	159	61	%	%	NOUN
bracis-28401	159	62	for	for	ADP
bracis-28401	159	63	the	the	DET
bracis-28401	159	64	merged	merge	VERB
bracis-28401	159	65	dataset	dataset	NOUN
bracis-28401	159	66	)	)	PUNCT
bracis-28401	159	67	;	;	PUNCT
bracis-28401	159	68	ii	ii	X
bracis-28401	159	69	)	)	PUNCT
bracis-28401	159	70	when	when	SCONJ
bracis-28401	159	71	train	train	NOUN
bracis-28401	159	72	and	and	CCONJ
bracis-28401	159	73	test	test	NOUN
bracis-28401	159	74	data	datum	NOUN
bracis-28401	159	75	are	be	AUX
bracis-28401	159	76	from	from	ADP
bracis-28401	159	77	distinct	distinct	ADJ
bracis-28401	159	78	datasets	dataset	NOUN
bracis-28401	159	79	,	,	PUNCT
bracis-28401	159	80	accuracy	accuracy	NOUN
bracis-28401	159	81	drops	drop	VERB
bracis-28401	159	82	to	to	ADP
bracis-28401	159	83	83.57	83.57	NUM
bracis-28401	159	84	%	%	NOUN
bracis-28401	159	85	(	(	PUNCT
bracis-28401	159	86	trained	train	VERB
bracis-28401	159	87	with	with	ADP
bracis-28401	159	88	70	70	NUM
bracis-28401	159	89	%	%	NOUN
bracis-28401	159	90	of	of	ADP
bracis-28401	159	91	crawled	crawl	VERB
bracis-28401	159	92	dataset	dataset	NOUN
bracis-28401	159	93	and	and	CCONJ
bracis-28401	159	94	100	100	NUM
bracis-28401	159	95	%	%	NOUN
bracis-28401	159	96	of	of	ADP
bracis-28401	159	97	reference	reference	NOUN
bracis-28401	159	98	dataset	dataset	NOUN
bracis-28401	159	99	)	)	PUNCT
bracis-28401	159	100	.	.	PUNCT
bracis-28401	160	1	although	although	SCONJ
bracis-28401	160	2	this	this	DET
bracis-28401	160	3	fall	fall	NOUN
bracis-28401	160	4	in	in	ADP
bracis-28401	160	5	accuracy	accuracy	NOUN
bracis-28401	160	6	seems	seem	VERB
bracis-28401	160	7	a	a	DET
bracis-28401	160	8	poor	poor	ADJ
bracis-28401	160	9	result	result	NOUN
bracis-28401	160	10	,	,	PUNCT
bracis-28401	160	11	if	if	SCONJ
bracis-28401	160	12	we	we	PRON
bracis-28401	160	13	consider	consider	VERB
bracis-28401	160	14	that	that	SCONJ
bracis-28401	160	15	the	the	DET
bracis-28401	160	16	data	datum	NOUN
bracis-28401	160	17	are	be	AUX
bracis-28401	160	18	from	from	ADP
bracis-28401	160	19	distinct	distinct	ADJ
bracis-28401	160	20	sources	source	NOUN
bracis-28401	160	21	,	,	PUNCT
bracis-28401	160	22	the	the	DET
bracis-28401	160	23	crawled	crawl	VERB
bracis-28401	160	24	dataset	dataset	NOUN
bracis-28401	160	25	has	have	VERB
bracis-28401	160	26	a	a	DET
bracis-28401	160	27	good	good	ADJ
bracis-28401	160	28	generalization	generalization	NOUN
bracis-28401	160	29	concerning	concern	VERB
bracis-28401	160	30	efficiency	efficiency	NOUN
bracis-28401	160	31	classification	classification	NOUN
bracis-28401	160	32	.	.	PUNCT
bracis-28401	161	1	also	also	ADV
bracis-28401	161	2	,	,	PUNCT
bracis-28401	161	3	by	by	ADP
bracis-28401	161	4	analyzing	analyze	VERB
bracis-28401	161	5	the	the	DET
bracis-28401	161	6	f1	f1	NOUN
bracis-28401	161	7	-	-	PUNCT
bracis-28401	161	8	score	score	NOUN
bracis-28401	161	9	’s	’s	PART
bracis-28401	161	10	results	result	NOUN
bracis-28401	161	11	(	(	PUNCT
bracis-28401	161	12	up	up	ADP
bracis-28401	161	13	to	to	PART
bracis-28401	161	14	80	80	NUM
bracis-28401	161	15	%	%	NOUN
bracis-28401	161	16	)	)	PUNCT
bracis-28401	161	17	,	,	PUNCT
bracis-28401	161	18	we	we	PRON
bracis-28401	161	19	can	can	AUX
bracis-28401	161	20	conclude	conclude	VERB
bracis-28401	161	21	that	that	SCONJ
bracis-28401	161	22	all	all	DET
bracis-28401	161	23	the	the	DET
bracis-28401	161	24	random	random	ADJ
bracis-28401	161	25	forest	forest	NOUN
bracis-28401	161	26	models	model	NOUN
bracis-28401	161	27	have	have	VERB
bracis-28401	161	28	a	a	DET
bracis-28401	161	29	good	good	ADJ
bracis-28401	161	30	balance	balance	NOUN
bracis-28401	161	31	between	between	ADP
bracis-28401	161	32	precision	precision	NOUN
bracis-28401	161	33	and	and	CCONJ
bracis-28401	161	34	recall	recall	NOUN
bracis-28401	161	35	,	,	PUNCT
bracis-28401	161	36	which	which	PRON
bracis-28401	161	37	means	mean	VERB
bracis-28401	161	38	that	that	SCONJ
bracis-28401	161	39	they	they	PRON
bracis-28401	161	40	have	have	VERB
bracis-28401	161	41	a	a	DET
bracis-28401	161	42	good	good	ADJ
bracis-28401	161	43	fit	fit	NOUN
bracis-28401	161	44	to	to	PART
bracis-28401	161	45	distinguish	distinguish	VERB
bracis-28401	161	46	the	the	DET
bracis-28401	161	47	efficiency	efficiency	NOUN
bracis-28401	161	48	of	of	ADP
bracis-28401	161	49	source	source	NOUN
bracis-28401	161	50	codes	code	NOUN
bracis-28401	161	51	.	.	PUNCT
bracis-28401	162	1	table	table	NOUN
bracis-28401	162	2	4	4	NUM
bracis-28401	162	3	.	.	PUNCT
bracis-28401	163	1	summary	summary	NOUN
bracis-28401	163	2	of	of	ADP
bracis-28401	163	3	efficiency	efficiency	NOUN
bracis-28401	163	4	prediction	prediction	NOUN
bracis-28401	163	5	using	use	VERB
bracis-28401	163	6	random	random	ADJ
bracis-28401	163	7	forestfull	forestfull	ADJ
bracis-28401	163	8	size	size	NOUN
bracis-28401	163	9	table	table	NOUN
bracis-28401	163	10	after	after	ADP
bracis-28401	163	11	assessing	assess	VERB
bracis-28401	163	12	the	the	DET
bracis-28401	163	13	random	random	ADJ
bracis-28401	163	14	forest	forest	NOUN
bracis-28401	163	15	models	model	NOUN
bracis-28401	163	16	’	'	PUNCT
bracis-28401	163	17	ability	ability	NOUN
bracis-28401	163	18	to	to	PART
bracis-28401	163	19	classify	classify	VERB
bracis-28401	163	20	codes	code	NOUN
bracis-28401	163	21	regarding	regard	VERB
bracis-28401	163	22	their	their	PRON
bracis-28401	163	23	efficiency	efficiency	NOUN
bracis-28401	163	24	,	,	PUNCT
bracis-28401	163	25	we	we	PRON
bracis-28401	163	26	retrained	retrain	VERB
bracis-28401	163	27	each	each	DET
bracis-28401	163	28	model	model	NOUN
bracis-28401	163	29	to	to	PART
bracis-28401	163	30	predict	predict	VERB
bracis-28401	163	31	complexity	complexity	NOUN
bracis-28401	163	32	classes	class	NOUN
bracis-28401	163	33	.	.	PUNCT
bracis-28401	164	1	similar	similar	ADJ
bracis-28401	164	2	to	to	ADP
bracis-28401	164	3	the	the	DET
bracis-28401	164	4	efficiency	efficiency	NOUN
bracis-28401	164	5	classification	classification	NOUN
bracis-28401	164	6	,	,	PUNCT
bracis-28401	164	7	we	we	PRON
bracis-28401	164	8	leverage	leverage	VERB
bracis-28401	164	9	our	our	PRON
bracis-28401	164	10	four	four	NUM
bracis-28401	164	11	-	-	PUNCT
bracis-28401	164	12	step	step	NOUN
bracis-28401	164	13	systematic	systematic	ADJ
bracis-28401	164	14	process	process	NOUN
bracis-28401	164	15	to	to	PART
bracis-28401	164	16	compare	compare	VERB
bracis-28401	164	17	the	the	DET
bracis-28401	164	18	models	model	NOUN
bracis-28401	164	19	.	.	PUNCT
bracis-28401	165	1	table	table	NOUN
bracis-28401	165	2	 	 	SPACE
bracis-28401	165	3	5	5	NUM
bracis-28401	165	4	depicts	depict	VERB
bracis-28401	165	5	these	these	DET
bracis-28401	165	6	results	result	NOUN
bracis-28401	165	7	.	.	PUNCT
bracis-28401	166	1	an	an	DET
bracis-28401	166	2	accuracy	accuracy	NOUN
bracis-28401	166	3	analysis	analysis	NOUN
bracis-28401	166	4	shows	show	VERB
bracis-28401	166	5	that	that	SCONJ
bracis-28401	166	6	the	the	DET
bracis-28401	166	7	random	random	ADJ
bracis-28401	166	8	forest	forest	NOUN
bracis-28401	166	9	model	model	NOUN
bracis-28401	166	10	properly	properly	ADV
bracis-28401	166	11	predicts	predict	VERB
bracis-28401	166	12	the	the	DET
bracis-28401	166	13	complexity	complexity	NOUN
bracis-28401	166	14	class	class	NOUN
bracis-28401	166	15	of	of	ADP
bracis-28401	166	16	source	source	NOUN
bracis-28401	166	17	codes	code	NOUN
bracis-28401	166	18	from	from	ADP
bracis-28401	166	19	the	the	DET
bracis-28401	166	20	crawled	crawl	VERB
bracis-28401	166	21	dataset	dataset	NOUN
bracis-28401	166	22	,	,	PUNCT
bracis-28401	166	23	with	with	ADP
bracis-28401	166	24	an	an	DET
bracis-28401	166	25	accuracy	accuracy	NOUN
bracis-28401	166	26	of	of	ADP
bracis-28401	166	27	80	80	NUM
bracis-28401	166	28	%	%	NOUN
bracis-28401	166	29	.	.	PUNCT
bracis-28401	167	1	the	the	DET
bracis-28401	167	2	results	result	NOUN
bracis-28401	167	3	in	in	ADP
bracis-28401	167	4	table	table	NOUN
bracis-28401	167	5	 	 	SPACE
bracis-28401	167	6	5	5	NUM
bracis-28401	167	7	also	also	ADV
bracis-28401	167	8	show	show	VERB
bracis-28401	167	9	that	that	SCONJ
bracis-28401	167	10	the	the	DET
bracis-28401	167	11	referenceand	referenceand	NOUN
bracis-28401	167	12	merged	merge	VERB
bracis-28401	167	13	-	-	PUNCT
bracis-28401	167	14	based	base	VERB
bracis-28401	167	15	models	model	NOUN
bracis-28401	167	16	achieved	achieve	VERB
bracis-28401	167	17	an	an	DET
bracis-28401	167	18	accuracy	accuracy	NOUN
bracis-28401	167	19	superior	superior	ADJ
bracis-28401	167	20	to	to	ADP
bracis-28401	167	21	88	88	NUM
bracis-28401	167	22	%	%	NOUN
bracis-28401	167	23	,	,	PUNCT
bracis-28401	167	24	outstanding	outstanding	ADJ
bracis-28401	167	25	the	the	DET
bracis-28401	167	26	finds	find	NOUN
bracis-28401	167	27	of	of	ADP
bracis-28401	167	28	sikka	sikka	PROPN
bracis-28401	167	29	et	et	PROPN
bracis-28401	167	30	al	al	PROPN
bracis-28401	167	31	.	.	PUNCT
bracis-28401	168	1	[	[	X
bracis-28401	168	2	18	18	NUM
bracis-28401	168	3	]	]	PUNCT
bracis-28401	168	4	,	,	PUNCT
bracis-28401	168	5	which	which	PRON
bracis-28401	168	6	presented	present	VERB
bracis-28401	168	7	an	an	DET
bracis-28401	168	8	accuracy	accuracy	NOUN
bracis-28401	168	9	of	of	ADP
bracis-28401	168	10	71.4	71.4	NUM
bracis-28401	168	11	%	%	NOUN
bracis-28401	168	12	for	for	ADP
bracis-28401	168	13	predicting	predict	VERB
bracis-28401	168	14	all	all	DET
bracis-28401	168	15	classes	class	NOUN
bracis-28401	168	16	.	.	PUNCT
bracis-28401	169	1	we	we	PRON
bracis-28401	169	2	claim	claim	VERB
bracis-28401	169	3	that	that	SCONJ
bracis-28401	169	4	the	the	DET
bracis-28401	169	5	resultant	resultant	NOUN
bracis-28401	169	6	improvement	improvement	NOUN
bracis-28401	169	7	justifies	justifie	NOUN
bracis-28401	169	8	by	by	ADP
bracis-28401	169	9	both	both	DET
bracis-28401	169	10	the	the	DET
bracis-28401	169	11	balancing	balancing	NOUN
bracis-28401	169	12	and	and	CCONJ
bracis-28401	169	13	the	the	DET
bracis-28401	169	14	feature	feature	NOUN
bracis-28401	169	15	selection	selection	NOUN
bracis-28401	169	16	processes	process	NOUN
bracis-28401	169	17	we	we	PRON
bracis-28401	169	18	leveraged	leverage	VERB
bracis-28401	169	19	.	.	PUNCT
bracis-28401	170	1	however	however	ADV
bracis-28401	170	2	,	,	PUNCT
bracis-28401	170	3	when	when	SCONJ
bracis-28401	170	4	the	the	DET
bracis-28401	170	5	predictions	prediction	NOUN
bracis-28401	170	6	ran	run	VERB
bracis-28401	170	7	in	in	ADP
bracis-28401	170	8	the	the	DET
bracis-28401	170	9	reference	reference	NOUN
bracis-28401	170	10	dataset	dataset	NOUN
bracis-28401	170	11	,	,	PUNCT
bracis-28401	170	12	the	the	DET
bracis-28401	170	13	model	model	NOUN
bracis-28401	170	14	trained	train	VERB
bracis-28401	170	15	with	with	ADP
bracis-28401	170	16	data	datum	NOUN
bracis-28401	170	17	from	from	ADP
bracis-28401	170	18	the	the	DET
bracis-28401	170	19	crawled	crawl	VERB
bracis-28401	170	20	data	datum	NOUN
bracis-28401	170	21	had	have	VERB
bracis-28401	170	22	a	a	DET
bracis-28401	170	23	lower	low	ADJ
bracis-28401	170	24	accuracy	accuracy	NOUN
bracis-28401	170	25	,	,	PUNCT
bracis-28401	170	26	only	only	ADV
bracis-28401	170	27	44.04	44.04	NUM
bracis-28401	170	28	%	%	NOUN
bracis-28401	170	29	.	.	PUNCT
bracis-28401	171	1	this	this	PRON
bracis-28401	171	2	indicates	indicate	VERB
bracis-28401	171	3	that	that	SCONJ
bracis-28401	171	4	the	the	DET
bracis-28401	171	5	model	model	NOUN
bracis-28401	171	6	does	do	AUX
bracis-28401	171	7	not	not	PART
bracis-28401	171	8	have	have	VERB
bracis-28401	171	9	enough	enough	ADJ
bracis-28401	171	10	generalization	generalization	NOUN
bracis-28401	171	11	for	for	ADP
bracis-28401	171	12	distinguishing	distinguish	VERB
bracis-28401	171	13	the	the	DET
bracis-28401	171	14	complexity	complexity	NOUN
bracis-28401	171	15	class	class	NOUN
bracis-28401	171	16	when	when	SCONJ
bracis-28401	171	17	it	it	PRON
bracis-28401	171	18	only	only	ADV
bracis-28401	171	19	relies	rely	VERB
bracis-28401	171	20	on	on	ADP
bracis-28401	171	21	the	the	DET
bracis-28401	171	22	crawled	crawl	VERB
bracis-28401	171	23	dataset	dataset	NOUN
bracis-28401	171	24	for	for	ADP
bracis-28401	171	25	training	training	NOUN
bracis-28401	171	26	.	.	PUNCT
bracis-28401	172	1	it	it	PRON
bracis-28401	172	2	is	be	AUX
bracis-28401	172	3	worth	worth	ADJ
bracis-28401	172	4	mentioning	mention	VERB
bracis-28401	172	5	that	that	SCONJ
bracis-28401	172	6	the	the	DET
bracis-28401	172	7	trained	train	VERB
bracis-28401	172	8	model	model	NOUN
bracis-28401	172	9	does	do	AUX
bracis-28401	172	10	not	not	PART
bracis-28401	172	11	include	include	VERB
bracis-28401	172	12	any	any	PRON
bracis-28401	172	13	of	of	ADP
bracis-28401	172	14	the	the	DET
bracis-28401	172	15	data	datum	NOUN
bracis-28401	172	16	in	in	ADP
bracis-28401	172	17	the	the	DET
bracis-28401	172	18	reference	reference	NOUN
bracis-28401	172	19	dataset	dataset	VERB
bracis-28401	172	20	.	.	PUNCT
bracis-28401	173	1	to	to	PART
bracis-28401	173	2	understand	understand	VERB
bracis-28401	173	3	the	the	DET
bracis-28401	173	4	misclassifications	misclassification	NOUN
bracis-28401	173	5	,	,	PUNCT
bracis-28401	173	6	we	we	PRON
bracis-28401	173	7	analyzed	analyze	VERB
bracis-28401	173	8	the	the	DET
bracis-28401	173	9	confusion	confusion	NOUN
bracis-28401	173	10	matrix	matrix	NOUN
bracis-28401	173	11	of	of	ADP
bracis-28401	173	12	predictions	prediction	NOUN
bracis-28401	173	13	of	of	ADP
bracis-28401	173	14	the	the	DET
bracis-28401	173	15	crawled	crawl	VERB
bracis-28401	173	16	-	-	PUNCT
bracis-28401	173	17	based	base	VERB
bracis-28401	173	18	model	model	NOUN
bracis-28401	173	19	on	on	ADP
bracis-28401	173	20	the	the	DET
bracis-28401	173	21	reference	reference	NOUN
bracis-28401	173	22	dataset	dataset	NOUN
bracis-28401	173	23	(	(	PUNCT
bracis-28401	173	24	table	table	NOUN
bracis-28401	173	25	 	 	SPACE
bracis-28401	173	26	6	6	NUM
bracis-28401	173	27	)	)	PUNCT
bracis-28401	173	28	.	.	PUNCT
bracis-28401	174	1	table	table	NOUN
bracis-28401	174	2	5	5	NUM
bracis-28401	174	3	.	.	PUNCT
bracis-28401	175	1	summary	summary	NOUN
bracis-28401	175	2	of	of	ADP
bracis-28401	175	3	complexity	complexity	NOUN
bracis-28401	175	4	class	class	NOUN
bracis-28401	175	5	prediction	prediction	NOUN
bracis-28401	175	6	using	use	VERB
bracis-28401	175	7	random	random	ADJ
bracis-28401	175	8	forest	forest	NOUN
bracis-28401	175	9	modelfull	modelfull	ADJ
bracis-28401	175	10	size	size	NOUN
bracis-28401	175	11	table	table	NOUN
bracis-28401	175	12	table	table	NOUN
bracis-28401	175	13	6	6	NUM
bracis-28401	175	14	.	.	PUNCT
bracis-28401	175	15	confusion	confusion	NOUN
bracis-28401	175	16	matrix	matrix	NOUN
bracis-28401	175	17	of	of	ADP
bracis-28401	175	18	predictions	prediction	NOUN
bracis-28401	175	19	in	in	ADP
bracis-28401	175	20	the	the	DET
bracis-28401	175	21	reference	reference	NOUN
bracis-28401	175	22	dataset	dataset	VERB
bracis-28401	175	23	with	with	ADP
bracis-28401	175	24	the	the	DET
bracis-28401	175	25	random	random	ADJ
bracis-28401	175	26	forest	forest	NOUN
