id	sid	tid	token	lemma	pos
ejpam-2688	1	1	compile	compile	NOUN
ejpam-2688	1	2	/	/	SYM
ejpam-2688	1	3	output.dvi	output.dvi	PRON
ejpam-2688	1	4	regularized	regularize	VERB
ejpam-2688	1	5	svm	svm	ADJ
ejpam-2688	1	6	classification	classification	NOUN
ejpam-2688	1	7	with	with	ADP
ejpam-2688	1	8	a	a	DET
ejpam-2688	1	9	new	new	ADJ
ejpam-2688	1	10	complexity	complexity	NOUN
ejpam-2688	1	11	-	-	PUNCT
ejpam-2688	1	12	driven	drive	VERB
ejpam-2688	1	13	stochastic	stochastic	ADJ
ejpam-2688	1	14	optimizer	optimizer	NOUN
ejpam-2688	1	15	j.	j.	PROPN
ejpam-2688	1	16	andrew	andrew	PROPN
ejpam-2688	1	17	howe1,2,∗	howe1,2,∗	PROPN
ejpam-2688	1	18	,	,	PUNCT
ejpam-2688	1	19	hamparsum	hamparsum	ADJ
ejpam-2688	1	20	bozdogan3	bozdogan3	NOUN
ejpam-2688	1	21	1	1	NUM
ejpam-2688	1	22	risk	risk	NOUN
ejpam-2688	1	23	dynamics	dynamic	NOUN
ejpam-2688	1	24	consultancy	consultancy	NOUN
ejpam-2688	1	25	,	,	PUNCT
ejpam-2688	1	26	istanbul	istanbul	PROPN
ejpam-2688	1	27	,	,	PUNCT
ejpam-2688	1	28	turkey	turkey	PROPN
ejpam-2688	1	29	2	2	NUM
ejpam-2688	1	30	kapsarc	kapsarc	NOUN
ejpam-2688	1	31	,	,	PUNCT
ejpam-2688	1	32	riyadh	riyadh	PROPN
ejpam-2688	1	33	,	,	PUNCT
ejpam-2688	1	34	saudi	saudi	PROPN
ejpam-2688	1	35	arabia	arabia	PROPN
ejpam-2688	1	36	(	(	PUNCT
ejpam-2688	1	37	affiliated	affiliate	VERB
ejpam-2688	1	38	after	after	SCONJ
ejpam-2688	1	39	article	article	NOUN
ejpam-2688	1	40	accepted	accept	VERB
ejpam-2688	1	41	)	)	PUNCT
ejpam-2688	1	42	3	3	NUM
ejpam-2688	1	43	university	university	NOUN
ejpam-2688	1	44	of	of	ADP
ejpam-2688	1	45	tennessee	tennessee	PROPN
ejpam-2688	1	46	,	,	PUNCT
ejpam-2688	1	47	department	department	PROPN
ejpam-2688	1	48	of	of	ADP
ejpam-2688	1	49	business	business	NOUN
ejpam-2688	1	50	analytics	analytic	NOUN
ejpam-2688	1	51	&	&	CCONJ
ejpam-2688	1	52	statistics	statistics	PROPN
ejpam-2688	1	53	,	,	PUNCT
ejpam-2688	1	54	knoxville	knoxville	PROPN
ejpam-2688	1	55	,	,	PUNCT
ejpam-2688	1	56	tennessee	tennessee	PROPN
ejpam-2688	1	57	,	,	PUNCT
ejpam-2688	1	58	usa	usa	PROPN
ejpam-2688	1	59	abstract	abstract	PROPN
ejpam-2688	1	60	.	.	PUNCT
ejpam-2688	2	1	given	give	VERB
ejpam-2688	2	2	a	a	DET
ejpam-2688	2	3	multivariate	multivariate	NOUN
ejpam-2688	2	4	dataset	dataset	NOUN
ejpam-2688	2	5	composed	compose	VERB
ejpam-2688	2	6	of	of	ADP
ejpam-2688	2	7	data	datum	NOUN
ejpam-2688	2	8	from	from	ADP
ejpam-2688	2	9	different	different	ADJ
ejpam-2688	2	10	known	know	VERB
ejpam-2688	2	11	sources	source	NOUN
ejpam-2688	2	12	or	or	CCONJ
