id	sid	tid	token	lemma	pos
ajst-2538	1	1	academic	academic	ADJ
ajst-2538	1	2	journal	journal	NOUN
ajst-2538	1	3	of	of	ADP
ajst-2538	1	4	science	science	NOUN
ajst-2538	1	5	and	and	CCONJ
ajst-2538	1	6	technology	technology	NOUN
ajst-2538	1	7	issn	issn	NOUN
ajst-2538	1	8	:	:	PUNCT
ajst-2538	1	9	2771	2771	NUM
ajst-2538	1	10	-	-	SYM
ajst-2538	1	11	3032	3032	NUM
ajst-2538	1	12	|	|	NOUN
ajst-2538	1	13	vol	vol	NOUN
ajst-2538	1	14	.	.	PROPN
ajst-2538	2	1	3	3	NUM
ajst-2538	2	2	,	,	PUNCT
ajst-2538	2	3	no	no	INTJ
ajst-2538	2	4	.	.	NOUN
ajst-2538	2	5	3	3	NUM
ajst-2538	2	6	,	,	PUNCT
ajst-2538	2	7	2022	2022	NUM
ajst-2538	2	8	35	35	NUM
ajst-2538	2	9	a	a	DET
ajst-2538	2	10	review	review	NOUN
ajst-2538	2	11	of	of	ADP
ajst-2538	2	12	risks	risk	NOUN
ajst-2538	2	13	associated	associate	VERB
ajst-2538	2	14	with	with	ADP
ajst-2538	2	15	machine	machine	NOUN
ajst-2538	2	16	learning	learning	NOUN
ajst-2538	2	17	in	in	ADP
ajst-2538	2	18	application	application	NOUN
ajst-2538	2	19	to	to	ADP
ajst-2538	2	20	quantitative	quantitative	ADJ
ajst-2538	2	21	investment	investment	NOUN
ajst-2538	2	22	siyin	siyin	PROPN
ajst-2538	2	23	shen	shen	PROPN
ajst-2538	2	24	*	*	PROPN
ajst-2538	2	25	shanghai	shanghai	PROPN
ajst-2538	2	26	australia	australia	PROPN
ajst-2538	2	27	international	international	PROPN
ajst-2538	2	28	school	school	PROPN
ajst-2538	2	29	,	,	PUNCT
ajst-2538	2	30	shanghai	shanghai	PROPN
ajst-2538	2	31	200000	200000	NUM
ajst-2538	2	32	,	,	PUNCT
ajst-2538	2	33	china	china	PROPN
ajst-2538	2	34	*	*	PUNCT
ajst-2538	2	35	corresponding	correspond	VERB
ajst-2538	2	36	author	author	NOUN
ajst-2538	2	37	’s	’s	PART
ajst-2538	2	38	email	email	NOUN
ajst-2538	2	39	:	:	PUNCT
ajst-2538	3	1	xjf9699@126.com	xjf9699@126.com	PROPN
ajst-2538	3	2	abstract	abstract	NOUN
ajst-2538	3	3	:	:	PUNCT
ajst-2538	3	4	based	base	VERB
ajst-2538	3	5	on	on	ADP
ajst-2538	3	6	inspirations	inspiration	NOUN
ajst-2538	3	7	and	and	CCONJ
ajst-2538	3	8	ideas	idea	NOUN
ajst-2538	3	9	from	from	ADP
ajst-2538	3	10	relevant	relevant	ADJ
ajst-2538	3	11	literatures	literature	NOUN
ajst-2538	3	12	,	,	PUNCT
ajst-2538	3	13	this	this	DET
ajst-2538	3	14	paper	paper	NOUN
ajst-2538	3	15	evaluated	evaluate	VERB
ajst-2538	3	16	the	the	DET
ajst-2538	3	17	risks	risk	NOUN
ajst-2538	3	18	associated	associate	VERB
ajst-2538	3	19	with	with	ADP
ajst-2538	3	20	using	use	VERB
ajst-2538	3	21	random	random	ADJ
ajst-2538	3	22	forest	forest	NOUN
ajst-2538	3	23	,	,	PUNCT
ajst-2538	3	24	xg	xg	PROPN
ajst-2538	3	25	boost	boost	NOUN
ajst-2538	3	26	and	and	CCONJ
ajst-2538	3	27	logistic	logistic	ADJ
ajst-2538	3	28	regression	regression	NOUN
ajst-2538	3	29	for	for	ADP
ajst-2538	3	30	quantitative	quantitative	ADJ
ajst-2538	3	31	investment	investment	NOUN
ajst-2538	3	32	from	from	ADP
ajst-2538	3	33	the	the	DET
ajst-2538	3	34	perspective	perspective	NOUN
ajst-2538	3	35	of	of	ADP
ajst-2538	3	36	its	its	PRON
ajst-2538	3	37	accuracy	accuracy	NOUN
ajst-2538	3	38	,	,	PUNCT
ajst-2538	3	39	adaptability	adaptability	NOUN
ajst-2538	3	40	,	,	PUNCT
ajst-2538	3	41	efficiency	efficiency	NOUN
ajst-2538	3	42	,	,	PUNCT
ajst-2538	3	43	simplicity	simplicity	NOUN
ajst-2538	3	44	and	and	CCONJ
ajst-2538	3	45	interpretability	interpretability	NOUN
ajst-2538	3	46	.	.	PUNCT
ajst-2538	4	1	overall	overall	ADV
ajst-2538	4	2	,	,	PUNCT
ajst-2538	4	3	the	the	DET
ajst-2538	4	4	random	random	ADJ
ajst-2538	4	5	forest	forest	NOUN
ajst-2538	4	6	and	and	CCONJ
ajst-2538	4	7	the	the	DET
ajst-2538	4	8	xg	xg	PROPN
ajst-2538	4	9	boost	boost	NOUN
ajst-2538	4	10	contains	contain	VERB
ajst-2538	4	11	better	well	ADJ
ajst-2538	4	12	accuracy	accuracy	NOUN
ajst-2538	4	13	and	and	CCONJ
ajst-2538	4	14	have	have	VERB
ajst-2538	4	15	higher	high	ADJ
ajst-2538	4	16	adaptability	adaptability	NOUN
ajst-2538	4	17	than	than	ADP
ajst-2538	4	18	the	the	DET
ajst-2538	4	19	logistic	logistic	ADJ
ajst-2538	4	20	regression	regression	NOUN
ajst-2538	4	21	as	as	SCONJ
ajst-2538	4	22	they	they	PRON
ajst-2538	4	23	are	be	AUX
ajst-2538	4	24	susceptible	susceptible	ADJ
ajst-2538	4	25	to	to	ADP
ajst-2538	4	26	different	different	ADJ
ajst-2538	4	27	data	datum	NOUN
ajst-2538	4	28	types	type	NOUN
ajst-2538	4	29	.	.	PUNCT
ajst-2538	5	1	the	the	DET
ajst-2538	5	2	xg	xg	PROPN
ajst-2538	5	3	boost	boost	NOUN
ajst-2538	5	4	have	have	VERB
ajst-2538	5	5	the	the	DET
ajst-2538	5	6	fastest	fast	ADJ
ajst-2538	5	7	processing	processing	NOUN
ajst-2538	5	8	speed	speed	NOUN
ajst-2538	5	9	which	which	PRON
ajst-2538	5	10	gives	give	VERB
ajst-2538	5	11	it	it	PRON
ajst-2538	5	12	higher	high	ADJ
ajst-2538	5	13	efficiency	efficiency	NOUN
ajst-2538	5	14	over	over	ADP
ajst-2538	5	15	the	the	DET
ajst-2538	5	16	other	other	ADJ
ajst-2538	5	17	two	two	NUM
ajst-2538	5	18	,	,	PUNCT
ajst-2538	5	19	however	however	ADV
ajst-2538	5	20	it	it	PRON
ajst-2538	5	21	is	be	AUX
ajst-2538	5	22	also	also	ADV
ajst-2538	5	23	the	the	DET
ajst-2538	5	24	most	most	ADV
ajst-2538	5	25	difficult	difficult	ADJ
ajst-2538	5	26	to	to	PART
ajst-2538	5	27	implement	implement	VERB
ajst-2538	5	28	as	as	SCONJ
ajst-2538	5	29	it	it	PRON
ajst-2538	5	30	is	be	AUX
ajst-2538	5	31	written	write	VERB
ajst-2538	5	32	in	in	ADP
ajst-2538	5	33	c++	c++	NOUN
ajst-2538	5	34	.	.	PUNCT
ajst-2538	6	1	all	all	DET
ajst-2538	6	2	three	three	NUM
ajst-2538	6	3	algorithms	algorithm	NOUN
ajst-2538	6	4	are	be	AUX
ajst-2538	6	5	relatively	relatively	ADV
ajst-2538	6	6	clear	clear	ADJ
ajst-2538	6	7	and	and	CCONJ
ajst-2538	6	8	easy	easy	ADJ
ajst-2538	6	9	to	to	PART
ajst-2538	6	10	understand	understand	VERB
ajst-2538	6	11	.	.	PUNCT
ajst-2538	7	1	this	this	DET
ajst-2538	7	2	work	work	NOUN
ajst-2538	7	3	hopes	hope	VERB
ajst-2538	7	4	to	to	PART
ajst-2538	7	5	assist	assist	VERB
ajst-2538	7	6	investors	investor	NOUN
ajst-2538	7	7	in	in	ADP
ajst-2538	7	8	their	their	PRON
ajst-2538	7	9	decision	decision	NOUN
ajst-2538	7	10	making	make	VERB
ajst-2538	7	11	on	on	ADP
ajst-2538	7	12	which	which	DET
ajst-2538	7	13	model	model	NOUN
ajst-2538	7	14	to	to	PART
ajst-2538	7	15	use	use	VERB
ajst-2538	7	16	.	.	PUNCT
ajst-2538	8	1	keywords	keyword	NOUN
ajst-2538	8	2	:	:	PUNCT
ajst-2538	8	3	logistic	logistic	ADJ
ajst-2538	8	4	regression	regression	NOUN
ajst-2538	8	5	,	,	PUNCT
ajst-2538	8	6	random	random	ADJ
ajst-2538	8	7	forest	forest	NOUN
ajst-2538	8	8	,	,	PUNCT
ajst-2538	8	9	xg	xg	PROPN
ajst-2538	8	10	boost	boost	NOUN
ajst-2538	8	11	,	,	PUNCT
ajst-2538	8	12	risk	risk	NOUN
ajst-2538	8	13	evaluation	evaluation	NOUN
ajst-2538	8	14	.	.	PUNCT
ajst-2538	9	1	1	1	X
ajst-2538	9	2	.	.	X
ajst-2538	9	3	introduction	introduction	NOUN
ajst-2538	9	4	quantitative	quantitative	ADJ
ajst-2538	9	5	investment	investment	NOUN
ajst-2538	9	6	is	be	AUX
ajst-2538	9	7	associated	associate	VERB
ajst-2538	9	8	with	with	ADP
ajst-2538	9	9	using	use	VERB
ajst-2538	9	10	financial	financial	ADJ
ajst-2538	9	11	transactions	transaction	NOUN
ajst-2538	9	12	through	through	ADP
ajst-2538	9	13	quantifying	quantify	VERB
ajst-2538	9	14	methods	method	NOUN
ajst-2538	9	15	and	and	CCONJ
ajst-2538	9	16	computer	computer	NOUN
ajst-2538	9	17	programs	program	NOUN
ajst-2538	9	18	.	.	PUNCT
ajst-2538	10	1	through	through	ADP
ajst-2538	10	2	mining	mine	VERB
ajst-2538	10	3	large	large	ADJ
ajst-2538	10	4	amounts	amount	NOUN
ajst-2538	10	5	of	of	ADP
ajst-2538	10	6	data	datum	NOUN
ajst-2538	10	7	,	,	PUNCT
ajst-2538	10	8	machine	machine	NOUN
ajst-2538	10	9	learning	learning	NOUN
ajst-2538	10	10	methods	method	NOUN
ajst-2538	10	11	can	can	AUX
ajst-2538	10	12	obtain	obtain	VERB
ajst-2538	10	13	technical	technical	ADJ
ajst-2538	10	14	indicators	indicator	NOUN
ajst-2538	10	15	that	that	PRON
ajst-2538	10	16	are	be	AUX
ajst-2538	10	17	often	often	ADV
ajst-2538	10	18	ignored	ignore	VERB
ajst-2538	10	19	by	by	ADP
ajst-2538	10	20	traditional	traditional	ADJ
ajst-2538	10	21	methods	method	NOUN
ajst-2538	10	22	.	.	PUNCT
ajst-2538	11	1	through	through	ADP
ajst-2538	11	2	literature	literature	NOUN
ajst-2538	11	3	research	research	NOUN
ajst-2538	11	4	method	method	NOUN
ajst-2538	11	5	,	,	PUNCT
ajst-2538	11	6	this	this	DET
ajst-2538	11	7	paper	paper	NOUN
ajst-2538	11	8	was	be	AUX
ajst-2538	11	9	able	able	ADJ
ajst-2538	11	10	to	to	PART
ajst-2538	11	11	establish	establish	VERB
ajst-2538	11	12	an	an	DET
ajst-2538	11	13	evaluation	evaluation	NOUN
ajst-2538	11	14	on	on	ADP
ajst-2538	11	15	the	the	DET
ajst-2538	11	16	risks	risk	NOUN
ajst-2538	11	17	associated	associate	VERB
ajst-2538	11	18	with	with	ADP
ajst-2538	11	19	different	different	ADJ
ajst-2538	11	20	machine	machine	NOUN
ajst-2538	11	21	learning	learn	VERB
ajst-2538	11	22	algorithms	algorithm	NOUN
ajst-2538	11	23	in	in	ADP
ajst-2538	11	24	application	application	NOUN
ajst-2538	11	25	to	to	ADP
ajst-2538	11	26	quantitative	quantitative	ADJ
ajst-2538	11	27	investment	investment	NOUN
ajst-2538	11	28	.	.	PUNCT
ajst-2538	12	1	the	the	DET
ajst-2538	12	2	key	key	ADJ
ajst-2538	12	3	algorithms	algorithms	NOUN
ajst-2538	12	4	this	this	DET
ajst-2538	12	5	paper	paper	NOUN
ajst-2538	12	6	analysed	analyse	VERB
ajst-2538	12	7	include	include	VERB
ajst-2538	12	8	the	the	DET
ajst-2538	12	9	random	random	ADJ
ajst-2538	12	10	forest	forest	NOUN
ajst-2538	12	11	,	,	PUNCT
ajst-2538	12	12	xg	xg	PROPN
ajst-2538	12	13	boost	boost	NOUN
ajst-2538	12	14	,	,	PUNCT
ajst-2538	12	15	and	and	CCONJ
ajst-2538	12	16	logistic	logistic	ADJ
ajst-2538	12	17	regression	regression	NOUN
ajst-2538	12	18	.	.	PUNCT
ajst-2538	13	1	although	although	SCONJ
ajst-2538	13	2	many	many	ADJ
ajst-2538	13	3	past	past	ADJ
ajst-2538	13	4	researches	research	NOUN
ajst-2538	13	5	conducted	conduct	VERB
ajst-2538	13	6	a	a	DET
ajst-2538	13	7	comparison	comparison	NOUN
ajst-2538	13	8	between	between	ADP
ajst-2538	13	9	the	the	DET
ajst-2538	13	10	different	different	ADJ
ajst-2538	13	11	algorithms	algorithm	NOUN
ajst-2538	13	12	in	in	ADP
ajst-2538	13	13	the	the	DET
ajst-2538	13	14	fields	field	NOUN
ajst-2538	13	15	of	of	ADP
ajst-2538	13	16	quantitative	quantitative	ADJ
ajst-2538	13	17	investment	investment	NOUN
ajst-2538	13	18	,	,	PUNCT
ajst-2538	13	19	this	this	DET
ajst-2538	13	20	paper	paper	NOUN
ajst-2538	13	21	offers	offer	VERB
ajst-2538	13	22	a	a	DET
ajst-2538	13	23	new	new	ADJ
ajst-2538	13	24	approach	approach	NOUN
ajst-2538	13	25	as	as	SCONJ
ajst-2538	13	26	it	it	PRON
ajst-2538	13	27	breaks	break	VERB
ajst-2538	13	28	down	down	ADP
ajst-2538	13	29	the	the	DET
ajst-2538	13	30	factors	factor	NOUN
ajst-2538	13	31	that	that	PRON
ajst-2538	13	32	would	would	AUX
ajst-2538	13	33	affect	affect	VERB
ajst-2538	13	34	the	the	DET
ajst-2538	13	35	risk	risk	NOUN
ajst-2538	13	36	in	in	ADP
ajst-2538	13	37	using	use	VERB
ajst-2538	13	38	the	the	DET
ajst-2538	13	39	model	model	NOUN
ajst-2538	13	40	.	.	PUNCT
ajst-2538	14	1	the	the	DET
ajst-2538	14	2	paper	paper	NOUN
ajst-2538	14	3	would	would	AUX
ajst-2538	14	4	evaluate	evaluate	VERB
ajst-2538	14	5	each	each	PRON
ajst-2538	14	6	of	of	ADP
ajst-2538	14	7	the	the	DET
ajst-2538	14	8	following	follow	VERB
ajst-2538	14	9	components	component	NOUN
ajst-2538	14	10	;	;	PUNCT
ajst-2538	14	11	accuracy	accuracy	NOUN
ajst-2538	14	12	,	,	PUNCT
ajst-2538	14	13	adaptability	adaptability	NOUN
ajst-2538	14	14	,	,	PUNCT
ajst-2538	14	15	efficiency	efficiency	NOUN
ajst-2538	14	16	,	,	PUNCT
ajst-2538	14	17	simplicity	simplicity	NOUN
ajst-2538	14	18	and	and	CCONJ
ajst-2538	14	19	interpretability	interpretability	NOUN
ajst-2538	14	20	which	which	PRON
ajst-2538	14	21	would	would	AUX
ajst-2538	14	22	all	all	ADV
ajst-2538	14	23	play	play	VERB
ajst-2538	14	24	influence	influence	NOUN
ajst-2538	14	25	on	on	ADP
ajst-2538	14	26	the	the	DET
ajst-2538	14	27	model	model	NOUN
ajst-2538	14	28	failure	failure	NOUN
ajst-2538	14	29	risks	risk	NOUN
ajst-2538	14	30	and	and	CCONJ
ajst-2538	14	31	strategy	strategy	NOUN
ajst-2538	14	32	application	application	NOUN
ajst-2538	14	33	risks	risk	NOUN
ajst-2538	14	34	of	of	ADP
ajst-2538	14	35	quantitative	quantitative	ADJ
ajst-2538	14	36	investment	investment	NOUN
ajst-2538	14	37	.	.	PUNCT
ajst-2538	15	1	model	model	NOUN
ajst-2538	15	2	failure	failure	NOUN
ajst-2538	15	3	risk	risk	NOUN
ajst-2538	15	4	refers	refer	VERB
ajst-2538	15	5	to	to	ADP
ajst-2538	15	6	how	how	SCONJ
ajst-2538	15	7	changes	change	NOUN
ajst-2538	15	8	in	in	ADP
ajst-2538	15	9	the	the	DET
ajst-2538	15	10	market	market	NOUN
ajst-2538	15	11	could	could	AUX
ajst-2538	15	12	cause	cause	VERB
ajst-2538	15	13	the	the	DET
ajst-2538	15	14	strategies	strategy	NOUN
ajst-2538	15	15	applied	apply	VERB
ajst-2538	15	16	to	to	PART
ajst-2538	15	17	become	become	VERB
ajst-2538	15	18	invalid	invalid	ADJ
ajst-2538	15	19	.	.	PUNCT
ajst-2538	16	1	strategy	strategy	NOUN
ajst-2538	16	2	application	application	NOUN
ajst-2538	16	3	risk	risk	NOUN
ajst-2538	16	4	refers	refer	VERB
ajst-2538	16	5	to	to	ADP
ajst-2538	16	6	operational	operational	ADJ
ajst-2538	16	7	errors	error	NOUN
ajst-2538	16	8	or	or	CCONJ
ajst-2538	16	9	usage	usage	NOUN
ajst-2538	16	10	of	of	ADP
ajst-2538	16	11	unsuitable	unsuitable	ADJ
ajst-2538	16	12	parameters	parameter	NOUN
ajst-2538	16	13	which	which	PRON
ajst-2538	16	14	can	can	AUX
ajst-2538	16	15	lead	lead	VERB
ajst-2538	16	16	to	to	ADP
ajst-2538	16	17	risks	risk	NOUN