bracis-28401	175	27	model	model	NOUN
bracis-28401	175	28	trained	train	VERB
bracis-28401	175	29	using	use	VERB
bracis-28401	175	30	70	70	NUM
bracis-28401	175	31	%	%	NOUN
bracis-28401	175	32	of	of	ADP
bracis-28401	175	33	crawled	crawl	VERB
bracis-28401	175	34	datasetfull	datasetfull	ADJ
bracis-28401	175	35	size	size	NOUN
bracis-28401	175	36	table	table	NOUN
bracis-28401	175	37	the	the	DET
bracis-28401	175	38	results	result	NOUN
bracis-28401	175	39	depicted	depict	VERB
bracis-28401	175	40	in	in	ADP
bracis-28401	175	41	table	table	NOUN
bracis-28401	175	42	 	 	SPACE
bracis-28401	175	43	6	6	NUM
bracis-28401	175	44	show	show	VERB
bracis-28401	175	45	that	that	SCONJ
bracis-28401	175	46	112	112	NUM
bracis-28401	175	47	predictions	prediction	NOUN
bracis-28401	175	48	occurred	occur	VERB
bracis-28401	175	49	for	for	ADP
bracis-28401	175	50	classes	class	NOUN
bracis-28401	175	51	that	that	PRON
bracis-28401	175	52	even	even	ADV
bracis-28401	175	53	exist	exist	VERB
bracis-28401	175	54	in	in	ADP
bracis-28401	175	55	the	the	DET
bracis-28401	175	56	dataset	dataset	NOUN
bracis-28401	175	57	(	(	PUNCT
bracis-28401	175	58	sublinear	sublinear	NOUN
bracis-28401	175	59	,	,	PUNCT
bracis-28401	175	60	polynomial	polynomial	ADJ
bracis-28401	175	61	,	,	PUNCT
bracis-28401	175	62	and	and	CCONJ
bracis-28401	175	63	exponential	exponential	ADJ
bracis-28401	175	64	time	time	NOUN
bracis-28401	175	65	)	)	PUNCT
bracis-28401	175	66	,	,	PUNCT
bracis-28401	175	67	representing	represent	VERB
bracis-28401	175	68	12.03	12.03	NUM
bracis-28401	175	69	%	%	NOUN
bracis-28401	175	70	of	of	ADP
bracis-28401	175	71	the	the	DET
bracis-28401	175	72	total	total	ADJ
bracis-28401	175	73	data	datum	NOUN
bracis-28401	175	74	,	,	PUNCT
bracis-28401	175	75	most	most	ADJ
bracis-28401	175	76	of	of	ADP
bracis-28401	175	77	them	they	PRON
bracis-28401	175	78	pointing	point	VERB
bracis-28401	175	79	to	to	ADP
bracis-28401	175	80	inefficient	inefficient	ADJ
bracis-28401	175	81	classes	class	NOUN
bracis-28401	175	82	(	(	PUNCT
bracis-28401	175	83	polynomial	polynomial	ADJ
bracis-28401	175	84	and	and	CCONJ
bracis-28401	175	85	exponential	exponential	ADJ
bracis-28401	175	86	time	time	NOUN
bracis-28401	175	87	)	)	PUNCT
bracis-28401	175	88	.	.	PUNCT
bracis-28401	176	1	such	such	DET
bracis-28401	176	2	a	a	DET
bracis-28401	176	3	result	result	NOUN
bracis-28401	176	4	demonstrates	demonstrate	VERB
bracis-28401	176	5	that	that	SCONJ
bracis-28401	176	6	the	the	DET
bracis-28401	176	7	crawled	crawl	VERB
bracis-28401	176	8	dataset	dataset	NOUN
bracis-28401	176	9	does	do	AUX
bracis-28401	176	10	not	not	PART
bracis-28401	176	11	have	have	VERB
bracis-28401	176	12	enough	enough	ADJ
bracis-28401	176	13	representativeness	representativeness	ADJ
bracis-28401	176	14	to	to	PART
bracis-28401	176	15	allow	allow	VERB
bracis-28401	176	16	machine	machine	NOUN
bracis-28401	176	17	learning	learning	NOUN
bracis-28401	176	18	models	model	NOUN
bracis-28401	176	19	to	to	PART
bracis-28401	176	20	generalize	generalize	VERB
bracis-28401	176	21	complexity	complexity	NOUN
bracis-28401	176	22	classes	class	NOUN
bracis-28401	176	23	.	.	PUNCT
bracis-28401	177	1	also	also	ADV
bracis-28401	177	2	,	,	PUNCT
bracis-28401	177	3	we	we	PRON
bracis-28401	177	4	observed	observe	VERB
bracis-28401	177	5	that	that	SCONJ
bracis-28401	177	6	the	the	DET
bracis-28401	177	7	better	well	ADJ
bracis-28401	177	8	predictions	prediction	NOUN
bracis-28401	177	9	occurred	occur	VERB
bracis-28401	177	10	for	for	ADP
bracis-28401	177	11	the	the	DET
bracis-28401	177	12	linear	linear	ADJ
bracis-28401	177	13	and	and	CCONJ
bracis-28401	177	14	linearithmic	linearithmic	ADJ
bracis-28401	177	15	categories	category	NOUN
bracis-28401	177	16	(	(	PUNCT
bracis-28401	177	17	65.01	65.01	NUM
bracis-28401	177	18	%	%	NOUN
bracis-28401	177	19	and	and	CCONJ
bracis-28401	177	20	74	74	NUM
bracis-28401	177	21	%	%	NOUN
bracis-28401	177	22	of	of	ADP
bracis-28401	177	23	accuracy	accuracy	NOUN
bracis-28401	177	24	)	)	PUNCT
bracis-28401	177	25	,	,	PUNCT
bracis-28401	177	26	and	and	CCONJ
bracis-28401	177	27	the	the	DET
bracis-28401	177	28	worst	bad	ADJ
bracis-28401	177	29	case	case	NOUN
bracis-28401	177	30	occurred	occur	VERB
bracis-28401	177	31	in	in	ADP
bracis-28401	177	32	the	the	DET
bracis-28401	177	33	logarithmic	logarithmic	ADJ
bracis-28401	177	34	class	class	NOUN
bracis-28401	177	35	(	(	PUNCT
bracis-28401	177	36	09.09	09.09	NUM
bracis-28401	177	37	%	%	NOUN
bracis-28401	177	38	of	of	ADP
bracis-28401	177	39	accuracy	accuracy	NOUN
bracis-28401	177	40	)	)	PUNCT
bracis-28401	177	41	,	,	PUNCT
bracis-28401	177	42	which	which	PRON
bracis-28401	177	43	indicates	indicate	VERB
bracis-28401	177	44	that	that	SCONJ
bracis-28401	177	45	the	the	DET
bracis-28401	177	46	characteristics	characteristic	NOUN
bracis-28401	177	47	of	of	ADP
bracis-28401	177	48	these	these	DET
bracis-28401	177	49	classes	class	NOUN
bracis-28401	177	50	require	require	VERB
bracis-28401	177	51	a	a	DET
bracis-28401	177	52	more	more	ADV
bracis-28401	177	53	profound	profound	ADJ
bracis-28401	177	54	study	study	NOUN
bracis-28401	177	55	.	.	PUNCT
bracis-28401	178	1	for	for	ADP
bracis-28401	178	2	such	such	ADJ
bracis-28401	178	3	analysis	analysis	NOUN
bracis-28401	178	4	,	,	PUNCT
bracis-28401	178	5	we	we	PRON
bracis-28401	178	6	assess	assess	VERB
bracis-28401	178	7	the	the	DET
bracis-28401	178	8	mean	mean	ADJ
bracis-28401	178	9	decrease	decrease	NOUN
bracis-28401	178	10	accuracy	accuracy	NOUN
bracis-28401	178	11	measure	measure	NOUN
bracis-28401	178	12	mda	mda	PROPN
bracis-28401	179	1	[	[	X
bracis-28401	179	2	2	2	NUM
bracis-28401	179	3	]	]	PUNCT
bracis-28401	179	4	for	for	SCONJ
bracis-28401	179	5	each	each	DET
bracis-28401	179	6	feature	feature	NOUN
bracis-28401	179	7	to	to	PART
bracis-28401	179	8	understand	understand	VERB
bracis-28401	179	9	their	their	PRON
bracis-28401	179	10	importance	importance	NOUN
bracis-28401	179	11	in	in	ADP
bracis-28401	179	12	predicting	predict	VERB
bracis-28401	179	13	the	the	DET
bracis-28401	179	14	complexity	complexity	NOUN
bracis-28401	179	15	class	class	NOUN
bracis-28401	179	16	on	on	ADP
bracis-28401	179	17	each	each	DET
bracis-28401	179	18	model	model	NOUN
bracis-28401	179	19	.	.	PUNCT
bracis-28401	180	1	figure	figure	VERB
bracis-28401	180	2	 	 	SPACE
bracis-28401	180	3	2	2	NUM
bracis-28401	180	4	presents	present	NOUN
bracis-28401	180	5	such	such	ADJ
bracis-28401	180	6	mda	mda	PROPN
bracis-28401	180	7	results	result	NOUN
bracis-28401	180	8	.	.	PUNCT
bracis-28401	181	1	fig	fig	NOUN
bracis-28401	181	2	.	.	PUNCT
bracis-28401	182	1	2	2	X
bracis-28401	182	2	.	.	X
bracis-28401	182	3	most	most	ADV
bracis-28401	182	4	relevant	relevant	ADJ
bracis-28401	182	5	features	feature	NOUN
bracis-28401	182	6	according	accord	VERB
bracis-28401	182	7	to	to	ADP
bracis-28401	182	8	mda	mda	PROPN
bracis-28401	182	9	results	result	NOUN
bracis-28401	182	10	in	in	ADP
bracis-28401	182	11	each	each	DET
bracis-28401	182	12	model	model	NOUN
bracis-28401	182	13	full	full	ADJ
bracis-28401	182	14	size	size	NOUN
bracis-28401	182	15	image	image	VERB
bracis-28401	182	16	the	the	DET
bracis-28401	182	17	analysis	analysis	NOUN
bracis-28401	182	18	of	of	ADP
bracis-28401	182	19	top-3	top-3	NUM
bracis-28401	182	20	mda	mda	PROPN
bracis-28401	182	21	depicted	depict	VERB
bracis-28401	182	22	in	in	ADP
bracis-28401	182	23	fig	fig	NOUN
bracis-28401	182	24	.	.	PUNCT
bracis-28401	182	25	 	 	SPACE
bracis-28401	183	1	2	2	NUM
bracis-28401	183	2	allows	allow	VERB
bracis-28401	183	3	us	we	PRON
bracis-28401	183	4	to	to	PART
bracis-28401	183	5	conclude	conclude	VERB
bracis-28401	183	6	that	that	SCONJ
bracis-28401	183	7	the	the	DET
bracis-28401	183	8	three	three	NUM
bracis-28401	183	9	most	most	ADV
bracis-28401	183	10	relevant	relevant	ADJ
bracis-28401	183	11	features	feature	NOUN
bracis-28401	183	12	for	for	ADP
bracis-28401	183	13	code	code	NOUN
bracis-28401	183	14	complexity	complexity	NOUN
bracis-28401	183	15	classification	classification	NOUN
bracis-28401	183	16	in	in	ADP
bracis-28401	183	17	all	all	DET
bracis-28401	183	18	the	the	DET
bracis-28401	183	19	models	model	NOUN
bracis-28401	183	20	are	be	AUX
bracis-28401	183	21	the	the	DET
bracis-28401	183	22	number	number	NOUN
bracis-28401	183	23	of	of	ADP
bracis-28401	183	24	variables	variable	NOUN
bracis-28401	183	25	(	(	PUNCT
bracis-28401	183	26	num_vari	num_vari	NOUN
bracis-28401	183	27	)	)	PUNCT
bracis-28401	183	28	,	,	PUNCT
bracis-28401	183	29	the	the	DET
bracis-28401	183	30	number	number	NOUN
bracis-28401	183	31	of	of	ADP
bracis-28401	183	32	statements	statement	NOUN
bracis-28401	183	33	(	(	PUNCT
bracis-28401	183	34	num_state	num_state	NOUN
bracis-28401	183	35	)	)	PUNCT
bracis-28401	183	36	and	and	CCONJ
bracis-28401	183	37	the	the	DET
bracis-28401	183	38	number	number	NOUN
bracis-28401	183	39	of	of	ADP
bracis-28401	183	40	loops	loop	NOUN
bracis-28401	183	41	(	(	PUNCT
bracis-28401	183	42	num_loof	num_loof	NOUN
bracis-28401	183	43	)	)	PUNCT
bracis-28401	183	44	.	.	PUNCT
bracis-28401	184	1	the	the	DET
bracis-28401	184	2	depth	depth	NOUN
bracis-28401	184	3	of	of	ADP
bracis-28401	184	4	nested	nested	ADJ
bracis-28401	184	5	loops	loop	NOUN
bracis-28401	184	6	and	and	CCONJ
bracis-28401	184	7	the	the	DET
bracis-28401	184	8	number	number	NOUN
bracis-28401	184	9	of	of	ADP
bracis-28401	184	10	recursive	recursive	ADJ
bracis-28401	184	11	calls	call	NOUN
bracis-28401	184	12	only	only	ADV
bracis-28401	184	13	appear	appear	VERB
bracis-28401	184	14	in	in	ADP
bracis-28401	184	15	the	the	DET
bracis-28401	184	16	top-5	top-5	PUNCT
bracis-28401	184	17	relevant	relevant	ADJ
bracis-28401	184	18	features	feature	NOUN
bracis-28401	184	19	in	in	ADP
bracis-28401	184	20	two	two	NUM
bracis-28401	184	21	of	of	ADP
bracis-28401	184	22	three	three	NUM
bracis-28401	184	23	models	model	NOUN
bracis-28401	184	24	,	,	PUNCT
bracis-28401	184	25	which	which	PRON
bracis-28401	184	26	is	be	AUX
bracis-28401	184	27	surprising	surprising	ADJ
bracis-28401	184	28	,	,	PUNCT
bracis-28401	184	29	as	as	SCONJ
bracis-28401	184	30	these	these	DET
bracis-28401	184	31	metrics	metric	NOUN
bracis-28401	184	32	serve	serve	VERB
bracis-28401	184	33	to	to	PART
bracis-28401	184	34	compute	compute	VERB
bracis-28401	184	35	recurrence	recurrence	NOUN
bracis-28401	184	36	functions	function	NOUN
bracis-28401	184	37	in	in	ADP
bracis-28401	184	38	code	code	NOUN
bracis-28401	184	39	complexity	complexity	NOUN
bracis-28401	184	40	analysis	analysis	NOUN
bracis-28401	184	41	.	.	PUNCT
bracis-28401	185	1	another	another	DET
bracis-28401	185	2	relevant	relevant	ADJ
bracis-28401	185	3	aspect	aspect	NOUN
bracis-28401	185	4	of	of	ADP
bracis-28401	185	5	mda	mda	PROPN
bracis-28401	185	6	analysis	analysis	NOUN
bracis-28401	185	7	is	be	AUX
bracis-28401	185	8	that	that	SCONJ
bracis-28401	185	9	the	the	DET
bracis-28401	185	10	second	second	ADJ
bracis-28401	185	11	most	most	ADV
bracis-28401	185	12	relevant	relevant	ADJ
bracis-28401	185	13	feature	feature	NOUN
bracis-28401	185	14	varies	vary	VERB
bracis-28401	185	15	significantly	significantly	ADV
bracis-28401	185	16	from	from	ADP
bracis-28401	185	17	one	one	NUM
bracis-28401	185	18	model	model	NOUN
bracis-28401	185	19	to	to	ADP
bracis-28401	185	20	another	another	PRON
bracis-28401	185	21	,	,	PUNCT
bracis-28401	185	22	which	which	PRON
bracis-28401	185	23	also	also	ADV
bracis-28401	185	24	hinders	hinder	VERB
bracis-28401	185	25	the	the	DET
bracis-28401	185	26	abstraction	abstraction	NOUN
bracis-28401	185	27	capability	capability	NOUN
bracis-28401	185	28	of	of	ADP
bracis-28401	185	29	the	the	DET
bracis-28401	185	30	model	model	NOUN
bracis-28401	185	31	based	base	VERB
bracis-28401	185	32	on	on	ADP
bracis-28401	185	33	the	the	DET
bracis-28401	185	34	crawled	crawl	VERB
bracis-28401	185	35	dataset	dataset	NOUN
bracis-28401	185	36	.	.	PUNCT
bracis-28401	186	1	considering	consider	VERB
bracis-28401	186	2	that	that	SCONJ
bracis-28401	186	3	the	the	DET
bracis-28401	186	4	crawled	crawl	VERB
bracis-28401	186	5	-	-	PUNCT
bracis-28401	186	6	based	base	VERB
bracis-28401	186	7	and	and	CCONJ
bracis-28401	186	8	the	the	DET
bracis-28401	186	9	reference	reference	NOUN
bracis-28401	186	10	-	-	PUNCT
bracis-28401	186	11	based	base	VERB
bracis-28401	186	12	models	model	NOUN
bracis-28401	186	13	share	share	VERB
bracis-28401	186	14	the	the	DET
bracis-28401	186	15	top-3	top-3	NUM
bracis-28401	186	16	relevant	relevant	ADJ
bracis-28401	186	17	features	feature	NOUN
bracis-28401	186	18	,	,	PUNCT
bracis-28401	186	19	we	we	PRON
bracis-28401	186	20	now	now	ADV
bracis-28401	186	21	assess	assess	VERB
bracis-28401	186	22	the	the	DET
bracis-28401	186	23	frequency	frequency	NOUN
bracis-28401	186	24	density	density	NOUN
bracis-28401	186	25	function	function	NOUN
bracis-28401	186	26	of	of	ADP
bracis-28401	186	27	these	these	DET
bracis-28401	186	28	features	feature	NOUN
bracis-28401	186	29	in	in	ADP
bracis-28401	186	30	both	both	DET
bracis-28401	186	31	datasets	dataset	NOUN
bracis-28401	186	32	to	to	PART
bracis-28401	186	33	understand	understand	VERB
bracis-28401	186	34	the	the	DET
bracis-28401	186	35	reasons	reason	NOUN
bracis-28401	186	36	why	why	SCONJ
bracis-28401	186	37	models	model	NOUN
bracis-28401	186	38	misclassify	misclassify	VERB
bracis-28401	186	39	linear	linear	ADJ
bracis-28401	186	40	,	,	PUNCT
bracis-28401	186	41	linearithmic	linearithmic	ADJ
bracis-28401	186	42	,	,	PUNCT
bracis-28401	186	43	and	and	CCONJ
bracis-28401	186	44	logarithmic	logarithmic	ADJ
bracis-28401	186	45	classes	class	NOUN
bracis-28401	186	46	(	(	PUNCT
bracis-28401	186	47	fig	fig	NOUN
bracis-28401	186	48	.	.	PUNCT
bracis-28401	186	49	 	 	SPACE
bracis-28401	186	50	3	3	NUM
bracis-28401	186	51	)	)	PUNCT
bracis-28401	186	52	.	.	PUNCT
bracis-28401	187	1	fig	fig	NOUN
bracis-28401	187	2	.	.	PUNCT
bracis-28401	188	1	3	3	X
bracis-28401	188	2	.	.	NOUN
bracis-28401	188	3	frequency	frequency	NOUN
bracis-28401	188	4	density	density	NOUN
bracis-28401	188	5	functions	function	NOUN
bracis-28401	188	6	for	for	ADP
bracis-28401	188	7	the	the	DET
bracis-28401	188	8	top-3	top-3	NUM
bracis-28401	188	9	most	most	ADV
bracis-28401	188	10	relevant	relevant	ADJ
bracis-28401	188	11	features	feature	NOUN
bracis-28401	188	12	in	in	ADP
bracis-28401	188	13	the	the	DET
bracis-28401	188	14	crawled	crawl	VERB
bracis-28401	188	15	and	and	CCONJ
bracis-28401	188	16	reference	reference	NOUN
bracis-28401	188	17	datasets	dataset	NOUN
bracis-28401	188	18	in	in	ADP
bracis-28401	188	19	the	the	DET
bracis-28401	188	20	linear	linear	NOUN
bracis-28401	188	21	,	,	PUNCT
bracis-28401	188	22	linearithmic	linearithmic	ADJ
bracis-28401	188	23	,	,	PUNCT
bracis-28401	188	24	and	and	CCONJ
bracis-28401	188	25	logarithmic	logarithmic	ADJ
bracis-28401	188	26	classes	class	NOUN
bracis-28401	188	27	.	.	PUNCT
bracis-28401	189	1	full	full	ADJ
bracis-28401	189	2	size	size	NOUN