ejpam-2688	2	13	processes	process	NOUN
ejpam-2688	2	14	,	,	PUNCT
ejpam-2688	2	15	how	how	SCONJ
ejpam-2688	2	16	can	can	AUX
ejpam-2688	2	17	we	we	PRON
ejpam-2688	2	18	create	create	VERB
ejpam-2688	2	19	a	a	DET
ejpam-2688	2	20	rule	rule	NOUN
ejpam-2688	2	21	to	to	PART
ejpam-2688	2	22	separate	separate	VERB
ejpam-2688	2	23	the	the	DET
ejpam-2688	2	24	data	datum	NOUN
ejpam-2688	2	25	,	,	PUNCT
ejpam-2688	2	26	and	and	CCONJ
ejpam-2688	2	27	classify	classify	VERB
ejpam-2688	2	28	any	any	DET
ejpam-2688	2	29	future	future	ADJ
ejpam-2688	2	30	data	datum	NOUN
ejpam-2688	2	31	?	?	PUNCT
ejpam-2688	3	1	kernel	kernel	PROPN
ejpam-2688	3	2	discriminant	discriminant	PROPN
ejpam-2688	3	3	analysis	analysis	NOUN
ejpam-2688	3	4	is	be	AUX
ejpam-2688	3	5	one	one	NUM
ejpam-2688	3	6	of	of	ADP
ejpam-2688	3	7	many	many	ADJ
ejpam-2688	3	8	supervised	supervised	ADJ
ejpam-2688	3	9	learning	learning	NOUN
ejpam-2688	3	10	techniques	technique	NOUN
ejpam-2688	3	11	that	that	PRON
ejpam-2688	3	12	handle	handle	VERB
ejpam-2688	3	13	this	this	DET
ejpam-2688	3	14	problem	problem	NOUN
ejpam-2688	3	15	.	.	PUNCT
ejpam-2688	4	1	recently	recently	ADV
ejpam-2688	4	2	,	,	PUNCT
ejpam-2688	4	3	in	in	ADP
ejpam-2688	4	4	this	this	DET
ejpam-2688	4	5	and	and	CCONJ
ejpam-2688	4	6	other	other	ADJ
ejpam-2688	4	7	knowledge	knowledge	NOUN
ejpam-2688	4	8	discovery	discovery	NOUN
ejpam-2688	4	9	problems	problem	NOUN
ejpam-2688	4	10	,	,	PUNCT
ejpam-2688	4	11	kernel	kernel	PROPN
ejpam-2688	4	12	methods	method	NOUN
ejpam-2688	4	13	have	have	AUX
ejpam-2688	4	14	gained	gain	VERB
ejpam-2688	4	15	popularity	popularity	NOUN
ejpam-2688	4	16	.	.	PUNCT
ejpam-2688	5	1	this	this	PRON
ejpam-2688	5	2	is	be	AUX
ejpam-2688	5	3	somewhat	somewhat	ADV
ejpam-2688	5	4	ironic	ironic	ADJ
ejpam-2688	5	5	as	as	SCONJ
ejpam-2688	5	6	another	another	DET
ejpam-2688	5	7	common	common	ADJ
ejpam-2688	5	8	theme	theme	NOUN
ejpam-2688	5	9	is	be	AUX
ejpam-2688	5	10	variable	variable	ADJ
ejpam-2688	5	11	reduction	reduction	NOUN
ejpam-2688	5	12	,	,	PUNCT
ejpam-2688	5	13	and	and	CCONJ
ejpam-2688	5	14	kernel	kernel	PROPN
ejpam-2688	5	15	methods	method	NOUN
ejpam-2688	5	16	actually	actually	ADV
ejpam-2688	5	17	inflate	inflate	VERB
ejpam-2688	5	18	dimensionality	dimensionality	NOUN
ejpam-2688	5	19	.	.	PUNCT
ejpam-2688	6	1	due	due	ADP
ejpam-2688	6	2	to	to	ADP
ejpam-2688	6	3	the	the	DET
ejpam-2688	6	4	substantial	substantial	ADJ
ejpam-2688	6	5	benefits	benefit	NOUN
ejpam-2688	6	6	of	of	ADP