ajst-2538	16	18	in	in	ADP
ajst-2538	16	19	the	the	DET
ajst-2538	16	20	transaction	transaction	NOUN
ajst-2538	16	21	.	.	PUNCT
ajst-2538	17	1	increased	increase	VERB
ajst-2538	17	2	accuracy	accuracy	NOUN
ajst-2538	17	3	would	would	AUX
ajst-2538	17	4	result	result	VERB
ajst-2538	17	5	in	in	ADP
ajst-2538	17	6	lower	low	ADJ
ajst-2538	17	7	model	model	NOUN
ajst-2538	17	8	failure	failure	NOUN
ajst-2538	17	9	risks	risk	NOUN
ajst-2538	17	10	.	.	PUNCT
ajst-2538	18	1	the	the	DET
ajst-2538	18	2	adaptability	adaptability	NOUN
ajst-2538	18	3	of	of	ADP
ajst-2538	18	4	the	the	DET
ajst-2538	18	5	model	model	NOUN
ajst-2538	18	6	is	be	AUX
ajst-2538	18	7	important	important	ADJ
ajst-2538	18	8	to	to	PART
ajst-2538	18	9	face	face	VERB
ajst-2538	18	10	the	the	DET
ajst-2538	18	11	changes	change	NOUN
ajst-2538	18	12	in	in	ADP
ajst-2538	18	13	the	the	DET
ajst-2538	18	14	operational	operational	ADJ
ajst-2538	18	15	environment	environment	NOUN
ajst-2538	18	16	and	and	CCONJ
ajst-2538	18	17	would	would	AUX
ajst-2538	18	18	also	also	ADV
ajst-2538	18	19	lower	lower	VERB
ajst-2538	18	20	model	model	NOUN
ajst-2538	18	21	failure	failure	NOUN
ajst-2538	18	22	risks	risk	NOUN
ajst-2538	18	23	.	.	PUNCT
ajst-2538	19	1	greater	great	ADJ
ajst-2538	19	2	complexity	complexity	NOUN
ajst-2538	19	3	,	,	PUNCT
ajst-2538	19	4	and	and	CCONJ
ajst-2538	19	5	weaker	weak	ADJ
ajst-2538	19	6	interpretability	interpretability	NOUN
ajst-2538	19	7	would	would	AUX
ajst-2538	19	8	increase	increase	VERB
ajst-2538	19	9	the	the	DET
ajst-2538	19	10	difficulties	difficulty	NOUN
ajst-2538	19	11	for	for	SCONJ
ajst-2538	19	12	investors	investor	NOUN
ajst-2538	19	13	to	to	PART
ajst-2538	19	14	become	become	VERB
ajst-2538	19	15	familiar	familiar	ADJ
ajst-2538	19	16	with	with	ADP
ajst-2538	19	17	the	the	DET
ajst-2538	19	18	characteristics	characteristic	NOUN
ajst-2538	19	19	of	of	ADP
ajst-2538	19	20	the	the	DET
ajst-2538	19	21	model	model	NOUN
ajst-2538	19	22	.	.	PUNCT
ajst-2538	20	1	this	this	PRON
ajst-2538	20	2	,	,	PUNCT
ajst-2538	20	3	therefore	therefore	ADV
ajst-2538	20	4	,	,	PUNCT
ajst-2538	20	5	would	would	AUX
ajst-2538	20	6	increase	increase	VERB
ajst-2538	20	7	the	the	DET
ajst-2538	20	8	strategic	strategic	ADJ
ajst-2538	20	9	application	application	NOUN
ajst-2538	20	10	risks	risk	NOUN
ajst-2538	20	11	.	.	PUNCT
ajst-2538	21	1	the	the	DET
ajst-2538	21	2	efficiency	efficiency	NOUN
ajst-2538	21	3	of	of	ADP
ajst-2538	21	4	the	the	DET
ajst-2538	21	5	model	model	NOUN
ajst-2538	21	6	could	could	AUX
ajst-2538	21	7	allow	allow	VERB
ajst-2538	21	8	investors	investor	NOUN
ajst-2538	21	9	to	to	PART
ajst-2538	21	10	make	make	VERB
ajst-2538	21	11	decisions	decision	NOUN
ajst-2538	21	12	more	more	ADV
ajst-2538	21	13	quickly	quickly	ADV
ajst-2538	21	14	.	.	PUNCT
ajst-2538	22	1	2	2	X
ajst-2538	22	2	.	.	X
ajst-2538	22	3	random	random	ADJ
ajst-2538	22	4	forest	forest	NOUN
ajst-2538	22	5	2.1	2.1	NUM
ajst-2538	22	6	.	.	PUNCT
ajst-2538	22	7	introduction	introduction	NOUN
ajst-2538	22	8	to	to	ADP
ajst-2538	22	9	random	random	ADJ
ajst-2538	22	10	forest	forest	NOUN
ajst-2538	22	11	random	random	ADJ
ajst-2538	22	12	forest	forest	NOUN
ajst-2538	22	13	is	be	AUX
ajst-2538	22	14	a	a	DET
ajst-2538	22	15	combinatorial	combinatorial	ADJ
ajst-2538	22	16	classifier	classifier	NOUN
ajst-2538	22	17	algorithm	algorithm	NOUN
ajst-2538	22	18	which	which	PRON
ajst-2538	22	19	combines	combine	VERB
ajst-2538	22	20	bragging	bragging	NOUN
ajst-2538	22	21	and	and	CCONJ
ajst-2538	22	22	randomization	randomization	NOUN
ajst-2538	22	23	.	.	PUNCT
ajst-2538	23	1	it	it	PRON
ajst-2538	23	2	is	be	AUX
ajst-2538	23	3	composed	compose	VERB
ajst-2538	23	4	of	of	ADP
ajst-2538	23	5	many	many	ADJ
ajst-2538	23	6	single	single	ADJ
ajst-2538	23	7	classification	classification	NOUN
ajst-2538	23	8	regression	regression	NOUN
ajst-2538	23	9	trees	tree	NOUN
ajst-2538	23	10	,	,	PUNCT
ajst-2538	23	11	and	and	CCONJ
ajst-2538	23	12	the	the	DET
ajst-2538	23	13	generation	generation	NOUN
ajst-2538	23	14	of	of	ADP
ajst-2538	23	15	a	a	DET
ajst-2538	23	16	single	single	ADJ
ajst-2538	23	17	tree	tree	NOUN
ajst-2538	23	18	depends	depend	VERB
ajst-2538	23	19	on	on	ADP
ajst-2538	23	20	an	an	DET
ajst-2538	23	21	independent	independent	ADJ
ajst-2538	23	22	and	and	CCONJ
ajst-2538	23	23	identically	identically	ADV
ajst-2538	23	24	distributed	distribute	VERB
ajst-2538	23	25	random	random	ADJ
ajst-2538	23	26	vector	vector	NOUN
ajst-2538	23	27	.	.	PUNCT
ajst-2538	24	1	the	the	DET
ajst-2538	24	2	generalization	generalization	NOUN
ajst-2538	24	3	error	error	NOUN
ajst-2538	24	4	of	of	ADP
ajst-2538	24	5	the	the	DET
ajst-2538	24	6	whole	whole	ADJ
ajst-2538	24	7	tree	tree	NOUN
ajst-2538	24	8	depends	depend	VERB
ajst-2538	24	9	on	on	ADP
ajst-2538	24	10	the	the	DET
ajst-2538	24	11	classification	classification	NOUN
ajst-2538	24	12	efficiency	efficiency	NOUN
ajst-2538	24	13	of	of	ADP
ajst-2538	24	14	individual	individual	ADJ
ajst-2538	24	15	trees	tree	NOUN
ajst-2538	24	16	and	and	CCONJ
ajst-2538	24	17	the	the	DET
ajst-2538	24	18	degree	degree	NOUN
ajst-2538	24	19	of	of	ADP
ajst-2538	24	20	correlation	correlation	NOUN
ajst-2538	24	21	among	among	ADP
ajst-2538	24	22	the	the	DET
ajst-2538	24	23	trees	tree	NOUN
ajst-2538	24	24	.	.	PUNCT
ajst-2538	25	1	the	the	DET
ajst-2538	25	2	upper	upper	ADJ
ajst-2538	25	3	bound	bound	NOUN
ajst-2538	25	4	of	of	ADP
ajst-2538	25	5	generalization	generalization	NOUN
ajst-2538	25	6	error	error	NOUN
ajst-2538	25	7	∗	∗	NOUN
ajst-2538	25	8	of	of	ADP
ajst-2538	25	9	random	random	ADJ
ajst-2538	25	10	forest	forest	NOUN
ajst-2538	25	11	can	can	AUX
ajst-2538	25	12	be	be	AUX
ajst-2538	25	13	obtained	obtain	VERB
ajst-2538	25	14	as	as	ADP
ajst-2538	25	15	:	:	PUNCT
ajst-2538	25	16	∗	∗	NOUN
ajst-2538	25	17	̅	̅	NOUN
ajst-2538	25	18	1	1	NUM
ajst-2538	25	19	/	/	SYM
ajst-2538	25	20	where	where	SCONJ
ajst-2538	25	21	s	s	NOUN
ajst-2538	25	22	is	be	AUX
ajst-2538	25	23	the	the	DET
ajst-2538	25	24	overall	overall	ADJ
ajst-2538	25	25	classification	classification	NOUN
ajst-2538	25	26	efficiency	efficiency	NOUN
ajst-2538	25	27	of	of	ADP
ajst-2538	25	28	the	the	DET
ajst-2538	25	29	combinatorial	combinatorial	ADJ
ajst-2538	25	30	classifier	classifier	NOUN
ajst-2538	25	31	2.2	2.2	NUM
ajst-2538	25	32	.	.	PUNCT
ajst-2538	26	1	risk	risk	NOUN
ajst-2538	26	2	evaluation	evaluation	NOUN
ajst-2538	26	3	on	on	ADP
ajst-2538	26	4	random	random	ADJ
ajst-2538	26	5	forest	forest	NOUN
ajst-2538	26	6	2.2.1	2.2.1	NUM
ajst-2538	26	7	.	.	PUNCT
ajst-2538	27	1	accuracy	accuracy	NOUN
ajst-2538	27	2	assuming	assume	VERB
ajst-2538	27	3	s	s	VERB
ajst-2538	27	4	>	>	X
ajst-2538	27	5	0	0	PROPN
ajst-2538	27	6	,	,	PUNCT
ajst-2538	27	7	when	when	SCONJ
ajst-2538	27	8	there	there	PRON
ajst-2538	27	9	are	be	VERB
ajst-2538	27	10	enough	enough	ADJ
ajst-2538	27	11	classification	classification	NOUN
ajst-2538	27	12	trees	tree	NOUN
ajst-2538	27	13	in	in	ADP
ajst-2538	27	14	the	the	DET
ajst-2538	27	15	random	random	ADJ
ajst-2538	27	16	forest	forest	NOUN
ajst-2538	27	17	,	,	PUNCT
ajst-2538	27	18	the	the	DET
ajst-2538	27	19	generalization	generalization	NOUN
ajst-2538	27	20	error	error	NOUN
ajst-2538	27	21	of	of	ADP
ajst-2538	27	22	converges	converge	NOUN
ajst-2538	27	23	to	to	ADP
ajst-2538	27	24	a	a	DET
ajst-2538	27	25	finite	finite	ADJ
ajst-2538	27	26	value	value	NOUN
ajst-2538	27	27	everywhere	everywhere	ADV
ajst-2538	27	28	.	.	PUNCT
ajst-2538	28	1	therefore	therefore	ADV
ajst-2538	28	2	,	,	PUNCT
ajst-2538	28	3	as	as	SCONJ
ajst-2538	28	4	the	the	DET
ajst-2538	28	5	number	number	NOUN
ajst-2538	28	6	of	of	ADP
ajst-2538	28	7	classification	classification	NOUN
ajst-2538	28	8	trees	tree	NOUN
ajst-2538	28	9	increases	increase	NOUN
ajst-2538	28	10	,	,	PUNCT
ajst-2538	28	11	risk	risk	NOUN
ajst-2538	28	12	of	of	ADP
ajst-2538	28	13	overfitting	overfitting	NOUN
ajst-2538	28	14	is	be	AUX
ajst-2538	28	15	reduced	reduce	VERB
ajst-2538	28	16	.	.	PUNCT
ajst-2538	29	1	however	however	ADV
ajst-2538	29	2	,	,	PUNCT
ajst-2538	29	3	when	when	SCONJ
ajst-2538	29	4	it	it	PRON
ajst-2538	29	5	comes	come	VERB
ajst-2538	29	6	across	across	ADP
ajst-2538	29	7	classification	classification	NOUN
ajst-2538	29	8	and	and	CCONJ
ajst-2538	29	9	regression	regression	NOUN
ajst-2538	29	10	problems	problem	NOUN
ajst-2538	29	11	with	with	ADP
ajst-2538	29	12	large	large	ADJ
ajst-2538	29	13	noise	noise	NOUN
ajst-2538	29	14	,	,	PUNCT
ajst-2538	29	15	the	the	DET
ajst-2538	29	16	random	random	ADJ
ajst-2538	29	17	forest	forest	NOUN
ajst-2538	29	18	algorithm	algorithm	NOUN
ajst-2538	29	19	can	can	AUX
ajst-2538	29	20	easily	easily	ADV
ajst-2538	29	21	become	become	VERB
ajst-2538	29	22	overfit	overfit	NOUN
ajst-2538	29	23	.	.	PUNCT
ajst-2538	30	1	for	for	ADP
ajst-2538	30	2	data	datum	NOUN
ajst-2538	30	3	with	with	ADP
ajst-2538	30	4	imbalances	imbalance	NOUN
ajst-2538	30	5	,	,	PUNCT
ajst-2538	30	6	the	the	DET
ajst-2538	30	7	random	random	ADJ
ajst-2538	30	8	forest	forest	NOUN
ajst-2538	30	9	algorithm	algorithm	NOUN
ajst-2538	30	10	can	can	AUX
ajst-2538	30	11	effectively	effectively	ADV
ajst-2538	30	12	balance	balance	VERB
ajst-2538	30	13	these	these	DET
ajst-2538	30	14	errors	error	NOUN
ajst-2538	30	15	.	.	PUNCT
ajst-2538	31	1	for	for	ADP
ajst-2538	31	2	data	datum	NOUN
ajst-2538	31	3	with	with	ADP
ajst-2538	31	4	missing	miss	VERB
ajst-2538	31	5	values	value	NOUN
ajst-2538	31	6	,	,	PUNCT
ajst-2538	31	7	the	the	DET
ajst-2538	31	8	random	random	ADJ
ajst-2538	31	9	forest	forest	NOUN
ajst-2538	31	10	algorithm	algorithm	NOUN
ajst-2538	31	11	has	have	VERB
ajst-2538	31	12	a	a	DET
ajst-2538	31	13	relatively	relatively	ADV
ajst-2538	31	14	large	large	ADJ
ajst-2538	31	15	processing	processing	NOUN
ajst-2538	31	16	capacity	capacity	NOUN
ajst-2538	31	17	for	for	ADP
ajst-2538	31	18	missing	miss	VERB
ajst-2538	31	19	problems	problem	NOUN
ajst-2538	31	20	.	.	PUNCT
ajst-2538	32	1	for	for	ADP
ajst-2538	32	2	out	out	ADV
ajst-2538	32	3	-	-	PUNCT
ajst-2538	32	4	of	of	ADP
ajst-2538	32	5	-	-	PUNCT
ajst-2538	32	6	set	set	VERB
ajst-2538	32	7	data	datum	NOUN
ajst-2538	32	8	,	,	PUNCT
ajst-2538	32	9	an	an	DET
ajst-2538	32	10	unbiased	unbiased	ADJ
ajst-2538	32	11	estimate	estimate	NOUN
ajst-2538	32	12	of	of	ADP
ajst-2538	32	13	the	the	DET
ajst-2538	32	14	true	true	ADJ
ajst-2538	32	15	error	error	NOUN
ajst-2538	32	16	can	can	AUX
ajst-2538	32	17	be	be	AUX
ajst-2538	32	18	obtained	obtain	VERB
ajst-2538	32	19	during	during	ADP
ajst-2538	32	20	model	model	NOUN
ajst-2538	32	21	generation	generation	NOUN
ajst-2538	32	22	without	without	ADP
ajst-2538	32	23	loss	loss	NOUN
ajst-2538	32	24	of	of	ADP
ajst-2538	32	25	training	training	NOUN
ajst-2538	32	26	data	datum	NOUN
ajst-2538	32	27	.	.	PUNCT
ajst-2538	33	1	on	on	ADP
ajst-2538	33	2	the	the	DET
ajst-2538	33	3	other	other	ADJ
ajst-2538	33	4	hand	hand	NOUN
ajst-2538	33	5	,	,	PUNCT
ajst-2538	33	6	guan	guan	PROPN
ajst-2538	33	7	runjing	runjing	PROPN
ajst-2538	33	8	’s	’s	PART
ajst-2538	33	9	paper	paper	NOUN
ajst-2538	33	10	showed	show	VERB
ajst-2538	33	11	that	that	SCONJ
ajst-2538	33	12	when	when	SCONJ
ajst-2538	33	13	the	the	DET
ajst-2538	33	14	market	market	NOUN
ajst-2538	33	15	is	be	AUX
ajst-2538	33	16	poor	poor	ADJ
ajst-2538	33	17	,	,	PUNCT
ajst-2538	33	18	the	the	DET
ajst-2538	33	19	random	random	ADJ
ajst-2538	33	20	forest	forest	NOUN
ajst-2538	33	21	multi	multi	ADJ
ajst-2538	33	22	-	-	ADJ
ajst-2538	33	23	factor	factor	NOUN
ajst-2538	33	24	stock	stock	NOUN
ajst-2538	33	25	selection	selection	NOUN
ajst-2538	33	26	model	model	NOUN
ajst-2538	33	27	can	can	AUX
ajst-2538	33	28	not	not	PART
ajst-2538	33	29	create	create	VERB
ajst-2538	33	30	stable	stable	ADJ
ajst-2538	33	31	positive	positive	ADJ
ajst-2538	33	32	interests	interest	NOUN
ajst-2538	33	33	in	in	ADP
ajst-2538	33	34	the	the	DET
ajst-2538	33	35	stock	stock	NOUN
ajst-2538	33	36	market	market	NOUN
ajst-2538	33	37	,	,	PUNCT
ajst-2538	33	38	so	so	SCONJ
ajst-2538	33	39	it	it	PRON
ajst-2538	33	40	can	can	AUX
ajst-2538	33	41	not	not	PART
ajst-2538	33	42	be	be	AUX
ajst-2538	33	43	applied	apply	VERB
ajst-2538	33	44	to	to	ADP
ajst-2538	33	45	actual	actual	ADJ
ajst-2538	33	46	transactions	transaction	NOUN
ajst-2538	33	47	and	and	CCONJ
ajst-2538	33	48	needs	need	VERB
ajst-2538	33	49	improvement	improvement	NOUN
ajst-2538	33	50	[	[	X
ajst-2538	33	51	1	1	NUM
ajst-2538	33	52	]	]	PUNCT
ajst-2538	33	53	.	.	PUNCT
ajst-2538	34	1	2.2.2	2.2.2	X
ajst-2538	34	2	.	.	PUNCT
ajst-2538	35	1	adaptability	adaptability	NOUN
ajst-2538	35	2	due	due	ADP
ajst-2538	35	3	to	to	ADP
ajst-2538	35	4	the	the	DET
ajst-2538	35	5	combination	combination	NOUN
ajst-2538	35	6	of	of	ADP
ajst-2538	35	7	trees	tree	NOUN
ajst-2538	35	8	,	,	PUNCT
ajst-2538	35	9	the	the	DET
ajst-2538	35	10	random	random	ADJ
ajst-2538	35	11	forest	forest	NOUN
ajst-2538	35	12	can	can	AUX
ajst-2538	35	13	process	process	VERB
ajst-2538	35	14	nonlinear	nonlinear	ADJ
ajst-2538	35	15	data	datum	NOUN
ajst-2538	35	16	and	and	CCONJ
ajst-2538	35	17	can	can	AUX
ajst-2538	35	18	handle	handle	VERB
ajst-2538	35	19	both	both	CCONJ
ajst-2538	35	20	discrete	discrete	ADJ
ajst-2538	35	21	and	and	CCONJ
ajst-2538	35	22	continuous	continuous	ADJ