bracis-28401	189	3	image	image	NOUN
bracis-28401	189	4	two	two	NUM
bracis-28401	189	5	main	main	ADJ
bracis-28401	189	6	considerations	consideration	NOUN
bracis-28401	189	7	arise	arise	VERB
bracis-28401	189	8	from	from	ADP
bracis-28401	189	9	the	the	DET
bracis-28401	189	10	analysis	analysis	NOUN
bracis-28401	189	11	of	of	ADP
bracis-28401	189	12	fig	fig	NOUN
bracis-28401	189	13	.	.	PUNCT
bracis-28401	189	14	 	 	SPACE
bracis-28401	190	1	3	3	NUM
bracis-28401	190	2	:	:	PUNCT
bracis-28401	190	3	first	first	ADV
bracis-28401	190	4	,	,	PUNCT
bracis-28401	190	5	the	the	DET
bracis-28401	190	6	density	density	NOUN
bracis-28401	190	7	function	function	NOUN
bracis-28401	190	8	is	be	AUX
bracis-28401	190	9	different	different	ADJ
bracis-28401	190	10	in	in	ADP
bracis-28401	190	11	the	the	DET
bracis-28401	190	12	two	two	NUM
bracis-28401	190	13	datasets	dataset	NOUN
bracis-28401	190	14	,	,	PUNCT
bracis-28401	190	15	both	both	CCONJ
bracis-28401	190	16	in	in	ADP
bracis-28401	190	17	terms	term	NOUN
bracis-28401	190	18	of	of	ADP
bracis-28401	190	19	the	the	DET
bracis-28401	190	20	number	number	NOUN
bracis-28401	190	21	of	of	ADP
bracis-28401	190	22	occurrences	occurrence	NOUN
bracis-28401	190	23	and	and	CCONJ
bracis-28401	190	24	the	the	DET
bracis-28401	190	25	behavior	behavior	NOUN
bracis-28401	190	26	of	of	ADP
bracis-28401	190	27	the	the	DET
bracis-28401	190	28	distribution	distribution	NOUN
bracis-28401	190	29	;	;	PUNCT
bracis-28401	190	30	second	second	X
bracis-28401	190	31	,	,	PUNCT
bracis-28401	190	32	the	the	DET
bracis-28401	190	33	linear	linear	ADJ
bracis-28401	190	34	and	and	CCONJ
bracis-28401	190	35	linearithmic	linearithmic	ADJ
bracis-28401	190	36	classes	class	NOUN
bracis-28401	190	37	have	have	VERB
bracis-28401	190	38	density	density	NOUN
bracis-28401	190	39	distribution	distribution	NOUN
bracis-28401	190	40	functions	function	NOUN
bracis-28401	190	41	with	with	ADP
bracis-28401	190	42	similar	similar	ADJ
bracis-28401	190	43	behavior	behavior	NOUN
bracis-28401	190	44	for	for	ADP
bracis-28401	190	45	the	the	DET
bracis-28401	190	46	three	three	NUM
bracis-28401	190	47	evaluated	evaluated	ADJ
bracis-28401	190	48	metrics	metric	NOUN
bracis-28401	190	49	,	,	PUNCT
bracis-28401	190	50	independently	independently	ADV
bracis-28401	190	51	of	of	ADP
bracis-28401	190	52	the	the	DET
bracis-28401	190	53	dataset	dataset	NOUN
bracis-28401	190	54	.	.	PUNCT
bracis-28401	191	1	while	while	SCONJ
bracis-28401	191	2	the	the	DET
bracis-28401	191	3	first	first	ADJ
bracis-28401	191	4	consideration	consideration	NOUN
bracis-28401	191	5	explains	explain	VERB
bracis-28401	191	6	why	why	SCONJ
bracis-28401	191	7	the	the	DET
bracis-28401	191	8	crawled	crawl	VERB
bracis-28401	191	9	-	-	PUNCT
bracis-28401	191	10	based	base	VERB
bracis-28401	191	11	model	model	NOUN
bracis-28401	191	12	can	can	AUX
bracis-28401	191	13	not	not	PART
bracis-28401	191	14	properly	properly	ADV
bracis-28401	191	15	identify	identify	VERB
bracis-28401	191	16	the	the	DET
bracis-28401	191	17	classes	class	NOUN
bracis-28401	191	18	of	of	ADP
bracis-28401	191	19	the	the	DET
bracis-28401	191	20	reference	reference	NOUN
bracis-28401	191	21	dataset	dataset	NOUN
bracis-28401	191	22	,	,	PUNCT
bracis-28401	191	23	the	the	DET
bracis-28401	191	24	second	second	NOUN
bracis-28401	191	25	justifies	justify	VERB
bracis-28401	191	26	the	the	DET
bracis-28401	191	27	lack	lack	NOUN
bracis-28401	191	28	of	of	ADP
bracis-28401	191	29	distinction	distinction	NOUN
bracis-28401	191	30	between	between	ADP
bracis-28401	191	31	classes	class	NOUN
bracis-28401	191	32	.	.	PUNCT
bracis-28401	192	1	to	to	PART
bracis-28401	192	2	have	have	VERB
bracis-28401	192	3	a	a	DET
bracis-28401	192	4	clear	clear	ADJ
bracis-28401	192	5	view	view	NOUN
bracis-28401	192	6	of	of	ADP
bracis-28401	192	7	the	the	DET
bracis-28401	192	8	limitations	limitation	NOUN
bracis-28401	192	9	of	of	ADP
bracis-28401	192	10	the	the	DET
bracis-28401	192	11	merged	merge	VERB
bracis-28401	192	12	-	-	PUNCT
bracis-28401	192	13	based	base	VERB
bracis-28401	192	14	model	model	NOUN
bracis-28401	192	15	,	,	PUNCT
bracis-28401	192	16	we	we	PRON
bracis-28401	192	17	also	also	ADV
bracis-28401	192	18	depicted	depict	VERB
bracis-28401	192	19	the	the	DET
bracis-28401	192	20	confusion	confusion	NOUN
bracis-28401	192	21	matrix	matrix	NOUN
bracis-28401	192	22	of	of	ADP
bracis-28401	192	23	its	its	PRON
bracis-28401	192	24	predictions	prediction	NOUN
bracis-28401	192	25	.	.	PUNCT
bracis-28401	193	1	the	the	DET
bracis-28401	193	2	results	result	NOUN
bracis-28401	193	3	in	in	ADP
bracis-28401	193	4	table	table	NOUN
bracis-28401	193	5	 	 	SPACE
bracis-28401	193	6	7	7	NUM
bracis-28401	193	7	show	show	VERB
bracis-28401	193	8	accurate	accurate	ADJ
bracis-28401	193	9	predictions	prediction	NOUN
bracis-28401	193	10	for	for	ADP
bracis-28401	193	11	most	most	ADJ
bracis-28401	193	12	of	of	ADP
bracis-28401	193	13	the	the	DET
bracis-28401	193	14	class	class	NOUN
bracis-28401	193	15	,	,	PUNCT
bracis-28401	193	16	with	with	ADP
bracis-28401	193	17	accuracies	accuracy	NOUN
bracis-28401	193	18	superior	superior	ADJ
bracis-28401	193	19	to	to	ADP
bracis-28401	193	20	90	90	NUM
bracis-28401	193	21	%	%	NOUN
bracis-28401	193	22	;	;	PUNCT
bracis-28401	193	23	the	the	DET
bracis-28401	193	24	discrepant	discrepant	ADJ
bracis-28401	193	25	case	case	NOUN
bracis-28401	193	26	occurred	occur	VERB
bracis-28401	193	27	in	in	ADP
bracis-28401	193	28	the	the	DET
bracis-28401	193	29	linear	linear	ADJ
bracis-28401	193	30	class	class	NOUN
bracis-28401	193	31	,	,	PUNCT
bracis-28401	193	32	with	with	ADP
bracis-28401	193	33	25	25	NUM
bracis-28401	193	34	predictions	prediction	NOUN
bracis-28401	193	35	pointing	point	VERB
bracis-28401	193	36	to	to	ADP
bracis-28401	193	37	faster	fast	ADJ
bracis-28401	193	38	time	time	NOUN
bracis-28401	193	39	classes	class	NOUN
bracis-28401	193	40	(	(	PUNCT
bracis-28401	193	41	i.e.	i.e.	X
bracis-28401	193	42	,	,	PUNCT
bracis-28401	193	43	constant	constant	ADJ
bracis-28401	193	44	,	,	PUNCT
bracis-28401	193	45	logarithmic	logarithmic	ADJ
bracis-28401	193	46	,	,	PUNCT
bracis-28401	193	47	and	and	CCONJ
bracis-28401	193	48	sublinear	sublinear	NOUN
bracis-28401	193	49	)	)	PUNCT
bracis-28401	193	50	and	and	CCONJ
bracis-28401	193	51	29	29	NUM
bracis-28401	193	52	predictions	prediction	NOUN
bracis-28401	193	53	to	to	ADP
bracis-28401	193	54	slower	slow	ADJ
bracis-28401	193	55	classes	class	NOUN
bracis-28401	193	56	(	(	PUNCT
bracis-28401	193	57	i.e.	i.e.	X
bracis-28401	193	58	,	,	PUNCT
bracis-28401	193	59	linearithmic	linearithmic	ADJ
bracis-28401	193	60	,	,	PUNCT
bracis-28401	193	61	quadratic	quadratic	ADJ
bracis-28401	193	62	,	,	PUNCT
bracis-28401	193	63	polynomial	polynomial	ADJ
bracis-28401	193	64	,	,	PUNCT
bracis-28401	193	65	and	and	CCONJ
bracis-28401	193	66	exponential	exponential	NOUN
bracis-28401	193	67	)	)	PUNCT
bracis-28401	193	68	.	.	PUNCT
bracis-28401	194	1	to	to	PART
bracis-28401	194	2	understand	understand	VERB
bracis-28401	194	3	this	this	DET
bracis-28401	194	4	lack	lack	NOUN
bracis-28401	194	5	of	of	ADP
bracis-28401	194	6	accuracy	accuracy	NOUN
bracis-28401	194	7	,	,	PUNCT
bracis-28401	194	8	we	we	PRON
bracis-28401	194	9	plotted	plot	VERB
bracis-28401	194	10	the	the	DET
bracis-28401	194	11	frequency	frequency	NOUN
bracis-28401	194	12	density	density	NOUN
bracis-28401	194	13	function	function	NOUN
bracis-28401	194	14	for	for	ADP
bracis-28401	194	15	the	the	DET
bracis-28401	194	16	num_vari	num_vari	NOUN
bracis-28401	194	17	and	and	CCONJ
bracis-28401	194	18	num_state	num_state	VERB
bracis-28401	194	19	features	feature	NOUN
bracis-28401	194	20	in	in	ADP
bracis-28401	194	21	the	the	DET
bracis-28401	194	22	merged	merge	VERB
bracis-28401	194	23	dataset	dataset	NOUN
bracis-28401	194	24	(	(	PUNCT
bracis-28401	194	25	fig	fig	NOUN
bracis-28401	194	26	.	.	PUNCT
bracis-28401	194	27	 	 	SPACE
bracis-28401	194	28	4	4	NUM
bracis-28401	194	29	)	)	PUNCT
bracis-28401	194	30	.	.	PUNCT
bracis-28401	195	1	table	table	NOUN
bracis-28401	195	2	7	7	NUM
bracis-28401	195	3	.	.	PUNCT
bracis-28401	195	4	confusion	confusion	NOUN
bracis-28401	195	5	matrix	matrix	NOUN
bracis-28401	195	6	of	of	ADP
bracis-28401	195	7	predictions	prediction	NOUN
bracis-28401	195	8	in	in	ADP
bracis-28401	195	9	the	the	DET
bracis-28401	195	10	validation	validation	NOUN
bracis-28401	195	11	part	part	NOUN
bracis-28401	195	12	of	of	ADP
bracis-28401	195	13	merged	merged	ADJ
bracis-28401	195	14	datasetfull	datasetfull	ADJ
bracis-28401	195	15	size	size	NOUN
bracis-28401	195	16	table	table	NOUN
bracis-28401	195	17	fig	fig	NOUN
bracis-28401	195	18	.	.	PUNCT
bracis-28401	196	1	4	4	X
bracis-28401	196	2	.	.	NOUN
bracis-28401	196	3	frequency	frequency	NOUN
bracis-28401	196	4	density	density	NOUN
bracis-28401	196	5	functions	function	NOUN
bracis-28401	196	6	for	for	ADP
bracis-28401	196	7	the	the	DET
bracis-28401	196	8	num_vari	num_vari	X
bracis-28401	196	9	(	(	PUNCT
bracis-28401	196	10	a	a	NOUN
bracis-28401	196	11	)	)	PUNCT
bracis-28401	196	12	and	and	CCONJ
bracis-28401	196	13	num_state	num_state	ADJ
bracis-28401	196	14	(	(	PUNCT
bracis-28401	196	15	b	b	NOUN
bracis-28401	196	16	)	)	PUNCT
bracis-28401	196	17	features	feature	NOUN
bracis-28401	196	18	in	in	ADP
bracis-28401	196	19	the	the	DET
bracis-28401	196	20	merged	merge	VERB
bracis-28401	196	21	dataset	dataset	NOUN
bracis-28401	196	22	for	for	ADP
bracis-28401	196	23	the	the	DET
bracis-28401	196	24	misclassifications	misclassification	NOUN
bracis-28401	196	25	in	in	ADP
bracis-28401	196	26	the	the	DET
bracis-28401	196	27	linear	linear	ADJ
bracis-28401	196	28	class	class	NOUN
bracis-28401	196	29	full	full	ADJ
bracis-28401	196	30	size	size	NOUN
bracis-28401	196	31	image	image	NOUN
bracis-28401	196	32	the	the	DET
bracis-28401	196	33	density	density	NOUN
bracis-28401	196	34	functions	function	NOUN
bracis-28401	196	35	depicted	depict	VERB
bracis-28401	196	36	in	in	ADP
bracis-28401	196	37	fig	fig	NOUN
bracis-28401	196	38	.	.	PUNCT
bracis-28401	196	39	 	 	SPACE
bracis-28401	197	1	4	4	NUM
bracis-28401	197	2	show	show	VERB
bracis-28401	197	3	that	that	SCONJ
bracis-28401	197	4	misclassifications	misclassification	NOUN
bracis-28401	197	5	mainly	mainly	ADV
bracis-28401	197	6	occurred	occur	VERB
bracis-28401	197	7	because	because	SCONJ
bracis-28401	197	8	the	the	DET
bracis-28401	197	9	number	number	NOUN
bracis-28401	197	10	of	of	ADP
bracis-28401	197	11	variables	variable	NOUN
bracis-28401	197	12	and	and	CCONJ
bracis-28401	197	13	states	state	NOUN
bracis-28401	197	14	in	in	ADP
bracis-28401	197	15	codes	code	NOUN
bracis-28401	197	16	from	from	ADP
bracis-28401	197	17	the	the	DET
bracis-28401	197	18	mispointed	mispointe	VERB
bracis-28401	197	19	classes	class	NOUN
bracis-28401	197	20	have	have	VERB
bracis-28401	197	21	similar	similar	ADJ
bracis-28401	197	22	behavior	behavior	NOUN
bracis-28401	197	23	,	,	PUNCT
bracis-28401	197	24	hindering	hinder	VERB
bracis-28401	197	25	distinguishing	distinguish	VERB
bracis-28401	197	26	them	they	PRON
bracis-28401	197	27	.	.	PUNCT
bracis-28401	198	1	one	one	PRON
bracis-28401	198	2	can	can	AUX
bracis-28401	198	3	argue	argue	VERB
bracis-28401	198	4	that	that	SCONJ
bracis-28401	198	5	we	we	PRON
bracis-28401	198	6	could	could	AUX
bracis-28401	198	7	remove	remove	VERB
bracis-28401	198	8	this	this	DET
bracis-28401	198	9	attribute	attribute	NOUN
bracis-28401	198	10	from	from	ADP
bracis-28401	198	11	the	the	DET
bracis-28401	198	12	models	model	NOUN
bracis-28401	198	13	;	;	PUNCT
bracis-28401	198	14	however	however	ADV
bracis-28401	198	15	,	,	PUNCT
bracis-28401	198	16	even	even	ADV
bracis-28401	198	17	though	though	SCONJ
bracis-28401	198	18	these	these	DET
bracis-28401	198	19	features	feature	NOUN
bracis-28401	198	20	cause	cause	VERB
bracis-28401	198	21	misclassifications	misclassification	NOUN
bracis-28401	198	22	in	in	ADP
bracis-28401	198	23	the	the	DET
bracis-28401	198	24	linear	linear	ADJ
bracis-28401	198	25	class	class	NOUN
bracis-28401	198	26	,	,	PUNCT
bracis-28401	198	27	they	they	PRON
bracis-28401	198	28	are	be	AUX
bracis-28401	198	29	relevant	relevant	ADJ
bracis-28401	198	30	to	to	ADP
bracis-28401	198	31	the	the	DET
bracis-28401	198	32	overall	overall	ADJ
bracis-28401	198	33	model	model	NOUN
bracis-28401	198	34	classification	classification	NOUN
bracis-28401	198	35	.	.	PUNCT
bracis-28401	199	1	5	5	NUM
bracis-28401	199	2	discussion	discussion	NOUN
bracis-28401	199	3	besides	besides	SCONJ
bracis-28401	199	4	this	this	DET
bracis-28401	199	5	paper	paper	NOUN
bracis-28401	199	6	showing	show	VERB
bracis-28401	199	7	promising	promise	VERB
bracis-28401	199	8	results	result	NOUN
bracis-28401	199	9	in	in	ADP
bracis-28401	199	10	estimating	estimate	VERB
bracis-28401	199	11	the	the	DET
bracis-28401	199	12	code	code	NOUN
bracis-28401	199	13	runtime	runtime	NOUN
bracis-28401	199	14	complexity	complexity	NOUN
bracis-28401	199	15	,	,	PUNCT
bracis-28401	199	16	outperforming	outperform	VERB
bracis-28401	199	17	the	the	DET
bracis-28401	199	18	state	state	NOUN
bracis-28401	199	19	-	-	PUNCT
bracis-28401	199	20	of	of	ADP
bracis-28401	199	21	-	-	PUNCT
bracis-28401	199	22	the	the	DET
bracis-28401	199	23	-	-	PUNCT
bracis-28401	199	24	art	art	NOUN
bracis-28401	199	25	,	,	PUNCT
bracis-28401	199	26	we	we	PRON
bracis-28401	199	27	point	point	VERB
bracis-28401	199	28	out	out	ADP
bracis-28401	199	29	the	the	DET
bracis-28401	199	30	following	follow	VERB
bracis-28401	199	31	limitations	limitation	NOUN
bracis-28401	199	32	that	that	PRON
bracis-28401	199	33	will	will	AUX
bracis-28401	199	34	be	be	AUX
bracis-28401	199	35	addressed	address	VERB
bracis-28401	199	36	in	in	ADP
bracis-28401	199	37	future	future	ADJ
bracis-28401	199	38	research	research	NOUN
bracis-28401	199	39	:	:	PUNCT
bracis-28401	199	40	the	the	DET
bracis-28401	199	41	web	web	NOUN
bracis-28401	199	42	crawler	crawler	NOUN
bracis-28401	199	43	may	may	AUX
bracis-28401	199	44	not	not	PART
bracis-28401	199	45	collect	collect	VERB
bracis-28401	199	46	the	the	DET
bracis-28401	199	47	correct	correct	ADJ
bracis-28401	199	48	complexity	complexity	NOUN
bracis-28401	199	49	of	of	ADP
bracis-28401	199	50	each	each	DET
bracis-28401	199	51	code	code	NOUN
bracis-28401	199	52	.	.	PUNCT
bracis-28401	200	1	the	the	DET
bracis-28401	200	2	dataset	dataset	NOUN
bracis-28401	200	3	used	use	VERB
bracis-28401	200	4	for	for	ADP
bracis-28401	200	5	training	training	NOUN
bracis-28401	200	6	and	and	CCONJ
bracis-28401	200	7	estimations	estimation	NOUN
bracis-28401	200	8	resulted	result	VERB
bracis-28401	200	9	from	from	ADP
bracis-28401	200	10	a	a	DET
bracis-28401	200	11	web	web	NOUN
bracis-28401	200	12	scrapping	scrap	VERB
bracis-28401	200	13	process	process	NOUN
bracis-28401	200	14	.	.	PUNCT
bracis-28401	201	1	the	the	DET
bracis-28401	201	2	collection	collection	NOUN
