id	sid	tid	token	lemma	pos
fcis-30619	1	1	frontiers	frontier	NOUN
fcis-30619	1	2	in	in	ADP
fcis-30619	1	3	computing	computing	NOUN
fcis-30619	1	4	and	and	CCONJ
fcis-30619	1	5	intelligent	intelligent	ADJ
fcis-30619	1	6	systems	system	NOUN
fcis-30619	1	7	issn	issn	VERB
fcis-30619	1	8	:	:	PUNCT
fcis-30619	1	9	2832	2832	NUM
fcis-30619	1	10	-	-	SYM
fcis-30619	1	11	6024	6024	NUM
fcis-30619	1	12	|	|	NOUN
fcis-30619	1	13	vol	vol	NOUN
fcis-30619	1	14	.	.	PROPN
fcis-30619	2	1	12	12	NUM
fcis-30619	2	2	,	,	PUNCT
fcis-30619	2	3	no	no	INTJ
fcis-30619	2	4	.	.	NOUN
fcis-30619	2	5	1	1	NUM
fcis-30619	2	6	,	,	PUNCT
fcis-30619	2	7	2025	2025	NUM
fcis-30619	2	8	125	125	NUM
fcis-30619	2	9	application	application	NOUN
fcis-30619	2	10	of	of	ADP
fcis-30619	2	11	composite	composite	ADJ
fcis-30619	2	12	kernel	kernel	NOUN
fcis-30619	2	13	function	function	NOUN
fcis-30619	2	14	in	in	ADP
fcis-30619	2	15	gaussian	gaussian	ADJ
fcis-30619	2	16	process	process	NOUN
fcis-30619	2	17	prediction	prediction	NOUN
fcis-30619	2	18	yulin	yulin	PROPN
fcis-30619	2	19	zhang	zhang	PROPN
fcis-30619	2	20	*	*	PUNCT
fcis-30619	2	21	school	school	NOUN
fcis-30619	2	22	of	of	ADP
fcis-30619	2	23	science	science	NOUN
fcis-30619	2	24	,	,	PUNCT
fcis-30619	2	25	tianjin	tianjin	PROPN
fcis-30619	2	26	university	university	PROPN
fcis-30619	2	27	of	of	ADP
fcis-30619	2	28	commerce	commerce	PROPN
fcis-30619	2	29	,	,	PUNCT
fcis-30619	2	30	tianjin	tianjin	PROPN
fcis-30619	2	31	,	,	PUNCT
fcis-30619	2	32	china	china	PROPN
fcis-30619	2	33	*	*	PUNCT
fcis-30619	2	34	corresponding	correspond	VERB
fcis-30619	2	35	author	author	NOUN
fcis-30619	2	36	email	email	NOUN
fcis-30619	2	37	:	:	PUNCT
fcis-30619	3	1	cherry888yu@163.com	cherry888yu@163.com	X
fcis-30619	3	2	abstract	abstract	NOUN
fcis-30619	3	3	:	:	PUNCT
fcis-30619	3	4	gaussian	gaussian	ADJ
fcis-30619	3	5	process	process	NOUN
fcis-30619	3	6	is	be	AUX
fcis-30619	3	7	a	a	DET
fcis-30619	3	8	non	non	ADJ
fcis-30619	3	9	-	-	ADJ
fcis-30619	3	10	parametric	parametric	ADJ
fcis-30619	3	11	bayesian	bayesian	NOUN
fcis-30619	3	12	method	method	NOUN
fcis-30619	3	13	based	base	VERB
fcis-30619	3	14	on	on	ADP
fcis-30619	3	15	kernel	kernel	PROPN
fcis-30619	3	16	functions	function	NOUN
fcis-30619	3	17	,	,	PUNCT
fcis-30619	3	18	widely	widely	ADV
fcis-30619	3	19	used	use	VERB
fcis-30619	3	20	in	in	ADP
fcis-30619	3	21	regression	regression	NOUN
fcis-30619	3	22	tasks	task	NOUN
fcis-30619	3	23	and	and	CCONJ
fcis-30619	3	24	bayesian	bayesian	NOUN
fcis-30619	3	25	optimization	optimization	NOUN
fcis-30619	3	26	.	.	PUNCT
fcis-30619	4	1	kernel	kernel	PROPN
fcis-30619	4	2	functions	function	NOUN
fcis-30619	4	3	play	play	VERB
fcis-30619	4	4	a	a	DET
fcis-30619	4	5	crucial	crucial	ADJ
fcis-30619	4	6	role	role	NOUN
fcis-30619	4	7	in	in	ADP
fcis-30619	4	8	gaussian	gaussian	ADJ
fcis-30619	4	9	processes	process	NOUN
fcis-30619	4	10	as	as	SCONJ
fcis-30619	4	11	they	they	PRON
fcis-30619	4	12	directly	directly	ADV
fcis-30619	4	13	impact	impact	VERB
fcis-30619	4	14	the	the	DET
fcis-30619	4	15	model	model	NOUN
fcis-30619	4	16	's	's	PART
fcis-30619	4	17	ability	ability	NOUN
fcis-30619	4	18	to	to	PART
fcis-30619	4	19	fit	fit	VERB
fcis-30619	4	20	the	the	DET
fcis-30619	4	21	data	datum	NOUN
fcis-30619	4	22	distribution	distribution	NOUN
fcis-30619	4	23	.	.	PUNCT
fcis-30619	5	1	different	different	ADJ
fcis-30619	5	2	kernel	kernel	NOUN
fcis-30619	5	3	functions	function	NOUN
fcis-30619	5	4	can	can	AUX
fcis-30619	5	5	be	be	AUX
fcis-30619	5	6	selected	select	VERB
fcis-30619	5	7	based	base	VERB
fcis-30619	5	8	on	on	ADP
fcis-30619	5	9	the	the	DET
fcis-30619	5	10	characteristics	characteristic	NOUN
fcis-30619	5	11	of	of	ADP
fcis-30619	5	12	the	the	DET
fcis-30619	5	13	data	datum	NOUN
fcis-30619	5	14	to	to	PART
fcis-30619	5	15	improve	improve	VERB
fcis-30619	5	16	model	model	NOUN
fcis-30619	5	17	performance	performance	NOUN
fcis-30619	5	18	.	.	PUNCT
fcis-30619	6	1	in	in	ADP
fcis-30619	6	2	practical	practical	ADJ
fcis-30619	6	3	applications	application	NOUN
fcis-30619	6	4	,	,	PUNCT
fcis-30619	6	5	combining	combine	VERB
fcis-30619	6	6	multiple	multiple	ADJ
fcis-30619	6	7	basic	basic	ADJ
fcis-30619	6	8	kernel	kernel	NOUN
fcis-30619	6	9	functions	function	NOUN
fcis-30619	6	10	can	can	AUX
fcis-30619	6	11	construct	construct	VERB
fcis-30619	6	12	more	more	ADJ
fcis-30619	6	13	complex	complex	ADJ
fcis-30619	6	14	kernel	kernel	NOUN
fcis-30619	6	15	functions	function	NOUN
fcis-30619	6	16	,	,	PUNCT
fcis-30619	6	17	enhancing	enhance	VERB
fcis-30619	6	18	the	the	DET
fcis-30619	6	19	flexibility	flexibility	NOUN
fcis-30619	6	20	and	and	CCONJ
fcis-30619	6	21	adaptability	adaptability	NOUN
fcis-30619	6	22	of	of	ADP
fcis-30619	6	23	gaussian	gaussian	ADJ
fcis-30619	6	24	processes	process	NOUN
fcis-30619	6	25	,	,	PUNCT
fcis-30619	6	26	making	make	VERB
fcis-30619	6	27	them	they	PRON
fcis-30619	6	28	better	well	ADV
fcis-30619	6	29	suited	suit	VERB
fcis-30619	6	30	to	to	ADP
fcis-30619	6	31	complex	complex	ADJ
fcis-30619	6	32	data	datum	NOUN
fcis-30619	6	33	modeling	modeling	NOUN
fcis-30619	6	34	challenges	challenge	NOUN
fcis-30619	6	35	.	.	PUNCT
fcis-30619	7	1	this	this	DET
fcis-30619	7	2	paper	paper	NOUN
fcis-30619	7	3	uses	use	VERB
fcis-30619	7	4	california	california	PROPN
fcis-30619	7	5	housing	housing	NOUN
fcis-30619	7	6	price	price	NOUN
fcis-30619	7	7	data	datum	NOUN
fcis-30619	7	8	as	as	ADP
fcis-30619	7	9	an	an	DET
fcis-30619	7	10	example	example	NOUN
fcis-30619	7	11	to	to	PART
fcis-30619	7	12	analyze	analyze	VERB
fcis-30619	7	13	the	the	DET
fcis-30619	7	14	impact	impact	NOUN
fcis-30619	7	15	of	of	ADP
fcis-30619	7	16	different	different	ADJ
fcis-30619	7	17	kernel	kernel	NOUN
fcis-30619	7	18	function	function	NOUN
fcis-30619	7	19	combinations	combination	NOUN
fcis-30619	7	20	on	on	ADP
fcis-30619	7	21	model	model	NOUN
fcis-30619	7	22	prediction	prediction	NOUN
fcis-30619	7	23	performance	performance	NOUN
fcis-30619	7	24	.	.	PUNCT
fcis-30619	8	1	the	the	DET
fcis-30619	8	2	experimental	experimental	ADJ
fcis-30619	8	3	results	result	NOUN
fcis-30619	8	4	validate	validate	VERB
fcis-30619	8	5	the	the	DET
fcis-30619	8	6	importance	importance	NOUN
fcis-30619	8	7	of	of	ADP
fcis-30619	8	8	kernel	kernel	PROPN
fcis-30619	8	9	selection	selection	NOUN
fcis-30619	8	10	in	in	ADP
fcis-30619	8	11	gaussian	gaussian	ADJ
fcis-30619	8	12	process	process	NOUN
fcis-30619	8	13	models	model	NOUN
fcis-30619	8	14	and	and	CCONJ
fcis-30619	8	15	demonstrate	demonstrate	VERB
fcis-30619	8	16	the	the	DET
fcis-30619	8	17	effectiveness	effectiveness	NOUN
fcis-30619	8	18	of	of	ADP
fcis-30619	8	19	composite	composite	ADJ
fcis-30619	8	20	kernels	kernel	NOUN
fcis-30619	8	21	in	in	ADP
fcis-30619	8	22	handling	handle	VERB
fcis-30619	8	23	complex	complex	ADJ
fcis-30619	8	24	data	datum	NOUN
fcis-30619	8	25	distributions	distribution	NOUN
fcis-30619	8	26	.	.	PUNCT
fcis-30619	9	1	keywords	keyword	NOUN
fcis-30619	9	2	:	:	PUNCT
fcis-30619	9	3	gaussian	gaussian	ADJ
fcis-30619	9	4	process	process	NOUN
fcis-30619	9	5	;	;	PUNCT
fcis-30619	9	6	composite	composite	ADJ
fcis-30619	9	7	;	;	PUNCT
fcis-30619	9	8	kernel	kernel	PROPN
fcis-30619	9	9	function	function	NOUN
fcis-30619	9	10	.	.	PUNCT
fcis-30619	10	1	1	1	X
fcis-30619	10	2	.	.	X
fcis-30619	10	3	introduction	introduction	NOUN
fcis-30619	10	4	gaussian	gaussian	ADJ
fcis-30619	10	5	process	process	NOUN
fcis-30619	10	6	[	[	X
fcis-30619	10	7	1	1	X
fcis-30619	10	8	]	]	PUNCT
fcis-30619	10	9	is	be	AUX
fcis-30619	10	10	a	a	DET
fcis-30619	10	11	non	non	ADJ
fcis-30619	10	12	-	-	ADJ
fcis-30619	10	13	parametric	parametric	ADJ
fcis-30619	10	14	bayesian	bayesian	NOUN
fcis-30619	10	15	method	method	NOUN
fcis-30619	10	16	widely	widely	ADV