ajst-2538	35	23	data	datum	NOUN
ajst-2538	35	24	without	without	ADP
ajst-2538	35	25	normalization	normalization	NOUN
ajst-2538	35	26	.	.	PUNCT
ajst-2538	36	1	liu	liu	PROPN
ajst-2538	36	2	wei	wei	PROPN
ajst-2538	36	3	and	and	CCONJ
ajst-2538	36	4	others	other	NOUN
ajst-2538	36	5	found	find	VERB
ajst-2538	36	6	that	that	SCONJ
ajst-2538	36	7	the	the	DET
ajst-2538	36	8	nonlinear	nonlinear	ADJ
ajst-2538	36	9	characteristic	characteristic	NOUN
ajst-2538	36	10	of	of	ADP
ajst-2538	36	11	their	their	PRON
ajst-2538	36	12	forecast	forecast	NOUN
ajst-2538	36	13	model	model	NOUN
ajst-2538	36	14	based	base	VERB
ajst-2538	36	15	on	on	ADP
ajst-2538	36	16	random	random	ADJ
ajst-2538	36	17	forest	forest	NOUN
ajst-2538	36	18	would	would	AUX
ajst-2538	36	19	reduce	reduce	VERB
ajst-2538	36	20	model	model	NOUN
ajst-2538	36	21	mismatches	mismatch	NOUN
ajst-2538	36	22	as	as	SCONJ
ajst-2538	36	23	its	its	PRON
ajst-2538	36	24	accuracy	accuracy	NOUN
ajst-2538	36	25	is	be	AUX
ajst-2538	36	26	not	not	PART
ajst-2538	36	27	susceptible	susceptible	ADJ
ajst-2538	36	28	to	to	ADP
ajst-2538	36	29	model	model	NOUN
ajst-2538	36	30	definition	definition	NOUN
ajst-2538	36	31	errors	error	NOUN
ajst-2538	36	32	[	[	X
ajst-2538	36	33	2	2	NUM
ajst-2538	36	34	]	]	PUNCT
ajst-2538	36	35	.	.	PUNCT
ajst-2538	37	1	in	in	ADP
ajst-2538	37	2	36	36	NUM
ajst-2538	37	3	addition	addition	NOUN
ajst-2538	37	4	,	,	PUNCT
ajst-2538	37	5	it	it	PRON
ajst-2538	37	6	is	be	AUX
ajst-2538	37	7	suitable	suitable	ADJ
ajst-2538	37	8	for	for	ADP
ajst-2538	37	9	the	the	DET
ajst-2538	37	10	many	many	ADJ
ajst-2538	37	11	characteristic	characteristic	ADJ
ajst-2538	37	12	factors	factor	NOUN
ajst-2538	37	13	of	of	ADP
ajst-2538	37	14	the	the	DET
ajst-2538	37	15	fund	fund	NOUN
ajst-2538	37	16	’s	’s	PART
ajst-2538	37	17	heavy	heavy	ADJ
ajst-2538	37	18	stock	stock	NOUN
ajst-2538	37	19	holding	holding	NOUN
ajst-2538	37	20	and	and	CCONJ
ajst-2538	37	21	can	can	AUX
ajst-2538	37	22	be	be	AUX
ajst-2538	37	23	applied	apply	VERB
ajst-2538	37	24	to	to	ADP
ajst-2538	37	25	largescale	largescale	ADJ
ajst-2538	37	26	datasets	dataset	NOUN
ajst-2538	37	27	,	,	PUNCT
ajst-2538	37	28	which	which	PRON
ajst-2538	37	29	is	be	AUX
ajst-2538	37	30	suitable	suitable	ADJ
ajst-2538	37	31	to	to	ADP
ajst-2538	37	32	the	the	DET
ajst-2538	37	33	complexity	complexity	NOUN
ajst-2538	37	34	of	of	ADP
ajst-2538	37	35	the	the	DET
ajst-2538	37	36	financial	financial	ADJ
ajst-2538	37	37	market	market	NOUN
ajst-2538	37	38	.	.	PUNCT
ajst-2538	38	1	dierefich	dierefich	PROPN
ajst-2538	38	2	proved	prove	VERB
ajst-2538	38	3	through	through	ADP
ajst-2538	38	4	experiences	experience	NOUN
ajst-2538	38	5	,	,	PUNCT
ajst-2538	38	6	the	the	DET
ajst-2538	38	7	combination	combination	NOUN
ajst-2538	38	8	of	of	ADP
ajst-2538	38	9	bragging	brag	VERB
ajst-2538	38	10	method	method	NOUN
ajst-2538	38	11	and	and	CCONJ
ajst-2538	38	12	randomization	randomization	NOUN
ajst-2538	38	13	can	can	AUX
ajst-2538	38	14	effectively	effectively	ADV
ajst-2538	38	15	reduce	reduce	VERB
ajst-2538	38	16	the	the	DET
ajst-2538	38	17	influence	influence	NOUN
ajst-2538	38	18	of	of	ADP
ajst-2538	38	19	noise	noise	NOUN
ajst-2538	38	20	,	,	PUNCT
ajst-2538	38	21	and	and	CCONJ
ajst-2538	38	22	hence	hence	ADV
ajst-2538	38	23	random	random	ADJ
ajst-2538	38	24	forest	forest	NOUN
ajst-2538	38	25	can	can	AUX
ajst-2538	38	26	effectively	effectively	ADV
ajst-2538	38	27	process	process	VERB
ajst-2538	38	28	the	the	DET
ajst-2538	38	29	data	datum	NOUN
ajst-2538	38	30	containing	contain	VERB
ajst-2538	38	31	noise	noise	NOUN
ajst-2538	38	32	[	[	X
ajst-2538	38	33	3	3	NUM
ajst-2538	38	34	]	]	PUNCT
ajst-2538	38	35	.	.	PUNCT
ajst-2538	39	1	random	random	ADJ
ajst-2538	39	2	forest	forest	NOUN
ajst-2538	39	3	is	be	AUX
ajst-2538	39	4	also	also	ADV
ajst-2538	39	5	suitable	suitable	ADJ
ajst-2538	39	6	for	for	ADP
ajst-2538	39	7	feature	feature	NOUN
ajst-2538	39	8	selection	selection	NOUN
ajst-2538	39	9	of	of	ADP
ajst-2538	39	10	highdimensional	highdimensional	ADJ
ajst-2538	39	11	input	input	NOUN
ajst-2538	39	12	space	space	NOUN
ajst-2538	39	13	and	and	CCONJ
ajst-2538	39	14	have	have	VERB
ajst-2538	39	15	strong	strong	ADJ
ajst-2538	39	16	adaptability	adaptability	NOUN
ajst-2538	39	17	to	to	ADP
ajst-2538	39	18	changing	change	VERB
ajst-2538	39	19	data	datum	NOUN
ajst-2538	39	20	.	.	PUNCT
ajst-2538	40	1	2.2.3	2.2.3	X
ajst-2538	40	2	.	.	X
ajst-2538	40	3	efficiency	efficiency	NOUN
ajst-2538	40	4	random	random	ADJ
ajst-2538	40	5	forest	forest	NOUN
ajst-2538	40	6	obtains	obtain	VERB
ajst-2538	40	7	the	the	DET
ajst-2538	40	8	efficiency	efficiency	NOUN
ajst-2538	40	9	of	of	ADP
ajst-2538	40	10	single	single	ADJ
ajst-2538	40	11	classification	classification	NOUN
ajst-2538	40	12	tree	tree	NOUN
ajst-2538	40	13	and	and	CCONJ
ajst-2538	40	14	have	have	VERB
ajst-2538	40	15	a	a	DET
ajst-2538	40	16	relatively	relatively	ADV
ajst-2538	40	17	fast	fast	ADJ
ajst-2538	40	18	training	training	NOUN
ajst-2538	40	19	speed	speed	NOUN
ajst-2538	40	20	.	.	PUNCT
ajst-2538	41	1	zhang	zhang	PROPN
ajst-2538	41	2	xiao	xiao	PROPN
ajst-2538	41	3	constructs	construct	VERB
ajst-2538	41	4	a	a	DET
ajst-2538	41	5	trend	trend	NOUN
ajst-2538	41	6	-	-	PUNCT
ajst-2538	41	7	tracking	track	VERB
ajst-2538	41	8	model	model	NOUN
ajst-2538	41	9	based	base	VERB
ajst-2538	41	10	on	on	ADP
ajst-2538	41	11	rfgb	rfgb	PROPN
ajst-2538	41	12	algorithm	algorithm	NOUN
ajst-2538	41	13	.	.	PUNCT
ajst-2538	42	1	he	he	PRON
ajst-2538	42	2	found	find	VERB
ajst-2538	42	3	that	that	SCONJ
ajst-2538	42	4	random	random	ADJ
ajst-2538	42	5	forest	forest	NOUN
ajst-2538	42	6	reduced	reduce	VERB
ajst-2538	42	7	the	the	DET
ajst-2538	42	8	number	number	NOUN
ajst-2538	42	9	of	of	ADP
ajst-2538	42	10	tuning	tune	VERB
ajst-2538	42	11	parameters	parameter	NOUN
ajst-2538	42	12	needs	need	NOUN
ajst-2538	42	13	of	of	ADP
ajst-2538	42	14	gbdt	gbdt	NOUN
ajst-2538	42	15	algorithm	algorithm	NOUN
ajst-2538	42	16	and	and	CCONJ
ajst-2538	42	17	improve	improve	VERB
ajst-2538	42	18	the	the	DET
ajst-2538	42	19	training	training	NOUN
ajst-2538	42	20	speed	speed	NOUN
ajst-2538	42	21	[	[	X
ajst-2538	42	22	4	4	NUM
ajst-2538	42	23	]	]	PUNCT
ajst-2538	42	24	.	.	PUNCT
ajst-2538	43	1	however	however	ADV
ajst-2538	43	2	,	,	PUNCT
ajst-2538	43	3	the	the	DET
ajst-2538	43	4	efficiency	efficiency	NOUN
ajst-2538	43	5	of	of	ADP
ajst-2538	43	6	random	random	ADJ
ajst-2538	43	7	forest	forest	NOUN
ajst-2538	43	8	algorithm	algorithm	NOUN
ajst-2538	43	9	is	be	AUX
ajst-2538	43	10	compromised	compromise	VERB
ajst-2538	43	11	when	when	SCONJ
ajst-2538	43	12	dealing	deal	VERB
ajst-2538	43	13	with	with	ADP
ajst-2538	43	14	unbalanced	unbalanced	ADJ
ajst-2538	43	15	data	datum	NOUN
ajst-2538	43	16	or	or	CCONJ
ajst-2538	43	17	continuous	continuous	ADJ
ajst-2538	43	18	data	datum	NOUN
ajst-2538	43	19	.	.	PUNCT
ajst-2538	44	1	li	li	PROPN
ajst-2538	44	2	xiang	xiang	PROPN
ajst-2538	44	3	concluded	conclude	VERB
ajst-2538	44	4	that	that	SCONJ
ajst-2538	44	5	the	the	DET
ajst-2538	44	6	xg	xg	PROPN
ajst-2538	44	7	boost	boost	PROPN
ajst-2538	44	8	algorithm	algorithm	NOUN
ajst-2538	44	9	have	have	VERB
ajst-2538	44	10	stability	stability	NOUN
ajst-2538	44	11	over	over	ADP
ajst-2538	44	12	random	random	ADJ
ajst-2538	44	13	forest	forest	NOUN
ajst-2538	45	1	[	[	X
ajst-2538	45	2	5	5	NUM
ajst-2538	45	3	]	]	PUNCT
ajst-2538	45	4	,	,	PUNCT
ajst-2538	45	5	while	while	SCONJ
ajst-2538	45	6	zhu	zhu	PROPN
ajst-2538	45	7	yangbao	yangbao	PROPN
ajst-2538	45	8	concluded	conclude	VERB
ajst-2538	45	9	that	that	SCONJ
ajst-2538	45	10	though	though	SCONJ
ajst-2538	45	11	random	random	ADJ
ajst-2538	45	12	forest	forest	NOUN
ajst-2538	45	13	have	have	VERB
ajst-2538	45	14	good	good	ADJ
ajst-2538	45	15	stock	stock	NOUN
ajst-2538	45	16	selection	selection	NOUN
ajst-2538	45	17	capabilities	capability	NOUN
ajst-2538	45	18	,	,	PUNCT
ajst-2538	45	19	xg	xg	PROPN
ajst-2538	45	20	boost	boost	NOUN
ajst-2538	45	21	have	have	VERB
ajst-2538	45	22	better	well	ADJ
ajst-2538	45	23	stock	stock	NOUN
ajst-2538	45	24	selection	selection	NOUN
ajst-2538	45	25	capabilities	capability	NOUN
ajst-2538	45	26	and	and	CCONJ
ajst-2538	45	27	are	be	AUX
ajst-2538	45	28	faster	fast	ADJ
ajst-2538	45	29	than	than	ADP
ajst-2538	45	30	the	the	DET
ajst-2538	45	31	random	random	ADJ
ajst-2538	45	32	forest	forest	NOUN
ajst-2538	45	33	when	when	SCONJ
ajst-2538	45	34	applied	apply	VERB
ajst-2538	45	35	to	to	PART
ajst-2538	45	36	quantify	quantify	VERB
ajst-2538	45	37	stock	stock	NOUN
ajst-2538	45	38	selection	selection	NOUN
ajst-2538	45	39	[	[	X
ajst-2538	45	40	6	6	NUM
ajst-2538	45	41	]	]	PUNCT
ajst-2538	45	42	.	.	PUNCT
ajst-2538	46	1	2.2.4	2.2.4	X
ajst-2538	46	2	.	.	X
ajst-2538	46	3	interpretability	interpretability	NOUN
ajst-2538	46	4	random	random	ADJ
ajst-2538	46	5	forest	forest	NOUN
ajst-2538	46	6	is	be	AUX
ajst-2538	46	7	easy	easy	ADJ
ajst-2538	46	8	to	to	PART
ajst-2538	46	9	interpret	interpret	VERB
ajst-2538	46	10	.	.	PUNCT
ajst-2538	47	1	after	after	ADP
ajst-2538	47	2	training	train	VERB
ajst-2538	47	3	the	the	DET
ajst-2538	47	4	model	model	NOUN
ajst-2538	47	5	using	use	VERB
ajst-2538	47	6	the	the	DET
ajst-2538	47	7	random	random	ADJ
ajst-2538	47	8	forest	forest	NOUN
ajst-2538	47	9	algorithm	algorithm	NOUN
ajst-2538	47	10	,	,	PUNCT
ajst-2538	47	11	the	the	DET
ajst-2538	47	12	algorithm	algorithm	NOUN
ajst-2538	47	13	can	can	AUX
ajst-2538	47	14	determine	determine	VERB
ajst-2538	47	15	which	which	DET
ajst-2538	47	16	features	feature	NOUN
ajst-2538	47	17	are	be	AUX
ajst-2538	47	18	important	important	ADJ
ajst-2538	47	19	and	and	CCONJ
ajst-2538	47	20	the	the	DET
ajst-2538	47	21	random	random	ADJ
ajst-2538	47	22	forest	forest	NOUN
ajst-2538	47	23	algorithm	algorithm	NOUN
ajst-2538	47	24	can	can	AUX
ajst-2538	47	25	be	be	AUX
ajst-2538	47	26	used	use	VERB
ajst-2538	47	27	to	to	PART
ajst-2538	47	28	make	make	VERB
ajst-2538	47	29	feature	feature	NOUN
ajst-2538	47	30	selection	selection	NOUN
ajst-2538	47	31	.	.	PUNCT
ajst-2538	48	1	2.2.5	2.2.5	X
ajst-2538	48	2	.	.	X
ajst-2538	48	3	simplicity	simplicity	NOUN
ajst-2538	48	4	due	due	ADP
ajst-2538	48	5	to	to	ADP
ajst-2538	48	6	the	the	DET
ajst-2538	48	7	large	large	ADJ
ajst-2538	48	8	number	number	NOUN
ajst-2538	48	9	of	of	ADP
ajst-2538	48	10	stock	stock	NOUN
ajst-2538	48	11	data	datum	NOUN
ajst-2538	48	12	features	feature	NOUN
ajst-2538	48	13	and	and	CCONJ
ajst-2538	48	14	high	high	ADJ
ajst-2538	48	15	noise	noise	NOUN
ajst-2538	48	16	,	,	PUNCT
ajst-2538	48	17	random	random	ADJ
ajst-2538	48	18	forest	forest	NOUN
ajst-2538	48	19	is	be	AUX
ajst-2538	48	20	considered	consider	VERB
ajst-2538	48	21	to	to	PART
ajst-2538	48	22	be	be	AUX
ajst-2538	48	23	introduced	introduce	VERB
ajst-2538	48	24	into	into	ADP
ajst-2538	48	25	the	the	DET
ajst-2538	48	26	feature	feature	NOUN
ajst-2538	48	27	selection	selection	NOUN
ajst-2538	48	28	of	of	ADP
ajst-2538	48	29	the	the	DET
ajst-2538	48	30	model	model	NOUN
ajst-2538	48	31	.	.	PUNCT
ajst-2538	49	1	random	random	ADJ
ajst-2538	49	2	forest	forest	NOUN
ajst-2538	49	3	is	be	AUX
ajst-2538	49	4	simple	simple	ADJ
ajst-2538	49	5	in	in	ADP
ajst-2538	49	6	its	its	PRON
ajst-2538	49	7	application	application	NOUN
ajst-2538	49	8	.	.	PUNCT
ajst-2538	50	1	it	it	PRON
ajst-2538	50	2	can	can	AUX
ajst-2538	50	3	observe	observe	VERB
ajst-2538	50	4	the	the	DET
ajst-2538	50	5	change	change	NOUN
ajst-2538	50	6	of	of	ADP
ajst-2538	50	7	model	model	NOUN
ajst-2538	50	8	accuracy	accuracy	NOUN
ajst-2538	50	9	by	by	ADP
ajst-2538	50	10	randomly	randomly	ADV
ajst-2538	50	11	adding	add	VERB
ajst-2538	50	12	noise	noise	NOUN
ajst-2538	50	13	interference	interference	NOUN
ajst-2538	50	14	to	to	ADP
ajst-2538	50	15	each	each	DET
ajst-2538	50	16	feature	feature	NOUN
ajst-2538	50	17	,	,	PUNCT
ajst-2538	50	18	and	and	CCONJ
ajst-2538	50	19	measure	measure	VERB
ajst-2538	50	20	the	the	DET
ajst-2538	50	21	importance	importance	NOUN
ajst-2538	50	22	of	of	ADP
ajst-2538	50	23	feature	feature	NOUN
ajst-2538	50	24	by	by	ADP
ajst-2538	50	25	the	the	DET
ajst-2538	50	26	extent	extent	NOUN
ajst-2538	50	27	of	of	ADP
ajst-2538	50	28	accuracy	accuracy	NOUN
ajst-2538	50	29	reduction	reduction	NOUN
ajst-2538	50	30	.	.	PUNCT
ajst-2538	51	1	if	if	SCONJ
ajst-2538	51	2	the	the	DET
ajst-2538	51	3	model	model	NOUN
ajst-2538	51	4	accuracy	accuracy	NOUN
ajst-2538	51	5	increases	increase	VERB
ajst-2538	51	6	after	after	ADP
ajst-2538	51	7	noise	noise	NOUN
ajst-2538	51	8	reduction	reduction	NOUN
ajst-2538	51	9	for	for	ADP
ajst-2538	51	10	a	a	DET
ajst-2538	51	11	feature	feature	NOUN
ajst-2538	51	12	,	,	PUNCT
ajst-2538	51	13	it	it	PRON
ajst-2538	51	14	indicates	indicate	VERB
ajst-2538	51	15	that	that	SCONJ
ajst-2538	51	16	the	the	DET
ajst-2538	51	17	feature	feature	NOUN
ajst-2538	51	18	is	be	AUX
ajst-2538	51	19	of	of	ADP
ajst-2538	51	20	high	high	ADJ
ajst-2538	51	21	importance	importance	NOUN
ajst-2538	51	22	.	.	PUNCT
ajst-2538	52	1	3	3	X
ajst-2538	52	2	.	.	X
ajst-2538	52	3	xg	xg	PROPN
ajst-2538	52	4	boost	boost	VERB
ajst-2538	52	5	3.1	3.1	NUM
ajst-2538	52	6	.	.	PUNCT
ajst-2538	53	1	introduction	introduction	NOUN
ajst-2538	53	2	to	to	ADP
ajst-2538	53	3	xg	xg	NOUN