bracis-28401	201	3	process	process	NOUN
bracis-28401	201	4	may	may	AUX
bracis-28401	201	5	imply	imply	VERB
bracis-28401	201	6	biased	biased	ADJ
bracis-28401	201	7	information	information	NOUN
bracis-28401	201	8	,	,	PUNCT
bracis-28401	201	9	as	as	SCONJ
bracis-28401	201	10	the	the	DET
bracis-28401	201	11	crawler	crawler	NOUN
bracis-28401	201	12	ran	run	VERB
bracis-28401	201	13	automatically	automatically	ADV
bracis-28401	201	14	.	.	PUNCT
bracis-28401	202	1	however	however	ADV
bracis-28401	202	2	,	,	PUNCT
bracis-28401	202	3	given	give	VERB
bracis-28401	202	4	the	the	DET
bracis-28401	202	5	lack	lack	NOUN
bracis-28401	202	6	of	of	ADP
bracis-28401	202	7	datasets	dataset	NOUN
bracis-28401	202	8	containing	contain	VERB
bracis-28401	202	9	inefficient	inefficient	ADJ
bracis-28401	202	10	codes	code	NOUN
bracis-28401	202	11	,	,	PUNCT
bracis-28401	202	12	we	we	PRON
bracis-28401	202	13	understand	understand	VERB
bracis-28401	202	14	that	that	SCONJ
bracis-28401	202	15	the	the	DET
bracis-28401	202	16	potential	potential	ADJ
bracis-28401	202	17	bias	bias	NOUN
bracis-28401	202	18	does	do	AUX
bracis-28401	202	19	not	not	PART
bracis-28401	202	20	influence	influence	VERB
bracis-28401	202	21	the	the	DET
bracis-28401	202	22	comparison	comparison	NOUN
bracis-28401	202	23	results	result	NOUN
bracis-28401	202	24	,	,	PUNCT
bracis-28401	202	25	which	which	PRON
bracis-28401	202	26	shows	show	VERB
bracis-28401	202	27	that	that	SCONJ
bracis-28401	202	28	random	random	ADJ
bracis-28401	202	29	forest	forest	NOUN
bracis-28401	202	30	achieved	achieve	VERB
bracis-28401	202	31	the	the	DET
bracis-28401	202	32	best	good	ADJ
bracis-28401	202	33	results	result	NOUN
bracis-28401	202	34	.	.	PUNCT
bracis-28401	203	1	we	we	PRON
bracis-28401	203	2	will	will	AUX
bracis-28401	203	3	provide	provide	VERB
bracis-28401	203	4	an	an	DET
bracis-28401	203	5	in	in	ADP
bracis-28401	203	6	-	-	PUNCT
bracis-28401	203	7	depth	depth	NOUN
bracis-28401	203	8	analysis	analysis	NOUN
bracis-28401	203	9	of	of	ADP
bracis-28401	203	10	the	the	DET
bracis-28401	203	11	collected	collect	VERB
bracis-28401	203	12	data	datum	NOUN
bracis-28401	203	13	in	in	ADP
bracis-28401	203	14	future	future	ADJ
bracis-28401	203	15	works	work	NOUN
bracis-28401	203	16	,	,	PUNCT
bracis-28401	203	17	including	include	VERB
bracis-28401	203	18	a	a	DET
bracis-28401	203	19	manual	manual	ADJ
bracis-28401	203	20	verification	verification	NOUN
bracis-28401	203	21	.	.	PUNCT
bracis-28401	204	1	trustworthiness	trustworthiness	NOUN
bracis-28401	204	2	of	of	ADP
bracis-28401	204	3	geeksforgeeks.org	geeksforgeeks.org	PROPN
bracis-28401	204	4	.	.	PUNCT
bracis-28401	205	1	one	one	PRON
bracis-28401	205	2	can	can	AUX
bracis-28401	205	3	argue	argue	VERB
bracis-28401	205	4	that	that	SCONJ
bracis-28401	205	5	the	the	DET
bracis-28401	205	6	information	information	NOUN
bracis-28401	205	7	provided	provide	VERB
bracis-28401	205	8	by	by	ADP
bracis-28401	205	9	geeksforgeeks.org	geeksforgeeks.org	PROPN
bracis-28401	205	10	may	may	AUX
bracis-28401	205	11	not	not	PART
bracis-28401	205	12	be	be	AUX
bracis-28401	205	13	trustworthy	trustworthy	ADJ
bracis-28401	205	14	.	.	PUNCT
bracis-28401	206	1	however	however	ADV
bracis-28401	206	2	,	,	PUNCT
bracis-28401	206	3	considering	consider	VERB
bracis-28401	206	4	the	the	DET
bracis-28401	206	5	lack	lack	NOUN
bracis-28401	206	6	of	of	ADP
bracis-28401	206	7	publicly	publicly	ADV
bracis-28401	206	8	available	available	ADJ
bracis-28401	206	9	datasets	dataset	NOUN
bracis-28401	206	10	containing	contain	VERB
bracis-28401	206	11	inefficient	inefficient	ADJ
bracis-28401	206	12	codes	code	NOUN
bracis-28401	206	13	and	and	CCONJ
bracis-28401	206	14	their	their	PRON
bracis-28401	206	15	respective	respective	ADJ
bracis-28401	206	16	complexity	complexity	NOUN
bracis-28401	206	17	classes	class	NOUN
bracis-28401	206	18	,	,	PUNCT
bracis-28401	206	19	we	we	PRON
bracis-28401	206	20	understand	understand	VERB
bracis-28401	206	21	that	that	SCONJ
bracis-28401	206	22	the	the	DET
bracis-28401	206	23	provided	provide	VERB
bracis-28401	206	24	information	information	NOUN
bracis-28401	206	25	is	be	AUX
bracis-28401	206	26	the	the	DET
bracis-28401	206	27	best	good	ADJ
bracis-28401	206	28	effort	effort	NOUN
bracis-28401	206	29	to	to	PART
bracis-28401	206	30	have	have	AUX
bracis-28401	206	31	a	a	DET
bracis-28401	206	32	comprehensive	comprehensive	ADJ
bracis-28401	206	33	dataset	dataset	NOUN
bracis-28401	206	34	containing	contain	VERB
bracis-28401	206	35	the	the	DET
bracis-28401	206	36	most	most	ADV
bracis-28401	206	37	relevant	relevant	ADJ
bracis-28401	206	38	complexity	complexity	NOUN
bracis-28401	206	39	classes	class	NOUN
bracis-28401	206	40	.	.	PUNCT
bracis-28401	207	1	small	small	ADJ
bracis-28401	207	2	dataset	dataset	NOUN
bracis-28401	207	3	for	for	ADP
bracis-28401	207	4	machine	machine	NOUN
bracis-28401	207	5	learning	learning	NOUN
bracis-28401	207	6	purposes	purpose	NOUN
bracis-28401	207	7	.	.	PUNCT
bracis-28401	208	1	the	the	DET
bracis-28401	208	2	merged	merge	VERB
bracis-28401	208	3	dataset	dataset	NOUN
bracis-28401	208	4	used	use	VERB
bracis-28401	208	5	for	for	ADP
bracis-28401	208	6	training	train	VERB
bracis-28401	208	7	the	the	DET
bracis-28401	208	8	machine	machine	NOUN
bracis-28401	208	9	learning	learning	NOUN
bracis-28401	208	10	models	model	NOUN
bracis-28401	208	11	contains	contain	VERB
bracis-28401	208	12	1325	1325	NUM
bracis-28401	208	13	entries	entry	NOUN
bracis-28401	208	14	,	,	PUNCT
bracis-28401	208	15	which	which	PRON
bracis-28401	208	16	is	be	AUX
bracis-28401	208	17	small	small	ADJ
bracis-28401	208	18	compared	compare	VERB
bracis-28401	208	19	to	to	ADP
bracis-28401	208	20	today	today	NOUN
bracis-28401	208	21	’s	’s	PART
bracis-28401	208	22	standards	standard	NOUN
bracis-28401	208	23	.	.	PUNCT
bracis-28401	209	1	however	however	ADV
bracis-28401	209	2	,	,	PUNCT
bracis-28401	209	3	considering	consider	VERB
bracis-28401	209	4	the	the	DET
bracis-28401	209	5	lack	lack	NOUN
bracis-28401	209	6	of	of	ADP
bracis-28401	209	7	comprehensive	comprehensive	ADJ
bracis-28401	209	8	datasets	dataset	NOUN
bracis-28401	209	9	and	and	CCONJ
bracis-28401	209	10	the	the	DET
bracis-28401	209	11	absence	absence	NOUN
bracis-28401	209	12	of	of	ADP
bracis-28401	209	13	tags	tag	NOUN
bracis-28401	209	14	to	to	PART
bracis-28401	209	15	classify	classify	VERB
bracis-28401	209	16	the	the	DET
bracis-28401	209	17	codes	code	NOUN
bracis-28401	209	18	published	publish	VERB
bracis-28401	209	19	in	in	ADP
bracis-28401	209	20	the	the	DET
bracis-28401	209	21	codenet	codenet	ADJ
bracis-28401	209	22	dataset	dataset	NOUN
bracis-28401	209	23	,	,	PUNCT
bracis-28401	209	24	we	we	PRON
bracis-28401	209	25	consider	consider	VERB
bracis-28401	209	26	our	our	PRON
bracis-28401	209	27	results	result	NOUN
bracis-28401	209	28	as	as	ADP
bracis-28401	209	29	a	a	DET
bracis-28401	209	30	relevant	relevant	ADJ
bracis-28401	209	31	step	step	NOUN
bracis-28401	209	32	towards	towards	ADP
bracis-28401	209	33	the	the	DET
bracis-28401	209	34	use	use	NOUN
bracis-28401	209	35	of	of	ADP
bracis-28401	209	36	ai	ai	VERB
bracis-28401	209	37	to	to	PART
bracis-28401	209	38	predict	predict	VERB
bracis-28401	209	39	code	code	NOUN
bracis-28401	209	40	complexity	complexity	NOUN
bracis-28401	209	41	.	.	PUNCT
bracis-28401	210	1	the	the	DET
bracis-28401	210	2	dataset	dataset	NOUN
bracis-28401	210	3	balancing	balancing	NOUN
bracis-28401	210	4	process	process	NOUN
bracis-28401	210	5	may	may	AUX
bracis-28401	210	6	cause	cause	VERB
bracis-28401	210	7	overfitting	overfitte	VERB
bracis-28401	210	8	.	.	PUNCT
bracis-28401	211	1	santos	santos	PROPN
bracis-28401	211	2	et	et	PROPN
bracis-28401	211	3	al	al	PROPN
bracis-28401	211	4	.	.	PUNCT
bracis-28401	212	1	[	[	X
bracis-28401	212	2	15	15	NUM
bracis-28401	212	3	]	]	PUNCT
bracis-28401	212	4	discuss	discuss	VERB
bracis-28401	212	5	the	the	DET
bracis-28401	212	6	impacts	impact	NOUN
bracis-28401	212	7	of	of	ADP
bracis-28401	212	8	balancing	balance	VERB
bracis-28401	212	9	datasets	dataset	NOUN
bracis-28401	212	10	before	before	ADP
bracis-28401	212	11	running	run	VERB
bracis-28401	212	12	the	the	DET
bracis-28401	212	13	cross	cross	ADJ
bracis-28401	212	14	-	-	ADJ
bracis-28401	212	15	validation	validation	ADJ
bracis-28401	212	16	process	process	NOUN
bracis-28401	212	17	;	;	PUNCT
bracis-28401	212	18	they	they	PRON
bracis-28401	212	19	demonstrate	demonstrate	VERB
bracis-28401	212	20	that	that	SCONJ
bracis-28401	212	21	oversampling	oversample	VERB
bracis-28401	212	22	techniques	technique	NOUN
bracis-28401	212	23	may	may	AUX
bracis-28401	212	24	generate	generate	VERB
bracis-28401	212	25	replicated	replicated	ADJ
bracis-28401	212	26	entries	entry	NOUN
bracis-28401	212	27	in	in	ADP
bracis-28401	212	28	test	test	NOUN
bracis-28401	212	29	and	and	CCONJ
bracis-28401	212	30	training	training	NOUN
bracis-28401	212	31	sets	set	NOUN
bracis-28401	212	32	,	,	PUNCT
bracis-28401	212	33	which	which	PRON
bracis-28401	212	34	implies	imply	VERB
bracis-28401	212	35	in	in	ADP
bracis-28401	212	36	lack	lack	NOUN
bracis-28401	212	37	of	of	ADP
bracis-28401	212	38	generalization	generalization	NOUN
bracis-28401	212	39	of	of	ADP
bracis-28401	212	40	ml	ml	NOUN
bracis-28401	212	41	models	model	NOUN
bracis-28401	212	42	caused	cause	VERB
bracis-28401	212	43	by	by	ADP
bracis-28401	212	44	overfitting	overfitte	VERB
bracis-28401	212	45	.	.	PUNCT
bracis-28401	213	1	however	however	ADV
bracis-28401	213	2	,	,	PUNCT
bracis-28401	213	3	the	the	DET
bracis-28401	213	4	smote	smote	ADJ
bracis-28401	213	5	method	method	NOUN
bracis-28401	213	6	generates	generate	VERB
bracis-28401	213	7	synthetic	synthetic	ADJ
bracis-28401	213	8	entries	entry	NOUN
bracis-28401	213	9	based	base	VERB
bracis-28401	213	10	on	on	ADP
bracis-28401	213	11	a	a	DET
bracis-28401	213	12	proximity	proximity	NOUN
bracis-28401	213	13	function	function	NOUN
bracis-28401	213	14	,	,	PUNCT
bracis-28401	213	15	without	without	ADP
bracis-28401	213	16	duplicating	duplicate	VERB
bracis-28401	213	17	any	any	DET
bracis-28401	213	18	entry	entry	NOUN
bracis-28401	213	19	.	.	PUNCT
bracis-28401	214	1	thus	thus	ADV
bracis-28401	214	2	,	,	PUNCT
bracis-28401	214	3	we	we	PRON
bracis-28401	214	4	argue	argue	VERB
bracis-28401	214	5	that	that	SCONJ
bracis-28401	214	6	the	the	DET
bracis-28401	214	7	lack	lack	NOUN
bracis-28401	214	8	of	of	ADP
bracis-28401	214	9	duplication	duplication	NOUN
bracis-28401	214	10	reduces	reduce	VERB
bracis-28401	214	11	the	the	DET
bracis-28401	214	12	overfitting	overfitte	VERB
bracis-28401	214	13	issues	issue	NOUN
bracis-28401	214	14	.	.	PUNCT
bracis-28401	215	1	6	6	NUM
bracis-28401	215	2	concluding	conclude	VERB
bracis-28401	215	3	remarks	remark	NOUN
bracis-28401	215	4	in	in	ADP
bracis-28401	215	5	this	this	DET
bracis-28401	215	6	paper	paper	NOUN
bracis-28401	215	7	,	,	PUNCT
bracis-28401	215	8	we	we	PRON
bracis-28401	215	9	investigated	investigate	VERB
bracis-28401	215	10	the	the	DET
bracis-28401	215	11	use	use	NOUN
bracis-28401	215	12	of	of	ADP
bracis-28401	215	13	machine	machine	NOUN
bracis-28401	215	14	learning	learning	NOUN
bracis-28401	215	15	models	model	NOUN
bracis-28401	215	16	to	to	PART
bracis-28401	215	17	predict	predict	VERB
bracis-28401	215	18	the	the	DET
bracis-28401	215	19	runtime	runtime	NOUN
bracis-28401	215	20	complexity	complexity	NOUN
bracis-28401	215	21	class	class	NOUN
bracis-28401	215	22	of	of	ADP
bracis-28401	215	23	computer	computer	NOUN
bracis-28401	215	24	program	program	NOUN
bracis-28401	215	25	codes	code	NOUN
bracis-28401	215	26	.	.	PUNCT
bracis-28401	216	1	considering	consider	VERB
bracis-28401	216	2	that	that	SCONJ
bracis-28401	216	3	the	the	DET
bracis-28401	216	4	reference	reference	NOUN
bracis-28401	216	5	dataset	dataset	NOUN
bracis-28401	216	6	published	publish	VERB
bracis-28401	216	7	by	by	ADP
bracis-28401	216	8	sikka	sikka	PROPN
bracis-28401	216	9	et	et	PROPN
bracis-28401	216	10	al	al	PROPN
bracis-28401	216	11	.	.	PUNCT
bracis-28401	217	1	[	[	X
bracis-28401	217	2	18	18	NUM
bracis-28401	217	3	]	]	PUNCT
bracis-28401	217	4	does	do	AUX
bracis-28401	217	5	not	not	PART
bracis-28401	217	6	contain	contain	VERB
bracis-28401	217	7	most	most	ADJ
bracis-28401	217	8	of	of	ADP
bracis-28401	217	9	the	the	DET
bracis-28401	217	10	inefficient	inefficient	ADJ
bracis-28401	217	11	classes	class	NOUN
bracis-28401	217	12	from	from	ADP
bracis-28401	217	13	the	the	DET
bracis-28401	217	14	literature	literature	NOUN
bracis-28401	217	15	,	,	PUNCT
bracis-28401	217	16	we	we	PRON
bracis-28401	217	17	build	build	VERB
bracis-28401	217	18	a	a	DET
bracis-28401	217	19	second	second	ADJ
bracis-28401	217	20	one	one	NUM
bracis-28401	217	21	with	with	ADP
bracis-28401	217	22	data	datum	NOUN
bracis-28401	217	23	from	from	ADP
bracis-28401	217	24	a	a	DET
bracis-28401	217	25	publicly	publicly	ADV
bracis-28401	217	26	available	available	ADJ
bracis-28401	217	27	website	website	NOUN
bracis-28401	217	28	.	.	PUNCT
bracis-28401	218	1	next	next	ADV
bracis-28401	218	2	,	,	PUNCT
bracis-28401	218	3	we	we	PRON
bracis-28401	218	4	compare	compare	VERB
bracis-28401	218	5	machine	machine	NOUN
bracis-28401	218	6	learning	learning	NOUN
bracis-28401	218	7	models	model	NOUN
bracis-28401	218	8	to	to	PART
bracis-28401	218	9	predict	predict	VERB
bracis-28401	218	10	program	program	NOUN
bracis-28401	218	11	codes	code	NOUN
bracis-28401	218	12	’	'	PUNCT
bracis-28401	218	13	efficiency	efficiency	NOUN
bracis-28401	218	14	and	and	CCONJ
bracis-28401	218	15	complexity	complexity	NOUN
bracis-28401	218	16	classes	class	NOUN
bracis-28401	218	17	.	.	PUNCT
bracis-28401	219	1	results	result	NOUN
bracis-28401	219	2	show	show	VERB
bracis-28401	219	3	the	the	DET
bracis-28401	219	4	random	random	ADJ
bracis-28401	219	5	forest	forest	NOUN
bracis-28401	219	6	as	as	ADP
bracis-28401	219	7	the	the	DET
bracis-28401	219	8	best	good	ADJ
bracis-28401	219	9	approach	approach	NOUN
bracis-28401	219	10	,	,	PUNCT
bracis-28401	219	11	predicting	predict	VERB
bracis-28401	219	12	code	code	NOUN
bracis-28401	219	13	efficiency	efficiency	NOUN
bracis-28401	219	14	with	with	ADP
bracis-28401	219	15	an	an	DET
bracis-28401	219	16	accuracy	accuracy	NOUN
bracis-28401	219	17	of	of	ADP
bracis-28401	219	18	up	up	ADP
bracis-28401	219	19	to	to	PART
bracis-28401	219	20	80	80	NUM
bracis-28401	219	21	%	%	NOUN
bracis-28401	219	22	and	and	CCONJ
bracis-28401	219	23	can	can	AUX
bracis-28401	219	24	classify	classify	VERB
bracis-28401	219	25	the	the	DET
bracis-28401	219	26	runtime	runtime	NOUN
bracis-28401	219	27	complexity	complexity	NOUN
bracis-28401	219	28	with	with	ADP
bracis-28401	219	29	an	an	DET
bracis-28401	219	30	accuracy	accuracy	NOUN
bracis-28401	219	31	superior	superior	ADJ
bracis-28401	219	32	to	to	ADP
bracis-28401	219	33	81	81	NUM
bracis-28401	219	34	%	%	NOUN
bracis-28401	219	35	for	for	ADP
bracis-28401	219	36	a	a	DET