ejpam-2688	6	7	processing	process	VERB
ejpam-2688	6	8	"	"	PUNCT
ejpam-2688	6	9	kernelized	kernelize	VERB
ejpam-2688	6	10	"	"	PUNCT
ejpam-2688	6	11	data	datum	NOUN
ejpam-2688	6	12	,	,	PUNCT
ejpam-2688	6	13	this	this	PRON
ejpam-2688	6	14	is	be	AUX
ejpam-2688	6	15	excusable	excusable	ADJ
ejpam-2688	6	16	kernel	kernel	NOUN
ejpam-2688	6	17	methods	method	NOUN
ejpam-2688	6	18	frequently	frequently	ADV
ejpam-2688	6	19	outperform	outperform	VERB
ejpam-2688	6	20	traditional	traditional	ADJ
ejpam-2688	6	21	classification	classification	NOUN
ejpam-2688	6	22	techniques	technique	NOUN
ejpam-2688	6	23	for	for	ADP
ejpam-2688	6	24	real	real	ADJ
ejpam-2688	6	25	data	datum	NOUN
ejpam-2688	6	26	when	when	SCONJ
ejpam-2688	6	27	the	the	DET
ejpam-2688	6	28	classes	class	NOUN
ejpam-2688	6	29	are	be	AUX
ejpam-2688	6	30	not	not	PART
ejpam-2688	6	31	easily	easily	ADV
ejpam-2688	6	32	separable	separable	ADJ
ejpam-2688	6	33	.	.	PUNCT
ejpam-2688	7	1	in	in	ADP
ejpam-2688	7	2	performing	perform	VERB
ejpam-2688	7	3	kernel	kernel	NOUN
ejpam-2688	7	4	discriminant	discriminant	ADJ
ejpam-2688	7	5	analysis	analysis	NOUN
ejpam-2688	7	6	,	,	PUNCT
ejpam-2688	7	7	there	there	PRON
ejpam-2688	7	8	are	be	VERB
ejpam-2688	7	9	two	two	NUM
ejpam-2688	7	10	main	main	ADJ
ejpam-2688	7	11	issues	issue	NOUN
ejpam-2688	7	12	that	that	PRON
ejpam-2688	7	13	we	we	PRON
ejpam-2688	7	14	address	address	VERB
ejpam-2688	7	15	in	in	ADP
ejpam-2688	7	16	this	this	DET
ejpam-2688	7	17	article	article	NOUN
ejpam-2688	7	18	.	.	PUNCT
ejpam-2688	8	1	the	the	DET
ejpam-2688	8	2	first	first	ADJ
ejpam-2688	8	3	is	be	AUX
ejpam-2688	8	4	that	that	SCONJ
ejpam-2688	8	5	,	,	PUNCT
ejpam-2688	8	6	in	in	ADP
ejpam-2688	8	7	the	the	DET
ejpam-2688	8	8	literature	literature	NOUN
ejpam-2688	8	9	,	,	PUNCT
ejpam-2688	8	10	the	the	DET
ejpam-2688	8	11	question	question	NOUN
ejpam-2688	8	12	of	of	ADP
ejpam-2688	8	13	which	which	DET
ejpam-2688	8	14	kernel	kernel	PROPN
ejpam-2688	8	15	function	function	VERB
ejpam-2688	8	16	to	to	PART
ejpam-2688	8	17	use	use	VERB
ejpam-2688	8	18	is	be	AUX
ejpam-2688	8	19	often	often	ADV
ejpam-2688	8	20	subjectively	subjectively	ADV
ejpam-2688	8	21	selected	select	VERB
ejpam-2688	8	22	a	a	DET
ejpam-2688	8	23	prior	prior	ADJ
ejpam-2688	8	24	,	,	PUNCT
ejpam-2688	8	25	or	or	CCONJ
ejpam-2688	8	26	determined	determine	VERB
ejpam-2688	8	27	by	by	ADP
ejpam-2688	8	28	cross	cross	NOUN
ejpam-2688	8	29	-	-	NOUN
ejpam-2688	8	30	validation	validation	NOUN
ejpam-2688	8	31	with	with	ADP