ajst-2538	53	4	boost	boost	VERB
ajst-2538	53	5	boosting	boost	VERB
ajst-2538	53	6	algorithm	algorithm	NOUN
ajst-2538	53	7	is	be	AUX
ajst-2538	53	8	a	a	DET
ajst-2538	53	9	machine	machine	NOUN
ajst-2538	53	10	learning	learning	NOUN
ajst-2538	53	11	method	method	NOUN
ajst-2538	53	12	that	that	PRON
ajst-2538	53	13	integrates	integrate	VERB
ajst-2538	53	14	many	many	ADJ
ajst-2538	53	15	weak	weak	ADJ
ajst-2538	53	16	classifiers	classifier	NOUN
ajst-2538	53	17	together	together	ADV
ajst-2538	53	18	to	to	PART
ajst-2538	53	19	generate	generate	VERB
ajst-2538	53	20	a	a	DET
ajst-2538	53	21	strong	strong	ADJ
ajst-2538	53	22	classifier	classifier	NOUN
ajst-2538	53	23	by	by	ADP
ajst-2538	53	24	reducing	reduce	VERB
ajst-2538	53	25	the	the	DET
ajst-2538	53	26	bias	bias	NOUN
ajst-2538	53	27	in	in	ADP
ajst-2538	53	28	supervised	supervised	ADJ
ajst-2538	53	29	learning	learning	NOUN
ajst-2538	53	30	.	.	PUNCT
ajst-2538	54	1	xg	xg	PROPN
ajst-2538	54	2	boost	boost	PROPN
ajst-2538	54	3	is	be	AUX
ajst-2538	54	4	an	an	DET
ajst-2538	54	5	algorithm	algorithm	NOUN
ajst-2538	54	6	based	base	VERB
ajst-2538	54	7	on	on	ADP
ajst-2538	54	8	many	many	ADJ
ajst-2538	54	9	boosting	boost	VERB
ajst-2538	54	10	algorithms	algorithm	NOUN
ajst-2538	54	11	such	such	ADJ
ajst-2538	54	12	as	as	ADP
ajst-2538	54	13	adaboost	adaboost	ADJ
ajst-2538	54	14	and	and	CCONJ
ajst-2538	54	15	gdbt	gdbt	NOUN
ajst-2538	54	16	,	,	PUNCT
ajst-2538	54	17	whose	whose	DET
ajst-2538	54	18	principle	principle	NOUN
ajst-2538	54	19	is	be	AUX
ajst-2538	54	20	to	to	PART
ajst-2538	54	21	optimize	optimize	VERB
ajst-2538	54	22	the	the	DET
ajst-2538	54	23	objective	objective	ADJ
ajst-2538	54	24	function	function	NOUN
ajst-2538	54	25	and	and	CCONJ
ajst-2538	54	26	minimize	minimize	VERB
ajst-2538	54	27	it	it	PRON
ajst-2538	54	28	.	.	PUNCT
ajst-2538	55	1	by	by	ADP
ajst-2538	55	2	optimizing	optimize	VERB
ajst-2538	55	3	the	the	DET
ajst-2538	55	4	objective	objective	ADJ
ajst-2538	55	5	function	function	NOUN
ajst-2538	55	6	,	,	PUNCT
ajst-2538	55	7	the	the	DET
ajst-2538	55	8	error	error	NOUN
ajst-2538	55	9	and	and	CCONJ
ajst-2538	55	10	complexity	complexity	NOUN
ajst-2538	55	11	are	be	AUX
ajst-2538	55	12	optimized	optimize	VERB
ajst-2538	55	13	.	.	PUNCT
ajst-2538	56	1	the	the	DET
ajst-2538	56	2	xg	xg	PROPN
ajst-2538	56	3	boost	boost	PROPN
ajst-2538	56	4	algorithm	algorithm	PROPN
ajst-2538	56	5	uses	use	VERB
ajst-2538	56	6	a	a	DET
ajst-2538	56	7	large	large	ADJ
ajst-2538	56	8	number	number	NOUN
ajst-2538	56	9	of	of	ADP
ajst-2538	56	10	base	base	NOUN
ajst-2538	56	11	classifiers	classifier	NOUN
ajst-2538	56	12	,	,	PUNCT
ajst-2538	56	13	which	which	PRON
ajst-2538	56	14	need	need	VERB
ajst-2538	56	15	a	a	DET
ajst-2538	56	16	more	more	ADV
ajst-2538	56	17	general	general	ADJ
ajst-2538	56	18	algorithm	algorithm	NOUN
ajst-2538	56	19	to	to	PART
ajst-2538	56	20	achieve	achieve	VERB
ajst-2538	56	21	gradient	gradient	ADJ
ajst-2538	56	22	descent	descent	NOUN
ajst-2538	56	23	.	.	PUNCT
ajst-2538	57	1	this	this	PRON
ajst-2538	57	2	can	can	AUX
ajst-2538	57	3	be	be	AUX
ajst-2538	57	4	achieved	achieve	VERB
ajst-2538	57	5	by	by	ADP
ajst-2538	57	6	using	use	VERB
ajst-2538	57	7	the	the	DET
ajst-2538	57	8	taylor	taylor	PROPN
ajst-2538	57	9	second	second	ADJ
ajst-2538	57	10	-	-	PUNCT
ajst-2538	57	11	order	order	NOUN
ajst-2538	57	12	expansion	expansion	NOUN
ajst-2538	57	13	is	be	AUX
ajst-2538	57	14	used	use	VERB
ajst-2538	57	15	:	:	PUNCT
ajst-2538	57	16	≅	≅	PROPN
ajst-2538	57	17	,	,	PUNCT
ajst-2538	57	18	1	1	NUM
ajst-2538	57	19	2	2	NUM
ajst-2538	57	20	∆	∆	NOUN
ajst-2538	57	21	∅	∅	NOUN
ajst-2538	57	22	where	where	SCONJ
ajst-2538	57	23	n	n	PRON
ajst-2538	57	24	represents	represent	VERB
ajst-2538	57	25	the	the	DET
ajst-2538	57	26	number	number	NOUN
ajst-2538	57	27	of	of	ADP
ajst-2538	57	28	samples	sample	NOUN
ajst-2538	57	29	used	use	VERB
ajst-2538	57	30	,	,	PUNCT
ajst-2538	57	31	the	the	DET
ajst-2538	57	32	number	number	NOUN
ajst-2538	57	33	of	of	ADP
ajst-2538	57	34	current	current	ADJ
ajst-2538	57	35	iterations	iteration	NOUN
ajst-2538	57	36	of	of	ADP
ajst-2538	57	37	the	the	DET
ajst-2538	57	38	m	m	NOUN
ajst-2538	57	39	table	table	NOUN
ajst-2538	57	40	,	,	PUNCT
ajst-2538	57	41	and	and	CCONJ
ajst-2538	57	42	f(m	f(m	PROPN
ajst-2538	57	43	)	)	PUNCT
ajst-2538	57	44	represents	represent	VERB
ajst-2538	57	45	the	the	DET
ajst-2538	57	46	current	current	ADJ
ajst-2538	57	47	iteration	iteration	NOUN
ajst-2538	57	48	error	error	NOUN
ajst-2538	57	49	.	.	PUNCT
ajst-2538	58	1	3.2	3.2	NUM
ajst-2538	58	2	.	.	PUNCT
ajst-2538	59	1	risk	risk	NOUN
ajst-2538	59	2	evaluation	evaluation	NOUN
ajst-2538	59	3	on	on	ADP
ajst-2538	59	4	xg	xg	PROPN
ajst-2538	59	5	boost	boost	PROPN
ajst-2538	59	6	3.2.1	3.2.1	NUM
ajst-2538	59	7	.	.	PUNCT
ajst-2538	60	1	accuracy	accuracy	NOUN
ajst-2538	60	2	xg	xg	PROPN
ajst-2538	60	3	boost	boost	PROPN
ajst-2538	60	4	adds	add	VERB
ajst-2538	60	5	the	the	DET
ajst-2538	60	6	regularization	regularization	NOUN
ajst-2538	60	7	term	term	NOUN
ajst-2538	60	8	into	into	ADP
ajst-2538	60	9	the	the	DET
ajst-2538	60	10	objective	objective	ADJ
ajst-2538	60	11	function	function	NOUN
ajst-2538	60	12	to	to	PART
ajst-2538	60	13	ensure	ensure	VERB
ajst-2538	60	14	that	that	SCONJ
ajst-2538	60	15	every	every	DET
ajst-2538	60	16	iteration	iteration	NOUN
ajst-2538	60	17	hedged	hedge	VERB
ajst-2538	60	18	the	the	DET
ajst-2538	60	19	complexity	complexity	NOUN
ajst-2538	60	20	of	of	ADP
ajst-2538	60	21	the	the	DET
ajst-2538	60	22	model	model	NOUN
ajst-2538	60	23	and	and	CCONJ
ajst-2538	60	24	effectively	effectively	ADV
ajst-2538	60	25	reduces	reduce	VERB
ajst-2538	60	26	the	the	DET
ajst-2538	60	27	possibility	possibility	NOUN
ajst-2538	60	28	of	of	ADP
ajst-2538	60	29	overfitting	overfitte	VERB
ajst-2538	60	30	.	.	PUNCT
ajst-2538	61	1	since	since	SCONJ
ajst-2538	61	2	the	the	DET
ajst-2538	61	3	numerical	numerical	ADJ
ajst-2538	61	4	value	value	NOUN
ajst-2538	61	5	of	of	ADP
ajst-2538	61	6	each	each	DET
ajst-2538	61	7	feature	feature	NOUN
ajst-2538	61	8	is	be	AUX
ajst-2538	61	9	only	only	ADV
ajst-2538	61	10	used	use	VERB
ajst-2538	61	11	for	for	ADP
ajst-2538	61	12	size	size	NOUN
ajst-2538	61	13	comparison	comparison	NOUN
ajst-2538	61	14	,	,	PUNCT
ajst-2538	61	15	the	the	DET
ajst-2538	61	16	xg	xg	PROPN
ajst-2538	61	17	boost	boost	PROPN
ajst-2538	61	18	model	model	NOUN
ajst-2538	61	19	have	have	VERB
ajst-2538	61	20	good	good	ADJ
ajst-2538	61	21	tolerance	tolerance	NOUN
ajst-2538	61	22	for	for	ADP
ajst-2538	61	23	outliers	outlier	NOUN
ajst-2538	61	24	.	.	PUNCT
ajst-2538	62	1	for	for	ADP
ajst-2538	62	2	the	the	DET
ajst-2538	62	3	treatment	treatment	NOUN
ajst-2538	62	4	of	of	ADP
ajst-2538	62	5	missing	miss	VERB
ajst-2538	62	6	values	value	NOUN
ajst-2538	62	7	,	,	PUNCT
ajst-2538	62	8	xg	xg	PROPN
ajst-2538	62	9	boost	boost	NOUN
ajst-2538	62	10	can	can	AUX
ajst-2538	62	11	automatically	automatically	ADV
ajst-2538	62	12	learn	learn	VERB
ajst-2538	62	13	the	the	DET
ajst-2538	62	14	splitting	splitting	NOUN
ajst-2538	62	15	direction	direction	NOUN
ajst-2538	62	16	of	of	ADP
ajst-2538	62	17	missing	miss	VERB
ajst-2538	62	18	values	value	NOUN
ajst-2538	62	19	.	.	PUNCT
ajst-2538	63	1	tian	tian	PROPN
ajst-2538	63	2	hao	hao	PROPN
ajst-2538	63	3	analysed	analyse	VERB
ajst-2538	63	4	the	the	DET
ajst-2538	63	5	xg	xg	PROPN
ajst-2538	63	6	boost	boost	NOUN
ajst-2538	63	7	algorithm	algorithm	NOUN
ajst-2538	63	8	and	and	CCONJ
ajst-2538	63	9	compared	compare	VERB
ajst-2538	63	10	it	it	PRON
ajst-2538	63	11	with	with	ADP
ajst-2538	63	12	other	other	ADJ
ajst-2538	63	13	mainstream	mainstream	ADJ
ajst-2538	63	14	algorithms	algorithm	NOUN
ajst-2538	63	15	.	.	PUNCT
ajst-2538	64	1	tian	tian	PROPN
ajst-2538	64	2	applied	apply	VERB
ajst-2538	64	3	a	a	DET
ajst-2538	64	4	data	datum	NOUN
ajst-2538	64	5	preprocessing	preprocessing	NOUN
ajst-2538	64	6	method	method	NOUN
ajst-2538	64	7	in	in	ADP
ajst-2538	64	8	which	which	PRON
ajst-2538	64	9	the	the	DET
ajst-2538	64	10	original	original	ADJ
ajst-2538	64	11	data	datum	NOUN
ajst-2538	64	12	can	can	AUX
ajst-2538	64	13	be	be	AUX
ajst-2538	64	14	displayed	display	VERB
ajst-2538	64	15	in	in	ADP
ajst-2538	64	16	a	a	DET
ajst-2538	64	17	smaller	small	ADJ
ajst-2538	64	18	specification	specification	NOUN
ajst-2538	64	19	.	.	PUNCT
ajst-2538	65	1	this	this	DET
ajst-2538	65	2	method	method	NOUN
ajst-2538	65	3	can	can	AUX
ajst-2538	65	4	achieve	achieve	VERB
ajst-2538	65	5	the	the	DET
ajst-2538	65	6	purpose	purpose	NOUN
ajst-2538	65	7	of	of	ADP
ajst-2538	65	8	dimensionality	dimensionality	NOUN
ajst-2538	65	9	reduction	reduction	NOUN
ajst-2538	65	10	and	and	CCONJ
ajst-2538	65	11	retain	retain	VERB
ajst-2538	65	12	the	the	DET
ajst-2538	65	13	information	information	NOUN
ajst-2538	65	14	of	of	ADP
ajst-2538	65	15	the	the	DET
ajst-2538	65	16	original	original	ADJ
ajst-2538	65	17	data	datum	NOUN
ajst-2538	65	18	more	more	ADV
ajst-2538	65	19	completely	completely	ADV
ajst-2538	65	20	,	,	PUNCT
ajst-2538	65	21	so	so	CCONJ
ajst-2538	65	22	it	it	PRON
ajst-2538	65	23	reduces	reduce	VERB
ajst-2538	65	24	the	the	DET
ajst-2538	65	25	time	time	NOUN
ajst-2538	65	26	required	require	VERB
ajst-2538	65	27	for	for	ADP
ajst-2538	65	28	modelling	modelling	NOUN
ajst-2538	65	29	,	,	PUNCT
ajst-2538	65	30	while	while	SCONJ
ajst-2538	65	31	maintaining	maintain	VERB
ajst-2538	65	32	the	the	DET
ajst-2538	65	33	accuracy	accuracy	NOUN
ajst-2538	65	34	of	of	ADP
ajst-2538	65	35	the	the	DET
ajst-2538	65	36	model	model	NOUN
ajst-2538	65	37	[	[	X
ajst-2538	65	38	7	7	NUM
ajst-2538	65	39	]	]	PUNCT
ajst-2538	65	40	.	.	PUNCT
ajst-2538	66	1	3.2.2	3.2.2	NUM
ajst-2538	66	2	.	.	PUNCT
ajst-2538	67	1	adaptability	adaptability	NOUN
ajst-2538	67	2	the	the	DET
ajst-2538	67	3	weak	weak	ADJ
ajst-2538	67	4	classifier	classifier	NOUN
ajst-2538	67	5	that	that	PRON
ajst-2538	67	6	makes	make	VERB
ajst-2538	67	7	up	up	ADP
ajst-2538	67	8	xg	xg	PROPN
ajst-2538	67	9	boost	boost	NOUN
ajst-2538	67	10	is	be	AUX
ajst-2538	67	11	a	a	DET
ajst-2538	67	12	decision	decision	NOUN
ajst-2538	67	13	tree	tree	NOUN
ajst-2538	67	14	,	,	PUNCT
ajst-2538	67	15	and	and	CCONJ
ajst-2538	67	16	its	its	PRON
ajst-2538	67	17	appropriate	appropriate	ADJ
ajst-2538	67	18	data	datum	NOUN
ajst-2538	67	19	type	type	NOUN
ajst-2538	67	20	is	be	AUX
ajst-2538	67	21	categorical	categorical	ADJ
ajst-2538	67	22	data	datum	NOUN
ajst-2538	67	23	.	.	PUNCT
ajst-2538	68	1	therefore	therefore	ADV
ajst-2538	68	2	,	,	PUNCT
ajst-2538	68	3	it	it	PRON
ajst-2538	68	4	is	be	AUX
ajst-2538	68	5	necessary	necessary	ADJ
ajst-2538	68	6	to	to	PART
ajst-2538	68	7	convert	convert	VERB
ajst-2538	68	8	the	the	DET
ajst-2538	68	9	data	datum	NOUN
ajst-2538	68	10	input	input	NOUN
ajst-2538	68	11	into	into	ADP
ajst-2538	68	12	classed	class	VERB
ajst-2538	68	13	data	datum	NOUN
ajst-2538	68	14	.	.	PUNCT
ajst-2538	69	1	the	the	DET
ajst-2538	69	2	xg	xg	PROPN
ajst-2538	69	3	boost	boost	PROPN
ajst-2538	69	4	algorithm	algorithm	NOUN
ajst-2538	69	5	can	can	AUX
ajst-2538	69	6	be	be	AUX
ajst-2538	69	7	used	use	VERB
ajst-2538	69	8	for	for	ADP
ajst-2538	69	9	both	both	CCONJ
ajst-2538	69	10	nonlinear	nonlinear	ADJ
ajst-2538	69	11	classification	classification	NOUN
ajst-2538	69	12	and	and	CCONJ
ajst-2538	69	13	linear	linear	ADJ
ajst-2538	69	14	classification	classification	NOUN
ajst-2538	69	15	.	.	PUNCT
ajst-2538	70	1	xiang	xiang	PROPN
ajst-2538	70	2	li	li	PROPN
ajst-2538	70	3	showed	show	VERB
ajst-2538	70	4	based	base	VERB
ajst-2538	70	5	on	on	ADP
ajst-2538	70	6	the	the	DET
ajst-2538	70	7	classification	classification	NOUN
ajst-2538	70	8	of	of	ADP
ajst-2538	70	9	data	datum	NOUN
ajst-2538	70	10	from	from	ADP
ajst-2538	70	11	xg	xg	PROPN
ajst-2538	70	12	boost	boost	NOUN
ajst-2538	70	13	,	,	PUNCT
ajst-2538	70	14	quantify	quantify	VERB
ajst-2538	70	15	stock	stock	NOUN
ajst-2538	70	16	selection	selection	NOUN
ajst-2538	70	17	objectives	objective	NOUN
ajst-2538	70	18	and	and	CCONJ
ajst-2538	70	19	a	a	DET
ajst-2538	70	20	yield	yield	NOUN
ajst-2538	70	21	that	that	PRON
ajst-2538	70	22	outperform	outperform	VERB
ajst-2538	70	23	the	the	DET
ajst-2538	70	24	broader	broad	ADJ
ajst-2538	70	25	market	market	NOUN
ajst-2538	70	26	can	can	AUX
ajst-2538	70	27	be	be	AUX
ajst-2538	70	28	achieved	achieve	VERB
ajst-2538	70	29	[	[	PUNCT
ajst-2538	70	30	5	5	NUM
ajst-2538	70	31	]	]	PUNCT
ajst-2538	70	32	.	.	PUNCT
ajst-2538	71	1	for	for	ADP
ajst-2538	71	2	the	the	DET
ajst-2538	71	3	first	first	ADJ
ajst-2538	71	4	time	time	NOUN
ajst-2538	71	5	,	,	PUNCT
ajst-2538	71	6	the	the	DET
ajst-2538	71	7	xg	xg	PROPN
ajst-2538	71	8	boost	boost	PROPN
ajst-2538	71	9	algorithm	algorithm	NOUN
ajst-2538	71	10	was	be	AUX
ajst-2538	71	11	applied	apply	VERB
ajst-2538	71	12	to	to	ADP
ajst-2538	71	13	quantitative	quantitative	ADJ
ajst-2538	71	14	stock	stock	NOUN
ajst-2538	71	15	selection	selection	NOUN
ajst-2538	71	16	,	,	PUNCT
ajst-2538	71	17	which	which	PRON
ajst-2538	71	18	made	make	VERB
ajst-2538	71	19	it	it	PRON
ajst-2538	71	20	possible	possible	ADJ
ajst-2538	71	21	to	to	PART
ajst-2538	71	22	handle	handle	VERB
ajst-2538	71	23	highdimensional	highdimensional	NOUN
ajst-2538	71	24	.	.	PUNCT
ajst-2538	72	1	as	as	SCONJ