bracis-28401	219	37	model	model	NOUN
bracis-28401	219	38	trained	train	VERB
bracis-28401	219	39	with	with	ADP
bracis-28401	219	40	data	datum	NOUN
bracis-28401	219	41	from	from	ADP
bracis-28401	219	42	a	a	DET
bracis-28401	219	43	merged	merge	VERB
bracis-28401	219	44	dataset	dataset	NOUN
bracis-28401	219	45	and	and	CCONJ
bracis-28401	219	46	87.4	87.4	NUM
bracis-28401	219	47	%	%	NOUN
bracis-28401	219	48	when	when	SCONJ
bracis-28401	219	49	the	the	DET
bracis-28401	219	50	model	model	NOUN
bracis-28401	219	51	is	be	AUX
bracis-28401	219	52	trained	train	VERB
bracis-28401	219	53	with	with	ADP
bracis-28401	219	54	the	the	DET
bracis-28401	219	55	reference	reference	NOUN
bracis-28401	219	56	dataset	dataset	VERB
bracis-28401	219	57	.	.	PUNCT
bracis-28401	220	1	such	such	DET
bracis-28401	220	2	a	a	DET
bracis-28401	220	3	result	result	NOUN
bracis-28401	220	4	outperforms	outperform	VERB
bracis-28401	220	5	the	the	DET
bracis-28401	220	6	ones	one	NOUN
bracis-28401	220	7	found	find	VERB
bracis-28401	220	8	by	by	ADP
bracis-28401	220	9	sikka	sikka	PROPN
bracis-28401	220	10	et	et	PROPN
bracis-28401	220	11	al	al	PROPN
bracis-28401	220	12	.	.	PUNCT
bracis-28401	221	1	[	[	X
bracis-28401	221	2	18	18	NUM
bracis-28401	221	3	]	]	PUNCT
bracis-28401	221	4	,	,	PUNCT
bracis-28401	221	5	which	which	PRON
bracis-28401	221	6	found	find	VERB
bracis-28401	221	7	an	an	DET
bracis-28401	221	8	accuracy	accuracy	NOUN
bracis-28401	221	9	of	of	ADP
bracis-28401	221	10	71.4	71.4	NUM
bracis-28401	221	11	%	%	NOUN
bracis-28401	221	12	using	use	VERB
bracis-28401	221	13	a	a	DET
bracis-28401	221	14	random	random	ADJ
bracis-28401	221	15	forest	forest	NOUN
bracis-28401	221	16	model	model	NOUN
bracis-28401	221	17	.	.	PUNCT
bracis-28401	222	1	we	we	PRON
bracis-28401	222	2	argue	argue	VERB
bracis-28401	222	3	that	that	SCONJ
bracis-28401	222	4	the	the	DET
bracis-28401	222	5	feature	feature	NOUN
bracis-28401	222	6	selection	selection	NOUN
bracis-28401	222	7	process	process	NOUN
bracis-28401	222	8	and	and	CCONJ
bracis-28401	222	9	balanced	balanced	ADJ
bracis-28401	222	10	datasets	dataset	NOUN
bracis-28401	222	11	supported	support	VERB
bracis-28401	222	12	the	the	DET
bracis-28401	222	13	accuracy	accuracy	NOUN
bracis-28401	222	14	enhancement	enhancement	NOUN
bracis-28401	222	15	.	.	PUNCT
bracis-28401	223	1	however	however	ADV
bracis-28401	223	2	,	,	PUNCT
bracis-28401	223	3	the	the	DET
bracis-28401	223	4	random	random	ADJ
bracis-28401	223	5	forest	forest	NOUN
bracis-28401	223	6	model	model	NOUN
bracis-28401	223	7	’s	’s	PART
bracis-28401	223	8	accuracy	accuracy	NOUN
bracis-28401	223	9	drops	drop	VERB
bracis-28401	223	10	to	to	ADP
bracis-28401	223	11	less	less	ADJ
bracis-28401	223	12	than	than	ADP
bracis-28401	223	13	50	50	NUM
bracis-28401	223	14	%	%	NOUN
bracis-28401	223	15	when	when	SCONJ
bracis-28401	223	16	we	we	PRON
bracis-28401	223	17	train	train	VERB
bracis-28401	223	18	it	it	PRON
bracis-28401	223	19	with	with	ADP
bracis-28401	223	20	the	the	DET
bracis-28401	223	21	crawled	crawl	VERB
bracis-28401	223	22	dataset	dataset	NOUN
bracis-28401	223	23	and	and	CCONJ
bracis-28401	223	24	try	try	VERB
bracis-28401	223	25	to	to	PART
bracis-28401	223	26	predict	predict	VERB
bracis-28401	223	27	the	the	DET
bracis-28401	223	28	complexity	complexity	NOUN
bracis-28401	223	29	classes	class	NOUN
bracis-28401	223	30	in	in	ADP
bracis-28401	223	31	the	the	DET
bracis-28401	223	32	reference	reference	NOUN
bracis-28401	223	33	dataset	dataset	NOUN
bracis-28401	223	34	.	.	PUNCT
bracis-28401	224	1	we	we	PRON
bracis-28401	224	2	claim	claim	VERB
bracis-28401	224	3	that	that	SCONJ
bracis-28401	224	4	this	this	PRON
bracis-28401	224	5	occurred	occur	VERB
bracis-28401	224	6	for	for	ADP
bracis-28401	224	7	two	two	NUM
bracis-28401	224	8	primary	primary	ADJ
bracis-28401	224	9	reasons	reason	NOUN
bracis-28401	224	10	:	:	PUNCT
bracis-28401	224	11	first	first	ADV
bracis-28401	224	12	,	,	PUNCT
bracis-28401	224	13	we	we	PRON
bracis-28401	224	14	trained	train	VERB
bracis-28401	224	15	the	the	DET
bracis-28401	224	16	model	model	NOUN
bracis-28401	224	17	in	in	ADP
bracis-28401	224	18	a	a	DET
bracis-28401	224	19	dataset	dataset	NOUN
bracis-28401	224	20	that	that	PRON
bracis-28401	224	21	has	have	VERB
bracis-28401	224	22	more	more	ADJ
bracis-28401	224	23	classes	class	NOUN
bracis-28401	224	24	than	than	SCONJ
bracis-28401	224	25	the	the	DET
bracis-28401	224	26	reference	reference	NOUN
bracis-28401	224	27	dataset	dataset	NOUN
bracis-28401	224	28	;	;	PUNCT
bracis-28401	224	29	two	two	NUM
bracis-28401	224	30	,	,	PUNCT
bracis-28401	224	31	most	most	ADJ
bracis-28401	224	32	of	of	ADP
bracis-28401	224	33	the	the	DET
bracis-28401	224	34	classification	classification	NOUN
bracis-28401	224	35	errors	error	NOUN
bracis-28401	224	36	occurred	occur	VERB
bracis-28401	224	37	in	in	ADP
bracis-28401	224	38	the	the	DET
bracis-28401	224	39	logarithmic	logarithmic	ADJ
bracis-28401	224	40	and	and	CCONJ
bracis-28401	224	41	linearithmic	linearithmic	ADJ
bracis-28401	224	42	categories	category	NOUN
bracis-28401	224	43	,	,	PUNCT
bracis-28401	224	44	which	which	PRON
bracis-28401	224	45	we	we	PRON
bracis-28401	224	46	demonstrated	demonstrate	VERB
bracis-28401	224	47	to	to	PART
bracis-28401	224	48	have	have	VERB
bracis-28401	224	49	a	a	DET
bracis-28401	224	50	similar	similar	ADJ
bracis-28401	224	51	behavior	behavior	NOUN
bracis-28401	224	52	regarding	regard	VERB
bracis-28401	224	53	the	the	DET
bracis-28401	224	54	top-3	top-3	NUM
bracis-28401	224	55	most	most	ADV
bracis-28401	224	56	important	important	ADJ
bracis-28401	224	57	features	feature	NOUN
bracis-28401	224	58	.	.	PUNCT
bracis-28401	225	1	in	in	ADP
bracis-28401	225	2	future	future	ADJ
bracis-28401	225	3	work	work	NOUN
bracis-28401	225	4	,	,	PUNCT
bracis-28401	225	5	we	we	PRON
bracis-28401	225	6	aim	aim	VERB
bracis-28401	225	7	to	to	PART
bracis-28401	225	8	develop	develop	VERB
bracis-28401	225	9	a	a	DET
bracis-28401	225	10	complete	complete	ADJ
bracis-28401	225	11	complexity	complexity	NOUN
bracis-28401	225	12	prediction	prediction	NOUN
bracis-28401	225	13	framework	framework	NOUN
bracis-28401	225	14	containing	contain	VERB
bracis-28401	225	15	a	a	DET
bracis-28401	225	16	learning	learn	VERB
bracis-28401	225	17	component	component	NOUN
bracis-28401	225	18	deployed	deploy	VERB
bracis-28401	225	19	on	on	ADP
bracis-28401	225	20	the	the	DET
bracis-28401	225	21	cloud	cloud	NOUN
bracis-28401	225	22	and	and	CCONJ
bracis-28401	225	23	an	an	DET
bracis-28401	225	24	extension	extension	NOUN
bracis-28401	225	25	for	for	ADP
bracis-28401	225	26	software	software	NOUN
bracis-28401	225	27	ides	ide	NOUN
bracis-28401	225	28	.	.	PUNCT
bracis-28401	226	1	research	research	NOUN
bracis-28401	226	2	challenges	challenge	NOUN
bracis-28401	226	3	related	relate	VERB
bracis-28401	226	4	to	to	ADP
bracis-28401	226	5	the	the	DET
bracis-28401	226	6	framework	framework	NOUN
bracis-28401	226	7	include	include	VERB
bracis-28401	226	8	but	but	CCONJ
bracis-28401	226	9	are	be	AUX
bracis-28401	226	10	not	not	PART
bracis-28401	226	11	limited	limit	VERB
bracis-28401	226	12	to	to	ADP
bracis-28401	226	13	:	:	PUNCT
bracis-28401	226	14	i	i	NOUN
bracis-28401	226	15	)	)	PUNCT
bracis-28401	226	16	studying	study	VERB
bracis-28401	226	17	the	the	DET
bracis-28401	226	18	applicability	applicability	NOUN
bracis-28401	226	19	of	of	ADP
bracis-28401	226	20	other	other	ADJ
bracis-28401	226	21	machine	machine	NOUN
bracis-28401	226	22	learning	learning	NOUN
bracis-28401	226	23	models	model	NOUN
bracis-28401	226	24	to	to	PART
bracis-28401	226	25	predict	predict	VERB
bracis-28401	226	26	computer	computer	NOUN
bracis-28401	226	27	programs	program	NOUN
bracis-28401	226	28	’	'	PUNCT
bracis-28401	226	29	efficiency	efficiency	NOUN
bracis-28401	226	30	and	and	CCONJ
bracis-28401	226	31	complexity	complexity	NOUN
bracis-28401	226	32	class	class	NOUN
bracis-28401	226	33	,	,	PUNCT
bracis-28401	226	34	including	include	VERB
bracis-28401	226	35	natural	natural	ADJ
bracis-28401	226	36	language	language	NOUN
bracis-28401	226	37	processing	processing	NOUN
bracis-28401	226	38	and	and	CCONJ
bracis-28401	226	39	deep	deep	ADJ
bracis-28401	226	40	learning	learning	NOUN
bracis-28401	226	41	frameworks	framework	NOUN
bracis-28401	226	42	;	;	PUNCT
bracis-28401	226	43	and	and	CCONJ
bracis-28401	226	44	ii	ii	X
bracis-28401	226	45	)	)	PUNCT
bracis-28401	226	46	building	build	VERB
bracis-28401	226	47	an	an	DET
bracis-28401	226	48	even	even	ADV
bracis-28401	226	49	more	more	ADV
bracis-28401	226	50	comprehensive	comprehensive	ADJ
bracis-28401	226	51	dataset	dataset	NOUN
bracis-28401	226	52	of	of	ADP
bracis-28401	226	53	program	program	NOUN
bracis-28401	226	54	codes	code	NOUN
bracis-28401	226	55	and	and	CCONJ
bracis-28401	226	56	complexity	complexity	NOUN
bracis-28401	226	57	classes	class	NOUN
bracis-28401	226	58	mainly	mainly	ADV
bracis-28401	226	59	in	in	ADP
bracis-28401	226	60	polynomial	polynomial	ADJ
bracis-28401	226	61	and	and	CCONJ
bracis-28401	226	62	exponential	exponential	ADJ
bracis-28401	226	63	classes	class	NOUN
bracis-28401	226	64	with	with	ADP
bracis-28401	226	65	constant	constant	ADJ
bracis-28401	226	66	update	update	NOUN
bracis-28401	226	67	.	.	PUNCT
bracis-28401	227	1	in	in	ADP
bracis-28401	227	2	addition	addition	NOUN
bracis-28401	227	3	,	,	PUNCT
bracis-28401	227	4	we	we	PRON
bracis-28401	227	5	aim	aim	VERB
bracis-28401	227	6	to	to	PART
bracis-28401	227	7	manually	manually	ADV
bracis-28401	227	8	tag	tag	VERB
bracis-28401	227	9	the	the	DET
bracis-28401	227	10	dataset	dataset	NOUN
bracis-28401	227	11	published	publish	VERB
bracis-28401	227	12	by	by	ADP
bracis-28401	227	13	the	the	DET
bracis-28401	227	14	codenet	codenet	ADJ
bracis-28401	227	15	project	project	NOUN
bracis-28401	227	16	,	,	PUNCT
bracis-28401	227	17	which	which	PRON
bracis-28401	227	18	will	will	AUX
bracis-28401	227	19	benefit	benefit	VERB
bracis-28401	227	20	future	future	ADJ
bracis-28401	227	21	research	research	NOUN
bracis-28401	227	22	and	and	CCONJ
bracis-28401	227	23	improve	improve	VERB
bracis-28401	227	24	the	the	DET
bracis-28401	227	25	accuracy	accuracy	NOUN
bracis-28401	227	26	of	of	ADP
bracis-28401	227	27	predictors	predictor	NOUN
bracis-28401	227	28	.	.	PUNCT
bracis-28401	228	1	notes	note	VERB
bracis-28401	228	2	1.https://github.com/ricardopfitscher/rutico	1.https://github.com/ricardopfitscher/rutico	NUM
bracis-28401	228	3	.	.	PUNCT
bracis-28401	229	1	2.https://www.geeksforgeeks.org/fundamentals-of-algorithms/.	2.https://www.geeksforgeeks.org/fundamentals-of-algorithms/.	NUM
bracis-28401	229	2	references	reference	NOUN
bracis-28401	229	3	bergstra	bergstra	PROPN
bracis-28401	229	4	,	,	PUNCT
bracis-28401	229	5	j.	j.	PROPN
bracis-28401	229	6	,	,	PUNCT
bracis-28401	229	7	bengio	bengio	PROPN
bracis-28401	229	8	,	,	PUNCT
bracis-28401	229	9	y.	y.	NOUN
bracis-28401	229	10	:	:	PUNCT
bracis-28401	229	11	random	random	ADJ
bracis-28401	229	12	search	search	NOUN
bracis-28401	229	13	for	for	ADP
bracis-28401	229	14	hyper	hyper	ADJ
bracis-28401	229	15	-	-	ADJ
bracis-28401	229	16	parameter	parameter	ADJ
bracis-28401	229	17	optimization	optimization	NOUN
bracis-28401	229	18	.	.	PUNCT
bracis-28401	230	1	j.	j.	PROPN
bracis-28401	230	2	mach	mach	PROPN
bracis-28401	230	3	.	.	PUNCT
bracis-28401	231	1	learn	learn	VERB
bracis-28401	231	2	.	.	PUNCT
bracis-28401	232	1	res	re	NOUN
bracis-28401	232	2	.	.	PUNCT
bracis-28401	233	1	13(2	13(2	NOUN
bracis-28401	233	2	)	)	PUNCT
bracis-28401	233	3	(	(	PUNCT
bracis-28401	233	4	2012	2012	NUM
bracis-28401	233	5	)	)	PUNCT
bracis-28401	233	6	google	google	PROPN
bracis-28401	233	7	scholar	scholar	NOUN
bracis-28401	233	8	  	  	SPACE
bracis-28401	233	9	breiman	breiman	NOUN
bracis-28401	233	10	,	,	PUNCT
bracis-28401	233	11	l.	l.	PROPN
bracis-28401	233	12	:	:	PUNCT
bracis-28401	233	13	random	random	ADJ
bracis-28401	233	14	forests	forest	NOUN
bracis-28401	233	15	.	.	PUNCT
bracis-28401	234	1	mach	mach	NOUN
bracis-28401	234	2	.	.	PUNCT
bracis-28401	235	1	learn	learn	VERB
bracis-28401	235	2	.	.	PUNCT
bracis-28401	236	1	45	45	NUM
bracis-28401	236	2	,	,	PUNCT
bracis-28401	236	3	5–32	5–32	NUM
bracis-28401	236	4	(	(	PUNCT
bracis-28401	236	5	2001	2001	NUM
bracis-28401	236	6	)	)	PUNCT
bracis-28401	236	7	article	article	NOUN
bracis-28401	236	8	  	  	SPACE
bracis-28401	236	9	google	google	PROPN
bracis-28401	236	10	scholar	scholar	NOUN
bracis-28401	236	11	  	  	SPACE
bracis-28401	236	12	chang	chang	PROPN
bracis-28401	236	13	,	,	PUNCT
bracis-28401	236	14	y.c	y.c	PROPN
bracis-28401	236	15	.	.	PROPN
bracis-28401	236	16	,	,	PUNCT
bracis-28401	236	17	chang	chang	PROPN
bracis-28401	236	18	,	,	PUNCT
bracis-28401	236	19	k.h	k.h	PROPN
bracis-28401	236	20	.	.	PROPN
bracis-28401	236	21	,	,	PUNCT
bracis-28401	236	22	wu	wu	PROPN
bracis-28401	236	23	,	,	PUNCT
bracis-28401	236	24	g.j	g.j	PROPN
bracis-28401	236	25	.	.	PROPN
bracis-28401	236	26	:	:	PUNCT
bracis-28401	236	27	application	application	NOUN
bracis-28401	236	28	of	of	ADP
bracis-28401	236	29	extreme	extreme	ADJ
bracis-28401	236	30	gradient	gradient	NOUN
bracis-28401	236	31	boosting	boost	VERB
bracis-28401	236	32	trees	tree	NOUN
bracis-28401	236	33	in	in	ADP
bracis-28401	236	34	the	the	DET
bracis-28401	236	35	construction	construction	NOUN
bracis-28401	236	36	of	of	ADP
bracis-28401	236	37	credit	credit	NOUN
bracis-28401	236	38	risk	risk	NOUN
bracis-28401	236	39	assessment	assessment	NOUN
bracis-28401	236	40	models	model	NOUN
bracis-28401	236	41	for	for	ADP
bracis-28401	236	42	financial	financial	ADJ
bracis-28401	236	43	institutions	institution	NOUN
bracis-28401	236	44	.	.	PUNCT
bracis-28401	237	1	appl	appl	PROPN
bracis-28401	237	2	.	.	PUNCT
bracis-28401	237	3	soft	soft	ADJ
bracis-28401	237	4	comput	comput	NOUN
bracis-28401	237	5	.	.	PUNCT
bracis-28401	238	1	73	73	NUM
bracis-28401	238	2	,	,	PUNCT
bracis-28401	238	3	914–920	914–920	NUM
bracis-28401	238	4	(	(	PUNCT
bracis-28401	238	5	2018	2018	NUM
bracis-28401	238	6	)	)	PUNCT
bracis-28401	238	7	article	article	NOUN
bracis-28401	238	8	  	  	SPACE
bracis-28401	238	9	google	google	PROPN
bracis-28401	238	10	scholar	scholar	NOUN
bracis-28401	238	11	  	  	SPACE
bracis-28401	238	12	chawla	chawla	PROPN
bracis-28401	238	13	,	,	PUNCT
bracis-28401	238	14	n.v	n.v	PROPN
bracis-28401	238	15	.	.	PROPN
bracis-28401	238	16	,	,	PUNCT
bracis-28401	238	17	bowyer	bowyer	PROPN
bracis-28401	238	18	,	,	PUNCT
bracis-28401	238	19	k.w	k.w	PROPN
bracis-28401	238	20	.	.	PROPN
bracis-28401	238	21	,	,	PUNCT
bracis-28401	238	22	hall	hall	PROPN
bracis-28401	238	23	,	,	PUNCT
bracis-28401	238	24	l.o	l.o	PROPN
bracis-28401	238	25	.	.	PROPN
bracis-28401	238	26	,	,	PUNCT
bracis-28401	238	27	kegelmeyer	kegelmeyer	PROPN
bracis-28401	238	28	,	,	PUNCT
bracis-28401	238	29	w.p	w.p	PROPN
bracis-28401	238	30	.	.	PROPN
bracis-28401	238	31	:	:	PUNCT