fcis-30619	10	17	used	use	VERB
fcis-30619	10	18	in	in	ADP
fcis-30619	10	19	regression	regression	NOUN
fcis-30619	10	20	tasks	task	NOUN
fcis-30619	10	21	and	and	CCONJ
fcis-30619	10	22	bayesian	bayesian	NOUN
fcis-30619	10	23	optimization	optimization	NOUN
fcis-30619	10	24	[	[	X
fcis-30619	10	25	2,3	2,3	NUM
fcis-30619	10	26	]	]	PUNCT
fcis-30619	10	27	.	.	PUNCT
fcis-30619	11	1	the	the	DET
fcis-30619	11	2	kernel	kernel	PROPN
fcis-30619	11	3	function	function	NOUN
fcis-30619	11	4	(	(	PUNCT
fcis-30619	11	5	or	or	CCONJ
fcis-30619	11	6	covariance	covariance	NOUN
fcis-30619	11	7	function	function	NOUN
fcis-30619	11	8	)	)	PUNCT
fcis-30619	11	9	in	in	ADP
fcis-30619	11	10	a	a	DET
fcis-30619	11	11	gaussian	gaussian	ADJ
fcis-30619	11	12	process	process	NOUN
fcis-30619	11	13	is	be	AUX
fcis-30619	11	14	one	one	NUM
fcis-30619	11	15	of	of	ADP
fcis-30619	11	16	its	its	PRON
fcis-30619	11	17	core	core	NOUN
fcis-30619	11	18	components	component	NOUN
fcis-30619	11	19	,	,	PUNCT
fcis-30619	11	20	defining	define	VERB
fcis-30619	11	21	the	the	DET
fcis-30619	11	22	similarity	similarity	NOUN
fcis-30619	11	23	between	between	ADP
fcis-30619	11	24	two	two	NUM
fcis-30619	11	25	input	input	NOUN
fcis-30619	11	26	data	datum	NOUN
fcis-30619	11	27	points	point	NOUN
fcis-30619	11	28	and	and	CCONJ
fcis-30619	11	29	determining	determine	VERB
fcis-30619	11	30	the	the	DET
fcis-30619	11	31	covariance	covariance	NOUN
fcis-30619	11	32	structure	structure	NOUN
fcis-30619	11	33	of	of	ADP
fcis-30619	11	34	the	the	DET
fcis-30619	11	35	gaussian	gaussian	ADJ
fcis-30619	11	36	process	process	NOUN
fcis-30619	11	37	,	,	PUNCT
fcis-30619	11	38	thereby	thereby	ADV
fcis-30619	11	39	influencing	influence	VERB
fcis-30619	11	40	the	the	DET
fcis-30619	11	41	predicted	predict	VERB
fcis-30619	11	42	mean	mean	NOUN
fcis-30619	11	43	and	and	CCONJ
fcis-30619	11	44	variance	variance	NOUN
fcis-30619	11	45	[	[	X
fcis-30619	11	46	4	4	NUM
fcis-30619	11	47	]	]	PUNCT
fcis-30619	11	48	.	.	PUNCT
fcis-30619	12	1	different	different	ADJ
fcis-30619	12	2	kernel	kernel	PROPN
fcis-30619	12	3	functions	function	NOUN
fcis-30619	12	4	have	have	VERB
fcis-30619	12	5	different	different	ADJ
fcis-30619	12	6	smoothness	smoothness	NOUN
fcis-30619	12	7	and	and	CCONJ
fcis-30619	12	8	periodicity	periodicity	NOUN
fcis-30619	12	9	properties	property	NOUN
fcis-30619	12	10	,	,	PUNCT
fcis-30619	12	11	affecting	affect	VERB
fcis-30619	12	12	the	the	DET
fcis-30619	12	13	gaussian	gaussian	ADJ
fcis-30619	12	14	process	process	NOUN
fcis-30619	12	15	’s	’s	PART
fcis-30619	12	16	ability	ability	NOUN
fcis-30619	12	17	to	to	PART
fcis-30619	12	18	fit	fit	VERB
fcis-30619	12	19	data	datum	NOUN
fcis-30619	12	20	.	.	PUNCT
fcis-30619	13	1	thus	thus	ADV
fcis-30619	13	2	,	,	PUNCT
fcis-30619	13	3	the	the	DET
fcis-30619	13	4	choice	choice	NOUN
fcis-30619	13	5	of	of	ADP
fcis-30619	13	6	kernel	kernel	PROPN
fcis-30619	13	7	function	function	PROPN
fcis-30619	13	8	impacts	impact	VERB
fcis-30619	13	9	the	the	DET
fcis-30619	13	10	model	model	NOUN
fcis-30619	13	11	's	's	PART
fcis-30619	13	12	generalization	generalization	NOUN
fcis-30619	13	13	ability	ability	NOUN
fcis-30619	13	14	—	—	PUNCT
fcis-30619	13	15	incorrect	incorrect	ADJ
fcis-30619	13	16	kernels	kernel	NOUN
fcis-30619	13	17	may	may	AUX
fcis-30619	13	18	lead	lead	VERB
fcis-30619	13	19	to	to	ADP
fcis-30619	13	20	overfitting	overfitte	VERB
fcis-30619	13	21	or	or	CCONJ
fcis-30619	13	22	underfitting	underfitte	VERB
fcis-30619	13	23	[	[	X
fcis-30619	13	24	5	5	NUM
fcis-30619	13	25	]	]	PUNCT
fcis-30619	13	26	.	.	PUNCT
fcis-30619	14	1	kernel	kernel	PROPN
fcis-30619	14	2	functions	function	NOUN
fcis-30619	14	3	are	be	AUX
fcis-30619	14	4	interchangeable	interchangeable	ADJ
fcis-30619	14	5	,	,	PUNCT
fcis-30619	14	6	and	and	CCONJ
fcis-30619	14	7	appropriate	appropriate	ADJ
fcis-30619	14	8	kernel	kernel	NOUN
fcis-30619	14	9	functions	function	NOUN
fcis-30619	14	10	can	can	AUX
fcis-30619	14	11	be	be	AUX
fcis-30619	14	12	selected	select	VERB
fcis-30619	14	13	or	or	CCONJ
fcis-30619	14	14	designed	design	VERB
fcis-30619	14	15	based	base	VERB
fcis-30619	14	16	on	on	ADP
fcis-30619	14	17	data	datum	NOUN
fcis-30619	14	18	characteristics	characteristic	NOUN
fcis-30619	14	19	and	and	CCONJ
fcis-30619	14	20	task	task	NOUN
fcis-30619	14	21	requirements	requirement	NOUN
fcis-30619	14	22	.	.	PUNCT
fcis-30619	15	1	in	in	ADP
fcis-30619	15	2	many	many	ADJ
fcis-30619	15	3	cases	case	NOUN
fcis-30619	15	4	,	,	PUNCT
fcis-30619	15	5	composite	composite	ADJ
fcis-30619	15	6	kernel	kernel	NOUN
fcis-30619	15	7	functions	function	NOUN
fcis-30619	15	8	[	[	X
fcis-30619	15	9	6	6	NUM
fcis-30619	15	10	]	]	PUNCT
fcis-30619	15	11	are	be	AUX
fcis-30619	15	12	considered	consider	VERB
fcis-30619	15	13	.	.	PUNCT
fcis-30619	16	1	composite	composite	ADJ
fcis-30619	16	2	kernels	kernel	NOUN
fcis-30619	16	3	combine	combine	VERB
fcis-30619	16	4	multiple	multiple	ADJ
fcis-30619	16	5	base	base	NOUN
fcis-30619	16	6	kernels	kernel	NOUN
fcis-30619	16	7	to	to	PART
fcis-30619	16	8	create	create	VERB
fcis-30619	16	9	a	a	DET
fcis-30619	16	10	new	new	ADJ
fcis-30619	16	11	kernel	kernel	NOUN
fcis-30619	16	12	function	function	NOUN
fcis-30619	16	13	,	,	PUNCT
fcis-30619	16	14	enhancing	enhance	VERB
fcis-30619	16	15	the	the	DET
fcis-30619	16	16	performance	performance	NOUN
fcis-30619	16	17	of	of	ADP
fcis-30619	16	18	gaussian	gaussian	ADJ
fcis-30619	16	19	process	process	NOUN
fcis-30619	16	20	models	model	NOUN
fcis-30619	16	21	and	and	CCONJ
fcis-30619	16	22	enabling	enable	VERB
fcis-30619	16	23	them	they	PRON
fcis-30619	16	24	to	to	PART
fcis-30619	16	25	fit	fit	VERB
fcis-30619	16	26	more	more	ADV
fcis-30619	16	27	complex	complex	ADJ
fcis-30619	16	28	data	data	NOUN
fcis-30619	16	29	patterns	pattern	NOUN
fcis-30619	16	30	[	[	X
fcis-30619	16	31	7	7	NUM
fcis-30619	16	32	]	]	PUNCT
fcis-30619	16	33	.	.	PUNCT
fcis-30619	17	1	common	common	ADJ
fcis-30619	17	2	ways	way	NOUN
fcis-30619	17	3	to	to	PART
fcis-30619	17	4	construct	construct	VERB
fcis-30619	17	5	composite	composite	ADJ
fcis-30619	17	6	kernels	kernel	NOUN
fcis-30619	17	7	include	include	VERB
fcis-30619	17	8	additive	additive	NOUN
fcis-30619	17	9	and	and	CCONJ
fcis-30619	17	10	multiplicative	multiplicative	ADJ
fcis-30619	17	11	combinations	combination	NOUN
fcis-30619	17	12	.	.	PUNCT
fcis-30619	18	1	organization	organization	NOUN
fcis-30619	18	2	of	of	ADP
fcis-30619	18	3	the	the	DET
fcis-30619	18	4	text	text	NOUN
fcis-30619	18	5	2	2	NUM
fcis-30619	18	6	.	.	PUNCT
fcis-30619	18	7	gaussian	gaussian	ADJ
fcis-30619	18	8	process	process	NOUN
fcis-30619	18	9	regression	regression	VERB
fcis-30619	18	10	2.1	2.1	NUM
fcis-30619	18	11	.	.	PUNCT
fcis-30619	19	1	model	model	NOUN
fcis-30619	19	2	gaussian	gaussian	ADJ
fcis-30619	19	3	process	process	NOUN
fcis-30619	19	4	is	be	AUX
fcis-30619	19	5	a	a	DET
fcis-30619	19	6	non	non	ADJ
fcis-30619	19	7	-	-	ADJ
fcis-30619	19	8	parametric	parametric	ADJ
fcis-30619	19	9	bayesian	bayesian	NOUN
fcis-30619	19	10	method	method	NOUN
fcis-30619	19	11	used	use	VERB
fcis-30619	19	12	to	to	PART
fcis-30619	19	13	model	model	VERB
fcis-30619	19	14	stochastic	stochastic	ADJ
fcis-30619	19	15	processes	process	NOUN
fcis-30619	19	16	.	.	PUNCT
fcis-30619	20	1	essentially	essentially	ADV
fcis-30619	20	2	,	,	PUNCT
fcis-30619	20	3	it	it	PRON
fcis-30619	20	4	is	be	AUX
fcis-30619	20	5	an	an	DET
fcis-30619	20	6	infinite	infinite	ADJ
fcis-30619	20	7	-	-	PUNCT
fcis-30619	20	8	dimensional	dimensional	ADJ
fcis-30619	20	9	probability	probability	NOUN
fcis-30619	20	10	distribution	distribution	NOUN
fcis-30619	20	11	operating	operate	VERB
fcis-30619	20	12	in	in	ADP
fcis-30619	20	13	function	function	NOUN
fcis-30619	20	14	space	space	NOUN
fcis-30619	20	15	,	,	PUNCT