ajst-2538	72	2	multi	multi	ADJ
ajst-2538	72	3	-	-	ADJ
ajst-2538	72	4	factor	factor	NOUN
ajst-2538	72	5	selection	selection	NOUN
ajst-2538	72	6	stock	stock	NOUN
ajst-2538	72	7	method	method	NOUN
ajst-2538	72	8	became	become	VERB
ajst-2538	72	9	possible	possible	ADJ
ajst-2538	72	10	,	,	PUNCT
ajst-2538	72	11	it	it	PRON
ajst-2538	72	12	presents	present	VERB
ajst-2538	72	13	broader	broad	ADJ
ajst-2538	72	14	development	development	NOUN
ajst-2538	72	15	ideas	idea	NOUN
ajst-2538	72	16	about	about	ADP
ajst-2538	72	17	new	new	ADJ
ajst-2538	72	18	multifactor	multifactor	NOUN
ajst-2538	72	19	models	model	NOUN
ajst-2538	72	20	.	.	PUNCT
ajst-2538	73	1	runjing	runje	VERB
ajst-2538	73	2	guan	guan	PROPN
ajst-2538	73	3	constructed	construct	VERB
ajst-2538	73	4	a	a	DET
ajst-2538	73	5	quantitative	quantitative	ADJ
ajst-2538	73	6	multi	multi	ADJ
ajst-2538	73	7	factor	factor	NOUN
ajst-2538	73	8	stock	stock	NOUN
ajst-2538	73	9	selection	selection	NOUN
ajst-2538	73	10	model	model	NOUN
ajst-2538	73	11	based	base	VERB
ajst-2538	73	12	on	on	ADP
ajst-2538	73	13	xg	xg	PROPN
ajst-2538	73	14	boost	boost	PROPN
ajst-2538	73	15	.	.	PUNCT
ajst-2538	74	1	the	the	DET
ajst-2538	74	2	model	model	NOUN
ajst-2538	74	3	can	can	AUX
ajst-2538	74	4	identify	identify	VERB
ajst-2538	74	5	the	the	DET
ajst-2538	74	6	downtrend	downtrend	NOUN
ajst-2538	74	7	of	of	ADP
ajst-2538	74	8	the	the	DET
ajst-2538	74	9	stock	stock	NOUN
ajst-2538	74	10	well	well	ADV
ajst-2538	74	11	,	,	PUNCT
ajst-2538	74	12	thus	thus	ADV
ajst-2538	74	13	it	it	PRON
ajst-2538	74	14	reduces	reduce	VERB
ajst-2538	74	15	volatility	volatility	NOUN
ajst-2538	74	16	.	.	PUNCT
ajst-2538	75	1	however	however	ADV
ajst-2538	75	2	,	,	PUNCT
ajst-2538	75	3	the	the	DET
ajst-2538	75	4	model	model	NOUN
ajst-2538	75	5	fails	fail	VERB
ajst-2538	75	6	to	to	PART
ajst-2538	75	7	identify	identify	VERB
ajst-2538	75	8	the	the	DET
ajst-2538	75	9	rise	rise	NOUN
ajst-2538	75	10	in	in	ADP
ajst-2538	75	11	the	the	DET
ajst-2538	75	12	stocks	stock	NOUN
ajst-2538	75	13	,	,	PUNCT
ajst-2538	75	14	making	make	VERB
ajst-2538	75	15	it	it	PRON
ajst-2538	75	16	difficult	difficult	ADJ
ajst-2538	75	17	for	for	SCONJ
ajst-2538	75	18	higher	high	ADJ
ajst-2538	75	19	returns	return	NOUN
ajst-2538	75	20	to	to	PART
ajst-2538	75	21	be	be	AUX
ajst-2538	75	22	achieved	achieve	VERB
ajst-2538	75	23	[	[	PUNCT
ajst-2538	75	24	1	1	NUM
ajst-2538	75	25	]	]	PUNCT
ajst-2538	75	26	.	.	PUNCT
ajst-2538	76	1	3.2.3	3.2.3	X
ajst-2538	76	2	.	.	X
ajst-2538	76	3	efficiency	efficiency	NOUN
ajst-2538	76	4	the	the	DET
ajst-2538	76	5	xg	xg	PROPN
ajst-2538	76	6	boost	boost	PROPN
ajst-2538	76	7	algorithm	algorithm	NOUN
ajst-2538	76	8	supports	support	VERB
ajst-2538	76	9	cpu	cpu	NOUN
ajst-2538	76	10	parallel	parallel	NOUN
ajst-2538	76	11	operations	operation	NOUN
ajst-2538	76	12	and	and	CCONJ
ajst-2538	76	13	column	column	NOUN
ajst-2538	76	14	sampling	sample	VERB
ajst-2538	76	15	which	which	PRON
ajst-2538	76	16	can	can	AUX
ajst-2538	76	17	assist	assist	VERB
ajst-2538	76	18	in	in	ADP
ajst-2538	76	19	reducing	reduce	VERB
ajst-2538	76	20	the	the	DET
ajst-2538	76	21	amount	amount	NOUN
ajst-2538	76	22	of	of	ADP
ajst-2538	76	23	computation	computation	NOUN
ajst-2538	76	24	.	.	PUNCT
ajst-2538	77	1	column	column	NOUN
ajst-2538	77	2	sampling	sample	VERB
ajst-2538	77	3	would	would	AUX
ajst-2538	77	4	also	also	ADV
ajst-2538	77	5	reduce	reduce	VERB
ajst-2538	77	6	overfitting	overfitte	VERB
ajst-2538	77	7	.	.	PUNCT
ajst-2538	78	1	though	though	SCONJ
ajst-2538	78	2	xg	xg	PROPN
ajst-2538	78	3	boost	boost	NOUN
ajst-2538	78	4	have	have	VERB
ajst-2538	78	5	many	many	ADJ
ajst-2538	78	6	parameters	parameter	NOUN
ajst-2538	78	7	,	,	PUNCT
ajst-2538	78	8	but	but	CCONJ
ajst-2538	78	9	in	in	ADP
ajst-2538	78	10	actual	actual	ADJ
ajst-2538	78	11	tuning	tuning	NOUN
ajst-2538	78	12	,	,	PUNCT
ajst-2538	78	13	there	there	PRON
ajst-2538	78	14	are	be	VERB
ajst-2538	78	15	very	very	ADV
ajst-2538	78	16	few	few	ADJ
ajst-2538	78	17	parameters	parameter	NOUN
ajst-2538	78	18	that	that	PRON
ajst-2538	78	19	can	can	AUX
ajst-2538	78	20	significantly	significantly	ADV
ajst-2538	78	21	improve	improve	VERB
ajst-2538	78	22	the	the	DET
ajst-2538	78	23	predictive	predictive	ADJ
ajst-2538	78	24	ability	ability	NOUN
ajst-2538	78	25	of	of	ADP
ajst-2538	78	26	the	the	DET
ajst-2538	78	27	model	model	NOUN
ajst-2538	78	28	.	.	PUNCT
ajst-2538	79	1	if	if	SCONJ
ajst-2538	79	2	the	the	DET
ajst-2538	79	3	amount	amount	NOUN
ajst-2538	79	4	of	of	ADP
ajst-2538	79	5	data	datum	NOUN
ajst-2538	79	6	is	be	AUX
ajst-2538	79	7	very	very	ADV
ajst-2538	79	8	large	large	ADJ
ajst-2538	79	9	,	,	PUNCT
ajst-2538	79	10	the	the	DET
ajst-2538	79	11	modelling	modelling	NOUN
ajst-2538	79	12	and	and	CCONJ
ajst-2538	79	13	parameter	parameter	NOUN
ajst-2538	79	14	optimization	optimization	NOUN
ajst-2538	79	15	process	process	NOUN
ajst-2538	79	16	will	will	AUX
ajst-2538	79	17	waste	waste	VERB
ajst-2538	79	18	more	more	ADJ
ajst-2538	79	19	time	time	NOUN
ajst-2538	79	20	for	for	ADP
ajst-2538	79	21	the	the	DET
ajst-2538	79	22	time	time	NOUN
ajst-2538	79	23	it	it	PRON
ajst-2538	79	24	takes	take	VERB
ajst-2538	79	25	.	.	PUNCT
ajst-2538	80	1	the	the	DET
ajst-2538	80	2	distributed	distribute	VERB
ajst-2538	80	3	method	method	NOUN
ajst-2538	80	4	can	can	AUX
ajst-2538	80	5	be	be	AUX
ajst-2538	80	6	used	use	VERB
ajst-2538	80	7	to	to	PART
ajst-2538	80	8	improve	improve	VERB
ajst-2538	80	9	the	the	DET
ajst-2538	80	10	efficiency	efficiency	NOUN
ajst-2538	80	11	when	when	SCONJ
ajst-2538	80	12	computing	compute	VERB
ajst-2538	80	13	as	as	ADP
ajst-2538	80	14	due	due	ADP
ajst-2538	80	15	to	to	ADP
ajst-2538	80	16	the	the	DET
ajst-2538	80	17	gradient	gradient	ADJ
ajst-2538	80	18	descent	descent	NOUN
ajst-2538	80	19	algorithm	algorithm	NOUN
ajst-2538	80	20	used	use	VERB
ajst-2538	80	21	,	,	PUNCT
ajst-2538	80	22	there	there	PRON
ajst-2538	80	23	is	be	VERB
ajst-2538	80	24	no	no	DET
ajst-2538	80	25	correlation	correlation	NOUN
ajst-2538	80	26	between	between	ADP
ajst-2538	80	27	the	the	DET
ajst-2538	80	28	multiple	multiple	ADJ
ajst-2538	80	29	classifiers	classifier	NOUN
ajst-2538	80	30	it	it	PRON
ajst-2538	80	31	uses	use	VERB
ajst-2538	80	32	.	.	PUNCT
ajst-2538	81	1	as	as	SCONJ
ajst-2538	81	2	mentioned	mention	VERB
ajst-2538	81	3	before	before	ADV
ajst-2538	81	4	,	,	PUNCT
ajst-2538	81	5	yangbao	yangbao	PROPN
ajst-2538	81	6	zhu	zhu	PROPN
ajst-2538	81	7	found	find	VERB
ajst-2538	81	8	that	that	SCONJ
ajst-2538	81	9	the	the	DET
ajst-2538	81	10	xg	xg	PROPN
ajst-2538	81	11	boost	boost	NOUN
ajst-2538	81	12	are	be	AUX
ajst-2538	81	13	better	well	ADJ
ajst-2538	81	14	than	than	ADP
ajst-2538	81	15	the	the	DET
ajst-2538	81	16	random	random	ADJ
ajst-2538	81	17	forest	forest	NOUN
ajst-2538	81	18	in	in	ADP
ajst-2538	81	19	terms	term	NOUN
ajst-2538	81	20	of	of	ADP
ajst-2538	81	21	running	run	VERB
ajst-2538	81	22	speed	speed	NOUN
ajst-2538	81	23	or	or	CCONJ
ajst-2538	81	24	stock	stock	NOUN
ajst-2538	81	25	selection	selection	NOUN
ajst-2538	81	26	ability	ability	NOUN
ajst-2538	81	27	[	[	X
ajst-2538	81	28	6	6	NUM
ajst-2538	81	29	]	]	PUNCT
ajst-2538	81	30	.	.	PUNCT
ajst-2538	82	1	speed	speed	NOUN
ajst-2538	82	2	can	can	AUX
ajst-2538	82	3	be	be	AUX
ajst-2538	82	4	improved	improve	VERB
ajst-2538	82	5	further	far	ADV
ajst-2538	82	6	by	by	ADP
ajst-2538	82	7	organizing	organize	VERB
ajst-2538	82	8	the	the	DET
ajst-2538	82	9	original	original	ADJ
ajst-2538	82	10	data	datum	NOUN
ajst-2538	82	11	to	to	PART
ajst-2538	82	12	be	be	AUX
ajst-2538	82	13	displayed	display	VERB
ajst-2538	82	14	in	in	ADP
ajst-2538	82	15	a	a	DET
ajst-2538	82	16	smaller	small	ADJ
ajst-2538	82	17	specification	specification	NOUN
ajst-2538	82	18	like	like	SCONJ
ajst-2538	82	19	tian	tian	PROPN
ajst-2538	82	20	hao	hao	PROPN
ajst-2538	82	21	did	do	VERB
ajst-2538	82	22	in	in	ADP
ajst-2538	82	23	his	his	PRON
ajst-2538	82	24	research	research	NOUN
ajst-2538	82	25	[	[	X
ajst-2538	82	26	7	7	NUM
ajst-2538	82	27	]	]	PUNCT
ajst-2538	82	28	.	.	PUNCT
ajst-2538	83	1	3.2.4	3.2.4	NUM
ajst-2538	83	2	.	.	PUNCT
ajst-2538	83	3	simplicity	simplicity	NOUN
ajst-2538	83	4	both	both	DET
ajst-2538	83	5	tree	tree	NOUN
ajst-2538	83	6	building	building	NOUN
ajst-2538	83	7	process	process	NOUN
ajst-2538	83	8	and	and	CCONJ
ajst-2538	83	9	boosting	boost	VERB
ajst-2538	83	10	process	process	NOUN
ajst-2538	83	11	of	of	ADP
ajst-2538	83	12	xg	xg	PROPN
ajst-2538	83	13	boost	boost	NOUN
ajst-2538	83	14	are	be	AUX
ajst-2538	83	15	based	base	VERB
ajst-2538	83	16	on	on	ADP
ajst-2538	83	17	the	the	DET
ajst-2538	83	18	objective	objective	ADJ
ajst-2538	83	19	function	function	NOUN
ajst-2538	83	20	,	,	PUNCT
ajst-2538	83	21	and	and	CCONJ
ajst-2538	83	22	all	all	DET
ajst-2538	83	23	operations	operation	NOUN
ajst-2538	83	24	37	37	NUM
ajst-2538	83	25	are	be	AUX
ajst-2538	83	26	evaluated	evaluate	VERB
ajst-2538	83	27	by	by	ADP
ajst-2538	83	28	minimizing	minimize	VERB
ajst-2538	83	29	objective	objective	ADJ
ajst-2538	83	30	function	function	NOUN
ajst-2538	83	31	.	.	PUNCT
ajst-2538	84	1	the	the	DET
ajst-2538	84	2	formula	formula	NOUN
ajst-2538	84	3	for	for	ADP
ajst-2538	84	4	it	it	PRON
ajst-2538	84	5	is	be	AUX
ajst-2538	84	6	relatively	relatively	ADV
ajst-2538	84	7	clear	clear	ADJ
ajst-2538	84	8	and	and	CCONJ
ajst-2538	84	9	easy	easy	ADJ
ajst-2538	84	10	to	to	PART
ajst-2538	84	11	understand	understand	VERB
ajst-2538	84	12	.	.	PUNCT
ajst-2538	85	1	however	however	ADV
ajst-2538	85	2	,	,	PUNCT
ajst-2538	85	3	its	its	PRON
ajst-2538	85	4	initial	initial	ADJ
ajst-2538	85	5	code	code	NOUN
ajst-2538	85	6	implementation	implementation	NOUN
ajst-2538	85	7	is	be	AUX
ajst-2538	85	8	written	write	VERB
ajst-2538	85	9	in	in	ADP
ajst-2538	85	10	c++	c++	NOUN
ajst-2538	85	11	,	,	PUNCT
ajst-2538	85	12	hence	hence	ADV
ajst-2538	85	13	when	when	SCONJ
ajst-2538	85	14	xg	xg	PROPN
ajst-2538	85	15	boost	boost	NOUN
ajst-2538	85	16	is	be	AUX
ajst-2538	85	17	used	use	VERB
ajst-2538	85	18	in	in	ADP
ajst-2538	85	19	such	such	ADJ
ajst-2538	85	20	as	as	ADP
ajst-2538	85	21	programs	program	NOUN
ajst-2538	85	22	such	such	ADJ
ajst-2538	85	23	as	as	ADP
ajst-2538	85	24	python	python	NOUN
ajst-2538	85	25	and	and	CCONJ
ajst-2538	85	26	r	r	NOUN
ajst-2538	85	27	,	,	PUNCT
ajst-2538	85	28	the	the	DET
ajst-2538	85	29	installation	installation	NOUN
ajst-2538	85	30	can	can	AUX
ajst-2538	85	31	be	be	AUX
ajst-2538	85	32	cumbersome	cumbersome	ADJ
ajst-2538	85	33	.	.	PUNCT
ajst-2538	86	1	3.2.5	3.2.5	X
ajst-2538	86	2	.	.	PUNCT
ajst-2538	87	1	interpretability	interpretability	NOUN
ajst-2538	87	2	due	due	ADP
ajst-2538	87	3	to	to	ADP
ajst-2538	87	4	taylor	taylor	PROPN
ajst-2538	87	5	's	's	PART
ajst-2538	87	6	second	second	ADJ
ajst-2538	87	7	-	-	PUNCT
ajst-2538	87	8	order	order	NOUN
ajst-2538	87	9	expansion	expansion	NOUN
ajst-2538	87	10	,	,	PUNCT
ajst-2538	87	11	the	the	DET
ajst-2538	87	12	process	process	NOUN
ajst-2538	87	13	of	of	ADP
ajst-2538	87	14	building	build	VERB
ajst-2538	87	15	trees	tree	NOUN
ajst-2538	87	16	and	and	CCONJ
ajst-2538	87	17	boosting	boost	VERB
ajst-2538	87	18	relies	relie	NOUN
ajst-2538	87	19	only	only	ADV
ajst-2538	87	20	on	on	ADP
ajst-2538	87	21	the	the	DET
ajst-2538	87	22	first	first	ADJ
ajst-2538	87	23	derivative	derivative	ADJ
ajst-2538	87	24	and	and	CCONJ
ajst-2538	87	25	second	second	ADJ
ajst-2538	87	26	derivative	derivative	NOUN
ajst-2538	87	27	of	of	ADP
ajst-2538	87	28	the	the	DET
ajst-2538	87	29	loss	loss	NOUN
ajst-2538	87	30	function	function	NOUN
ajst-2538	87	31	,	,	PUNCT
ajst-2538	87	32	and	and	CCONJ
ajst-2538	87	33	the	the	DET
ajst-2538	87	34	formula	formula	NOUN
ajst-2538	87	35	is	be	AUX
ajst-2538	87	36	relatively	relatively	ADV
ajst-2538	87	37	clear	clear	ADJ
ajst-2538	87	38	and	and	CCONJ
ajst-2538	87	39	easy	easy	ADJ
ajst-2538	87	40	to	to	PART
ajst-2538	87	41	understand	understand	VERB
ajst-2538	87	42	.	.	PUNCT
ajst-2538	88	1	4	4	X
ajst-2538	88	2	.	.	X
ajst-2538	88	3	logistic	logistic	ADJ
ajst-2538	88	4	regression	regression	NOUN
ajst-2538	88	5	4.1	4.1	NUM
ajst-2538	88	6	.	.	PUNCT
ajst-2538	89	1	introduction	introduction	NOUN
ajst-2538	89	2	to	to	ADP
ajst-2538	89	3	logistic	logistic	ADJ
ajst-2538	89	4	regression	regression	NOUN
ajst-2538	89	5	logistic	logistic	ADJ
ajst-2538	89	6	regression	regression	NOUN
ajst-2538	89	7	is	be	AUX
ajst-2538	89	8	a	a	DET
ajst-2538	89	9	probabilistic	probabilistic	ADJ
ajst-2538	89	10	model	model	NOUN
ajst-2538	89	11	in	in	ADP
ajst-2538	89	12	which	which	PRON
ajst-2538	89	13	the	the	DET
ajst-2538	89	14	probability	probability	NOUN
ajst-2538	89	15	of	of	ADP
ajst-2538	89	16	occurrence	occurrence	NOUN
ajst-2538	89	17	of	of	ADP
ajst-2538	89	18	an	an	DET
ajst-2538	89	19	event	event	NOUN
ajst-2538	89	20	is	be	AUX
ajst-2538	89	21	the	the	DET
ajst-2538	89	22	dependent	dependent	ADJ
ajst-2538	89	23	variable	variable	NOUN
ajst-2538	89	24	and	and	CCONJ
ajst-2538	89	25	the	the	DET
ajst-2538	89	26	influencing	influence	VERB
ajst-2538	89	27	factor	factor	NOUN
ajst-2538	89	28	is	be	AUX
ajst-2538	89	29	the	the	DET
ajst-2538	89	30	independent	independent	ADJ
ajst-2538	89	31	variable	variable	NOUN
ajst-2538	89	32	.	.	PUNCT
ajst-2538	90	1	it	it	PRON