bracis-28401	239	1	smote	smote	VERB
bracis-28401	239	2	:	:	PUNCT
bracis-28401	239	3	synthetic	synthetic	ADJ
bracis-28401	239	4	minority	minority	NOUN
bracis-28401	239	5	over	over	ADP
bracis-28401	239	6	-	-	PUNCT
bracis-28401	239	7	sampling	sample	VERB
bracis-28401	239	8	technique	technique	NOUN
bracis-28401	239	9	.	.	PUNCT
bracis-28401	240	1	j.	j.	PROPN
bracis-28401	240	2	artif	artif	PROPN
bracis-28401	240	3	.	.	PUNCT
bracis-28401	241	1	intell	intell	PROPN
bracis-28401	241	2	.	.	PUNCT
bracis-28401	242	1	res	re	NOUN
bracis-28401	242	2	.	.	PROPN
bracis-28401	243	1	16	16	NUM
bracis-28401	243	2	,	,	PUNCT
bracis-28401	243	3	321–357	321–357	NUM
bracis-28401	243	4	(	(	PUNCT
bracis-28401	243	5	2002	2002	NUM
bracis-28401	243	6	)	)	PUNCT
bracis-28401	243	7	article	article	NOUN
bracis-28401	243	8	  	  	SPACE
bracis-28401	243	9	math	math	NOUN
bracis-28401	243	10	  	  	SPACE
bracis-28401	243	11	google	google	PROPN
bracis-28401	243	12	scholar	scholar	NOUN
bracis-28401	243	13	  	  	SPACE
bracis-28401	243	14	chen	chen	PROPN
bracis-28401	243	15	,	,	PUNCT
bracis-28401	243	16	t.	t.	PROPN
bracis-28401	243	17	,	,	PUNCT
bracis-28401	243	18	guestrin	guestrin	NOUN
bracis-28401	243	19	,	,	PUNCT
bracis-28401	243	20	c.	c.	PROPN
bracis-28401	243	21	:	:	PUNCT
bracis-28401	243	22	xgboost	xgboost	ADV
bracis-28401	243	23	:	:	PUNCT
bracis-28401	243	24	a	a	DET
bracis-28401	243	25	scalable	scalable	ADJ
bracis-28401	243	26	tree	tree	NOUN
bracis-28401	243	27	boosting	boost	VERB
bracis-28401	243	28	system	system	NOUN
bracis-28401	243	29	.	.	PUNCT
bracis-28401	244	1	in	in	ADP
bracis-28401	244	2	:	:	PUNCT
bracis-28401	244	3	proceedings	proceeding	NOUN
bracis-28401	244	4	of	of	ADP
bracis-28401	244	5	the	the	DET
bracis-28401	244	6	22nd	22nd	PROPN
bracis-28401	244	7	acm	acm	PROPN
bracis-28401	244	8	sigkdd	sigkdd	PROPN
bracis-28401	244	9	international	international	ADJ
bracis-28401	244	10	conference	conference	NOUN
bracis-28401	244	11	on	on	ADP
bracis-28401	244	12	knowledge	knowledge	NOUN
bracis-28401	244	13	discovery	discovery	PROPN
bracis-28401	244	14	and	and	CCONJ
bracis-28401	244	15	data	datum	NOUN
bracis-28401	244	16	mining	mining	NOUN
bracis-28401	244	17	,	,	PUNCT
bracis-28401	244	18	pp	pp	ADP
bracis-28401	244	19	.	.	PUNCT
bracis-28401	245	1	785–794	785–794	NUM
bracis-28401	245	2	(	(	PUNCT
bracis-28401	245	3	2016	2016	NUM
bracis-28401	245	4	)	)	PUNCT
bracis-28401	245	5	google	google	PROPN
bracis-28401	245	6	scholar	scholar	NOUN
bracis-28401	245	7	  	  	SPACE
bracis-28401	245	8	cormen	corman	NOUN
bracis-28401	245	9	,	,	PUNCT
bracis-28401	245	10	t.h	t.h	PROPN
bracis-28401	245	11	.	.	PROPN
bracis-28401	245	12	,	,	PUNCT
bracis-28401	245	13	leiserson	leiserson	PROPN
bracis-28401	245	14	,	,	PUNCT
bracis-28401	245	15	c.e	c.e	PROPN
bracis-28401	245	16	.	.	PROPN
bracis-28401	245	17	,	,	PUNCT
bracis-28401	245	18	rivest	riv	ADJ
bracis-28401	245	19	,	,	PUNCT
bracis-28401	245	20	r.l	r.l	PROPN
bracis-28401	245	21	.	.	PROPN
bracis-28401	245	22	,	,	PUNCT
bracis-28401	245	23	stein	stein	PROPN
bracis-28401	245	24	,	,	PUNCT
bracis-28401	245	25	c.	c.	PROPN
bracis-28401	245	26	:	:	PUNCT
bracis-28401	245	27	introduction	introduction	NOUN
bracis-28401	245	28	to	to	ADP
bracis-28401	245	29	algorithms	algorithm	NOUN
bracis-28401	245	30	.	.	PUNCT
bracis-28401	246	1	mit	mit	PROPN
bracis-28401	246	2	press	press	NOUN
bracis-28401	246	3	(	(	PUNCT
bracis-28401	246	4	2022	2022	NUM
bracis-28401	246	5	)	)	PUNCT
bracis-28401	246	6	google	google	PROPN
bracis-28401	246	7	scholar	scholar	NOUN
bracis-28401	246	8	  	  	SPACE
bracis-28401	246	9	friedman	friedman	PROPN
bracis-28401	246	10	,	,	PUNCT
bracis-28401	246	11	j.h	j.h	PROPN
bracis-28401	246	12	.	.	PROPN
bracis-28401	246	13	:	:	PUNCT
bracis-28401	246	14	greedy	greedy	ADJ
bracis-28401	246	15	function	function	NOUN
bracis-28401	246	16	approximation	approximation	NOUN
bracis-28401	246	17	:	:	PUNCT
bracis-28401	246	18	a	a	DET
bracis-28401	246	19	gradient	gradient	ADJ
bracis-28401	246	20	boosting	boost	VERB
bracis-28401	246	21	machine	machine	NOUN
bracis-28401	246	22	.	.	PUNCT
bracis-28401	247	1	annals	annal	NOUN
bracis-28401	247	2	of	of	ADP
bracis-28401	247	3	statistics	statistic	NOUN
bracis-28401	247	4	,	,	PUNCT
bracis-28401	247	5	pp	pp	ADV
bracis-28401	247	6	.	.	PUNCT
bracis-28401	248	1	1189–1232	1189–1232	NUM
bracis-28401	248	2	(	(	PUNCT
bracis-28401	248	3	2001	2001	NUM
bracis-28401	248	4	)	)	PUNCT
bracis-28401	248	5	google	google	PROPN
bracis-28401	248	6	scholar	scholar	NOUN
bracis-28401	248	7	  	  	SPACE
bracis-28401	248	8	garbin	garbin	NOUN
bracis-28401	248	9	,	,	PUNCT
bracis-28401	248	10	c.	c.	PROPN
bracis-28401	248	11	,	,	PUNCT
bracis-28401	248	12	zhu	zhu	PROPN
bracis-28401	248	13	,	,	PUNCT
bracis-28401	248	14	x.	x.	PROPN
bracis-28401	248	15	,	,	PUNCT
bracis-28401	248	16	marques	marques	PROPN
bracis-28401	248	17	,	,	PUNCT
bracis-28401	248	18	o.	o.	NOUN
bracis-28401	248	19	:	:	PUNCT
bracis-28401	248	20	dropout	dropout	NOUN
bracis-28401	248	21	vs.	vs.	ADP
bracis-28401	248	22	batch	batch	NOUN
bracis-28401	248	23	normalization	normalization	NOUN
bracis-28401	248	24	:	:	PUNCT
bracis-28401	248	25	an	an	DET
bracis-28401	248	26	empirical	empirical	ADJ
bracis-28401	248	27	study	study	NOUN
bracis-28401	248	28	of	of	ADP
bracis-28401	248	29	their	their	PRON
bracis-28401	248	30	impact	impact	NOUN
bracis-28401	248	31	to	to	ADP
bracis-28401	248	32	deep	deep	ADJ
bracis-28401	248	33	learning	learning	NOUN
bracis-28401	248	34	.	.	PUNCT
bracis-28401	249	1	multimed	multime	VERB
bracis-28401	249	2	.	.	PUNCT
bracis-28401	250	1	tools	tool	NOUN
bracis-28401	250	2	appl	appl	PROPN
bracis-28401	250	3	.	.	PROPN
bracis-28401	250	4	79	79	NUM
bracis-28401	250	5	,	,	PUNCT
bracis-28401	250	6	12777–12815	12777–12815	NUM
bracis-28401	250	7	(	(	PUNCT
bracis-28401	250	8	2020	2020	NUM
bracis-28401	250	9	)	)	PUNCT
bracis-28401	250	10	google	google	NOUN
bracis-28401	250	11	scholar	scholar	NOUN
bracis-28401	250	12	  	  	SPACE
bracis-28401	250	13	hutter	hutter	NOUN
bracis-28401	250	14	,	,	PUNCT
bracis-28401	250	15	f.	f.	PROPN
bracis-28401	250	16	,	,	PUNCT
bracis-28401	250	17	xu	xu	PROPN
bracis-28401	250	18	,	,	PUNCT
bracis-28401	250	19	l.	l.	PROPN
bracis-28401	250	20	,	,	PUNCT
bracis-28401	250	21	hoos	hoos	PROPN
bracis-28401	250	22	,	,	PUNCT
bracis-28401	250	23	h.h	h.h	PROPN
bracis-28401	250	24	.	.	PROPN
bracis-28401	250	25	,	,	PUNCT
bracis-28401	250	26	leyton	leyton	PROPN
bracis-28401	250	27	-	-	PUNCT
bracis-28401	250	28	brown	brown	PROPN
bracis-28401	250	29	,	,	PUNCT
bracis-28401	250	30	k.	k.	PROPN
bracis-28401	250	31	:	:	PUNCT
bracis-28401	251	1	algorithm	algorithm	PROPN
bracis-28401	251	2	runtime	runtime	NOUN
bracis-28401	251	3	prediction	prediction	NOUN
bracis-28401	251	4	:	:	PUNCT
bracis-28401	251	5	methods	method	NOUN
bracis-28401	251	6	&	&	CCONJ
bracis-28401	251	7	evaluation	evaluation	NOUN
bracis-28401	251	8	.	.	PUNCT
bracis-28401	252	1	artif	artif	INTJ
bracis-28401	252	2	.	.	PUNCT
bracis-28401	253	1	intell	intell	PROPN
bracis-28401	253	2	.	.	PUNCT
bracis-28401	254	1	206	206	NUM
bracis-28401	254	2	,	,	PUNCT
bracis-28401	254	3	79–111	79–111	PROPN
bracis-28401	254	4	(	(	PUNCT
bracis-28401	254	5	2014	2014	NUM
bracis-28401	254	6	)	)	PUNCT
bracis-28401	254	7	article	article	NOUN
bracis-28401	254	8	  	  	SPACE
bracis-28401	254	9	mathscinet	mathscinet	NOUN
bracis-28401	254	10	  	  	SPACE
bracis-28401	254	11	math	math	NOUN
bracis-28401	254	12	  	  	SPACE
bracis-28401	254	13	google	google	PROPN
bracis-28401	254	14	scholar	scholar	NOUN
bracis-28401	254	15	  	  	SPACE
bracis-28401	254	16	kleinberg	kleinberg	PROPN
bracis-28401	254	17	,	,	PUNCT
bracis-28401	254	18	j.	j.	PROPN
bracis-28401	254	19	,	,	PUNCT
bracis-28401	254	20	tardos	tardo	NOUN
bracis-28401	254	21	,	,	PUNCT
bracis-28401	254	22	e.	e.	PROPN
bracis-28401	254	23	:	:	PUNCT
bracis-28401	254	24	algorithm	algorithm	PROPN
bracis-28401	254	25	design	design	PROPN
bracis-28401	254	26	.	.	PUNCT
bracis-28401	255	1	pearson	pearson	PROPN
bracis-28401	255	2	education	education	PROPN
bracis-28401	255	3	india	india	PROPN
bracis-28401	255	4	(	(	PUNCT
bracis-28401	255	5	2006	2006	NUM
bracis-28401	255	6	)	)	PUNCT
bracis-28401	255	7	google	google	PROPN
bracis-28401	255	8	scholar	scholar	NOUN
bracis-28401	255	9	  	  	SPACE
bracis-28401	255	10	kursa	kursa	PROPN
bracis-28401	255	11	,	,	PUNCT
bracis-28401	255	12	m.b	m.b	PROPN
bracis-28401	255	13	.	.	PROPN
bracis-28401	255	14	,	,	PUNCT
bracis-28401	255	15	rudnicki	rudnicki	PROPN
bracis-28401	255	16	,	,	PUNCT
bracis-28401	255	17	w.r	w.r	PROPN
bracis-28401	255	18	.	.	PUNCT
bracis-28401	255	19	:	:	PUNCT
bracis-28401	255	20	feature	feature	NOUN
bracis-28401	255	21	selection	selection	NOUN
bracis-28401	255	22	with	with	ADP
bracis-28401	255	23	the	the	DET
bracis-28401	255	24	boruta	boruta	PROPN
bracis-28401	255	25	package	package	NOUN
bracis-28401	255	26	.	.	PUNCT
bracis-28401	256	1	j.	j.	PROPN
bracis-28401	256	2	stat	stat	PROPN
bracis-28401	256	3	.	.	PUNCT
bracis-28401	257	1	softw	softw	PROPN
bracis-28401	257	2	.	.	PUNCT
bracis-28401	258	1	36	36	NUM
bracis-28401	258	2	,	,	PUNCT
bracis-28401	258	3	1–13	1–13	PROPN
bracis-28401	258	4	(	(	PUNCT
bracis-28401	258	5	2010	2010	NUM
bracis-28401	258	6	)	)	PUNCT
bracis-28401	258	7	article	article	NOUN
bracis-28401	258	8	  	  	SPACE
bracis-28401	258	9	google	google	PROPN
bracis-28401	258	10	scholar	scholar	NOUN
bracis-28401	258	11	  	  	SPACE
bracis-28401	258	12	lucas	lucas	NOUN
bracis-28401	258	13	,	,	PUNCT
bracis-28401	258	14	s.	s.	PROPN
bracis-28401	258	15	:	:	PUNCT
bracis-28401	258	16	the	the	DET
bracis-28401	258	17	origins	origin	NOUN
bracis-28401	258	18	of	of	ADP
bracis-28401	258	19	the	the	DET
bracis-28401	258	20	halting	halting	ADJ
bracis-28401	258	21	problem	problem	NOUN
bracis-28401	258	22	.	.	PUNCT
bracis-28401	259	1	j.	j.	PROPN
bracis-28401	259	2	logical	logical	ADJ
bracis-28401	259	3	algebraic	algebraic	ADJ
bracis-28401	259	4	methods	method	NOUN
bracis-28401	259	5	programming	program	VERB
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bracis-28401	259	7	,	,	PUNCT
bracis-28401	259	8	100687	100687	NUM
bracis-28401	259	9	(	(	PUNCT
bracis-28401	259	10	2021	2021	NUM
bracis-28401	259	11	)	)	PUNCT
bracis-28401	259	12	article	article	NOUN
bracis-28401	259	13	  	  	SPACE
bracis-28401	259	14	mathscinet	mathscinet	NOUN
bracis-28401	259	15	  	  	SPACE
bracis-28401	259	16	math	math	NOUN
bracis-28401	259	17	  	  	SPACE
bracis-28401	259	18	google	google	PROPN
bracis-28401	259	19	scholar	scholar	NOUN
bracis-28401	259	20	  	  	SPACE
bracis-28401	259	21	pedregosa	pedregosa	PROPN
bracis-28401	259	22	,	,	PUNCT
bracis-28401	259	23	f.	f.	PROPN
bracis-28401	259	24	,	,	PUNCT
bracis-28401	259	25	et	et	PROPN
bracis-28401	259	26	al	al	PROPN
bracis-28401	259	27	.	.	PROPN
bracis-28401	259	28	:	:	PUNCT
bracis-28401	260	1	scikit	scikit	NOUN
bracis-28401	260	2	-	-	PUNCT
bracis-28401	260	3	learn	learn	VERB
bracis-28401	260	4	:	:	PUNCT
bracis-28401	260	5	machine	machine	NOUN
bracis-28401	260	6	learning	learning	NOUN
bracis-28401	260	7	in	in	ADP
bracis-28401	260	8	python	python	PROPN
bracis-28401	260	9	.	.	PUNCT
bracis-28401	261	1	j.	j.	PROPN
bracis-28401	261	2	mach	mach	PROPN
bracis-28401	261	3	.	.	PUNCT
bracis-28401	262	1	learn	learn	VERB
bracis-28401	262	2	.	.	PUNCT
bracis-28401	263	1	res	re	NOUN
bracis-28401	263	2	.	.	PROPN
bracis-28401	264	1	12	12	NUM
bracis-28401	264	2	,	,	PUNCT
bracis-28401	264	3	2825–2830	2825–2830	NUM
bracis-28401	264	4	(	(	PUNCT
bracis-28401	264	5	2011	2011	NUM
bracis-28401	264	6	)	)	PUNCT
bracis-28401	264	7	mathscinet	mathscinet	NOUN
bracis-28401	264	8	  	  	SPACE
bracis-28401	264	9	math	math	NOUN
bracis-28401	264	10	  	  	SPACE
bracis-28401	264	11	google	google	PROPN
bracis-28401	264	12	scholar	scholar	NOUN
bracis-28401	264	13	  	  	SPACE
bracis-28401	264	14	ramyachitra	ramyachitra	PROPN
bracis-28401	264	15	,	,	PUNCT
bracis-28401	264	16	d.	d.	PROPN
bracis-28401	264	17	,	,	PUNCT
bracis-28401	264	18	manikandan	manikandan	PROPN
bracis-28401	264	19	,	,	PUNCT
bracis-28401	264	20	p.	p.	NOUN
bracis-28401	264	21	:	:	PUNCT
bracis-28401	264	22	imbalanced	imbalance	VERB
bracis-28401	264	23	dataset	dataset	NOUN
bracis-28401	264	24	classification	classification	NOUN
bracis-28401	264	25	and	and	CCONJ
bracis-28401	264	26	solutions	solution	NOUN
bracis-28401	264	27	:	:	PUNCT
bracis-28401	264	28	a	a	DET
bracis-28401	264	29	review	review	NOUN
bracis-28401	264	30	.	.	PUNCT
bracis-28401	265	1	int	int	NOUN
bracis-28401	265	2	.	.	PUNCT
bracis-28401	266	1	j.	j.	PROPN
bracis-28401	266	2	comput	comput	PROPN
bracis-28401	266	3	.	.	PUNCT
bracis-28401	267	1	bus	bus	NOUN
bracis-28401	267	2	.	.	PUNCT
bracis-28401	268	1	res	re	NOUN
bracis-28401	268	2	.	.	PUNCT
bracis-28401	269	1	(	(	PUNCT
bracis-28401	269	2	ijcbr	ijcbr	PROPN
bracis-28401	269	3	)	)	PUNCT
bracis-28401	269	4	5(4	5(4	NUM
bracis-28401	269	5	)	)	PUNCT
bracis-28401	269	6	,	,	PUNCT
bracis-28401	269	7	1–29	1–29	PROPN
bracis-28401	269	8	(	(	PUNCT
bracis-28401	269	9	2014	2014	NUM
bracis-28401	269	10	)	)	PUNCT
bracis-28401	269	11	google	google	PROPN
bracis-28401	269	12	scholar	scholar	NOUN
bracis-28401	269	13	  	  	SPACE
bracis-28401	269	14	santos	santo	NOUN
bracis-28401	269	15	,	,	PUNCT
bracis-28401	269	16	m.s	m.s	PROPN
bracis-28401	269	17	.	.	PROPN
bracis-28401	269	18	,	,	PUNCT
bracis-28401	269	19	soares	soares	PROPN
bracis-28401	269	20	,	,	PUNCT
bracis-28401	269	21	j.p	j.p	PROPN
bracis-28401	269	22	.	.	PROPN
bracis-28401	269	23	,	,	PUNCT
bracis-28401	269	24	abreu	abreu	PROPN
bracis-28401	269	25	,	,	PUNCT
bracis-28401	269	26	p.h	p.h	PROPN
bracis-28401	269	27	.	.	PROPN
bracis-28401	269	28	,	,	PUNCT
bracis-28401	269	29	araujo	araujo	PROPN
bracis-28401	269	30	,	,	PUNCT
bracis-28401	269	31	h.	h.	PROPN
bracis-28401	269	32	,	,	PUNCT
bracis-28401	269	33	santos	santos	PROPN
bracis-28401	269	34	,	,	PUNCT
bracis-28401	269	35	j.	j.	PROPN
bracis-28401	269	36	:	:	PUNCT
bracis-28401	269	37	cross	cross	NOUN
bracis-28401	269	38	-	-	NOUN
bracis-28401	269	39	validation	validation	ADJ
bracis-28401	269	40	for	for	ADP
bracis-28401	269	41	imbalanced	imbalanced	ADJ
bracis-28401	269	42	datasets	dataset	NOUN
bracis-28401	269	43	:	:	PUNCT
bracis-28401	269	44	avoiding	avoid	VERB
bracis-28401	269	45	overoptimistic	overoptimistic	ADJ
bracis-28401	269	46	and	and	CCONJ
bracis-28401	269	47	overfitting	overfitte	VERB
bracis-28401	269	48	approaches	approach	NOUN
bracis-28401	269	49	[	[	X
bracis-28401	269	50	research	research	NOUN
bracis-28401	269	51	frontier	frontier	NOUN
bracis-28401	269	52	]	]	PUNCT
bracis-28401	269	53	.	.	PUNCT
bracis-28401	270	1	ieee	ieee	NOUN
bracis-28401	270	2	comput	comput	PROPN
bracis-28401	270	3	.	.	PUNCT
bracis-28401	271	1	intell	intell	PROPN
bracis-28401	271	2	.	.	PUNCT
bracis-28401	272	1	magaz	magaz	NOUN
bracis-28401	272	2	.	.	PUNCT