fcis-30619	20	16	where	where	SCONJ
fcis-30619	20	17	the	the	DET
fcis-30619	20	18	function	function	NOUN
fcis-30619	20	19	values	value	NOUN
fcis-30619	20	20	at	at	ADP
fcis-30619	20	21	any	any	DET
fcis-30619	20	22	set	set	NOUN
fcis-30619	20	23	of	of	ADP
fcis-30619	20	24	input	input	NOUN
fcis-30619	20	25	points	point	NOUN
fcis-30619	20	26	follow	follow	VERB
fcis-30619	20	27	a	a	DET
fcis-30619	20	28	joint	joint	ADJ
fcis-30619	20	29	gaussian	gaussian	ADJ
fcis-30619	20	30	distribution	distribution	NOUN
fcis-30619	20	31	.	.	PUNCT
fcis-30619	21	1	this	this	DET
fcis-30619	21	2	property	property	NOUN
fcis-30619	21	3	allows	allow	VERB
fcis-30619	21	4	gaussian	gaussian	NOUN
fcis-30619	21	5	processes	process	NOUN
fcis-30619	21	6	to	to	PART
fcis-30619	21	7	probabilistically	probabilistically	ADV
fcis-30619	21	8	describe	describe	VERB
fcis-30619	21	9	function	function	NOUN
fcis-30619	21	10	values	value	NOUN
fcis-30619	21	11	at	at	ADP
fcis-30619	21	12	different	different	ADJ
fcis-30619	21	13	points	point	NOUN
fcis-30619	21	14	for	for	ADP
fcis-30619	21	15	prediction	prediction	NOUN
fcis-30619	21	16	and	and	CCONJ
fcis-30619	21	17	analysis	analysis	NOUN
fcis-30619	21	18	.	.	PUNCT
fcis-30619	22	1	given	give	VERB
fcis-30619	22	2	an	an	DET
fcis-30619	22	3	input	input	NOUN
fcis-30619	22	4	space	space	NOUN
fcis-30619	22	5	,	,	PUNCT
fcis-30619	22	6	a	a	DET
fcis-30619	22	7	gaussian	gaussian	ADJ
fcis-30619	22	8	process	process	NOUN
fcis-30619	22	9	is	be	AUX
fcis-30619	22	10	defined	define	VERB
fcis-30619	22	11	as	as	ADP
fcis-30619	22	12	:	:	PUNCT
fcis-30619	22	13	∼	∼	NOUN
fcis-30619	22	14	,	,	PUNCT
fcis-30619	22	15	,	,	PUNCT
fcis-30619	22	16	(	(	PUNCT
fcis-30619	22	17	1	1	X
fcis-30619	22	18	)	)	PUNCT
fcis-30619	22	19	where	where	SCONJ
fcis-30619	22	20	is	be	AUX
fcis-30619	22	21	the	the	DET
fcis-30619	22	22	mean	mean	ADJ
fcis-30619	22	23	function	function	NOUN
fcis-30619	22	24	(	(	PUNCT
fcis-30619	22	25	typically	typically	ADV
fcis-30619	22	26	assumed	assume	VERB
fcis-30619	22	27	to	to	PART
fcis-30619	22	28	be	be	AUX
fcis-30619	22	29	zero	zero	NUM
fcis-30619	22	30	)	)	PUNCT
fcis-30619	22	31	,	,	PUNCT
fcis-30619	22	32	and	and	CCONJ
fcis-30619	22	33	,	,	PUNCT
fcis-30619	22	34	is	be	AUX
fcis-30619	22	35	the	the	DET
fcis-30619	22	36	kernel	kernel	PROPN
fcis-30619	22	37	function	function	NOUN
fcis-30619	22	38	(	(	PUNCT
fcis-30619	22	39	or	or	CCONJ
fcis-30619	22	40	covariance	covariance	NOUN
fcis-30619	22	41	function	function	NOUN
fcis-30619	22	42	)	)	PUNCT
fcis-30619	22	43	,	,	PUNCT
fcis-30619	22	44	which	which	PRON
fcis-30619	22	45	describes	describe	VERB
fcis-30619	22	46	the	the	DET
fcis-30619	22	47	similarity	similarity	NOUN
fcis-30619	22	48	between	between	ADP
fcis-30619	22	49	different	different	ADJ
fcis-30619	22	50	input	input	NOUN
fcis-30619	22	51	points	point	NOUN
fcis-30619	22	52	and	and	CCONJ
fcis-30619	22	53	.	.	PUNCT
fcis-30619	23	1	2.2	2.2	NUM
fcis-30619	23	2	.	.	PUNCT
fcis-30619	23	3	prediction	prediction	NOUN
fcis-30619	23	4	given	give	VERB
fcis-30619	23	5	a	a	DET
fcis-30619	23	6	set	set	NOUN
fcis-30619	23	7	of	of	ADP
fcis-30619	23	8	training	training	NOUN
fcis-30619	23	9	data	datum	NOUN
fcis-30619	23	10	,	,	PUNCT
fcis-30619	23	11	,	,	PUNCT
fcis-30619	23	12	,	,	PUNCT
fcis-30619	23	13	where	where	SCONJ
fcis-30619	23	14	∈	∈	PROPN
fcis-30619	23	15	is	be	AUX
fcis-30619	23	16	the	the	DET
fcis-30619	23	17	input	input	NOUN
fcis-30619	23	18	and	and	CCONJ
fcis-30619	23	19	the	the	DET
fcis-30619	23	20	corresponding	correspond	VERB
fcis-30619	23	21	target	target	NOUN
fcis-30619	23	22	value	value	NOUN
fcis-30619	23	23	∈	∈	NOUN
fcis-30619	23	24	consists	consist	VERB
fcis-30619	23	25	of	of	ADP
fcis-30619	23	26	the	the	DET
fcis-30619	23	27	true	true	ADJ
fcis-30619	23	28	function	function	NOUN
fcis-30619	23	29	value	value	NOUN
fcis-30619	23	30	generated	generate	VERB
fcis-30619	23	31	by	by	ADP
fcis-30619	23	32	the	the	DET
fcis-30619	23	33	gaussian	gaussian	ADJ
fcis-30619	23	34	process	process	NOUN
fcis-30619	23	35	and	and	CCONJ
fcis-30619	23	36	observation	observation	NOUN
fcis-30619	23	37	noise	noise	NOUN
fcis-30619	23	38	:	:	PUNCT
fcis-30619	23	39	~	~	PUNCT
fcis-30619	23	40	0	0	X
fcis-30619	23	41	,	,	PUNCT
fcis-30619	23	42	(	(	PUNCT
fcis-30619	23	43	2	2	X
fcis-30619	23	44	)	)	PUNCT
fcis-30619	23	45	for	for	ADP
fcis-30619	23	46	a	a	DET
fcis-30619	23	47	new	new	ADJ
fcis-30619	23	48	test	test	NOUN
fcis-30619	23	49	point	point	NOUN
fcis-30619	23	50	∗	∗	NOUN
fcis-30619	23	51	,	,	PUNCT
fcis-30619	23	52	in	in	ADP
fcis-30619	23	53	order	order	NOUN
fcis-30619	23	54	to	to	PART
fcis-30619	23	55	predict	predict	VERB
fcis-30619	23	56	∗	∗	NOUN
fcis-30619	23	57	∗	∗	NOUN
fcis-30619	23	58	∗	∗	NOUN
fcis-30619	23	59	,	,	PUNCT
fcis-30619	23	60	we	we	PRON
fcis-30619	23	61	can	can	AUX
fcis-30619	23	62	calculate	calculate	VERB
fcis-30619	23	63	the	the	DET
fcis-30619	23	64	conditional	conditional	ADJ
fcis-30619	23	65	probability	probability	NOUN
fcis-30619	23	66	distribution	distribution	NOUN
fcis-30619	23	67	of	of	ADP
fcis-30619	23	68	∗	∗	NOUN
fcis-30619	23	69	based	base	VERB
fcis-30619	23	70	on	on	ADP
fcis-30619	23	71	the	the	DET
fcis-30619	23	72	training	training	NOUN
fcis-30619	23	73	data	datum	NOUN
fcis-30619	23	74	d.	d.	PROPN
fcis-30619	23	75	among	among	ADP
fcis-30619	23	76	them	they	PRON
fcis-30619	23	77	,	,	PUNCT
fcis-30619	23	78	the	the	DET
fcis-30619	23	79	joint	joint	ADJ
fcis-30619	23	80	distribution	distribution	NOUN
fcis-30619	23	81	of	of	ADP
fcis-30619	23	82	training	training	NOUN
fcis-30619	23	83	data	datum	NOUN
fcis-30619	23	84	and	and	CCONJ
fcis-30619	23	85	the	the	DET
fcis-30619	23	86	test	test	NOUN
fcis-30619	23	87	point	point	NOUN
fcis-30619	23	88	is	be	AUX
fcis-30619	23	89	given	give	VERB
fcis-30619	23	90	by	by	ADP
fcis-30619	23	91	:	:	PUNCT
fcis-30619	23	92	∗	∗	NOUN
fcis-30619	23	93	∼	∼	NOUN
fcis-30619	23	94	0	0	NUM
fcis-30619	23	95	,	,	PUNCT
fcis-30619	23	96	,	,	PUNCT
fcis-30619	23	97	,	,	PUNCT
fcis-30619	23	98	∗	∗	NOUN
fcis-30619	23	99	∗	∗	NOUN
fcis-30619	23	100	,	,	PUNCT
fcis-30619	23	101	∗	∗	NOUN
fcis-30619	23	102	,	,	PUNCT
fcis-30619	23	103	∗	∗	NOUN
fcis-30619	23	104	3	3	NUM
fcis-30619	23	105	by	by	ADP
fcis-30619	23	106	applying	apply	VERB
fcis-30619	23	107	the	the	DET
fcis-30619	23	108	conditional	conditional	ADJ
fcis-30619	23	109	distribution	distribution	NOUN
fcis-30619	23	110	property	property	NOUN
fcis-30619	23	111	of	of	ADP
fcis-30619	23	112	gaussian	gaussian	ADJ
fcis-30619	23	113	processes	process	NOUN
fcis-30619	23	114	,	,	PUNCT
fcis-30619	23	115	we	we	PRON
fcis-30619	23	116	obtain	obtain	VERB
fcis-30619	23	117	the	the	DET
fcis-30619	23	118	predicted	predict	VERB
fcis-30619	23	119	mean	mean	NOUN
fcis-30619	23	120	and	and	CCONJ
fcis-30619	23	121	covariance	covariance	NOUN
fcis-30619	23	122	matrix	matrix	NOUN
fcis-30619	23	123	:	:	PUNCT
fcis-30619	23	124	∗	∗	NOUN
fcis-30619	23	125	∗	∗	NOUN
fcis-30619	23	126	,	,	PUNCT
fcis-30619	23	127	,	,	PUNCT
fcis-30619	23	128	σ∗	σ∗	ADJ
fcis-30619	23	129	∗	∗	NOUN
fcis-30619	23	130	,	,	PUNCT
fcis-30619	23	131	∗	∗	NOUN
fcis-30619	23	132	∗	∗	NOUN
fcis-30619	23	133	,	,	PUNCT
fcis-30619	23	134	,	,	PUNCT
fcis-30619	23	135	,	,	PUNCT
fcis-30619	23	136	∗	∗	NOUN
fcis-30619	23	137	(	(	PUNCT
fcis-30619	23	138	4	4	NUM
fcis-30619	23	139	)	)	PUNCT
fcis-30619	23	140	2.3	2.3	NUM
fcis-30619	23	141	.	.	PUNCT
fcis-30619	24	1	kernel	kernel	PROPN
fcis-30619	24	2	functions	functions	PROPN
fcis-30619	24	3	kernel	kernel	PROPN
fcis-30619	24	4	functions	function	NOUN
fcis-30619	24	5	define	define	VERB
fcis-30619	24	6	the	the	DET
fcis-30619	24	7	similarity	similarity	NOUN
fcis-30619	24	8	between	between	ADP
fcis-30619	24	9	input	input	NOUN