ajst-2538	90	2	is	be	AUX
ajst-2538	90	3	widely	widely	ADV
ajst-2538	90	4	used	use	VERB
ajst-2538	90	5	in	in	ADP
ajst-2538	90	6	many	many	ADJ
ajst-2538	90	7	fields	field	NOUN
ajst-2538	90	8	such	such	ADJ
ajst-2538	90	9	as	as	ADP
ajst-2538	90	10	medical	medical	ADJ
ajst-2538	90	11	health	health	NOUN
ajst-2538	90	12	,	,	PUNCT
ajst-2538	90	13	disaster	disaster	NOUN
ajst-2538	90	14	prediction	prediction	NOUN
ajst-2538	90	15	,	,	PUNCT
ajst-2538	90	16	and	and	CCONJ
ajst-2538	90	17	risk	risk	NOUN
ajst-2538	90	18	rating	rating	NOUN
ajst-2538	90	19	.	.	PUNCT
ajst-2538	91	1	it	it	PRON
ajst-2538	91	2	assumes	assume	VERB
ajst-2538	91	3	that	that	SCONJ
ajst-2538	91	4	p(y	p(y	PROPN
ajst-2538	91	5	=	=	NOUN
ajst-2538	91	6	1	1	X
ajst-2538	91	7	)	)	PUNCT
ajst-2538	91	8	=	=	SYM
ajst-2538	91	9	p	p	NOUN
ajst-2538	91	10	,	,	PUNCT
ajst-2538	91	11	hence	hence	ADV
ajst-2538	91	12	p(y	p(y	ADJ
ajst-2538	91	13	=	=	NOUN
ajst-2538	91	14	0	0	NUM
ajst-2538	91	15	)	)	PUNCT
ajst-2538	91	16	=	=	SYM
ajst-2538	91	17	1	1	NUM
ajst-2538	91	18	−	−	NOUN
ajst-2538	91	19	p.	p.	NOUN
ajst-2538	91	20	from	from	ADP
ajst-2538	91	21	this	this	PRON
ajst-2538	91	22	,	,	PUNCT
ajst-2538	91	23	⋯	⋯	PROPN
ajst-2538	91	24	,	,	PUNCT
ajst-2538	91	25	and	and	CCONJ
ajst-2538	91	26	is	be	AUX
ajst-2538	91	27	denoted	denote	VERB
ajst-2538	91	28	as	as	ADP
ajst-2538	91	29	logit	logit	NOUN
ajst-2538	91	30	p.	p.	NOUN
ajst-2538	91	31	1	1	NUM
ajst-2538	91	32	from	from	ADP
ajst-2538	91	33	which	which	PRON
ajst-2538	91	34	,	,	PUNCT
ajst-2538	91	35	is	be	AUX
ajst-2538	91	36	constant	constant	ADJ
ajst-2538	91	37	,	,	PUNCT
ajst-2538	91	38	,	,	PUNCT
ajst-2538	91	39	,	,	PUNCT
ajst-2538	91	40	…	…	PUNCT
ajst-2538	91	41	,	,	PUNCT
ajst-2538	91	42	represents	represent	VERB
ajst-2538	91	43	the	the	DET
ajst-2538	91	44	size	size	NOUN
ajst-2538	91	45	of	of	ADP
ajst-2538	91	46	impact	impact	NOUN
ajst-2538	91	47	of	of	ADP
ajst-2538	91	48	independent	independent	ADJ
ajst-2538	91	49	variable	variable	NOUN
ajst-2538	91	50	on	on	ADP
ajst-2538	91	51	the	the	DET
ajst-2538	91	52	dependent	dependent	ADJ
ajst-2538	91	53	variable	variable	ADJ
ajst-2538	91	54	y	y	PROPN
ajst-2538	91	55	,	,	PUNCT
ajst-2538	91	56	is	be	AUX
ajst-2538	91	57	a	a	DET
ajst-2538	91	58	random	random	ADJ
ajst-2538	91	59	perturbation	perturbation	NOUN
ajst-2538	91	60	term	term	NOUN
ajst-2538	91	61	.	.	PUNCT
ajst-2538	92	1	assuming	assume	VERB
ajst-2538	92	2	that	that	SCONJ
ajst-2538	92	3	the	the	DET
ajst-2538	92	4	value	value	NOUN
ajst-2538	92	5	remained	remain	VERB
ajst-2538	92	6	unchanged	unchanged	ADJ
ajst-2538	92	7	,	,	PUNCT
ajst-2538	92	8	then	then	ADV
ajst-2538	92	9	the	the	DET
ajst-2538	92	10	regression	regression	NOUN
ajst-2538	92	11	coefficient	coefficient	NOUN
ajst-2538	92	12	and	and	CCONJ
ajst-2538	92	13	the	the	DET
ajst-2538	92	14	probability	probability	NOUN
ajst-2538	92	15	p	p	NOUN
ajst-2538	92	16	shares	share	VERB
ajst-2538	92	17	a	a	DET
ajst-2538	92	18	positive	positive	ADJ
ajst-2538	92	19	relationship	relationship	NOUN
ajst-2538	92	20	.	.	PUNCT
ajst-2538	93	1	represents	represent	VERB
ajst-2538	93	2	the	the	DET
ajst-2538	93	3	odds	odd	NOUN
ajst-2538	93	4	ratio	ratio	NOUN
ajst-2538	93	5	,	,	PUNCT
ajst-2538	93	6	which	which	PRON
ajst-2538	93	7	is	be	AUX
ajst-2538	93	8	the	the	DET
ajst-2538	93	9	ratio	ratio	NOUN
ajst-2538	93	10	of	of	ADP
ajst-2538	93	11	the	the	DET
ajst-2538	93	12	probability	probability	NOUN
ajst-2538	93	13	of	of	ADP
ajst-2538	93	14	an	an	DET
ajst-2538	93	15	event	event	NOUN
ajst-2538	93	16	occurring	occur	VERB
ajst-2538	93	17	and	and	CCONJ
ajst-2538	93	18	not	not	PART
ajst-2538	93	19	occurring	occur	VERB
ajst-2538	93	20	.	.	PUNCT
ajst-2538	94	1	if	if	SCONJ
ajst-2538	94	2	is	be	AUX
ajst-2538	94	3	positive	positive	ADJ
ajst-2538	94	4	the	the	DET
ajst-2538	94	5	odds	odd	NOUN
ajst-2538	94	6	ratio	ratio	NOUN
ajst-2538	94	7	would	would	AUX
ajst-2538	94	8	increase	increase	VERB
ajst-2538	94	9	.	.	PUNCT
ajst-2538	95	1	conversely	conversely	ADV
ajst-2538	95	2	,	,	PUNCT
ajst-2538	95	3	if	if	SCONJ
ajst-2538	95	4	is	be	AUX
ajst-2538	95	5	negative	negative	ADJ
ajst-2538	95	6	,	,	PUNCT
ajst-2538	95	7	then	then	ADV
ajst-2538	95	8	the	the	DET
ajst-2538	95	9	odds	odd	NOUN
ajst-2538	95	10	ratio	ratio	NOUN
ajst-2538	95	11	would	would	AUX
ajst-2538	95	12	decrease	decrease	VERB
ajst-2538	95	13	.	.	PUNCT
ajst-2538	96	1	from	from	ADP
ajst-2538	96	2	these	these	PRON
ajst-2538	96	3	,	,	PUNCT
ajst-2538	96	4	it	it	PRON
ajst-2538	96	5	can	can	AUX
ajst-2538	96	6	be	be	AUX
ajst-2538	96	7	established	establish	VERB
ajst-2538	96	8	:	:	PUNCT
ajst-2538	97	1	1	1	NUM
ajst-2538	97	2	1	1	NUM
ajst-2538	97	3	⋯	⋯	ADP
ajst-2538	97	4	4.2	4.2	NUM
ajst-2538	97	5	.	.	PUNCT
ajst-2538	98	1	risk	risk	NOUN
ajst-2538	98	2	evaluation	evaluation	NOUN
ajst-2538	98	3	on	on	ADP
ajst-2538	98	4	logistic	logistic	ADJ
ajst-2538	98	5	regression	regression	NOUN
ajst-2538	98	6	4.2.1	4.2.1	NUM
ajst-2538	98	7	.	.	PUNCT
ajst-2538	99	1	accuracy	accuracy	NOUN
ajst-2538	99	2	as	as	ADP
ajst-2538	99	3	a	a	DET
ajst-2538	99	4	linear	linear	ADJ
ajst-2538	99	5	model	model	NOUN
ajst-2538	99	6	,	,	PUNCT
ajst-2538	99	7	logistic	logistic	ADJ
ajst-2538	99	8	models	model	NOUN
ajst-2538	99	9	have	have	VERB
ajst-2538	99	10	high	high	ADJ
ajst-2538	99	11	accuracy	accuracy	NOUN
ajst-2538	99	12	,	,	PUNCT
ajst-2538	99	13	stability	stability	NOUN
ajst-2538	99	14	.	.	PUNCT
ajst-2538	100	1	logistic	logistic	ADJ
ajst-2538	100	2	regression	regression	NOUN
ajst-2538	100	3	requires	require	VERB
ajst-2538	100	4	more	more	ADJ
ajst-2538	100	5	data	datum	NOUN
ajst-2538	100	6	to	to	PART
ajst-2538	100	7	fit	fit	VERB
ajst-2538	100	8	a	a	DET
ajst-2538	100	9	better	well	ADJ
ajst-2538	100	10	model	model	NOUN
ajst-2538	100	11	;	;	PUNCT
ajst-2538	100	12	yet	yet	CCONJ
ajst-2538	100	13	a	a	DET
ajst-2538	100	14	large	large	ADJ
ajst-2538	100	15	number	number	NOUN
ajst-2538	100	16	of	of	ADP
ajst-2538	100	17	multiclass	multiclass	ADJ
ajst-2538	100	18	features	feature	NOUN
ajst-2538	100	19	or	or	CCONJ
ajst-2538	100	20	variables	variable	NOUN
ajst-2538	100	21	are	be	AUX
ajst-2538	100	22	not	not	PART
ajst-2538	100	23	handled	handle	VERB
ajst-2538	100	24	well	well	ADV
ajst-2538	100	25	as	as	SCONJ
ajst-2538	100	26	logistic	logistic	ADJ
ajst-2538	100	27	regression	regression	NOUN
ajst-2538	100	28	has	have	AUX
ajst-2538	100	29	limited	limit	VERB
ajst-2538	100	30	learning	learning	NOUN
ajst-2538	100	31	ability	ability	NOUN
ajst-2538	100	32	.	.	PUNCT
ajst-2538	101	1	logistic	logistic	ADJ
ajst-2538	101	2	regression	regression	NOUN
ajst-2538	101	3	is	be	AUX
ajst-2538	101	4	sensitive	sensitive	ADJ
ajst-2538	101	5	to	to	ADP
ajst-2538	101	6	outliers	outlier	NOUN
ajst-2538	101	7	and	and	CCONJ
ajst-2538	101	8	is	be	AUX
ajst-2538	101	9	easy	easy	ADJ
ajst-2538	101	10	to	to	PART
ajst-2538	101	11	overfit	overfit	VERB
ajst-2538	101	12	and	and	CCONJ
ajst-2538	101	13	underfit	underfit	NOUN
ajst-2538	101	14	.	.	PUNCT
ajst-2538	102	1	therefore	therefore	ADV
ajst-2538	102	2	,	,	PUNCT
ajst-2538	102	3	its	its	PRON
ajst-2538	102	4	classification	classification	NOUN
ajst-2538	102	5	accuracy	accuracy	NOUN
ajst-2538	102	6	is	be	AUX
ajst-2538	102	7	not	not	PART
ajst-2538	102	8	high	high	ADJ
ajst-2538	102	9	.	.	PUNCT
ajst-2538	103	1	for	for	ADP
ajst-2538	103	2	variable	variable	ADJ
ajst-2538	103	3	filtering	filtering	NOUN
ajst-2538	103	4	or	or	CCONJ
ajst-2538	103	5	dimensionality	dimensionality	NOUN
ajst-2538	103	6	reduction	reduction	NOUN
ajst-2538	103	7	,	,	PUNCT
ajst-2538	103	8	the	the	DET
ajst-2538	103	9	model	model	NOUN
ajst-2538	103	10	has	have	VERB
ajst-2538	103	11	high	high	ADJ
ajst-2538	103	12	requirements	requirement	NOUN
ajst-2538	103	13	of	of	ADP
ajst-2538	103	14	financial	financial	ADJ
ajst-2538	103	15	indicators	indicator	NOUN
ajst-2538	103	16	and	and	CCONJ
ajst-2538	103	17	data	datum	NOUN
ajst-2538	103	18	quality	quality	NOUN
ajst-2538	103	19	.	.	PUNCT
ajst-2538	104	1	if	if	SCONJ
ajst-2538	104	2	the	the	DET
ajst-2538	104	3	number	number	NOUN
ajst-2538	104	4	of	of	ADP
ajst-2538	104	5	metrics	metric	NOUN
ajst-2538	104	6	is	be	AUX
ajst-2538	104	7	large	large	ADJ
ajst-2538	104	8	and	and	CCONJ
ajst-2538	104	9	the	the	DET
ajst-2538	104	10	processing	processing	NOUN
ajst-2538	104	11	of	of	ADP
ajst-2538	104	12	it	it	PRON
ajst-2538	104	13	is	be	AUX
ajst-2538	104	14	inappropriate	inappropriate	ADJ
ajst-2538	104	15	,	,	PUNCT
ajst-2538	104	16	it	it	PRON
ajst-2538	104	17	reduces	reduce	VERB
ajst-2538	104	18	the	the	DET
ajst-2538	104	19	accuracy	accuracy	NOUN
ajst-2538	104	20	of	of	ADP
ajst-2538	104	21	the	the	DET
ajst-2538	104	22	model	model	NOUN
ajst-2538	104	23	's	's	PART
ajst-2538	104	24	predictions	prediction	NOUN
ajst-2538	104	25	.	.	PUNCT
ajst-2538	105	1	therefore	therefore	ADV
ajst-2538	105	2	,	,	PUNCT
ajst-2538	105	3	before	before	SCONJ
ajst-2538	105	4	the	the	DET
ajst-2538	105	5	model	model	NOUN
ajst-2538	105	6	predicts	predict	VERB
ajst-2538	105	7	the	the	DET
ajst-2538	105	8	classification	classification	NOUN
ajst-2538	105	9	,	,	PUNCT
ajst-2538	105	10	it	it	PRON
ajst-2538	105	11	needs	need	VERB
ajst-2538	105	12	to	to	PART
ajst-2538	105	13	add	add	VERB
ajst-2538	105	14	a	a	DET
ajst-2538	105	15	combination	combination	NOUN
ajst-2538	105	16	of	of	ADP
ajst-2538	105	17	feature	feature	NOUN
ajst-2538	105	18	indicators	indicator	NOUN
ajst-2538	105	19	to	to	ADP
ajst-2538	105	20	the	the	DET
ajst-2538	105	21	original	original	ADJ
ajst-2538	105	22	indicator	indicator	NOUN
ajst-2538	105	23	and	and	CCONJ
ajst-2538	105	24	apply	apply	VERB
ajst-2538	105	25	them	they	PRON
ajst-2538	105	26	to	to	ADP
ajst-2538	105	27	logistic	logistic	ADJ
ajst-2538	105	28	regression	regression	NOUN
ajst-2538	105	29	model	model	NOUN
ajst-2538	105	30	predictions	prediction	NOUN
ajst-2538	105	31	.	.	PUNCT
ajst-2538	106	1	to	to	PART
ajst-2538	106	2	compensate	compensate	VERB
ajst-2538	106	3	for	for	ADP
ajst-2538	106	4	the	the	DET
ajst-2538	106	5	logistic	logistic	ADJ
ajst-2538	106	6	model	model	NOUN
ajst-2538	106	7	's	's	PART
ajst-2538	106	8	high	high	ADJ
ajst-2538	106	9	data	datum	NOUN
ajst-2538	106	10	requirements	requirement	NOUN
ajst-2538	106	11	and	and	CCONJ
ajst-2538	106	12	insufficient	insufficient	ADJ
ajst-2538	106	13	interpretation	interpretation	NOUN
ajst-2538	106	14	of	of	ADP
ajst-2538	106	15	the	the	DET
ajst-2538	106	16	target	target	NOUN
ajst-2538	106	17	,	,	PUNCT
ajst-2538	106	18	logistic	logistic	ADJ
ajst-2538	106	19	regression	regression	NOUN
ajst-2538	106	20	is	be	AUX
ajst-2538	106	21	often	often	ADV
ajst-2538	106	22	combined	combine	VERB
ajst-2538	106	23	with	with	ADP
ajst-2538	106	24	the	the	DET
ajst-2538	106	25	gdbt	gdbt	PROPN
ajst-2538	106	26	model	model	PROPN
ajst-2538	106	27	.	.	PUNCT
ajst-2538	107	1	facebook	facebook	PROPN
ajst-2538	107	2	proposed	propose	VERB
ajst-2538	107	3	in	in	ADP
ajst-2538	107	4	2014	2014	NUM
ajst-2538	107	5	that	that	SCONJ
ajst-2538	107	6	gbdt	gbdt	NOUN
ajst-2538	107	7	is	be	AUX
ajst-2538	107	8	used	use	VERB
ajst-2538	107	9	to	to	PART
ajst-2538	107	10	solve	solve	VERB
ajst-2538	107	11	the	the	DET
ajst-2538	107	12	problem	problem	NOUN
ajst-2538	107	13	of	of	ADP
ajst-2538	107	14	logistic	logistic	ADJ
ajst-2538	107	15	model	model	NOUN
ajst-2538	107	16	feature	feature	NOUN
ajst-2538	107	17	combination	combination	NOUN
ajst-2538	107	18	,	,	PUNCT
ajst-2538	107	19	which	which	PRON
ajst-2538	107	20	successfully	successfully	ADV
ajst-2538	107	21	improves	improve	VERB
ajst-2538	107	22	the	the	DET
ajst-2538	107	23	accuracy	accuracy	NOUN
ajst-2538	107	24	of	of	ADP
ajst-2538	107	25	model	model	NOUN
ajst-2538	107	26	prediction	prediction	NOUN
ajst-2538	107	27	confirmatory	confirmatory	NOUN
ajst-2538	107	28	rate	rate	NOUN
ajst-2538	108	1	[	[	X
ajst-2538	108	2	8	8	NUM
ajst-2538	108	3	]	]	PUNCT
ajst-2538	108	4	.	.	PUNCT
ajst-2538	109	1	4.2.2	4.2.2	X
ajst-2538	109	2	.	.	PUNCT
ajst-2538	109	3	adaptability	adaptability	NOUN
ajst-2538	109	4	unlike	unlike	ADP
ajst-2538	109	5	multilinear	multilinear	PROPN
ajst-2538	109	6	regression	regression	NOUN
ajst-2538	109	7	,	,	PUNCT
ajst-2538	109	8	logistic	logistic	ADJ
ajst-2538	109	9	regression	regression	NOUN
ajst-2538	109	10	model	model	NOUN
ajst-2538	109	11	does	do	AUX
ajst-2538	109	12	not	not	PART
ajst-2538	109	13	require	require	VERB
ajst-2538	109	14	both	both	CCONJ
ajst-2538	109	15	independent	independent	ADJ
ajst-2538	109	16	and	and	CCONJ
ajst-2538	109	17	dependent	dependent	ADJ
ajst-2538	109	18	variables	variable	NOUN
ajst-2538	109	19	to	to	PART
ajst-2538	109	20	be	be	AUX
ajst-2538	109	21	continuous	continuous	ADJ
ajst-2538	109	22	variables	variable	NOUN
ajst-2538	109	23	.	.	PUNCT
ajst-2538	110	1	however	however	ADV
ajst-2538	110	2	,	,	PUNCT
ajst-2538	110	3	the	the	DET
ajst-2538	110	4	dependent	dependent	ADJ
ajst-2538	110	5	variable	variable	NOUN
ajst-2538	110	6	can	can	AUX
ajst-2538	110	7	only	only	ADV
ajst-2538	110	8	take	take	VERB
ajst-2538	110	9	the	the	DET
ajst-2538	110	10	values	value	NOUN
ajst-2538	110	11	0	0	PUNCT
ajst-2538	110	12	and	and	CCONJ
ajst-2538	110	13	1	1	NUM
ajst-2538	110	14	.	.	PUNCT
ajst-2538	111	1	therefore	therefore	ADV
ajst-2538	111	2	,	,	PUNCT