bracis-28401	273	1	13(4	13(4	NUM
bracis-28401	273	2	)	)	PUNCT
bracis-28401	273	3	,	,	PUNCT
bracis-28401	273	4	59–76	59–76	NUM
bracis-28401	273	5	(	(	PUNCT
bracis-28401	273	6	2018	2018	NUM
bracis-28401	273	7	)	)	PUNCT
bracis-28401	273	8	google	google	PROPN
bracis-28401	273	9	scholar	scholar	NOUN
bracis-28401	273	10	  	  	SPACE
bracis-28401	273	11	sechidis	sechidi	NOUN
bracis-28401	273	12	,	,	PUNCT
bracis-28401	273	13	k.	k.	PROPN
bracis-28401	273	14	,	,	PUNCT
bracis-28401	273	15	tsoumakas	tsoumakas	PROPN
bracis-28401	273	16	,	,	PUNCT
bracis-28401	273	17	g.	g.	PROPN
bracis-28401	273	18	,	,	PUNCT
bracis-28401	273	19	vlahavas	vlahavas	PROPN
bracis-28401	273	20	,	,	PUNCT
bracis-28401	273	21	i.	i.	NOUN
bracis-28401	273	22	:	:	PUNCT
bracis-28401	273	23	on	on	ADP
bracis-28401	273	24	the	the	DET
bracis-28401	273	25	stratification	stratification	NOUN
bracis-28401	273	26	of	of	ADP
bracis-28401	273	27	multi	multi	ADJ
bracis-28401	273	28	-	-	ADJ
bracis-28401	273	29	label	label	ADJ
bracis-28401	273	30	data	datum	NOUN
bracis-28401	273	31	.	.	PUNCT
bracis-28401	274	1	in	in	ADP
bracis-28401	274	2	:	:	PUNCT
bracis-28401	274	3	gunopulos	gunopulo	NOUN
bracis-28401	274	4	,	,	PUNCT
bracis-28401	274	5	d.	d.	PROPN
bracis-28401	274	6	,	,	PUNCT
bracis-28401	274	7	hofmann	hofmann	PROPN
bracis-28401	274	8	,	,	PUNCT
bracis-28401	274	9	t.	t.	PROPN
bracis-28401	274	10	,	,	PUNCT
bracis-28401	274	11	malerba	malerba	PROPN
bracis-28401	274	12	,	,	PUNCT
bracis-28401	274	13	d.	d.	PROPN
bracis-28401	274	14	,	,	PUNCT
bracis-28401	274	15	vazirgiannis	vazirgiannis	PROPN
bracis-28401	274	16	,	,	PUNCT
bracis-28401	274	17	m.	m.	NOUN
bracis-28401	274	18	(	(	PUNCT
bracis-28401	274	19	eds	ed	NOUN
bracis-28401	274	20	.	.	PUNCT
bracis-28401	274	21	)	)	PUNCT
bracis-28401	275	1	ecml	ecml	PROPN
bracis-28401	275	2	pkdd	pkdd	NOUN
bracis-28401	275	3	2011	2011	NUM
bracis-28401	275	4	.	.	PUNCT
bracis-28401	276	1	lncs	lncs	PROPN
bracis-28401	276	2	(	(	PUNCT
bracis-28401	276	3	lnai	lnai	ADJ
bracis-28401	276	4	)	)	PUNCT
bracis-28401	276	5	,	,	PUNCT
bracis-28401	276	6	vol	vol	NOUN
bracis-28401	276	7	.	.	PROPN
bracis-28401	276	8	6913	6913	NUM
bracis-28401	276	9	,	,	PUNCT
bracis-28401	276	10	pp	pp	ADV
bracis-28401	276	11	.	.	PUNCT
bracis-28401	277	1	145–158	145–158	NUM
bracis-28401	277	2	.	.	PUNCT
bracis-28401	277	3	springer	springer	NOUN
bracis-28401	277	4	,	,	PUNCT
bracis-28401	277	5	heidelberg	heidelberg	PROPN
bracis-28401	277	6	(	(	PUNCT
bracis-28401	277	7	2011	2011	NUM
bracis-28401	277	8	)	)	PUNCT
bracis-28401	277	9	.	.	PUNCT
bracis-28401	278	1	https://doi.org/10.1007/978-3-642-23808-6_10	https://doi.org/10.1007/978-3-642-23808-6_10	PROPN
bracis-28401	278	2	chapter	chapter	NOUN
bracis-28401	278	3	  	  	SPACE
bracis-28401	278	4	google	google	PROPN
bracis-28401	278	5	scholar	scholar	NOUN
bracis-28401	278	6	  	  	SPACE
bracis-28401	278	7	seifzadeh	seifzadeh	NOUN
bracis-28401	278	8	,	,	PUNCT
bracis-28401	278	9	s.	s.	PROPN
bracis-28401	278	10	:	:	PUNCT
bracis-28401	278	11	ai	ai	VERB
bracis-28401	278	12	for	for	ADP
bracis-28401	278	13	code	code	NOUN
bracis-28401	278	14	:	:	PUNCT
bracis-28401	278	15	predict	predict	VERB
bracis-28401	278	16	code	code	NOUN
bracis-28401	278	17	complexity	complexity	NOUN
bracis-28401	278	18	using	use	VERB
bracis-28401	278	19	ibm	ibm	PROPN
bracis-28401	278	20	’s	’s	PART
bracis-28401	278	21	codenet	codenet	ADJ
bracis-28401	278	22	dataset	dataset	NOUN
bracis-28401	278	23	,	,	PUNCT
bracis-28401	278	24	october	october	PROPN
bracis-28401	278	25	2021	2021	NUM
bracis-28401	278	26	.	.	PUNCT
bracis-28401	279	1	https://community.ibm.com/community/user/ai-datascience/blogs/sepideh-seifzadeh1/2021/10/05/ai-for-code-predict-code-complexity-using-ibms-cod	https://community.ibm.com/community/user/ai-datascience/blogs/sepideh-seifzadeh1/2021/10/05/ai-for-code-predict-code-complexity-using-ibms-cod	NOUN
bracis-28401	279	2	sikka	sikka	PROPN
bracis-28401	279	3	,	,	PUNCT
bracis-28401	279	4	j.	j.	PROPN
bracis-28401	279	5	,	,	PUNCT
bracis-28401	279	6	satya	satya	PROPN
bracis-28401	279	7	,	,	PUNCT
bracis-28401	279	8	k.	k.	PROPN
bracis-28401	279	9	,	,	PUNCT
bracis-28401	279	10	kumar	kumar	PROPN
bracis-28401	279	11	,	,	PUNCT
bracis-28401	279	12	y.	y.	PROPN
bracis-28401	279	13	,	,	PUNCT
bracis-28401	279	14	uppal	uppal	PROPN
bracis-28401	279	15	,	,	PUNCT
bracis-28401	279	16	s.	s.	PROPN
bracis-28401	279	17	,	,	PUNCT
bracis-28401	279	18	shah	shah	PROPN
bracis-28401	279	19	,	,	PUNCT
bracis-28401	279	20	r.r	r.r	PROPN
bracis-28401	279	21	.	.	PROPN
bracis-28401	279	22	,	,	PUNCT
bracis-28401	279	23	zimmermann	zimmermann	PROPN
bracis-28401	279	24	,	,	PUNCT
bracis-28401	279	25	r.	r.	PROPN
bracis-28401	279	26	:	:	PUNCT
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bracis-28401	279	30	for	for	ADP
bracis-28401	279	31	code	code	NOUN
bracis-28401	279	32	runtime	runtime	NOUN
bracis-28401	279	33	complexity	complexity	NOUN
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bracis-28401	279	35	.	.	PUNCT
bracis-28401	280	1	in	in	ADP
bracis-28401	280	2	:	:	PUNCT
bracis-28401	280	3	jose	jose	PROPN
bracis-28401	280	4	,	,	PUNCT
bracis-28401	280	5	j.m	j.m	PROPN
bracis-28401	280	6	.	.	PROPN
bracis-28401	280	7	,	,	PUNCT
bracis-28401	280	8	yilmaz	yilmaz	PROPN
bracis-28401	280	9	,	,	PUNCT
bracis-28401	280	10	e.	e.	PROPN
bracis-28401	280	11	,	,	PUNCT
bracis-28401	280	12	magalhães	magalhães	PROPN
bracis-28401	280	13	,	,	PUNCT
bracis-28401	280	14	j.	j.	PROPN
bracis-28401	280	15	,	,	PUNCT
bracis-28401	280	16	castells	castells	PROPN
bracis-28401	280	17	,	,	PUNCT
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bracis-28401	280	19	,	,	PUNCT
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bracis-28401	280	21	,	,	PUNCT
bracis-28401	280	22	n.	n.	NOUN
bracis-28401	280	23	,	,	PUNCT
bracis-28401	280	24	silva	silva	PROPN
bracis-28401	280	25	,	,	PUNCT
bracis-28401	280	26	m.j	m.j	PROPN
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bracis-28401	280	28	,	,	PUNCT
bracis-28401	280	29	martins	martins	PROPN
bracis-28401	280	30	,	,	PUNCT
bracis-28401	280	31	f.	f.	PROPN
bracis-28401	280	32	(	(	PUNCT
bracis-28401	280	33	eds	eds	PROPN
bracis-28401	280	34	.	.	PUNCT
bracis-28401	280	35	)	)	PUNCT
bracis-28401	280	36	ecir	ecir	PROPN
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bracis-28401	280	38	.	.	PUNCT
bracis-28401	281	1	lncs	lncs	PROPN
bracis-28401	281	2	,	,	PUNCT
bracis-28401	281	3	vol	vol	NOUN
bracis-28401	281	4	.	.	PROPN
bracis-28401	281	5	12035	12035	NUM
bracis-28401	281	6	,	,	PUNCT
bracis-28401	281	7	pp	pp	ADP
bracis-28401	281	8	.	.	PUNCT
bracis-28401	282	1	313–325	313–325	NUM
bracis-28401	282	2	.	.	PUNCT
bracis-28401	282	3	springer	springer	NOUN
bracis-28401	282	4	,	,	PUNCT
bracis-28401	282	5	cham	cham	PROPN
bracis-28401	282	6	(	(	PUNCT
bracis-28401	282	7	2020	2020	NUM
bracis-28401	282	8	)	)	PUNCT
bracis-28401	282	9	.	.	PUNCT
bracis-28401	283	1	https://doi.org/10.1007/978-3-030-45439-5_21	https://doi.org/10.1007/978-3-030-45439-5_21	PROPN
bracis-28401	283	2	chapter	chapter	NOUN
bracis-28401	283	3	  	  	SPACE
bracis-28401	283	4	google	google	PROPN
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bracis-28401	283	6	  	  	SPACE
bracis-28401	283	7	speiser	speiser	NOUN
bracis-28401	283	8	,	,	PUNCT
bracis-28401	283	9	j.l	j.l	PROPN
bracis-28401	283	10	.	.	PROPN
bracis-28401	283	11	,	,	PUNCT
bracis-28401	283	12	miller	miller	PROPN
bracis-28401	283	13	,	,	PUNCT
bracis-28401	283	14	m.e	m.e	PROPN
bracis-28401	283	15	.	.	PROPN
bracis-28401	283	16	,	,	PUNCT
bracis-28401	283	17	tooze	tooze	PROPN
bracis-28401	283	18	,	,	PUNCT
bracis-28401	283	19	j.	j.	PROPN
bracis-28401	283	20	,	,	PUNCT
bracis-28401	283	21	ip	ip	PROPN
bracis-28401	283	22	,	,	PUNCT
bracis-28401	283	23	e.	e.	PROPN
bracis-28401	283	24	:	:	PUNCT
bracis-28401	283	25	a	a	DET
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bracis-28401	283	27	of	of	ADP
bracis-28401	283	28	random	random	ADJ
bracis-28401	283	29	forest	forest	NOUN
bracis-28401	283	30	variable	variable	ADJ
bracis-28401	283	31	selection	selection	NOUN
bracis-28401	283	32	methods	method	NOUN
bracis-28401	283	33	for	for	ADP
bracis-28401	283	34	classification	classification	NOUN
bracis-28401	283	35	prediction	prediction	NOUN
bracis-28401	283	36	modeling	modeling	NOUN
bracis-28401	283	37	.	.	PUNCT
bracis-28401	284	1	expert	expert	NOUN
bracis-28401	284	2	syst	syst	PROPN
bracis-28401	284	3	.	.	PUNCT
bracis-28401	285	1	appl	appl	PROPN
bracis-28401	285	2	.	.	PROPN
bracis-28401	286	1	134	134	NUM
bracis-28401	286	2	,	,	PUNCT
bracis-28401	286	3	93–101	93–101	PROPN
bracis-28401	286	4	(	(	PUNCT
bracis-28401	286	5	2019	2019	NUM
bracis-28401	286	6	)	)	PUNCT
bracis-28401	286	7	article	article	NOUN
bracis-28401	286	8	  	  	SPACE
bracis-28401	286	9	google	google	PROPN
bracis-28401	286	10	scholar	scholar	NOUN
bracis-28401	286	11	  	  	SPACE
bracis-28401	286	12	thara	thara	NOUN
bracis-28401	286	13	,	,	PUNCT
bracis-28401	286	14	d.	d.	PROPN
bracis-28401	286	15	,	,	PUNCT
bracis-28401	286	16	premasudha	premasudha	PROPN
bracis-28401	286	17	,	,	PUNCT
bracis-28401	286	18	b.	b.	PROPN
bracis-28401	286	19	,	,	PUNCT
bracis-28401	286	20	xiong	xiong	PROPN
bracis-28401	286	21	,	,	PUNCT
bracis-28401	286	22	f.	f.	PROPN
bracis-28401	286	23	:	:	PUNCT
bracis-28401	286	24	auto	auto	NOUN
bracis-28401	286	25	-	-	PUNCT
bracis-28401	286	26	detection	detection	NOUN
bracis-28401	286	27	of	of	ADP
bracis-28401	286	28	epileptic	epileptic	ADJ
bracis-28401	286	29	seizure	seizure	NOUN
bracis-28401	286	30	events	event	NOUN
bracis-28401	286	31	using	use	VERB
bracis-28401	286	32	deep	deep	ADJ
bracis-28401	286	33	neural	neural	ADJ
bracis-28401	286	34	network	network	NOUN
bracis-28401	286	35	with	with	ADP
bracis-28401	286	36	different	different	ADJ
bracis-28401	286	37	feature	feature	NOUN
bracis-28401	286	38	scaling	scale	VERB
bracis-28401	286	39	techniques	technique	NOUN
bracis-28401	286	40	.	.	PUNCT
bracis-28401	287	1	pattern	pattern	NOUN
bracis-28401	287	2	recogn	recogn	PROPN
bracis-28401	287	3	.	.	PUNCT
bracis-28401	288	1	lett	lett	PROPN
bracis-28401	288	2	.	.	PROPN
bracis-28401	289	1	128	128	NUM
bracis-28401	289	2	,	,	PUNCT
bracis-28401	289	3	544–550	544–550	NUM
bracis-28401	289	4	(	(	PUNCT
bracis-28401	289	5	2019	2019	NUM
bracis-28401	289	6	)	)	PUNCT
bracis-28401	289	7	article	article	NOUN
bracis-28401	289	8	  	  	SPACE
bracis-28401	289	9	google	google	PROPN
bracis-28401	289	10	scholar	scholar	NOUN
bracis-28401	289	11	  	  	SPACE
bracis-28401	289	12	download	download	NOUN
bracis-28401	289	13	references	reference	NOUN
bracis-28401	289	14	author	author	NOUN
bracis-28401	289	15	information	information	NOUN
bracis-28401	289	16	authors	author	NOUN
bracis-28401	289	17	and	and	CCONJ
bracis-28401	289	18	affiliations	affiliation	NOUN
bracis-28401	289	19	federal	federal	PROPN
bracis-28401	289	20	university	university	PROPN
bracis-28401	289	21	of	of	ADP
bracis-28401	289	22	santa	santa	PROPN
bracis-28401	289	23	catarina	catarina	PROPN
bracis-28401	289	24	,	,	PUNCT
bracis-28401	289	25	florianópolis	florianópolis	PROPN
bracis-28401	289	26	,	,	PUNCT
bracis-28401	289	27	brazil	brazil	PROPN
bracis-28401	289	28	ricardo	ricardo	PROPN
bracis-28401	289	29	j.	j.	PROPN
bracis-28401	289	30	pfitscher	pfitscher	PROPN
bracis-28401	289	31	 	 	SPACE
bracis-28401	289	32	&	&	CCONJ
bracis-28401	289	33	 	 	SPACE
bracis-28401	289	34	gabriel	gabriel	PROPN
bracis-28401	289	35	b.	b.	PROPN
bracis-28401	289	36	rodenbusch	rodenbusch	VERB
bracis-28401	289	37	unisociesc	unisociesc	NOUN
bracis-28401	289	38	campus	campus	PROPN
bracis-28401	289	39	anita	anita	PROPN
bracis-28401	289	40	garibaldi	garibaldi	PROPN
bracis-28401	289	41	,	,	PUNCT
bracis-28401	289	42	joinville	joinville	PROPN
bracis-28401	289	43	,	,	PUNCT
bracis-28401	289	44	brazil	brazil	PROPN
bracis-28401	289	45	anderson	anderson	PROPN
bracis-28401	289	46	dias	dias	PROPN
bracis-28401	289	47	 	 	SPACE
bracis-28401	289	48	&	&	CCONJ
bracis-28401	289	49	 	 	SPACE
bracis-28401	289	50	paulo	paulo	PROPN
bracis-28401	289	51	vieira	vieira	PROPN
bracis-28401	289	52	university	university	PROPN
bracis-28401	289	53	of	of	ADP
bracis-28401	289	54	são	são	PROPN
bracis-28401	289	55	paulo	paulo	PROPN
bracis-28401	289	56	,	,	PUNCT
bracis-28401	289	57	são	são	PROPN
bracis-28401	289	58	paulo	paulo	PROPN
bracis-28401	289	59	,	,	PUNCT
bracis-28401	289	60	brazil	brazil	PROPN
bracis-28401	289	61	nuno	nuno	PROPN
bracis-28401	289	62	m.	m.	PROPN
bracis-28401	289	63	m.	m.	PROPN
bracis-28401	289	64	d.	d.	PROPN
bracis-28401	289	65	fouto	fouto	PROPN
bracis-28401	289	66	authors	authors	PROPN
bracis-28401	289	67	ricardo	ricardo	PROPN
bracis-28401	289	68	j.	j.	PROPN
bracis-28401	289	69	pfitscherview	pfitscherview	PROPN
bracis-28401	289	70	author	author	NOUN
bracis-28401	289	71	publications	publication	NOUN
bracis-28401	289	72	search	search	NOUN
bracis-28401	289	73	author	author	NOUN
bracis-28401	289	74	on	on	ADP
bracis-28401	289	75	:	:	PUNCT
bracis-28401	289	76	pubmed	pubmed	PROPN
bracis-28401	289	77	 	 	SPACE
bracis-28401	289	78	google	google	PROPN
bracis-28401	289	79	scholar	scholar	PROPN
bracis-28401	289	80	gabriel	gabriel	PROPN
bracis-28401	289	81	b.	b.	PROPN
bracis-28401	289	82	rodenbuschview	rodenbuschview	PROPN
bracis-28401	289	83	author	author	NOUN
bracis-28401	289	84	publications	publication	NOUN
bracis-28401	289	85	search	search	NOUN
bracis-28401	289	86	author	author	NOUN
bracis-28401	289	87	on	on	ADP
bracis-28401	289	88	:	:	PUNCT
bracis-28401	289	89	pubmed	pubmed	PROPN
bracis-28401	289	90	 	 	SPACE
bracis-28401	289	91	google	google	PROPN
bracis-28401	289	92	scholar	scholar	PROPN
bracis-28401	289	93	anderson	anderson	PROPN
bracis-28401	289	94	diasview	diasview	PROPN
bracis-28401	289	95	author	author	NOUN
bracis-28401	289	96	publications	publication	NOUN
bracis-28401	289	97	search	search	NOUN
bracis-28401	289	98	author	author	NOUN
bracis-28401	289	99	on	on	ADP
bracis-28401	289	100	:	:	PUNCT
bracis-28401	289	101	pubmed	pubmed	PROPN
bracis-28401	289	102	 	 	SPACE
bracis-28401	289	103	google	google	PROPN
bracis-28401	289	104	scholar	scholar	NOUN
bracis-28401	289	105	paulo	paulo	VERB
bracis-28401	289	106	vieiraview	vieiraview	NOUN
bracis-28401	289	107	author	author	NOUN
bracis-28401	289	108	publications	publication	NOUN
bracis-28401	289	109	search	search	NOUN
bracis-28401	289	110	author	author	NOUN
bracis-28401	289	111	on	on	ADP
bracis-28401	289	112	:	:	PUNCT
bracis-28401	289	113	pubmed	pubmed	PROPN
bracis-28401	289	114	 	 	SPACE
bracis-28401	289	115	google	google	PROPN
bracis-28401	289	116	scholar	scholar	PROPN
bracis-28401	289	117	nuno	nuno	PROPN
bracis-28401	289	118	m.	m.	PROPN
bracis-28401	289	119	m.	m.	PROPN
bracis-28401	289	120	d.	d.	PROPN
bracis-28401	289	121	foutoview	foutoview	PROPN
bracis-28401	289	122	author	author	NOUN