fcis-30619	24	10	data	datum	NOUN
fcis-30619	24	11	points	point	NOUN
fcis-30619	24	12	and	and	CCONJ
fcis-30619	24	13	determine	determine	VERB
fcis-30619	24	14	the	the	DET
fcis-30619	24	15	covariance	covariance	NOUN
fcis-30619	24	16	structure	structure	NOUN
fcis-30619	24	17	of	of	ADP
fcis-30619	24	18	gaussian	gaussian	ADJ
fcis-30619	24	19	processes	process	NOUN
fcis-30619	24	20	,	,	PUNCT
fcis-30619	24	21	directly	directly	ADV
fcis-30619	24	22	affecting	affect	VERB
fcis-30619	24	23	model	model	NOUN
fcis-30619	24	24	generalization	generalization	NOUN
fcis-30619	24	25	.	.	PUNCT
fcis-30619	25	1	incorrect	incorrect	ADJ
fcis-30619	25	2	kernels	kernel	NOUN
fcis-30619	25	3	can	can	AUX
fcis-30619	25	4	lead	lead	VERB
fcis-30619	25	5	to	to	ADP
fcis-30619	25	6	overfitting	overfitte	VERB
fcis-30619	25	7	or	or	CCONJ
fcis-30619	25	8	underfitting	underfitting	NOUN
fcis-30619	25	9	.	.	PUNCT
fcis-30619	26	1	common	common	ADJ
fcis-30619	26	2	kernel	kernel	NOUN
fcis-30619	26	3	functions	function	NOUN
fcis-30619	26	4	include	include	VERB
fcis-30619	26	5	:	:	PUNCT
fcis-30619	26	6	radial	radial	ADJ
fcis-30619	26	7	basis	basis	NOUN
fcis-30619	26	8	function	function	NOUN
fcis-30619	26	9	,	,	PUNCT
fcis-30619	26	10	matern	matern	PROPN
fcis-30619	26	11	kernel	kernel	PROPN
fcis-30619	26	12	.	.	PUNCT
fcis-30619	27	1	(	(	PUNCT
fcis-30619	27	2	1	1	X
fcis-30619	27	3	)	)	PUNCT
fcis-30619	27	4	radial	radial	ADJ
fcis-30619	27	5	basis	basis	NOUN
fcis-30619	27	6	function	function	NOUN
fcis-30619	27	7	(	(	PUNCT
fcis-30619	27	8	rbf	rbf	PROPN
fcis-30619	27	9	):	):	PUNCT
fcis-30619	27	10	,	,	PUNCT
fcis-30619	27	11	exp	exp	NOUN
fcis-30619	27	12	∣∣	∣∣	NUM
fcis-30619	27	13	∣∣	∣∣	NUM
fcis-30619	27	14	ℓ	ℓ	PROPN
fcis-30619	27	15	126	126	NUM
fcis-30619	27	16	(	(	PUNCT
fcis-30619	27	17	2	2	NUM
fcis-30619	27	18	)	)	PUNCT
fcis-30619	27	19	matern	matern	ADJ
fcis-30619	27	20	kernel	kernel	NOUN
fcis-30619	27	21	:	:	PUNCT
fcis-30619	27	22	,	,	PUNCT
fcis-30619	27	23	√	√	NUM
fcis-30619	27	24	∣∣	∣∣	NUM
fcis-30619	27	25	∣∣	∣∣	NUM
fcis-30619	27	26	ℓ	ℓ	NOUN
fcis-30619	27	27	√	√	NUM
fcis-30619	27	28	∣∣	∣∣	NUM
fcis-30619	27	29	∣∣	∣∣	NUM
fcis-30619	27	30	ℓ	ℓ	PROPN
fcis-30619	27	31	1	1	NUM
fcis-30619	27	32	∣∣	∣∣	NUM
fcis-30619	27	33	∣∣	∣∣	NUM
fcis-30619	27	34	ℓ	ℓ	NOUN
fcis-30619	27	35	selecting	selecting	NOUN
fcis-30619	27	36	and	and	CCONJ
fcis-30619	27	37	optimizing	optimize	VERB
fcis-30619	27	38	kernel	kernel	NOUN
fcis-30619	27	39	functions	function	NOUN
fcis-30619	27	40	is	be	AUX
fcis-30619	27	41	one	one	NUM
fcis-30619	27	42	of	of	ADP
fcis-30619	27	43	the	the	DET
fcis-30619	27	44	most	most	ADV
fcis-30619	27	45	critical	critical	ADJ
fcis-30619	27	46	steps	step	NOUN
fcis-30619	27	47	in	in	ADP
fcis-30619	27	48	gaussian	gaussian	ADJ
fcis-30619	27	49	process	process	NOUN
fcis-30619	27	50	regression	regression	NOUN
fcis-30619	27	51	as	as	SCONJ
fcis-30619	27	52	it	it	PRON
fcis-30619	27	53	directly	directly	ADV
fcis-30619	27	54	impacts	impact	VERB
fcis-30619	27	55	prediction	prediction	NOUN
fcis-30619	27	56	performance	performance	NOUN
fcis-30619	27	57	and	and	CCONJ
fcis-30619	27	58	generalization	generalization	NOUN
fcis-30619	27	59	ability	ability	NOUN
fcis-30619	27	60	.	.	PUNCT
fcis-30619	28	1	3	3	X
fcis-30619	28	2	.	.	X
fcis-30619	28	3	empirical	empirical	ADJ
fcis-30619	28	4	study	study	NOUN
fcis-30619	28	5	3.1	3.1	NUM
fcis-30619	28	6	.	.	PUNCT
fcis-30619	28	7	kernel	kernel	PROPN
fcis-30619	28	8	selection	selection	NOUN
fcis-30619	28	9	in	in	ADP
fcis-30619	28	10	this	this	DET
fcis-30619	28	11	article	article	NOUN
fcis-30619	29	1	,	,	PUNCT
fcis-30619	29	2	we	we	PRON
fcis-30619	29	3	used	use	VERB
fcis-30619	29	4	three	three	NUM
fcis-30619	29	5	different	different	ADJ
fcis-30619	29	6	combination	combination	NOUN
fcis-30619	29	7	kernel	kernel	NOUN
fcis-30619	29	8	functions	function	NOUN
fcis-30619	29	9	for	for	ADP
fcis-30619	29	10	prediction	prediction	NOUN
fcis-30619	29	11	in	in	ADP
fcis-30619	29	12	order	order	NOUN
fcis-30619	29	13	to	to	PART
fcis-30619	29	14	compare	compare	VERB
fcis-30619	29	15	and	and	CCONJ
fcis-30619	29	16	evaluate	evaluate	VERB
fcis-30619	29	17	their	their	PRON
fcis-30619	29	18	differences	difference	NOUN
fcis-30619	29	19	in	in	ADP
fcis-30619	29	20	model	model	NOUN
fcis-30619	29	21	performance	performance	NOUN
fcis-30619	29	22	.	.	PUNCT
fcis-30619	30	1	through	through	ADP
fcis-30619	30	2	this	this	DET
fcis-30619	30	3	approach	approach	NOUN
fcis-30619	30	4	,	,	PUNCT
fcis-30619	30	5	we	we	PRON
fcis-30619	30	6	can	can	AUX
fcis-30619	30	7	observe	observe	VERB
fcis-30619	30	8	the	the	DET
fcis-30619	30	9	impact	impact	NOUN
fcis-30619	30	10	of	of	ADP
fcis-30619	30	11	different	different	ADJ
fcis-30619	30	12	combinations	combination	NOUN
fcis-30619	30	13	of	of	ADP
fcis-30619	30	14	kernel	kernel	NOUN
fcis-30619	30	15	functions	function	NOUN
fcis-30619	30	16	on	on	ADP
fcis-30619	30	17	the	the	DET
fcis-30619	30	18	prediction	prediction	NOUN
fcis-30619	30	19	results	result	NOUN
fcis-30619	30	20	.	.	PUNCT
fcis-30619	31	1	(	(	PUNCT
fcis-30619	31	2	1	1	X
fcis-30619	31	3	)	)	PUNCT
fcis-30619	31	4	constantkernel	constantkernel	NOUN
fcis-30619	31	5	*	*	PUNCT
fcis-30619	31	6	rbf	rbf	PROPN
fcis-30619	31	7	constantkernel	constantkernel	PROPN
fcis-30619	31	8	defines	define	VERB
fcis-30619	31	9	a	a	DET
fcis-30619	31	10	constant	constant	ADJ
fcis-30619	31	11	kernel	kernel	NOUN
fcis-30619	31	12	that	that	PRON
fcis-30619	31	13	determines	determine	VERB
fcis-30619	31	14	the	the	DET
fcis-30619	31	15	overall	overall	ADJ
fcis-30619	31	16	scaling	scaling	NOUN
fcis-30619	31	17	between	between	ADP
fcis-30619	31	18	data	datum	NOUN
fcis-30619	31	19	.	.	PUNCT
fcis-30619	32	1	radial	radial	ADJ
fcis-30619	32	2	basis	basis	NOUN
fcis-30619	32	3	functio	functio	NOUN
fcis-30619	32	4	defines	define	VERB
fcis-30619	32	5	the	the	DET
fcis-30619	32	6	rbf	rbf	PROPN
fcis-30619	32	7	kernel	kernel	PROPN
fcis-30619	32	8	,	,	PUNCT
fcis-30619	32	9	which	which	PRON
fcis-30619	32	10	represents	represent	VERB
fcis-30619	32	11	how	how	SCONJ
fcis-30619	32	12	the	the	DET
fcis-30619	32	13	similarity	similarity	NOUN
fcis-30619	32	14	between	between	ADP
fcis-30619	32	15	data	datum	NOUN
fcis-30619	32	16	points	point	NOUN
fcis-30619	32	17	varies	vary	VERB
fcis-30619	32	18	with	with	ADP
fcis-30619	32	19	distance	distance	NOUN
fcis-30619	32	20	.	.	PUNCT
fcis-30619	33	1	the	the	DET
fcis-30619	33	2	product	product	NOUN
fcis-30619	33	3	of	of	ADP
fcis-30619	33	4	these	these	DET
fcis-30619	33	5	two	two	NUM
fcis-30619	33	6	kernels	kernel	NOUN
fcis-30619	33	7	represents	represent	VERB
fcis-30619	33	8	the	the	DET
fcis-30619	33	9	similarity	similarity	NOUN
fcis-30619	33	10	between	between	ADP
fcis-30619	33	11	data	datum	NOUN
fcis-30619	33	12	points	point	NOUN
fcis-30619	33	13	,	,	PUNCT
fcis-30619	33	14	taking	take	VERB
fcis-30619	33	15	into	into	ADP
fcis-30619	33	16	account	account	NOUN
fcis-30619	33	17	both	both	CCONJ
fcis-30619	33	18	the	the	DET
fcis-30619	33	19	constant	constant	ADJ
fcis-30619	33	20	scaling	scale	VERB
fcis-30619	33	21	factor	factor	NOUN
fcis-30619	33	22	and	and	CCONJ
fcis-30619	33	23	the	the	DET
fcis-30619	33	24	variation	variation	NOUN
fcis-30619	33	25	of	of	ADP
fcis-30619	33	26	similarity	similarity	NOUN
fcis-30619	33	27	in	in	ADP
fcis-30619	33	28	the	the	DET
fcis-30619	33	29	input	input	NOUN
fcis-30619	33	30	space	space	NOUN
fcis-30619	33	31	with	with	ADP
fcis-30619	33	32	distance	distance	NOUN
fcis-30619	33	33	.	.	PUNCT
fcis-30619	34	1	(	(	PUNCT
fcis-30619	34	2	2	2	X
fcis-30619	34	3	)	)	PUNCT
fcis-30619	34	4	matern	matern	NOUN
fcis-30619	34	5	+	+	CCONJ
fcis-30619	34	6	whitekernel	whitekernel	NOUN
fcis-30619	34	7	:	:	PUNCT
fcis-30619	34	8	the	the	DET