ajst-2538	111	3	the	the	DET
ajst-2538	111	4	model	model	NOUN
ajst-2538	111	5	is	be	AUX
ajst-2538	111	6	more	more	ADV
ajst-2538	111	7	suitable	suitable	ADJ
ajst-2538	111	8	for	for	SCONJ
ajst-2538	111	9	binary	binary	ADJ
ajst-2538	111	10	classification	classification	NOUN
ajst-2538	111	11	problems	problem	NOUN
ajst-2538	111	12	ohlson	ohlson	PROPN
ajst-2538	111	13	was	be	AUX
ajst-2538	111	14	the	the	DET
ajst-2538	111	15	first	first	ADJ
ajst-2538	111	16	to	to	PART
ajst-2538	111	17	apply	apply	VERB
ajst-2538	111	18	logistic	logistic	ADJ
ajst-2538	111	19	regression	regression	NOUN
ajst-2538	111	20	to	to	ADP
ajst-2538	111	21	financial	financial	ADJ
ajst-2538	111	22	risk	risk	NOUN
ajst-2538	111	23	warning	warning	NOUN
ajst-2538	111	24	,	,	PUNCT
ajst-2538	111	25	which	which	PRON
ajst-2538	111	26	confirmed	confirm	VERB
ajst-2538	111	27	to	to	PART
ajst-2538	111	28	have	have	VERB
ajst-2538	111	29	a	a	DET
ajst-2538	111	30	good	good	ADJ
ajst-2538	111	31	classification	classification	NOUN
ajst-2538	111	32	effect	effect	NOUN
ajst-2538	111	33	[	[	X
ajst-2538	111	34	9	9	NUM
ajst-2538	111	35	]	]	PUNCT
ajst-2538	111	36	.	.	PUNCT
ajst-2538	112	1	the	the	DET
ajst-2538	112	2	model	model	NOUN
ajst-2538	112	3	was	be	AUX
ajst-2538	112	4	able	able	ADJ
ajst-2538	112	5	to	to	PART
ajst-2538	112	6	determine	determine	VERB
ajst-2538	112	7	whether	whether	SCONJ
ajst-2538	112	8	financial	financial	ADJ
ajst-2538	112	9	risks	risk	NOUN
ajst-2538	112	10	have	have	AUX
ajst-2538	112	11	occurred	occur	VERB
ajst-2538	112	12	and	and	CCONJ
ajst-2538	112	13	can	can	AUX
ajst-2538	112	14	objectively	objectively	ADV
ajst-2538	112	15	assess	assess	VERB
ajst-2538	112	16	the	the	DET
ajst-2538	112	17	probability	probability	NOUN
ajst-2538	112	18	of	of	ADP
ajst-2538	112	19	financial	financial	ADJ
ajst-2538	112	20	risk	risk	NOUN
ajst-2538	112	21	in	in	ADP
ajst-2538	112	22	a	a	DET
ajst-2538	112	23	business	business	NOUN
ajst-2538	112	24	.	.	PUNCT
ajst-2538	113	1	at	at	ADP
ajst-2538	113	2	the	the	DET
ajst-2538	113	3	same	same	ADJ
ajst-2538	113	4	time	time	NOUN
ajst-2538	113	5	,	,	PUNCT
ajst-2538	113	6	the	the	DET
ajst-2538	113	7	model	model	NOUN
ajst-2538	113	8	overcomes	overcome	VERB
ajst-2538	113	9	the	the	DET
ajst-2538	113	10	shortcomings	shortcoming	NOUN
ajst-2538	113	11	of	of	ADP
ajst-2538	113	12	multivariate	multivariate	NOUN
ajst-2538	113	13	discriminant	discriminant	ADJ
ajst-2538	113	14	analysis	analysis	NOUN
ajst-2538	113	15	,	,	PUNCT
ajst-2538	113	16	which	which	PRON
ajst-2538	113	17	requires	require	VERB
ajst-2538	113	18	the	the	DET
ajst-2538	113	19	data	datum	NOUN
ajst-2538	113	20	to	to	PART
ajst-2538	113	21	satisfy	satisfy	VERB
ajst-2538	113	22	the	the	DET
ajst-2538	113	23	normal	normal	ADJ
ajst-2538	113	24	distribution	distribution	NOUN
ajst-2538	113	25	.	.	PUNCT
ajst-2538	114	1	4.2.3	4.2.3	X
ajst-2538	114	2	.	.	PUNCT
ajst-2538	115	1	efficiency	efficiency	VERB
ajst-2538	115	2	the	the	DET
ajst-2538	115	3	amount	amount	NOUN
ajst-2538	115	4	of	of	ADP
ajst-2538	115	5	calculation	calculation	NOUN
ajst-2538	115	6	involved	involve	VERB
ajst-2538	115	7	is	be	AUX
ajst-2538	115	8	small	small	ADJ
ajst-2538	115	9	,	,	PUNCT
ajst-2538	115	10	hence	hence	ADV
ajst-2538	115	11	it	it	PRON
ajst-2538	115	12	is	be	AUX
ajst-2538	115	13	fast	fast	ADJ
ajst-2538	115	14	and	and	CCONJ
ajst-2538	115	15	does	do	AUX
ajst-2538	115	16	not	not	PART
ajst-2538	115	17	require	require	VERB
ajst-2538	115	18	much	much	ADJ
ajst-2538	115	19	storage	storage	NOUN
ajst-2538	115	20	.	.	PUNCT
ajst-2538	116	1	however	however	ADV
ajst-2538	116	2	,	,	PUNCT
ajst-2538	116	3	there	there	PRON
ajst-2538	116	4	is	be	VERB
ajst-2538	116	5	a	a	DET
ajst-2538	116	6	tradeoff	tradeoff	NOUN
ajst-2538	116	7	between	between	ADP
ajst-2538	116	8	feature	feature	NOUN
ajst-2538	116	9	space	space	NOUN
ajst-2538	116	10	and	and	CCONJ
ajst-2538	116	11	logistic	logistic	ADJ
ajst-2538	116	12	regression	regression	NOUN
ajst-2538	116	13	performance	performance	NOUN
ajst-2538	116	14	.	.	PUNCT
ajst-2538	117	1	4.2.4	4.2.4	X
ajst-2538	117	2	.	.	PUNCT
ajst-2538	118	1	simplicity	simplicity	NOUN
ajst-2538	118	2	logistic	logistic	ADJ
ajst-2538	118	3	regression	regression	NOUN
ajst-2538	118	4	holds	hold	VERB
ajst-2538	118	5	the	the	DET
ajst-2538	118	6	advantage	advantage	NOUN
ajst-2538	118	7	of	of	ADP
ajst-2538	118	8	having	have	VERB
ajst-2538	118	9	fewer	few	ADJ
ajst-2538	118	10	parameters	parameter	NOUN
ajst-2538	118	11	.	.	PUNCT
ajst-2538	119	1	it	it	PRON
ajst-2538	119	2	is	be	AUX
ajst-2538	119	3	a	a	DET
ajst-2538	119	4	generalized	generalized	ADJ
ajst-2538	119	5	linear	linear	ADJ
ajst-2538	119	6	regression	regression	NOUN
ajst-2538	119	7	analytical	analytical	ADJ
ajst-2538	119	8	model	model	NOUN
ajst-2538	119	9	,	,	PUNCT
ajst-2538	119	10	and	and	CCONJ
ajst-2538	119	11	is	be	AUX
ajst-2538	119	12	simple	simple	ADJ
ajst-2538	119	13	to	to	PART
ajst-2538	119	14	implement	implement	VERB
ajst-2538	119	15	.	.	PUNCT
ajst-2538	120	1	it	it	PRON
ajst-2538	120	2	is	be	AUX
ajst-2538	120	3	an	an	DET
ajst-2538	120	4	excellent	excellent	ADJ
ajst-2538	120	5	classification	classification	NOUN
ajst-2538	120	6	model	model	NOUN
ajst-2538	120	7	for	for	ADP
ajst-2538	120	8	linear	linear	PROPN
ajst-2538	120	9	separable	separable	ADJ
ajst-2538	120	10	problems	problem	NOUN
ajst-2538	120	11	.	.	PUNCT
ajst-2538	121	1	4.2.5	4.2.5	X
ajst-2538	121	2	.	.	X
ajst-2538	122	1	interpretability	interpretability	NOUN
ajst-2538	122	2	the	the	DET
ajst-2538	122	3	explanatory	explanatory	ADJ
ajst-2538	122	4	ability	ability	NOUN
ajst-2538	122	5	of	of	ADP
ajst-2538	122	6	logistic	logistic	ADJ
ajst-2538	122	7	regression	regression	NOUN
ajst-2538	122	8	is	be	AUX
ajst-2538	122	9	relatively	relatively	ADV
ajst-2538	122	10	strong	strong	ADJ
ajst-2538	122	11	and	and	CCONJ
ajst-2538	122	12	convenient	convenient	ADJ
ajst-2538	122	13	to	to	PART
ajst-2538	122	14	use	use	VERB
ajst-2538	122	15	,	,	PUNCT
ajst-2538	122	16	and	and	CCONJ
ajst-2538	122	17	most	most	ADJ
ajst-2538	122	18	scorecards	scorecard	NOUN
ajst-2538	122	19	are	be	AUX
ajst-2538	122	20	based	base	VERB
ajst-2538	122	21	on	on	ADP
ajst-2538	122	22	logic	logic	NOUN
ajst-2538	122	23	regression	regression	NOUN
ajst-2538	122	24	build	build	VERB
ajst-2538	122	25	.	.	PUNCT
ajst-2538	123	1	the	the	DET
ajst-2538	123	2	output	output	NOUN
ajst-2538	123	3	of	of	ADP
ajst-2538	123	4	the	the	DET
ajst-2538	123	5	prediction	prediction	NOUN
ajst-2538	123	6	result	result	NOUN
ajst-2538	123	7	is	be	AUX
ajst-2538	123	8	probability	probability	NOUN
ajst-2538	123	9	,	,	PUNCT
ajst-2538	123	10	between	between	ADP
ajst-2538	123	11	0	0	NUM
ajst-2538	123	12	and	and	CCONJ
ajst-2538	123	13	1	1	NUM
ajst-2538	123	14	.	.	PUNCT
ajst-2538	124	1	the	the	DET
ajst-2538	124	2	weighting	weighting	NOUN
ajst-2538	124	3	of	of	ADP
ajst-2538	124	4	each	each	DET
ajst-2538	124	5	variable	variable	NOUN
ajst-2538	124	6	is	be	AUX
ajst-2538	124	7	also	also	ADV
ajst-2538	124	8	evident	evident	ADJ
ajst-2538	124	9	and	and	CCONJ
ajst-2538	124	10	the	the	DET
ajst-2538	124	11	calculated	calculate	VERB
ajst-2538	124	12	coefficients	coefficient	NOUN
ajst-2538	124	13	are	be	AUX
ajst-2538	124	14	interpretable	interpretable	ADJ
ajst-2538	124	15	,	,	PUNCT
ajst-2538	124	16	so	so	SCONJ
ajst-2538	124	17	the	the	DET
ajst-2538	124	18	result	result	NOUN
ajst-2538	124	19	is	be	AUX
ajst-2538	124	20	easy	easy	ADJ
ajst-2538	124	21	to	to	PART
ajst-2538	124	22	understand	understand	VERB
ajst-2538	124	23	.	.	PUNCT
ajst-2538	125	1	however	however	ADV
ajst-2538	125	2	,	,	PUNCT
ajst-2538	125	3	if	if	SCONJ
ajst-2538	125	4	the	the	DET
ajst-2538	125	5	number	number	NOUN
ajst-2538	125	6	of	of	ADP
ajst-2538	125	7	metrics	metric	NOUN
ajst-2538	125	8	is	be	AUX
ajst-2538	125	9	large	large	ADJ
ajst-2538	125	10	and	and	CCONJ
ajst-2538	125	11	the	the	DET
ajst-2538	125	12	processing	processing	NOUN
ajst-2538	125	13	of	of	ADP
ajst-2538	125	14	it	it	PRON
ajst-2538	125	15	is	be	AUX
ajst-2538	125	16	inappropriate	inappropriate	ADJ
ajst-2538	125	17	,	,	PUNCT
ajst-2538	125	18	the	the	DET
ajst-2538	125	19	interpretation	interpretation	NOUN
ajst-2538	125	20	of	of	ADP
ajst-2538	125	21	the	the	DET
ajst-2538	125	22	metrics	metric	NOUN
ajst-2538	125	23	on	on	ADP
ajst-2538	125	24	the	the	DET
ajst-2538	125	25	objective	objective	NOUN
ajst-2538	125	26	is	be	AUX
ajst-2538	125	27	quite	quite	ADV
ajst-2538	125	28	poor	poor	ADJ
ajst-2538	125	29	.	.	PUNCT
ajst-2538	126	1	5	5	X
ajst-2538	126	2	.	.	X
ajst-2538	126	3	conclusion	conclusion	NOUN
ajst-2538	126	4	it	it	PRON
ajst-2538	126	5	is	be	AUX
ajst-2538	126	6	impossible	impossible	ADJ
ajst-2538	126	7	to	to	PART
ajst-2538	126	8	anticipate	anticipate	VERB
ajst-2538	126	9	the	the	DET
ajst-2538	126	10	changes	change	NOUN
ajst-2538	126	11	in	in	ADP
ajst-2538	126	12	exogenous	exogenous	ADJ
ajst-2538	126	13	factors	factor	NOUN
ajst-2538	126	14	,	,	PUNCT
ajst-2538	126	15	hence	hence	ADV
ajst-2538	126	16	it	it	PRON
ajst-2538	126	17	is	be	AUX
ajst-2538	126	18	particularly	particularly	ADV
ajst-2538	126	19	important	important	ADJ
ajst-2538	126	20	for	for	SCONJ
ajst-2538	126	21	quantitative	quantitative	ADJ
ajst-2538	126	22	investment	investment	NOUN
ajst-2538	126	23	institutions	institution	NOUN
ajst-2538	126	24	to	to	PART
ajst-2538	126	25	enhance	enhance	VERB
ajst-2538	126	26	their	their	PRON
ajst-2538	126	27	capabilities	capability	NOUN
ajst-2538	126	28	and	and	CCONJ
ajst-2538	126	29	reserve	reserve	VERB
ajst-2538	126	30	differentiated	differentiated	ADJ
ajst-2538	126	31	investment	investment	NOUN
ajst-2538	126	32	strategies	strategy	NOUN
ajst-2538	126	33	to	to	PART
ajst-2538	126	34	cope	cope	VERB
ajst-2538	126	35	with	with	ADP
ajst-2538	126	36	market	market	NOUN
ajst-2538	126	37	shocks	shock	NOUN
ajst-2538	126	38	.	.	PUNCT
ajst-2538	127	1	asset	asset	NOUN
ajst-2538	127	2	managers	manager	NOUN
ajst-2538	127	3	should	should	AUX
ajst-2538	127	4	be	be	AUX
ajst-2538	127	5	equipped	equip	VERB
ajst-2538	127	6	with	with	ADP
ajst-2538	127	7	the	the	DET
ajst-2538	127	8	ability	ability	NOUN
ajst-2538	127	9	to	to	PART
ajst-2538	127	10	understand	understand	VERB
ajst-2538	127	11	the	the	DET
ajst-2538	127	12	inner	inner	ADJ
ajst-2538	127	13	workings	working	NOUN
ajst-2538	127	14	of	of	ADP
ajst-2538	127	15	a	a	DET
ajst-2538	127	16	model	model	NOUN
ajst-2538	127	17	as	as	SCONJ
ajst-2538	127	18	they	they	PRON
ajst-2538	127	19	have	have	VERB
ajst-2538	127	20	a	a	DET
ajst-2538	127	21	fiduciary	fiduciary	ADJ
ajst-2538	127	22	responsibility	responsibility	NOUN
ajst-2538	127	23	to	to	PART
ajst-2538	127	24	understand	understand	VERB
ajst-2538	127	25	and	and	CCONJ
ajst-2538	127	26	communicate	communicate	VERB
ajst-2538	127	27	the	the	DET
ajst-2538	127	28	risks	risk	NOUN
ajst-2538	127	29	of	of	ADP
ajst-2538	127	30	their	their	PRON
ajst-2538	127	31	clients	client	NOUN
ajst-2538	127	32	’	’	PART
ajst-2538	127	33	portfolios	portfolio	NOUN
ajst-2538	127	34	.	.	PUNCT
ajst-2538	128	1	this	this	DET
ajst-2538	128	2	places	place	NOUN
ajst-2538	128	3	particular	particular	ADJ
ajst-2538	128	4	emphasis	emphasis	NOUN
ajst-2538	128	5	on	on	ADP
ajst-2538	128	6	the	the	DET
ajst-2538	128	7	interpretability	interpretability	NOUN
ajst-2538	128	8	of	of	ADP
ajst-2538	128	9	their	their	PRON
ajst-2538	128	10	models	model	NOUN
ajst-2538	128	11	.	.	PUNCT
ajst-2538	129	1	in	in	ADP
ajst-2538	129	2	addition	addition	NOUN
ajst-2538	129	3	,	,	PUNCT
ajst-2538	129	4	institutions	institution	NOUN
ajst-2538	129	5	should	should	AUX
ajst-2538	129	6	set	set	VERB
ajst-2538	129	7	appropriate	appropriate	ADJ
ajst-2538	129	8	investment	investment	NOUN
ajst-2538	129	9	target	target	NOUN
ajst-2538	129	10	and	and	CCONJ
ajst-2538	129	11	select	select	VERB
ajst-2538	129	12	the	the	DET
ajst-2538	129	13	strategic	strategic	ADJ
ajst-2538	129	14	model	model	NOUN
ajst-2538	129	15	that	that	PRON
ajst-2538	129	16	can	can	AUX
ajst-2538	129	17	undertake	undertake	VERB
ajst-2538	129	18	risks	risk	NOUN
ajst-2538	129	19	under	under	ADP
ajst-2538	129	20	the	the	DET
ajst-2538	129	21	target	target	NOUN
ajst-2538	129	22	frame	frame	NOUN
ajst-2538	129	23	.	.	PUNCT
ajst-2538	130	1	through	through	ADP
ajst-2538	130	2	evaluations	evaluation	NOUN
ajst-2538	130	3	of	of	ADP
ajst-2538	130	4	past	past	ADJ
ajst-2538	130	5	researches	research	NOUN
ajst-2538	130	6	,	,	PUNCT
ajst-2538	130	7	this	this	DET
ajst-2538	130	8	paper	paper	NOUN
ajst-2538	130	9	first	first	ADV
ajst-2538	130	10	highlighted	highlight	VERB
ajst-2538	130	11	the	the	DET
ajst-2538	130	12	characteristics	characteristic	NOUN
ajst-2538	130	13	of	of	ADP
ajst-2538	130	14	random	random	ADJ
ajst-2538	130	15	forest	forest	NOUN
ajst-2538	130	16	,	,	PUNCT
ajst-2538	130	17	xg	xg	PROPN
ajst-2538	130	18	boost	boost	NOUN
ajst-2538	130	19	,	,	PUNCT
ajst-2538	130	20	and	and	CCONJ
ajst-2538	130	21	logistic	logistic	ADJ
ajst-2538	130	22	regression	regression	NOUN
ajst-2538	130	23	.	.	PUNCT
ajst-2538	131	1	then	then	ADV
ajst-2538	131	2	this	this	DET
ajst-2538	131	3	paper	paper	NOUN
ajst-2538	131	4	evaluates	evaluate	VERB
ajst-2538	131	5	the	the	DET
ajst-2538	131	6	accuracy	accuracy	NOUN
ajst-2538	131	7	,	,	PUNCT