bracis-28401	289	123	publications	publication	NOUN
bracis-28401	289	124	search	search	NOUN
bracis-28401	289	125	author	author	NOUN
bracis-28401	289	126	on	on	ADP
bracis-28401	289	127	:	:	PUNCT
bracis-28401	289	128	pubmed	pubmed	PROPN
bracis-28401	289	129	 	 	SPACE
bracis-28401	289	130	google	google	PROPN
bracis-28401	289	131	scholar	scholar	NOUN
bracis-28401	289	132	corresponding	correspond	VERB
bracis-28401	289	133	author	author	NOUN
bracis-28401	289	134	correspondence	correspondence	NOUN
bracis-28401	289	135	to	to	ADP
bracis-28401	289	136	ricardo	ricardo	PROPN
bracis-28401	289	137	j.	j.	PROPN
bracis-28401	289	138	pfitscher	pfitscher	PROPN
bracis-28401	289	139	.	.	PUNCT
bracis-28401	290	1	editor	editor	NOUN
bracis-28401	290	2	information	information	NOUN
bracis-28401	290	3	editors	editor	NOUN
bracis-28401	290	4	and	and	CCONJ
bracis-28401	290	5	affiliations	affiliation	NOUN
bracis-28401	290	6	federal	federal	PROPN
bracis-28401	290	7	university	university	PROPN
bracis-28401	290	8	of	of	ADP
bracis-28401	290	9	são	são	PROPN
bracis-28401	290	10	carlos	carlos	PROPN
bracis-28401	290	11	,	,	PUNCT
bracis-28401	290	12	são	são	PROPN
bracis-28401	290	13	carlos	carlos	PROPN
bracis-28401	290	14	,	,	PUNCT
bracis-28401	290	15	brazil	brazil	PROPN
bracis-28401	290	16	murilo	murilo	PROPN
bracis-28401	290	17	c.	c.	PROPN
bracis-28401	290	18	naldi	naldi	PROPN
bracis-28401	290	19	centro	centro	PROPN
bracis-28401	290	20	universitario	universitario	PROPN
bracis-28401	290	21	da	da	PROPN
bracis-28401	290	22	fei	fei	PROPN
bracis-28401	290	23	,	,	PUNCT
bracis-28401	290	24	são	são	PROPN
bracis-28401	290	25	bernardo	bernardo	PROPN
bracis-28401	290	26	do	do	AUX
bracis-28401	290	27	campo	campo	PROPN
bracis-28401	290	28	,	,	PUNCT
bracis-28401	290	29	brazil	brazil	PROPN
bracis-28401	290	30	reinaldo	reinaldo	PROPN
bracis-28401	290	31	a.	a.	PROPN
bracis-28401	290	32	c.	c.	PROPN
bracis-28401	290	33	bianchi	bianchi	PROPN
bracis-28401	290	34	rights	right	NOUN
bracis-28401	290	35	and	and	CCONJ
bracis-28401	290	36	permissions	permission	NOUN
bracis-28401	290	37	reprints	reprint	NOUN
bracis-28401	290	38	and	and	CCONJ
bracis-28401	290	39	permissions	permission	VERB
bracis-28401	290	40	copyright	copyright	NOUN
bracis-28401	290	41	information	information	NOUN
bracis-28401	290	42	©	©	ADP
bracis-28401	290	43	2023	2023	NUM
bracis-28401	290	44	the	the	DET
bracis-28401	290	45	author(s	author(s	NOUN
bracis-28401	290	46	)	)	PUNCT
bracis-28401	290	47	,	,	PUNCT
bracis-28401	290	48	under	under	ADP
bracis-28401	290	49	exclusive	exclusive	ADJ
bracis-28401	290	50	license	license	NOUN
bracis-28401	290	51	to	to	ADP
bracis-28401	290	52	springer	springer	NOUN
bracis-28401	290	53	nature	nature	PROPN
bracis-28401	290	54	switzerland	switzerland	PROPN
bracis-28401	290	55	ag	ag	PROPN
bracis-28401	290	56	about	about	ADP
bracis-28401	290	57	this	this	DET
bracis-28401	290	58	paper	paper	NOUN
bracis-28401	290	59	cite	cite	VERB
bracis-28401	290	60	this	this	DET
bracis-28401	290	61	paper	paper	NOUN
bracis-28401	290	62	pfitscher	pfitscher	NOUN
bracis-28401	290	63	,	,	PUNCT
bracis-28401	290	64	r.j	r.j	PROPN
bracis-28401	290	65	.	.	PROPN
bracis-28401	290	66	,	,	PUNCT
bracis-28401	290	67	rodenbusch	rodenbusch	PROPN
bracis-28401	290	68	,	,	PUNCT
bracis-28401	290	69	g.b	g.b	PROPN
bracis-28401	290	70	.	.	PROPN
bracis-28401	290	71	,	,	PUNCT
bracis-28401	290	72	dias	dias	PROPN
bracis-28401	290	73	,	,	PUNCT
bracis-28401	290	74	a.	a.	NOUN
bracis-28401	290	75	,	,	PUNCT
bracis-28401	290	76	vieira	vieira	PROPN
bracis-28401	290	77	,	,	PUNCT
bracis-28401	290	78	p.	p.	NOUN
bracis-28401	290	79	,	,	PUNCT
bracis-28401	290	80	fouto	fouto	PROPN
bracis-28401	290	81	,	,	PUNCT
bracis-28401	290	82	n.m.m.d	n.m.m.d	PROPN
bracis-28401	290	83	.	.	PROPN
bracis-28401	290	84	(	(	PUNCT
bracis-28401	290	85	2023	2023	NUM
bracis-28401	290	86	)	)	PUNCT
bracis-28401	290	87	.	.	PUNCT
bracis-28401	291	1	estimating	estimate	VERB
bracis-28401	291	2	code	code	NOUN
bracis-28401	291	3	running	running	NOUN
bracis-28401	291	4	time	time	NOUN
bracis-28401	291	5	complexity	complexity	NOUN
bracis-28401	291	6	with	with	ADP
bracis-28401	291	7	 	 	SPACE
bracis-28401	291	8	machine	machine	NOUN
bracis-28401	291	9	learning	learning	NOUN
bracis-28401	291	10	.	.	PUNCT
bracis-28401	292	1	in	in	ADP
bracis-28401	292	2	:	:	PUNCT
bracis-28401	292	3	naldi	naldi	PROPN
bracis-28401	292	4	,	,	PUNCT
bracis-28401	292	5	m.c	m.c	PROPN
bracis-28401	292	6	.	.	PROPN
bracis-28401	292	7	,	,	PUNCT
bracis-28401	292	8	bianchi	bianchi	PROPN
bracis-28401	292	9	,	,	PUNCT
bracis-28401	292	10	r.a.c	r.a.c	ADP
bracis-28401	292	11	.	.	PUNCT
bracis-28401	292	12	(	(	PUNCT
bracis-28401	292	13	eds	ed	NOUN
bracis-28401	292	14	)	)	PUNCT
bracis-28401	292	15	intelligent	intelligent	ADJ
bracis-28401	292	16	systems	system	NOUN
bracis-28401	292	17	.	.	PUNCT
bracis-28401	293	1	bracis	bracis	PROPN
bracis-28401	293	2	2023	2023	NUM
bracis-28401	293	3	.	.	PUNCT
bracis-28401	294	1	lecture	lecture	NOUN
bracis-28401	294	2	notes	note	NOUN
bracis-28401	294	3	in	in	ADP
bracis-28401	294	4	computer	computer	NOUN
bracis-28401	294	5	science	science	NOUN
bracis-28401	294	6	(	(	PUNCT
bracis-28401	294	7	)	)	PUNCT
bracis-28401	294	8	,	,	PUNCT
bracis-28401	294	9	vol	vol	NOUN
bracis-28401	294	10	14196	14196	NUM
bracis-28401	294	11	.	.	PUNCT
bracis-28401	295	1	springer	springer	NOUN
bracis-28401	295	2	,	,	PUNCT
bracis-28401	295	3	cham	cham	PROPN
bracis-28401	295	4	.	.	PUNCT
bracis-28401	296	1	https://doi.org/10.1007/978-3-031-45389-2_27	https://doi.org/10.1007/978-3-031-45389-2_27	PROPN
bracis-28401	296	2	download	download	NOUN
bracis-28401	296	3	citation	citation	NOUN
bracis-28401	296	4	.ris	.ris	PUNCT
bracis-28401	297	1	.enw	.enw	PROPN
bracis-28401	297	2	.bib	.bib	PUNCT
bracis-28401	298	1	doi	doi	PROPN
bracis-28401	298	2	:	:	PUNCT
bracis-28401	298	3	https://doi.org/10.1007/978-3-031-45389-2_27	https://doi.org/10.1007/978-3-031-45389-2_27	PROPN
bracis-28401	298	4	published	publish	VERB
bracis-28401	298	5	:	:	PUNCT
bracis-28401	298	6	12	12	NUM
bracis-28401	298	7	october	october	PROPN
bracis-28401	298	8	2023	2023	NUM
bracis-28401	298	9	publisher	publisher	NOUN
bracis-28401	298	10	name	name	NOUN
bracis-28401	298	11	:	:	PUNCT
bracis-28401	298	12	springer	springer	NOUN
bracis-28401	298	13	,	,	PUNCT
bracis-28401	298	14	cham	cham	PROPN
bracis-28401	298	15	print	print	PROPN
bracis-28401	298	16	isbn	isbn	PROPN
bracis-28401	298	17	:	:	PUNCT
bracis-28401	298	18	978	978	NUM
bracis-28401	298	19	-	-	SYM
bracis-28401	298	20	3	3	NUM
bracis-28401	298	21	-	-	PUNCT
bracis-28401	298	22	031	031	NUM
bracis-28401	298	23	-	-	PUNCT
bracis-28401	298	24	45388	45388	NUM
bracis-28401	298	25	-	-	SYM
bracis-28401	298	26	5	5	NUM
bracis-28401	298	27	online	online	ADJ
bracis-28401	298	28	isbn	isbn	NOUN
bracis-28401	298	29	:	:	PUNCT
bracis-28401	298	30	978	978	NUM
bracis-28401	298	31	-	-	SYM
bracis-28401	298	32	3	3	NUM
bracis-28401	298	33	-	-	PUNCT
bracis-28401	298	34	031	031	NUM
bracis-28401	298	35	-	-	PUNCT
bracis-28401	298	36	45389	45389	NUM
bracis-28401	298	37	-	-	SYM
bracis-28401	298	38	2	2	NUM
bracis-28401	298	39	ebook	ebook	NOUN
bracis-28401	298	40	packages	package	NOUN
bracis-28401	298	41	:	:	PUNCT
bracis-28401	298	42	computer	computer	NOUN
bracis-28401	298	43	sciencecomputer	sciencecomputer	NOUN
bracis-28401	298	44	science	science	NOUN
bracis-28401	298	45	(	(	PUNCT
bracis-28401	298	46	r0	r0	NOUN
bracis-28401	298	47	)	)	PUNCT
bracis-28401	298	48	share	share	VERB
bracis-28401	298	49	this	this	DET
bracis-28401	298	50	paper	paper	NOUN
bracis-28401	298	51	anyone	anyone	PRON
bracis-28401	298	52	you	you	PRON
bracis-28401	298	53	share	share	VERB
bracis-28401	298	54	the	the	DET
bracis-28401	298	55	following	follow	VERB
bracis-28401	298	56	link	link	NOUN
bracis-28401	298	57	with	with	ADP
bracis-28401	298	58	will	will	AUX
bracis-28401	298	59	be	be	AUX
bracis-28401	298	60	able	able	ADJ
bracis-28401	298	61	to	to	PART
bracis-28401	298	62	read	read	VERB
bracis-28401	298	63	this	this	DET
bracis-28401	298	64	content	content	NOUN
bracis-28401	298	65	:	:	PUNCT
bracis-28401	298	66	get	get	VERB
bracis-28401	298	67	shareable	shareable	ADJ
bracis-28401	298	68	linksorry	linksorry	NOUN
bracis-28401	298	69	,	,	PUNCT
bracis-28401	298	70	a	a	DET
bracis-28401	298	71	shareable	shareable	ADJ
bracis-28401	298	72	link	link	NOUN
bracis-28401	298	73	is	be	AUX
bracis-28401	298	74	not	not	PART
bracis-28401	298	75	currently	currently	ADV
bracis-28401	298	76	available	available	ADJ
bracis-28401	298	77	for	for	ADP
bracis-28401	298	78	this	this	DET
bracis-28401	298	79	article	article	NOUN
bracis-28401	298	80	.	.	PUNCT
bracis-28401	299	1	copy	copy	VERB
bracis-28401	299	2	shareable	shareable	ADJ
bracis-28401	299	3	link	link	NOUN
bracis-28401	299	4	to	to	PART
bracis-28401	299	5	clipboard	clipboard	NOUN
bracis-28401	299	6	provided	provide	VERB
bracis-28401	299	7	by	by	ADP
bracis-28401	299	8	the	the	DET
bracis-28401	299	9	springer	springer	NOUN
bracis-28401	299	10	nature	nature	PROPN
bracis-28401	299	11	sharedit	sharedit	PROPN
bracis-28401	299	12	content	content	NOUN
bracis-28401	299	13	-	-	PUNCT
bracis-28401	299	14	sharing	share	VERB
bracis-28401	299	15	initiative	initiative	NOUN
bracis-28401	299	16	keywords	keyword	NOUN
bracis-28401	299	17	running	run	VERB
bracis-28401	299	18	time	time	NOUN
bracis-28401	299	19	complexity	complexity	NOUN
bracis-28401	299	20	prediction	prediction	NOUN
bracis-28401	299	21	algorithm	algorithm	NOUN
bracis-28401	299	22	analysis	analysis	NOUN
bracis-28401	299	23	machine	machine	NOUN
bracis-28401	299	24	learning	learning	NOUN
bracis-28401	299	25	publish	publish	VERB
bracis-28401	299	26	with	with	ADP
bracis-28401	299	27	us	us	PROPN
bracis-28401	299	28	policies	policy	NOUN
bracis-28401	299	29	and	and	CCONJ
bracis-28401	299	30	ethics	ethic	NOUN
bracis-28401	299	31	profiles	profile	NOUN
bracis-28401	299	32	ricardo	ricardo	PROPN
bracis-28401	299	33	j.	j.	PROPN
bracis-28401	299	34	pfitscher	pfitscher	PROPN
bracis-28401	299	35	view	view	NOUN
bracis-28401	299	36	author	author	NOUN
bracis-28401	299	37	profile	profile	NOUN
bracis-28401	299	38	search	search	NOUN
bracis-28401	299	39	search	search	NOUN
bracis-28401	299	40	by	by	ADP
bracis-28401	299	41	keyword	keyword	NOUN
bracis-28401	299	42	or	or	CCONJ
bracis-28401	299	43	author	author	NOUN
bracis-28401	299	44	search	search	NOUN
bracis-28401	299	45	navigation	navigation	NOUN
bracis-28401	299	46	find	find	VERB
bracis-28401	299	47	a	a	DET
bracis-28401	299	48	journal	journal	NOUN
bracis-28401	299	49	publish	publish	VERB
bracis-28401	299	50	with	with	ADP
bracis-28401	299	51	us	we	PRON
bracis-28401	299	52	track	track	VERB
bracis-28401	299	53	your	your	PRON
bracis-28401	299	54	research	research	NOUN
bracis-28401	299	55	discover	discover	VERB
bracis-28401	299	56	content	content	NOUN
bracis-28401	299	57	journals	journal	NOUN
bracis-28401	299	58	a	a	DET
bracis-28401	299	59	-	-	PUNCT
bracis-28401	299	60	z	z	NOUN
bracis-28401	299	61	books	book	NOUN
bracis-28401	299	62	a	a	DET
bracis-28401	299	63	-	-	PUNCT
bracis-28401	299	64	z	z	NOUN
bracis-28401	299	65	publish	publish	NOUN
bracis-28401	299	66	with	with	ADP
bracis-28401	299	67	us	us	PROPN
bracis-28401	299	68	journal	journal	PROPN
bracis-28401	299	69	finder	finder	PROPN
bracis-28401	299	70	publish	publish	VERB
bracis-28401	299	71	your	your	PRON
bracis-28401	299	72	research	research	NOUN
bracis-28401	299	73	language	language	NOUN
bracis-28401	299	74	editing	edit	VERB
bracis-28401	299	75	open	open	ADJ
bracis-28401	299	76	access	access	NOUN
bracis-28401	299	77	publishing	publishing	NOUN
bracis-28401	299	78	products	product	NOUN
bracis-28401	299	79	and	and	CCONJ
bracis-28401	299	80	services	service	NOUN
bracis-28401	299	81	our	our	PRON
bracis-28401	299	82	products	product	NOUN
bracis-28401	299	83	librarians	librarian	VERB
bracis-28401	299	84	societies	society	NOUN
bracis-28401	299	85	partners	partner	NOUN
bracis-28401	299	86	and	and	CCONJ
bracis-28401	299	87	advertisers	advertiser	NOUN
bracis-28401	299	88	our	our	PRON
bracis-28401	299	89	brands	brand	NOUN
bracis-28401	299	90	springer	springer	NOUN
bracis-28401	299	91	nature	nature	PROPN
bracis-28401	299	92	portfolio	portfolio	PROPN
bracis-28401	299	93	bmc	bmc	PROPN
bracis-28401	299	94	palgrave	palgrave	PROPN
bracis-28401	299	95	macmillan	macmillan	PROPN
bracis-28401	299	96	apress	apress	PROPN
bracis-28401	299	97	discover	discover	VERB
bracis-28401	299	98	your	your	PRON
bracis-28401	299	99	privacy	privacy	NOUN
bracis-28401	299	100	choices	choice	NOUN
bracis-28401	299	101	/	/	SYM
bracis-28401	299	102	manage	manage	NOUN
bracis-28401	299	103	cookies	cookie	NOUN
bracis-28401	299	104	your	your	PRON
bracis-28401	299	105	us	us	PROPN
bracis-28401	300	1	state	state	NOUN
bracis-28401	300	2	privacy	privacy	NOUN
bracis-28401	300	3	rights	right	NOUN
bracis-28401	300	4	accessibility	accessibility	NOUN
bracis-28401	300	5	statement	statement	NOUN
bracis-28401	300	6	terms	term	NOUN
bracis-28401	300	7	and	and	CCONJ
bracis-28401	300	8	conditions	condition	NOUN
bracis-28401	300	9	privacy	privacy	NOUN
bracis-28401	300	10	policy	policy	NOUN
bracis-28401	300	11	help	help	NOUN
bracis-28401	300	12	and	and	CCONJ
bracis-28401	300	13	support	support	VERB
bracis-28401	300	14	legal	legal	ADJ
bracis-28401	300	15	notice	notice	NOUN
bracis-28401	300	16	cancel	cancel	VERB
bracis-28401	300	17	contracts	contract	NOUN
bracis-28401	300	18	here	here	ADV
bracis-28401	300	19	129.74.145.123	129.74.145.123	NUM
bracis-28401	300	20	hesburgh	hesburgh	PROPN
bracis-28401	300	21	library	library	PROPN
bracis-28401	300	22	er	er	INTJ
bracis-28401	300	23	unit	unit	NOUN
bracis-28401	300	24	(	(	PUNCT
bracis-28401	300	25	3005732405	3005732405	NUM
bracis-28401	300	26	)	)	PUNCT
bracis-28401	300	27	northeast	northeast	ADJ
bracis-28401	300	28	research	research	NOUN
bracis-28401	300	29	libraries	library	NOUN
bracis-28401	300	30	(	(	PUNCT
bracis-28401	300	31	nerl	nerl	PROPN
bracis-28401	300	32	)	)	PUNCT
bracis-28401	300	33	(	(	PUNCT
bracis-28401	300	34	8200828607	8200828607	NUM
bracis-28401	300	35	)	)	PUNCT
bracis-28401	300	36	nerl	nerl	VERB
bracis-28401	300	37	ta	ta	X
bracis-28401	300	38	account	account	NOUN
bracis-28401	300	39	(	(	PUNCT
bracis-28401	300	40	3006206169	3006206169	NUM
bracis-28401	300	41	)	)	PUNCT
bracis-28401	300	42	university	university	NOUN
bracis-28401	300	43	of	of	ADP
bracis-28401	300	44	notre	notre	PROPN
bracis-28401	300	45	dame	dame	PROPN
bracis-28401	300	46	hesburgh	hesburgh	PROPN
bracis-28401	300	47	library	library	NOUN
bracis-28401	300	48	(	(	PUNCT
bracis-28401	300	49	3000184373	3000184373	NUM
bracis-28401	300	50	)	)	PUNCT
bracis-28401	301	1	©	©	ADP
bracis-28401	301	2	2025	2025	NUM
bracis-28401	301	3	springer	springer	NOUN
bracis-28401	301	4	nature	nature	NOUN