fcis-30619	34	9	matern	matern	PROPN
fcis-30619	34	10	kernel	kernel	PROPN
fcis-30619	34	11	can	can	AUX
fcis-30619	34	12	control	control	VERB
fcis-30619	34	13	the	the	DET
fcis-30619	34	14	smoothness	smoothness	NOUN
fcis-30619	34	15	of	of	ADP
fcis-30619	34	16	the	the	DET
fcis-30619	34	17	function	function	NOUN
fcis-30619	34	18	.	.	PUNCT
fcis-30619	35	1	whitekernel	whitekernel	PROPN
fcis-30619	35	2	defines	define	VERB
fcis-30619	35	3	the	the	DET
fcis-30619	35	4	white	white	PROPN
fcis-30619	35	5	noise	noise	PROPN
fcis-30619	35	6	kernel	kernel	PROPN
fcis-30619	35	7	and	and	CCONJ
fcis-30619	35	8	simulates	simulate	VERB
fcis-30619	35	9	the	the	DET
fcis-30619	35	10	noise	noise	NOUN
fcis-30619	35	11	in	in	ADP
fcis-30619	35	12	observed	observed	ADJ
fcis-30619	35	13	data	datum	NOUN
fcis-30619	35	14	.	.	PUNCT
fcis-30619	36	1	the	the	DET
fcis-30619	36	2	addition	addition	NOUN
fcis-30619	36	3	of	of	ADP
fcis-30619	36	4	these	these	DET
fcis-30619	36	5	two	two	NUM
fcis-30619	36	6	kernels	kernel	NOUN
fcis-30619	36	7	is	be	AUX
fcis-30619	36	8	suitable	suitable	ADJ
fcis-30619	36	9	for	for	ADP
fcis-30619	36	10	data	datum	NOUN
fcis-30619	36	11	with	with	ADP
fcis-30619	36	12	certain	certain	ADJ
fcis-30619	36	13	noise	noise	NOUN
fcis-30619	36	14	,	,	PUNCT
fcis-30619	36	15	while	while	SCONJ
fcis-30619	36	16	the	the	DET
fcis-30619	36	17	matern	matern	PROPN
fcis-30619	36	18	kernel	kernel	PROPN
fcis-30619	36	19	can	can	AUX
fcis-30619	36	20	fit	fit	VERB
fcis-30619	36	21	incomplete	incomplete	ADJ
fcis-30619	36	22	smooth	smooth	ADJ
fcis-30619	36	23	data	datum	NOUN
fcis-30619	36	24	changes	change	NOUN
fcis-30619	36	25	.	.	PUNCT
fcis-30619	37	1	(	(	PUNCT
fcis-30619	37	2	3	3	X
fcis-30619	37	3	)	)	PUNCT
fcis-30619	37	4	rational	rational	ADJ
fcis-30619	37	5	quadratic	quadratic	ADJ
fcis-30619	37	6	+	+	NUM
fcis-30619	37	7	whitekernel	whitekernel	NOUN
fcis-30619	37	8	:	:	PUNCT
fcis-30619	37	9	the	the	DET
fcis-30619	37	10	rational	rational	ADJ
fcis-30619	37	11	quadratic	quadratic	ADJ
fcis-30619	37	12	kernel	kernel	NOUN
fcis-30619	37	13	can	can	AUX
fcis-30619	37	14	handle	handle	VERB
fcis-30619	37	15	multi	multi	ADJ
fcis-30619	37	16	-	-	ADJ
fcis-30619	37	17	scale	scale	ADJ
fcis-30619	37	18	variations	variation	NOUN
fcis-30619	37	19	and	and	CCONJ
fcis-30619	37	20	is	be	AUX
fcis-30619	37	21	suitable	suitable	ADJ
fcis-30619	37	22	for	for	ADP
fcis-30619	37	23	situations	situation	NOUN
fcis-30619	37	24	where	where	SCONJ
fcis-30619	37	25	data	datum	NOUN
fcis-30619	37	26	changes	change	NOUN
fcis-30619	37	27	are	be	AUX
fcis-30619	37	28	uneven	uneven	ADJ
fcis-30619	37	29	.	.	PUNCT
fcis-30619	38	1	whitekernel	whitekernel	PROPN
fcis-30619	38	2	also	also	ADV
fcis-30619	38	3	defines	define	VERB
fcis-30619	38	4	a	a	DET
fcis-30619	38	5	white	white	ADJ
fcis-30619	38	6	noise	noise	NOUN
fcis-30619	38	7	kernel	kernel	PROPN
fcis-30619	38	8	to	to	PART
fcis-30619	38	9	represent	represent	VERB
fcis-30619	38	10	noise	noise	NOUN
fcis-30619	38	11	in	in	ADP
fcis-30619	38	12	the	the	DET
fcis-30619	38	13	data	datum	NOUN
fcis-30619	38	14	.	.	PUNCT
fcis-30619	39	1	these	these	DET
fcis-30619	39	2	two	two	NUM
fcis-30619	39	3	kernels	kernel	NOUN
fcis-30619	39	4	are	be	AUX
fcis-30619	39	5	applicable	applicable	ADJ
fcis-30619	39	6	to	to	ADP
fcis-30619	39	7	data	datum	NOUN
fcis-30619	39	8	with	with	ADP
fcis-30619	39	9	multi	multi	ADJ
fcis-30619	39	10	-	-	ADJ
fcis-30619	39	11	scale	scale	ADJ
fcis-30619	39	12	variations	variation	NOUN
fcis-30619	39	13	and	and	CCONJ
fcis-30619	39	14	take	take	VERB
fcis-30619	39	15	into	into	ADP
fcis-30619	39	16	account	account	NOUN
fcis-30619	39	17	the	the	DET
fcis-30619	39	18	noise	noise	NOUN
fcis-30619	39	19	in	in	ADP
fcis-30619	39	20	the	the	DET
fcis-30619	39	21	data	datum	NOUN
fcis-30619	39	22	.	.	PUNCT
fcis-30619	40	1	3.2	3.2	NUM
fcis-30619	40	2	.	.	PUNCT
fcis-30619	40	3	evaluation	evaluation	NOUN
fcis-30619	40	4	metrics	metric	NOUN
fcis-30619	40	5	this	this	DET
fcis-30619	40	6	article	article	NOUN
fcis-30619	40	7	chooses	choose	VERB
fcis-30619	40	8	rmse	rmse	PROPN
fcis-30619	40	9	to	to	PART
fcis-30619	40	10	evaluate	evaluate	VERB
fcis-30619	40	11	the	the	DET
fcis-30619	40	12	effectiveness	effectiveness	NOUN
fcis-30619	40	13	of	of	ADP
fcis-30619	40	14	the	the	DET
fcis-30619	40	15	model	model	NOUN
fcis-30619	40	16	.	.	PUNCT
fcis-30619	41	1	rmse	rmse	PROPN
fcis-30619	41	2	is	be	AUX
fcis-30619	41	3	a	a	DET
fcis-30619	41	4	very	very	ADV
fcis-30619	41	5	useful	useful	ADJ
fcis-30619	41	6	regression	regression	NOUN
fcis-30619	41	7	model	model	NOUN
fcis-30619	41	8	evaluation	evaluation	NOUN
fcis-30619	41	9	tool	tool	NOUN
fcis-30619	41	10	,	,	PUNCT
fcis-30619	41	11	mainly	mainly	ADV
fcis-30619	41	12	used	use	VERB
fcis-30619	41	13	to	to	PART
fcis-30619	41	14	measure	measure	VERB
fcis-30619	41	15	the	the	DET
fcis-30619	41	16	difference	difference	NOUN
fcis-30619	41	17	between	between	ADP
fcis-30619	41	18	the	the	DET
fcis-30619	41	19	predicted	predict	VERB
fcis-30619	41	20	and	and	CCONJ
fcis-30619	41	21	actual	actual	ADJ
fcis-30619	41	22	values	value	NOUN
fcis-30619	41	23	of	of	ADP
fcis-30619	41	24	the	the	DET
fcis-30619	41	25	model	model	NOUN
fcis-30619	41	26	,	,	PUNCT
fcis-30619	41	27	especially	especially	ADV
fcis-30619	41	28	suitable	suitable	ADJ
fcis-30619	41	29	for	for	ADP
fcis-30619	41	30	situations	situation	NOUN
fcis-30619	41	31	with	with	ADP
fcis-30619	41	32	large	large	ADJ
fcis-30619	41	33	errors	error	NOUN
fcis-30619	41	34	.	.	PUNCT
fcis-30619	42	1	by	by	ADP
fcis-30619	42	2	calculating	calculate	VERB
fcis-30619	42	3	rmse	rmse	NOUN
fcis-30619	42	4	,	,	PUNCT
fcis-30619	42	5	we	we	PRON
fcis-30619	42	6	can	can	AUX
fcis-30619	42	7	obtain	obtain	VERB
fcis-30619	42	8	the	the	DET
fcis-30619	42	9	average	average	ADJ
fcis-30619	42	10	error	error	NOUN
fcis-30619	42	11	between	between	ADP
fcis-30619	42	12	model	model	NOUN
fcis-30619	42	13	predictions	prediction	NOUN
fcis-30619	42	14	and	and	CCONJ
fcis-30619	42	15	actual	actual	ADJ
fcis-30619	42	16	values	value	NOUN
fcis-30619	42	17	,	,	PUNCT
fcis-30619	42	18	and	and	CCONJ
fcis-30619	42	19	compare	compare	VERB
fcis-30619	42	20	multiple	multiple	ADJ
fcis-30619	42	21	models	model	NOUN
fcis-30619	42	22	to	to	PART
fcis-30619	42	23	select	select	VERB
fcis-30619	42	24	the	the	DET
fcis-30619	42	25	best	good	ADJ
fcis-30619	42	26	performing	performing	NOUN
fcis-30619	42	27	model	model	NOUN
fcis-30619	42	28	.	.	PUNCT
fcis-30619	43	1	1	1	NUM
fcis-30619	43	2	5	5	NUM
fcis-30619	43	3	3.3	3.3	NUM
fcis-30619	43	4	.	.	PUNCT
fcis-30619	44	1	application	application	NOUN
fcis-30619	44	2	the	the	DET
fcis-30619	44	3	dataset	dataset	NOUN
fcis-30619	44	4	used	use	VERB
fcis-30619	44	5	is	be	AUX
fcis-30619	44	6	the	the	DET
fcis-30619	44	7	california	california	PROPN
fcis-30619	44	8	housing	housing	NOUN
fcis-30619	44	9	dataset	dataset	PROPN
fcis-30619	44	10	,	,	PUNCT
fcis-30619	44	11	which	which	PRON
fcis-30619	44	12	includes	include	VERB
fcis-30619	44	13	housing	housing	NOUN
fcis-30619	44	14	prices	price	NOUN
fcis-30619	44	15	from	from	ADP
fcis-30619	44	16	different	different	ADJ
fcis-30619	44	17	regions	region	NOUN
fcis-30619	44	18	of	of	ADP
fcis-30619	44	19	california	california	PROPN
fcis-30619	44	20	.	.	PUNCT
fcis-30619	45	1	the	the	DET
fcis-30619	45	2	dataset	dataset	NOUN
fcis-30619	45	3	contains	contain	VERB
fcis-30619	45	4	geographic	geographic	ADJ
fcis-30619	45	5	,	,	PUNCT
fcis-30619	45	6	population	population	NOUN
fcis-30619	45	7	,	,	PUNCT
fcis-30619	45	8	and	and	CCONJ
fcis-30619	45	9	income	income	NOUN
fcis-30619	45	10	features	feature	NOUN
fcis-30619	45	11	,	,	PUNCT
fcis-30619	45	12	with	with	ADP
fcis-30619	45	13	the	the	DET
fcis-30619	45	14	median	median	PROPN