ajst-2538	131	8	validity	validity	NOUN
ajst-2538	131	9	and	and	CCONJ
ajst-2538	131	10	the	the	DET
ajst-2538	131	11	adaptability	adaptability	NOUN
ajst-2538	131	12	of	of	ADP
ajst-2538	131	13	the	the	DET
ajst-2538	131	14	model	model	NOUN
ajst-2538	131	15	which	which	PRON
ajst-2538	131	16	would	would	AUX
ajst-2538	131	17	affect	affect	VERB
ajst-2538	131	18	the	the	DET
ajst-2538	131	19	model	model	NOUN
ajst-2538	131	20	failure	failure	NOUN
ajst-2538	131	21	risks	risk	NOUN
ajst-2538	131	22	,	,	PUNCT
ajst-2538	131	23	and	and	CCONJ
ajst-2538	131	24	the	the	DET
ajst-2538	131	25	efficiency	efficiency	NOUN
ajst-2538	131	26	,	,	PUNCT
ajst-2538	131	27	simplicity	simplicity	NOUN
ajst-2538	131	28	and	and	CCONJ
ajst-2538	131	29	the	the	DET
ajst-2538	131	30	interpretability	interpretability	NOUN
ajst-2538	131	31	of	of	ADP
ajst-2538	131	32	the	the	DET
ajst-2538	131	33	results	result	NOUN
ajst-2538	131	34	which	which	PRON
ajst-2538	131	35	would	would	AUX
ajst-2538	131	36	affect	affect	VERB
ajst-2538	131	37	strategic	strategic	ADJ
ajst-2538	131	38	application	application	NOUN
ajst-2538	131	39	risk	risk	NOUN
ajst-2538	131	40	.	.	PUNCT
ajst-2538	132	1	many	many	ADJ
ajst-2538	132	2	interesting	interesting	ADJ
ajst-2538	132	3	potential	potential	ADJ
ajst-2538	132	4	avenues	avenue	NOUN
ajst-2538	132	5	of	of	ADP
ajst-2538	132	6	research	research	NOUN
ajst-2538	132	7	to	to	PART
ajst-2538	132	8	draw	draw	VERB
ajst-2538	132	9	more	more	ADV
ajst-2538	132	10	meaningful	meaningful	ADJ
ajst-2538	132	11	and	and	CCONJ
ajst-2538	132	12	institutive	institutive	ADJ
ajst-2538	132	13	conclusions	conclusion	NOUN
ajst-2538	132	14	from	from	ADP
ajst-2538	132	15	financial	financial	ADJ
ajst-2538	132	16	machine	machine	NOUN
ajst-2538	132	17	learning	learning	NOUN
ajst-2538	132	18	models	model	NOUN
ajst-2538	132	19	.	.	PUNCT
ajst-2538	133	1	this	this	DET
ajst-2538	133	2	paper	paper	NOUN
ajst-2538	133	3	aimed	aim	VERB
ajst-2538	133	4	to	to	PART
ajst-2538	133	5	construct	construct	VERB
ajst-2538	133	6	a	a	DET
ajst-2538	133	7	theoretical	theoretical	ADJ
ajst-2538	133	8	comparison	comparison	NOUN
ajst-2538	133	9	between	between	ADP
ajst-2538	133	10	different	different	ADJ
ajst-2538	133	11	algorithms	algorithm	NOUN
ajst-2538	133	12	of	of	ADP
ajst-2538	133	13	machine	machine	NOUN
ajst-2538	133	14	learning	learning	NOUN
ajst-2538	133	15	that	that	PRON
ajst-2538	133	16	is	be	AUX
ajst-2538	133	17	used	use	VERB
ajst-2538	133	18	in	in	ADP
ajst-2538	133	19	quantitative	quantitative	ADJ
ajst-2538	133	20	investment	investment	NOUN
ajst-2538	133	21	.	.	PUNCT
ajst-2538	134	1	it	it	PRON
ajst-2538	134	2	38	38	NUM
ajst-2538	134	3	hopes	hope	VERB
ajst-2538	134	4	to	to	PART
ajst-2538	134	5	provide	provide	VERB
ajst-2538	134	6	investors	investor	NOUN
ajst-2538	134	7	undertaking	undertake	VERB
ajst-2538	134	8	quantitative	quantitative	ADJ
ajst-2538	134	9	investment	investment	NOUN
ajst-2538	134	10	with	with	ADP
ajst-2538	134	11	a	a	DET
ajst-2538	134	12	guideline	guideline	NOUN
ajst-2538	134	13	,	,	PUNCT
ajst-2538	134	14	from	from	ADP
ajst-2538	134	15	a	a	DET
ajst-2538	134	16	risk	risk	NOUN
ajst-2538	134	17	point	point	NOUN
ajst-2538	134	18	of	of	ADP
ajst-2538	134	19	view	view	NOUN
ajst-2538	134	20	,	,	PUNCT
ajst-2538	134	21	that	that	PRON
ajst-2538	134	22	can	can	AUX
ajst-2538	134	23	be	be	AUX
ajst-2538	134	24	considered	consider	VERB
ajst-2538	134	25	when	when	SCONJ
ajst-2538	134	26	deciding	decide	VERB
ajst-2538	134	27	upon	upon	SCONJ
ajst-2538	134	28	which	which	DET
ajst-2538	134	29	model	model	NOUN
ajst-2538	134	30	they	they	PRON
ajst-2538	134	31	should	should	AUX
ajst-2538	134	32	use	use	VERB
ajst-2538	134	33	.	.	PUNCT
ajst-2538	135	1	references	reference	NOUN
ajst-2538	135	2	[	[	X
ajst-2538	135	3	1	1	NUM
ajst-2538	135	4	]	]	X
ajst-2538	135	5	guan	guan	PROPN
ajst-2538	135	6	runjing	runjing	NOUN
ajst-2538	135	7	(	(	PUNCT
ajst-2538	135	8	southwestern	southwestern	ADJ
ajst-2538	135	9	university	university	NOUN
ajst-2538	135	10	of	of	ADP
ajst-2538	135	11	finance	finance	NOUN
ajst-2538	135	12	and	and	CCONJ
ajst-2538	135	13	economics	economic	NOUN
ajst-2538	135	14	)	)	PUNCT
ajst-2538	135	15	,	,	PUNCT
ajst-2538	135	16	2020	2020	NUM
ajst-2538	135	17	.	.	PUNCT
ajst-2538	136	1	research	research	NOUN
ajst-2538	136	2	on	on	ADP
ajst-2538	136	3	quantitative	quantitative	ADJ
ajst-2538	136	4	investment	investment	NOUN
ajst-2538	136	5	stock	stock	NOUN
ajst-2538	136	6	selection	selection	NOUN
ajst-2538	136	7	based	base	VERB
ajst-2538	136	8	on	on	ADP
ajst-2538	136	9	machine	machine	NOUN
ajst-2538	136	10	learning	learning	NOUN
ajst-2538	136	11	.	.	PUNCT
ajst-2538	137	1	http://jour.ucdrs.superlib.net/views/specific/2929/thesisdetail	http://jour.ucdrs.superlib.net/views/specific/2929/thesisdetail	PROPN
ajst-2538	137	2	.	.	PUNCT
ajst-2538	138	1	jsp?dxnumber=390108795987&d=24e1bb8447c99e46036	jsp?dxnumber=390108795987&d=24e1bb8447c99e46036	NOUN
ajst-2538	138	2	e3917f65046a2&sw	e3917f65046a2&sw	PROPN
ajst-2538	139	1	[	[	X
ajst-2538	139	2	2	2	X
ajst-2538	139	3	]	]	X
ajst-2538	139	4	liu	liu	PROPN
ajst-2538	139	5	wei	wei	PROPN
ajst-2538	139	6	.	.	PUNCT
ajst-2538	140	1	luo	luo	PROPN
ajst-2538	140	2	linkai	linkai	PROPN
ajst-2538	140	3	.	.	PUNCT
ajst-2538	141	1	wang	wang	PROPN
ajst-2538	141	2	huazhen	huazhen	PROPN
ajst-2538	141	3	.	.	PUNCT
ajst-2538	142	1	(	(	PUNCT
ajst-2538	142	2	2008	2008	NUM
ajst-2538	142	3	)	)	PUNCT
ajst-2538	142	4	a	a	DET
ajst-2538	142	5	forecast	forecast	NOUN
ajst-2538	142	6	of	of	ADP
ajst-2538	142	7	bulk	bulk	NOUN
ajst-2538	142	8	–	–	PUNCT
ajst-2538	142	9	holding	hold	VERB
ajst-2538	142	10	stock	stock	NOUN
ajst-2538	142	11	based	base	VERB
ajst-2538	142	12	on	on	ADP
ajst-2538	142	13	random	random	ADJ
ajst-2538	142	14	forest	forest	NOUN
ajst-2538	142	15	.	.	PUNCT
ajst-2538	143	1	journal	journal	PROPN
ajst-2538	143	2	of	of	ADP
ajst-2538	143	3	fuzhou	fuzhou	PROPN
ajst-2538	143	4	university	university	PROPN
ajst-2538	143	5	(	(	PUNCT
ajst-2538	143	6	natural	natural	ADJ
ajst-2538	143	7	science	science	NOUN
ajst-2538	143	8	)	)	PUNCT
ajst-2538	143	9	,	,	PUNCT
ajst-2538	143	10	36	36	NUM
ajst-2538	143	11	:	:	SYM
ajst-2538	143	12	134	134	NUM
ajst-2538	143	13	-	-	SYM
ajst-2538	143	14	139	139	NUM
ajst-2538	143	15	.	.	PUNCT
ajst-2538	144	1	[	[	X
ajst-2538	144	2	3	3	X
ajst-2538	144	3	]	]	X
ajst-2538	144	4	dietterich	dietterich	ADJ
ajst-2538	144	5	t.g	t.g	PROPN
ajst-2538	144	6	.	.	PROPN
ajst-2538	144	7	,	,	PUNCT
ajst-2538	144	8	1998	1998	NUM
ajst-2538	144	9	.	.	PUNCT
ajst-2538	145	1	an	an	DET
ajst-2538	145	2	experimental	experimental	ADJ
ajst-2538	145	3	comparison	comparison	NOUN
ajst-2538	145	4	of	of	ADP
ajst-2538	145	5	three	three	NUM
ajst-2538	145	6	methods	method	NOUN
ajst-2538	145	7	fottp://dx.doi.org/10.1023r	fottp://dx.doi.org/10.1023r	ADP
ajst-2538	145	8	constructing	construct	VERB
ajst-2538	145	9	ensembles	ensemble	NOUN
ajst-2538	145	10	of	of	ADP
ajst-2538	145	11	decision	decision	NOUN
ajst-2538	145	12	tree	tree	NOUN
ajst-2538	145	13	:	:	PUNCT
ajst-2538	145	14	bagging，boosting	bagging，boosting	NOUN
ajst-2538	145	15	and	and	CCONJ
ajst-2538	145	16	randomization	randomization	NOUN
ajst-2538	145	17	.	.	PUNCT
ajst-2538	146	1	machine	machine	NOUN
ajst-2538	146	2	learning	learning	NOUN
ajst-2538	146	3	.	.	PUNCT
ajst-2538	146	4	http://dx.doi.org/10.1023/a;1007607513941	http://dx.doi.org/10.1023/a;1007607513941	PUNCT
ajst-2538	147	1	[	[	X
ajst-2538	147	2	4	4	X
ajst-2538	147	3	]	]	X
ajst-2538	147	4	zhang	zhang	PROPN
ajst-2538	147	5	xiao	xiao	PROPN
ajst-2538	147	6	(	(	PUNCT
ajst-2538	147	7	guangxi	guangxi	PROPN
ajst-2538	147	8	university	university	PROPN
ajst-2538	147	9	)	)	PUNCT
ajst-2538	147	10	,	,	PUNCT
ajst-2538	147	11	2018	2018	NUM
ajst-2538	147	12	.	.	PUNCT
ajst-2538	148	1	quantitative	quantitative	ADJ
ajst-2538	148	2	investment	investment	NOUN
ajst-2538	148	3	model	model	NOUN
ajst-2538	148	4	based	base	VERB
ajst-2538	148	5	on	on	ADP
ajst-2538	148	6	improved	improved	ADJ
ajst-2538	148	7	gbdt	gbdt	NOUN
ajst-2538	148	8	.	.	PUNCT
ajst-2538	149	1	http://jour.ucdrs.superlib.net/views/specific/2929/thesisdetail	http://jour.ucdrs.superlib.net/views/specific/2929/thesisdetail	PROPN
ajst-2538	149	2	.	.	PUNCT
ajst-2538	150	1	jsp?dxnumber=390106882309&d=61e8f81f5e085dc2dd7	jsp?dxnumber=390106882309&d=61e8f81f5e085dc2dd7	PROPN
ajst-2538	150	2	dd12e879976ad&sw	dd12e879976ad&sw	PROPN
ajst-2538	151	1	[	[	X
ajst-2538	151	2	5	5	X
ajst-2538	151	3	]	]	X
ajst-2538	151	4	li	li	PROPN
ajst-2538	151	5	xiang	xiang	PROPN
ajst-2538	151	6	(	(	PUNCT
ajst-2538	151	7	china	china	PROPN
ajst-2538	151	8	academic	academic	PROPN
ajst-2538	151	9	journal	journal	PROPN
ajst-2538	151	10	electronic	electronic	PROPN
ajst-2538	151	11	publishing	publishing	PROPN
ajst-2538	151	12	house	house	PROPN
ajst-2538	151	13	)	)	PUNCT
ajst-2538	151	14	,	,	PUNCT
ajst-2538	151	15	2017	2017	NUM
ajst-2538	151	16	.	.	PUNCT
ajst-2538	152	1	multi	multi	ADJ
ajst-2538	152	2	-	-	ADJ
ajst-2538	152	3	factor	factor	ADJ
ajst-2538	152	4	quantitative	quantitative	ADJ
ajst-2538	152	5	stock	stock	NOUN
ajst-2538	152	6	option	option	NOUN
ajst-2538	152	7	planning	planning	NOUN
ajst-2538	152	8	based	base	VERB
ajst-2538	152	9	on	on	ADP
ajst-2538	152	10	xgboost	xgboost	PROPN
ajst-2538	152	11	algorithm	algorithm	PROPN
ajst-2538	152	12	.	.	PUNCT
ajst-2538	153	1	http://www.cnki.net	http://www.cnki.net	PUNCT
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ajst-2538	154	7	nanjing	nanjing	PROPN
ajst-2538	154	8	university	university	PROPN
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ajst-2538	154	10	,	,	PUNCT
ajst-2538	154	11	2017	2017	NUM
ajst-2538	154	12	.	.	PUNCT
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ajst-2538	155	2	-	-	ADJ
ajst-2538	155	3	factor	factor	NOUN
ajst-2538	155	4	stock	stock	NOUN
ajst-2538	155	5	selection	selection	NOUN
ajst-2538	155	6	scheme	scheme	NOUN
ajst-2538	155	7	design	design	NOUN
ajst-2538	155	8	based	base	VERB
ajst-2538	155	9	on	on	ADP
ajst-2538	155	10	xgboost	xgboost	ADV
ajst-2538	155	11	and	and	CCONJ
ajst-2538	155	12	lightgbm	lightgbm	ADJ
ajst-2538	155	13	algorithm	algorithm	NOUN
ajst-2538	155	14	.	.	PUNCT
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ajst-2538	156	2	.	.	PUNCT
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ajst-2538	158	7	shanghai	shanghai	PROPN
ajst-2538	158	8	normal	normal	ADJ
ajst-2538	158	9	university	university	NOUN
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ajst-2538	158	11	,	,	PUNCT
ajst-2538	158	12	2018	2018	NUM
ajst-2538	158	13	.	.	PUNCT
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ajst-2538	159	2	on	on	ADP
ajst-2538	159	3	shanghai	shanghai	PROPN
ajst-2538	159	4	and	and	CCONJ
ajst-2538	159	5	shenzhen	shenzhen	PROPN
ajst-2538	159	6	300	300	NUM
ajst-2538	159	7	quantitative	quantitative	ADJ
ajst-2538	159	8	investment	investment	NOUN
ajst-2538	159	9	based	base	VERB
ajst-2538	159	10	on	on	ADP
ajst-2538	159	11	xgboost	xgboost	PROPN
ajst-2538	159	12	algorithm	algorithm	PROPN
ajst-2538	159	13	.	.	PUNCT
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ajst-2538	160	2	.	.	PUNCT
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ajst-2538	162	5	x	x	PROPN
ajst-2538	162	6	,	,	PUNCT
ajst-2538	162	7	pan	pan	PROPN
ajst-2538	162	8	j	j	PROPN
ajst-2538	162	9	,	,	PUNCT
ajst-2538	162	10	jin	jin	PROPN
ajst-2538	162	11	o	o	NOUN
ajst-2538	162	12	,	,	PUNCT
ajst-2538	162	13	et	et	PROPN
ajst-2538	162	14	al	al	PROPN
ajst-2538	162	15	(	(	PUNCT
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ajst-2538	162	18	,	,	PUNCT
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ajst-2538	162	20	.	.	PUNCT
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ajst-2538	163	2	lessons	lesson	NOUN
ajst-2538	163	3	from	from	ADP
ajst-2538	163	4	predicting	predict	VERB
ajst-2538	163	5	clicks	click	NOUN
ajst-2538	163	6	on	on	ADP
ajst-2538	163	7	ads	ad	NOUN
ajst-2538	163	8	at	at	ADP
ajst-2538	163	9	facebook	facebook	PROPN
ajst-2538	163	10	.	.	PUNCT
ajst-2538	164	1	https://dl.acm.org/doi/abs/10.1145/2648584.2648589	https://dl.acm.org/doi/abs/10.1145/2648584.2648589	NOUN
ajst-2538	165	1	[	[	X
ajst-2538	165	2	9	9	NUM
ajst-2538	165	3	]	]	SYM
ajst-2538	165	4	ohlson	ohlson	NOUN
ajst-2538	165	5	,	,	PUNCT
ajst-2538	165	6	j.	j.	PROPN
ajst-2538	165	7	a.	a.	PROPN
ajst-2538	165	8	(	(	PUNCT
ajst-2538	165	9	1980	1980	NUM
ajst-2538	165	10	)	)	PUNCT
ajst-2538	165	11	.	.	PUNCT
ajst-2538	166	1	financial	financial	ADJ
ajst-2538	166	2	ratios	ratio	NOUN
ajst-2538	166	3	and	and	CCONJ
ajst-2538	166	4	the	the	DET
ajst-2538	166	5	probabilistic	probabilistic	ADJ
ajst-2538	166	6	prediction	prediction	NOUN
ajst-2538	166	7	of	of	ADP
ajst-2538	166	8	bankruptcy	bankruptcy	NOUN
ajst-2538	166	9	.	.	PUNCT
ajst-2538	167	1	journal	journal	PROPN
ajst-2538	167	2	of	of	ADP
ajst-2538	167	3	accounting	accounting	NOUN
ajst-2538	167	4	research	research	NOUN
ajst-2538	167	5	,	,	PUNCT
ajst-2538	167	6	18(1	18(1	NUM
ajst-2538	167	7	)	)	PUNCT
ajst-2538	167	8	,	,	PUNCT
ajst-2538	167	9	109–131	109–131	NUM
ajst-2538	167	10	.	.	PUNCT
ajst-2538	167	11	https://doi.org/10.2307/2490395	https://doi.org/10.2307/2490395	NUM