fcis-30619	45	15	house	house	NOUN
fcis-30619	45	16	price	price	NOUN
fcis-30619	45	17	as	as	ADP
fcis-30619	45	18	the	the	DET
fcis-30619	45	19	target	target	NOUN
fcis-30619	45	20	variable	variable	NOUN
fcis-30619	45	21	.	.	PUNCT
fcis-30619	46	1	by	by	ADP
fcis-30619	46	2	using	use	VERB
fcis-30619	46	3	gaussian	gaussian	ADJ
fcis-30619	46	4	process	process	NOUN
fcis-30619	46	5	regression	regression	NOUN
fcis-30619	46	6	models	model	NOUN
fcis-30619	46	7	with	with	ADP
fcis-30619	46	8	three	three	NUM
fcis-30619	46	9	different	different	ADJ
fcis-30619	46	10	combinations	combination	NOUN
fcis-30619	46	11	of	of	ADP
fcis-30619	46	12	kernel	kernel	NOUN
fcis-30619	46	13	functions	function	NOUN
fcis-30619	46	14	for	for	ADP
fcis-30619	46	15	prediction	prediction	NOUN
fcis-30619	46	16	,	,	PUNCT
fcis-30619	46	17	and	and	CCONJ
fcis-30619	46	18	observing	observe	VERB
fcis-30619	46	19	the	the	DET
fcis-30619	46	20	impact	impact	NOUN
fcis-30619	46	21	of	of	ADP
fcis-30619	46	22	different	different	ADJ
fcis-30619	46	23	combinations	combination	NOUN
fcis-30619	46	24	of	of	ADP
fcis-30619	46	25	kernel	kernel	NOUN
fcis-30619	46	26	functions	function	NOUN
fcis-30619	46	27	on	on	ADP
fcis-30619	46	28	the	the	DET
fcis-30619	46	29	prediction	prediction	NOUN
fcis-30619	46	30	results	result	NOUN
fcis-30619	46	31	.	.	PUNCT
fcis-30619	47	1	fig	fig	NOUN
fcis-30619	47	2	1	1	NUM
fcis-30619	47	3	.	.	PUNCT
fcis-30619	47	4	house	house	NOUN
fcis-30619	47	5	price	price	NOUN
fcis-30619	47	6	prediction	prediction	NOUN
fcis-30619	47	7	performance	performance	NOUN
fcis-30619	47	8	under	under	ADP
fcis-30619	47	9	different	different	ADJ
fcis-30619	47	10	kernel	kernel	NOUN
fcis-30619	47	11	functions	function	NOUN
fcis-30619	47	12	figure	figure	VERB
fcis-30619	47	13	1	1	NUM
fcis-30619	47	14	shows	show	VERB
fcis-30619	47	15	the	the	DET
fcis-30619	47	16	housing	housing	NOUN
fcis-30619	47	17	price	price	NOUN
fcis-30619	47	18	prediction	prediction	NOUN
fcis-30619	47	19	performance	performance	NOUN
fcis-30619	47	20	under	under	ADP
fcis-30619	47	21	different	different	ADJ
fcis-30619	47	22	kernel	kernel	NOUN
fcis-30619	47	23	functions	function	NOUN
fcis-30619	47	24	.	.	PUNCT
fcis-30619	48	1	when	when	SCONJ
fcis-30619	48	2	the	the	DET
fcis-30619	48	3	kernel	kernel	PROPN
fcis-30619	48	4	function	function	NOUN
fcis-30619	48	5	is	be	AUX
fcis-30619	48	6	constantkernel	constantkernel	NOUN
fcis-30619	48	7	*	*	PUNCT
fcis-30619	48	8	rbf	rbf	PROPN
fcis-30619	48	9	,	,	PUNCT
fcis-30619	48	10	the	the	DET
fcis-30619	48	11	predicted	predict	VERB
fcis-30619	48	12	results	result	NOUN
fcis-30619	48	13	(	(	PUNCT
fcis-30619	48	14	blue	blue	ADJ
fcis-30619	48	15	line	line	NOUN
fcis-30619	48	16	)	)	PUNCT
fcis-30619	48	17	are	be	AUX
fcis-30619	48	18	almost	almost	ADV
fcis-30619	48	19	horizontal	horizontal	ADJ
fcis-30619	48	20	,	,	PUNCT
fcis-30619	48	21	indicating	indicate	VERB
fcis-30619	48	22	that	that	SCONJ
fcis-30619	48	23	the	the	DET
fcis-30619	48	24	model	model	NOUN
fcis-30619	48	25	did	do	AUX
fcis-30619	48	26	not	not	PART
fcis-30619	48	27	capture	capture	VERB
fcis-30619	48	28	the	the	DET
fcis-30619	48	29	trend	trend	NOUN
fcis-30619	48	30	of	of	ADP
fcis-30619	48	31	the	the	DET
fcis-30619	48	32	data	datum	NOUN
fcis-30619	48	33	well	well	ADV
fcis-30619	48	34	.	.	PUNCT
fcis-30619	49	1	this	this	PRON
fcis-30619	49	2	may	may	AUX
fcis-30619	49	3	be	be	AUX
fcis-30619	49	4	because	because	SCONJ
fcis-30619	49	5	the	the	DET
fcis-30619	49	6	rbf	rbf	PROPN
fcis-30619	49	7	kernel	kernel	PROPN
fcis-30619	49	8	is	be	AUX
fcis-30619	49	9	too	too	ADV
fcis-30619	49	10	smooth	smooth	ADJ
fcis-30619	49	11	on	on	ADP
fcis-30619	49	12	this	this	DET
fcis-30619	49	13	dataset	dataset	NOUN
fcis-30619	49	14	,	,	PUNCT
fcis-30619	49	15	which	which	PRON
fcis-30619	49	16	makes	make	VERB
fcis-30619	49	17	it	it	PRON
fcis-30619	49	18	difficult	difficult	ADJ
fcis-30619	49	19	for	for	SCONJ
fcis-30619	49	20	the	the	DET
fcis-30619	49	21	model	model	NOUN
fcis-30619	49	22	to	to	PART
fcis-30619	49	23	fit	fit	VERB
fcis-30619	49	24	the	the	DET
fcis-30619	49	25	complexity	complexity	NOUN
fcis-30619	49	26	of	of	ADP
fcis-30619	49	27	the	the	DET
fcis-30619	49	28	data	datum	NOUN
fcis-30619	49	29	well	well	ADV
fcis-30619	49	30	,	,	PUNCT
fcis-30619	49	31	and	and	CCONJ
fcis-30619	49	32	the	the	DET
fcis-30619	49	33	confidence	confidence	NOUN
fcis-30619	49	34	interval	interval	NOUN
fcis-30619	49	35	(	(	PUNCT
fcis-30619	49	36	blue	blue	ADJ
fcis-30619	49	37	shaded	shaded	ADJ
fcis-30619	49	38	area	area	NOUN
fcis-30619	49	39	)	)	PUNCT
fcis-30619	49	40	is	be	AUX
fcis-30619	49	41	very	very	ADV
fcis-30619	49	42	wide	wide	ADJ
fcis-30619	49	43	,	,	PUNCT
fcis-30619	49	44	indicating	indicate	VERB
fcis-30619	49	45	that	that	SCONJ
fcis-30619	49	46	the	the	DET
fcis-30619	49	47	model	model	NOUN
fcis-30619	49	48	has	have	VERB
fcis-30619	49	49	a	a	DET
fcis-30619	49	50	high	high	ADJ
fcis-30619	49	51	degree	degree	NOUN
fcis-30619	49	52	of	of	ADP
fcis-30619	49	53	uncertainty	uncertainty	NOUN
fcis-30619	49	54	in	in	ADP
fcis-30619	49	55	the	the	DET
fcis-30619	49	56	predicted	predict	VERB
fcis-30619	49	57	results	result	NOUN
fcis-30619	49	58	.	.	PUNCT
fcis-30619	50	1	the	the	DET
fcis-30619	50	2	prediction	prediction	NOUN
fcis-30619	50	3	results	result	NOUN
fcis-30619	50	4	of	of	ADP
fcis-30619	50	5	matern	matern	PROPN
fcis-30619	50	6	kernel+	kernel+	VERB
fcis-30619	50	7	white	white	PROPN
fcis-30619	50	8	kernel	kernel	PROPN
fcis-30619	50	9	capture	capture	VERB
fcis-30619	50	10	the	the	DET
fcis-30619	50	11	trend	trend	NOUN
fcis-30619	50	12	of	of	ADP
fcis-30619	50	13	the	the	DET
fcis-30619	50	14	data	datum	NOUN
fcis-30619	50	15	well	well	ADV
fcis-30619	50	16	,	,	PUNCT
fcis-30619	50	17	showing	show	VERB
fcis-30619	50	18	a	a	DET
fcis-30619	50	19	clear	clear	ADJ
fcis-30619	50	20	nonlinear	nonlinear	ADJ
fcis-30619	50	21	relationship	relationship	NOUN
fcis-30619	50	22	,	,	PUNCT
fcis-30619	50	23	and	and	CCONJ
fcis-30619	50	24	the	the	DET
fcis-30619	50	25	confidence	confidence	NOUN
fcis-30619	50	26	interval	interval	NOUN
fcis-30619	50	27	is	be	AUX
fcis-30619	50	28	relatively	relatively	ADV
fcis-30619	50	29	narrow	narrow	ADJ
fcis-30619	50	30	,	,	PUNCT
fcis-30619	50	31	indicating	indicate	VERB
fcis-30619	50	32	that	that	SCONJ
fcis-30619	50	33	the	the	DET
fcis-30619	50	34	model	model	NOUN
fcis-30619	50	35	has	have	VERB
fcis-30619	50	36	less	less	ADJ
fcis-30619	50	37	uncertainty	uncertainty	NOUN
fcis-30619	50	38	in	in	ADP
fcis-30619	50	39	the	the	DET
fcis-30619	50	40	prediction	prediction	NOUN
fcis-30619	50	41	results	result	NOUN
fcis-30619	50	42	and	and	CCONJ
fcis-30619	50	43	the	the	DET
fcis-30619	50	44	prediction	prediction	NOUN
fcis-30619	50	45	is	be	AUX
fcis-30619	50	46	more	more	ADV
fcis-30619	50	47	reliable	reliable	ADJ
fcis-30619	50	48	.	.	PUNCT
fcis-30619	51	1	the	the	DET
fcis-30619	51	2	prediction	prediction	NOUN
fcis-30619	51	3	results	result	NOUN
fcis-30619	51	4	of	of	ADP
fcis-30619	51	5	rational	rational	ADJ
fcis-30619	51	6	quadratic+	quadratic+	ADJ
fcis-30619	51	7	whitekernel	whitekernel	NOUN
fcis-30619	51	8	also	also	ADV
fcis-30619	51	9	capture	capture	VERB
fcis-30619	51	10	the	the	DET
fcis-30619	51	11	trend	trend	NOUN
fcis-30619	51	12	of	of	ADP
fcis-30619	51	13	the	the	DET
fcis-30619	51	14	data	datum	NOUN
fcis-30619	51	15	well	well	ADV
fcis-30619	51	16	and	and	CCONJ
fcis-30619	51	17	show	show	VERB
fcis-30619	51	18	a	a	DET
fcis-30619	51	19	non	non	ADJ
fcis-30619	51	20	-	-	ADJ
fcis-30619	51	21	linear	linear	ADJ
fcis-30619	51	22	relationship	relationship	NOUN
fcis-30619	51	23	.	.	PUNCT
fcis-30619	52	1	however	however	ADV
fcis-30619	52	2	,	,	PUNCT
fcis-30619	52	3	compared	compare	VERB
fcis-30619	52	4	with	with	ADP
fcis-30619	52	5	the	the	DET
fcis-30619	52	6	previous	previous	ADJ
fcis-30619	52	7	combination	combination	NOUN
fcis-30619	52	8	kernel	kernel	NOUN
fcis-30619	52	9	function	function	NOUN
fcis-30619	52	10	,	,	PUNCT
fcis-30619	52	11	the	the	DET
fcis-30619	52	12	fitting	fitting	ADJ
fcis-30619	52	13	effect	effect	NOUN
fcis-30619	52	14	is	be	AUX
fcis-30619	52	15	slightly	slightly	ADV
fcis-30619	52	16	different	different	ADJ
fcis-30619	52	17	,	,	PUNCT
fcis-30619	52	18	and	and	CCONJ
fcis-30619	52	19	the	the	DET
fcis-30619	52	20	confidence	confidence	NOUN
fcis-30619	52	21	interval	interval	NOUN
fcis-30619	52	22	is	be	AUX
fcis-30619	52	23	relatively	relatively	ADV
fcis-30619	52	24	narrow	narrow	ADJ
fcis-30619	52	25	,	,	PUNCT
fcis-30619	52	26	indicating	indicate	VERB
fcis-30619	52	27	that	that	SCONJ
fcis-30619	52	28	the	the	DET
fcis-30619	52	29	model	model	NOUN
fcis-30619	52	30	has	have	VERB
fcis-30619	52	31	less	less	ADJ
fcis-30619	52	32	uncertainty	uncertainty	NOUN
fcis-30619	52	33	in	in	ADP
fcis-30619	52	34	the	the	DET
fcis-30619	52	35	prediction	prediction	NOUN
fcis-30619	52	36	results	result	NOUN
fcis-30619	52	37	and	and	CCONJ
fcis-30619	52	38	the	the	DET
fcis-30619	52	39	prediction	prediction	NOUN
fcis-30619	52	40	is	be	AUX
fcis-30619	52	41	more	more	ADV
fcis-30619	52	42	reliable	reliable	ADJ
fcis-30619	52	43	.	.	PUNCT
fcis-30619	53	1	table	table	NOUN
fcis-30619	53	2	1	1	NUM
fcis-30619	53	3	.	.	PUNCT
fcis-30619	54	1	forecasting	forecasting	NOUN
fcis-30619	54	2	error	error	NOUN
fcis-30619	54	3	analysis	analysis	NOUN
fcis-30619	54	4	.	.	PUNCT
fcis-30619	55	1	constantkernel	constantkernel	PROPN
fcis-30619	55	2	*	*	PUNCT
fcis-30619	56	1	rbf	rbf	PROPN
fcis-30619	56	2	matern	matern	PROPN
fcis-30619	56	3	kernel	kernel	PROPN
fcis-30619	56	4	+	+	CCONJ
fcis-30619	56	5	whitekernel	whitekernel	VERB
fcis-30619	56	6	rational	rational	ADJ
fcis-30619	56	7	quadratic	quadratic	ADJ
fcis-30619	56	8	+	+	NUM
fcis-30619	56	9	whitekernel	whitekernel	NOUN
fcis-30619	56	10	rmse	rmse	NOUN
fcis-30619	56	11	2.2745	2.2745	NUM
fcis-30619	56	12	0.8225	0.8225	NUM
fcis-30619	56	13	0.8231	0.8231	NUM
fcis-30619	56	14	127	127	NUM
fcis-30619	56	15	table	table	NOUN
fcis-30619	56	16	1	1	NUM
fcis-30619	56	17	presents	present	VERB
fcis-30619	56	18	the	the	DET
fcis-30619	56	19	rmse	rmse	NOUN
fcis-30619	56	20	of	of	ADP
fcis-30619	56	21	different	different	ADJ
fcis-30619	56	22	models	model	NOUN
fcis-30619	56	23	.	.	PUNCT
fcis-30619	57	1	when	when	SCONJ
fcis-30619	57	2	using	use	VERB
fcis-30619	57	3	the	the	DET
fcis-30619	57	4	constantkernel	constantkernel	NOUN
fcis-30619	57	5	*	*	PUNCT
fcis-30619	57	6	rbf	rbf	PROPN
fcis-30619	57	7	kernel	kernel	PROPN
fcis-30619	57	8	function	function	PROPN
fcis-30619	57	9	,	,	PUNCT
fcis-30619	57	10	the	the	DET
fcis-30619	57	11	model	model	NOUN
fcis-30619	57	12	has	have	VERB
fcis-30619	57	13	a	a	DET
fcis-30619	57	14	higher	high	ADJ
fcis-30619	57	15	prediction	prediction	NOUN
fcis-30619	57	16	error	error	NOUN
fcis-30619	57	17	on	on	ADP
fcis-30619	57	18	the	the	DET
fcis-30619	57	19	test	test	NOUN
fcis-30619	57	20	set	set	NOUN
fcis-30619	57	21	.	.	PUNCT
fcis-30619	58	1	in	in	ADP
fcis-30619	58	2	this	this	DET
fcis-30619	58	3	case	case	NOUN
fcis-30619	58	4	,	,	PUNCT
fcis-30619	58	5	the	the	DET
fcis-30619	58	6	model	model	NOUN
fcis-30619	58	7	's	's	PART
fcis-30619	58	8	performance	performance	NOUN
fcis-30619	58	9	may	may	AUX
fcis-30619	58	10	be	be	AUX
fcis-30619	58	11	affected	affect	VERB
fcis-30619	58	12	by	by	ADP
fcis-30619	58	13	data	datum	NOUN
fcis-30619	58	14	noise	noise	NOUN
fcis-30619	58	15	or	or	CCONJ
fcis-30619	58	16	feature	feature	NOUN
fcis-30619	58	17	selection	selection	NOUN
fcis-30619	58	18	,	,	PUNCT
fcis-30619	58	19	and	and	CCONJ
fcis-30619	58	20	it	it	PRON
fcis-30619	58	21	may	may	AUX
fcis-30619	58	22	not	not	PART
fcis-30619	58	23	be	be	AUX
fcis-30619	58	24	able	able	ADJ
fcis-30619	58	25	to	to	PART
fcis-30619	58	26	capture	capture	VERB
fcis-30619	58	27	the	the	DET
fcis-30619	58	28	patterns	pattern	NOUN
fcis-30619	58	29	of	of	ADP
fcis-30619	58	30	the	the	DET
fcis-30619	58	31	data	datum	NOUN
fcis-30619	58	32	well	well	ADV
fcis-30619	58	33	.	.	PUNCT
fcis-30619	59	1	both	both	PRON
fcis-30619	59	2	matern	matern	PROPN
fcis-30619	59	3	kernel+whitekernel	kernel+whitekernel	PROPN
fcis-30619	59	4	and	and	CCONJ
fcis-30619	59	5	rational	rational	ADJ
fcis-30619	59	6	quadratic+whitekernel	quadratic+whitekernel	PROPN
fcis-30619	59	7	perform	perform	VERB
fcis-30619	59	8	well	well	ADV
fcis-30619	59	9	on	on	ADP
fcis-30619	59	10	this	this	DET
fcis-30619	59	11	dataset	dataset	NOUN
fcis-30619	59	12	,	,	PUNCT
fcis-30619	59	13	with	with	ADP
fcis-30619	59	14	rmse	rmse	NOUN
fcis-30619	59	15	fluctuating	fluctuate	VERB
fcis-30619	59	16	around	around	ADV
fcis-30619	59	17	0.82	0.82	NUM
fcis-30619	59	18	.	.	PUNCT
fcis-30619	60	1	among	among	ADP
fcis-30619	60	2	them	they	PRON
fcis-30619	60	3	,	,	PUNCT
fcis-30619	60	4	matern	matern	PROPN
fcis-30619	60	5	kernel+whitekernel	kernel+whitekernel	PROPN
fcis-30619	60	6	has	have	VERB
fcis-30619	60	7	the	the	DET
fcis-30619	60	8	smallest	small	ADJ
fcis-30619	60	9	rmse	rmse	NOUN
fcis-30619	60	10	,	,	PUNCT
fcis-30619	60	11	indicating	indicate	VERB
fcis-30619	60	12	that	that	SCONJ
fcis-30619	60	13	this	this	DET
fcis-30619	60	14	method	method	NOUN
fcis-30619	60	15	is	be	AUX
fcis-30619	60	16	more	more	ADV
fcis-30619	60	17	accurate	accurate	ADJ
fcis-30619	60	18	.	.	PUNCT
fcis-30619	61	1	in	in	ADP
fcis-30619	61	2	summary	summary	NOUN
fcis-30619	61	3	,	,	PUNCT
fcis-30619	61	4	the	the	DET
fcis-30619	61	5	predicted	predict	VERB
fcis-30619	61	6	values	value	NOUN
fcis-30619	61	7	of	of	ADP
fcis-30619	61	8	both	both	DET
fcis-30619	61	9	kernel	kernel	NOUN
fcis-30619	61	10	functions	function	NOUN
fcis-30619	61	11	can	can	AUX
fcis-30619	61	12	serve	serve	VERB
fcis-30619	61	13	as	as	ADP
fcis-30619	61	14	references	reference	NOUN
fcis-30619	61	15	.	.	PUNCT
fcis-30619	62	1	4	4	X
fcis-30619	62	2	.	.	X
fcis-30619	62	3	summary	summary	VERB
fcis-30619	62	4	single	single	ADJ
fcis-30619	62	5	-	-	PUNCT
fcis-30619	62	6	scale	scale	NOUN
fcis-30619	62	7	kernels	kernel	NOUN
fcis-30619	62	8	like	like	ADP
fcis-30619	62	9	rbf	rbf	PROPN
fcis-30619	62	10	have	have	VERB
fcis-30619	62	11	limitations	limitation	NOUN
fcis-30619	62	12	in	in	ADP
fcis-30619	62	13	capturing	capture	VERB
fcis-30619	62	14	multi	multi	ADJ
fcis-30619	62	15	-	-	ADJ
fcis-30619	62	16	scale	scale	ADJ
fcis-30619	62	17	variations	variation	NOUN
fcis-30619	62	18	.	.	PUNCT
fcis-30619	63	1	matern	matern	ADJ
fcis-30619	63	2	and	and	CCONJ
fcis-30619	63	3	rational	rational	ADJ
fcis-30619	63	4	quadratic	quadratic	ADJ
fcis-30619	63	5	kernels	kernel	NOUN
fcis-30619	63	6	provide	provide	VERB
fcis-30619	63	7	better	well	ADJ
fcis-30619	63	8	flexibility	flexibility	NOUN
fcis-30619	63	9	in	in	ADP
fcis-30619	63	10	balancing	balance	VERB
fcis-30619	63	11	local	local	ADJ
fcis-30619	63	12	details	detail	NOUN
fcis-30619	63	13	and	and	CCONJ
fcis-30619	63	14	global	global	ADJ
fcis-30619	63	15	trends	trend	NOUN
fcis-30619	63	16	,	,	PUNCT
fcis-30619	63	17	while	while	SCONJ
fcis-30619	63	18	handling	handle	VERB
fcis-30619	63	19	noise	noise	NOUN
fcis-30619	63	20	more	more	ADV
fcis-30619	63	21	effectively	effectively	ADV
fcis-30619	63	22	.	.	PUNCT
fcis-30619	64	1	choosing	choose	VERB
fcis-30619	64	2	appropriate	appropriate	ADJ
fcis-30619	64	3	kernel	kernel	NOUN
fcis-30619	64	4	combinations	combination	NOUN
fcis-30619	64	5	significantly	significantly	ADV
fcis-30619	64	6	impacts	impact	VERB
fcis-30619	64	7	the	the	DET
fcis-30619	64	8	model	model	NOUN
fcis-30619	64	9	’s	’s	PART
fcis-30619	64	10	ability	ability	NOUN
fcis-30619	64	11	to	to	PART
fcis-30619	64	12	generalize	generalize	VERB
fcis-30619	64	13	.	.	PUNCT
fcis-30619	65	1	this	this	DET
fcis-30619	65	2	study	study	NOUN
fcis-30619	65	3	reveals	reveal	VERB
fcis-30619	65	4	that	that	SCONJ
fcis-30619	65	5	different	different	ADJ
fcis-30619	65	6	combinations	combination	NOUN
fcis-30619	65	7	of	of	ADP
fcis-30619	65	8	kernel	kernel	NOUN
fcis-30619	65	9	functions	function	NOUN
fcis-30619	65	10	have	have	VERB
fcis-30619	65	11	a	a	DET
fcis-30619	65	12	significant	significant	ADJ
fcis-30619	65	13	impact	impact	NOUN
fcis-30619	65	14	on	on	ADP
fcis-30619	65	15	the	the	DET
fcis-30619	65	16	fitting	fitting	ADJ
fcis-30619	65	17	performance	performance	NOUN
fcis-30619	65	18	of	of	ADP
fcis-30619	65	19	models	model	NOUN
fcis-30619	65	20	when	when	SCONJ
fcis-30619	65	21	data	datum	NOUN
fcis-30619	65	22	exhibits	exhibit	VERB
fcis-30619	65	23	complex	complex	ADJ
fcis-30619	65	24	nonlinear	nonlinear	ADJ
fcis-30619	65	25	characteristics	characteristic	NOUN
fcis-30619	65	26	.	.	PUNCT
fcis-30619	66	1	therefore	therefore	ADV
fcis-30619	66	2	,	,	PUNCT
fcis-30619	66	3	choosing	choose	VERB
fcis-30619	66	4	the	the	DET
fcis-30619	66	5	appropriate	appropriate	ADJ
fcis-30619	66	6	kernel	kernel	NOUN
fcis-30619	66	7	function	function	NOUN
fcis-30619	66	8	is	be	AUX
fcis-30619	66	9	crucial	crucial	ADJ
fcis-30619	66	10	for	for	ADP
fcis-30619	66	11	improving	improve	VERB
fcis-30619	66	12	the	the	DET
fcis-30619	66	13	generalization	generalization	NOUN
fcis-30619	66	14	ability	ability	NOUN
fcis-30619	66	15	and	and	CCONJ
fcis-30619	66	16	stability	stability	NOUN
fcis-30619	66	17	of	of	ADP
fcis-30619	66	18	the	the	DET
fcis-30619	66	19	model	model	NOUN
fcis-30619	66	20	.	.	PUNCT
fcis-30619	67	1	in	in	ADP
fcis-30619	67	2	addition	addition	NOUN
fcis-30619	67	3	,	,	PUNCT
fcis-30619	67	4	gaussian	gaussian	ADJ
fcis-30619	67	5	process	process	NOUN
fcis-30619	67	6	regression	regression	NOUN
fcis-30619	67	7	(	(	PUNCT
fcis-30619	67	8	gpr	gpr	PROPN
fcis-30619	67	9	)	)	PUNCT
fcis-30619	67	10	,	,	PUNCT
fcis-30619	67	11	as	as	ADP
fcis-30619	67	12	a	a	DET
fcis-30619	67	13	probabilistic	probabilistic	ADJ
fcis-30619	67	14	modeling	modeling	NOUN
fcis-30619	67	15	technique	technique	NOUN
fcis-30619	67	16	,	,	PUNCT
fcis-30619	67	17	can	can	AUX
fcis-30619	67	18	not	not	PART
fcis-30619	67	19	only	only	ADV
fcis-30619	67	20	predict	predict	VERB
fcis-30619	67	21	but	but	CCONJ
fcis-30619	67	22	also	also	ADV
fcis-30619	67	23	estimate	estimate	VERB
fcis-30619	67	24	variance	variance	NOUN
fcis-30619	67	25	,	,	PUNCT
fcis-30619	67	26	which	which	PRON
fcis-30619	67	27	is	be	AUX
fcis-30619	67	28	an	an	DET
fcis-30619	67	29	important	important	ADJ
fcis-30619	67	30	reference	reference	NOUN
fcis-30619	67	31	for	for	ADP
fcis-30619	67	32	market	market	NOUN
fcis-30619	67	33	analysis	analysis	NOUN
fcis-30619	67	34	and	and	CCONJ
fcis-30619	67	35	risk	risk	NOUN
fcis-30619	67	36	management	management	NOUN
fcis-30619	67	37	.	.	PUNCT
fcis-30619	68	1	compared	compare	VERB
fcis-30619	68	2	with	with	ADP
fcis-30619	68	3	traditional	traditional	ADJ
fcis-30619	68	4	regression	regression	NOUN
fcis-30619	68	5	methods	method	NOUN
fcis-30619	68	6	,	,	PUNCT
fcis-30619	68	7	the	the	DET
fcis-30619	68	8	advantage	advantage	NOUN
fcis-30619	68	9	of	of	ADP
fcis-30619	68	10	gaussian	gaussian	ADJ
fcis-30619	68	11	process	process	NOUN
fcis-30619	68	12	regression	regression	NOUN
fcis-30619	68	13	is	be	AUX
fcis-30619	68	14	that	that	SCONJ
fcis-30619	68	15	it	it	PRON
fcis-30619	68	16	can	can	AUX
fcis-30619	68	17	flexibly	flexibly	ADV
fcis-30619	68	18	adapt	adapt	VERB
fcis-30619	68	19	to	to	ADP
fcis-30619	68	20	the	the	DET
fcis-30619	68	21	characteristics	characteristic	NOUN
fcis-30619	68	22	of	of	ADP
fcis-30619	68	23	data	datum	NOUN
fcis-30619	68	24	by	by	ADP
fcis-30619	68	25	selecting	select	VERB
fcis-30619	68	26	different	different	ADJ
fcis-30619	68	27	kernel	kernel	NOUN
fcis-30619	68	28	functions	function	NOUN
fcis-30619	68	29	,	,	PUNCT
fcis-30619	68	30	making	make	VERB
fcis-30619	68	31	the	the	DET
fcis-30619	68	32	prediction	prediction	NOUN
fcis-30619	68	33	results	result	VERB
fcis-30619	68	34	more	more	ADV
fcis-30619	68	35	accurate	accurate	ADJ
fcis-30619	68	36	and	and	CCONJ
fcis-30619	68	37	easy	easy	ADJ
fcis-30619	68	38	to	to	PART
fcis-30619	68	39	interpret	interpret	VERB
fcis-30619	68	40	.	.	PUNCT
fcis-30619	69	1	references	reference	NOUN
fcis-30619	69	2	[	[	X
fcis-30619	69	3	1	1	NUM
fcis-30619	69	4	]	]	SYM
fcis-30619	69	5	matthias	matthias	PROPN
fcis-30619	69	6	,	,	PUNCT
fcis-30619	69	7	seeger	seeger	PROPN
fcis-30619	69	8	.	.	PUNCT
fcis-30619	70	1	gaussian	gaussian	ADJ
fcis-30619	70	2	processes	process	NOUN
fcis-30619	70	3	for	for	ADP
fcis-30619	70	4	machine	machine	NOUN
fcis-30619	70	5	learning	learn	VERB
fcis-30619	71	1	[	[	X
fcis-30619	71	2	j	j	X
fcis-30619	71	3	]	]	X
fcis-30619	71	4	.	.	PUNCT
fcis-30619	72	1	international	international	ADJ
fcis-30619	72	2	journal	journal	PROPN
fcis-30619	72	3	of	of	ADP
fcis-30619	72	4	neural	neural	ADJ
fcis-30619	72	5	systems	system	NOUN
fcis-30619	72	6	,	,	PUNCT
fcis-30619	72	7	2004	2004	NUM
fcis-30619	72	8	,	,	PUNCT
fcis-30619	72	9	14(2	14(2	NUM
fcis-30619	72	10	):	):	PUNCT
fcis-30619	72	11	69	69	NUM
fcis-30619	72	12	-	-	SYM
fcis-30619	72	13	106	106	NUM
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fcis-30619	73	3	]	]	PUNCT
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fcis-30619	73	8	x	x	PROPN
fcis-30619	73	9	,	,	PUNCT
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fcis-30619	75	2	3	3	X
fcis-30619	75	3	]	]	X
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fcis-30619	75	15	its	its	PRON
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fcis-30619	75	20	.	.	PUNCT
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fcis-30619	77	8	y.	y.	PROPN
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fcis-30619	77	13	.	.	PUNCT
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fcis-30619	79	3	]	]	PUNCT
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fcis-30619	79	19	]	]	PUNCT
fcis-30619	79	20	.	.	PUNCT
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fcis-30619	80	3	,	,	PUNCT
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fcis-30619	80	5	,	,	PUNCT
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fcis-30619	80	11	-	-	SYM
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fcis-30619	80	13	.	.	PUNCT
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fcis-30619	81	12	[	[	X
fcis-30619	81	13	j	j	X
fcis-30619	81	14	]	]	X
fcis-30619	81	15	.	.	PUNCT
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fcis-30619	82	2	.	.	PUNCT
fcis-30619	83	1	[	[	X
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fcis-30619	83	3	]	]	X
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fcis-30619	83	6	.	.	PUNCT
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fcis-30619	84	2	on	on	ADP
fcis-30619	84	3	stock	stock	NOUN
fcis-30619	84	4	index	index	NOUN
fcis-30619	84	5	volatility	volatility	NOUN
fcis-30619	84	6	prediction	prediction	NOUN
fcis-30619	84	7	based	base	VERB
fcis-30619	84	8	on	on	ADP
fcis-30619	84	9	gaussian	gaussian	ADJ
fcis-30619	84	10	process	process	NOUN
fcis-30619	84	11	regression	regression	NOUN
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fcis-30619	84	13	combined	combined	ADJ
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fcis-30619	84	15	function	function	NOUN
fcis-30619	85	1	[	[	X
fcis-30619	85	2	d	d	X
fcis-30619	85	3	]	]	X
fcis-30619	85	4	.	.	PUNCT
fcis-30619	86	1	hunan	hunan	PROPN
fcis-30619	86	2	university	university	PROPN
fcis-30619	86	3	,	,	PUNCT
fcis-30619	86	4	2021	2021	NUM
fcis-30619	86	5	.	.	PUNCT