ejpam-2688	8	32	the	the	DET
ejpam-2688	8	33	sole	sole	ADJ
ejpam-2688	8	34	objective	objective	NOUN
ejpam-2688	8	35	of	of	ADP
ejpam-2688	8	36	maximizing	maximize	VERB
ejpam-2688	8	37	classification	classification	NOUN
ejpam-2688	8	38	performance	performance	NOUN
ejpam-2688	8	39	.	.	PUNCT
ejpam-2688	9	1	secondly	secondly	ADV
ejpam-2688	9	2	,	,	PUNCT
ejpam-2688	9	3	after	after	ADP
ejpam-2688	9	4	obtaining	obtain	VERB
ejpam-2688	9	5	discriminant	discriminant	ADJ
ejpam-2688	9	6	functions	function	NOUN
ejpam-2688	9	7	or	or	CCONJ
ejpam-2688	9	8	support	support	VERB
ejpam-2688	9	9	vectors	vector	NOUN
ejpam-2688	9	10	to	to	PART
ejpam-2688	9	11	classify	classify	VERB
ejpam-2688	9	12	a	a	DET
ejpam-2688	9	13	dataset	dataset	NOUN
ejpam-2688	9	14	,	,	PUNCT
ejpam-2688	9	15	how	how	SCONJ
ejpam-2688	9	16	do	do	AUX
ejpam-2688	9	17	we	we	PRON
ejpam-2688	9	18	know	know	VERB
ejpam-2688	9	19	which	which	PRON
ejpam-2688	9	20	of	of	ADP
ejpam-2688	9	21	our	our	PRON
ejpam-2688	9	22	variables	variable	NOUN
ejpam-2688	9	23	are	be	AUX
ejpam-2688	9	24	most	most	ADV
ejpam-2688	9	25	responsible	responsible	ADJ
ejpam-2688	9	26	for	for	ADP
ejpam-2688	9	27	,	,	PUNCT
ejpam-2688	9	28	and	and	CCONJ
ejpam-2688	9	29	important	important	ADJ
ejpam-2688	9	30	to	to	ADP
ejpam-2688	9	31	,	,	PUNCT
ejpam-2688	9	32	the	the	DET
ejpam-2688	9	33	classification	classification	NOUN
ejpam-2688	9	34	?	?	PUNCT
ejpam-2688	10	1	in	in	ADP
ejpam-2688	10	2	this	this	DET
ejpam-2688	10	3	research	research	NOUN
ejpam-2688	10	4	,	,	PUNCT
ejpam-2688	10	5	we	we	PRON
ejpam-2688	10	6	develop	develop	VERB
ejpam-2688	10	7	a	a	DET
ejpam-2688	10	8	new	new	ADJ
ejpam-2688	10	9	regularized	regularize	VERB
ejpam-2688	10	10	algorithm	algorithm	NOUN
ejpam-2688	10	11	that	that	PRON
ejpam-2688	10	12	simultaneously	simultaneously	ADV
ejpam-2688	10	13	selects	select	VERB
ejpam-2688	10	14	the	the	DET
ejpam-2688	10	15	kernel	kernel	PROPN
ejpam-2688	10	16	function	function	NOUN
ejpam-2688	10	17	and	and	CCONJ
ejpam-2688	10	18	subset	subset	NOUN
ejpam-2688	10	19	of	of	ADP
ejpam-2688	10	20	original	original	ADJ
ejpam-2688	10	21	variables	variable	NOUN
ejpam-2688	10	22	.	.	PUNCT
ejpam-2688	11	1	our	our	PRON
ejpam-2688	11	2	algorithm	algorithm	NOUN
ejpam-2688	11	3	,	,	PUNCT
ejpam-2688	11	4	a	a	DET
ejpam-2688	11	5	hybrid	hybrid	NOUN
ejpam-2688	11	6	of	of	ADP
ejpam-2688	11	7	cross	cross	NOUN
ejpam-2688	11	8	-	-	NOUN
ejpam-2688	11	9	validation	validation	NOUN
ejpam-2688	11	10	and	and	CCONJ
ejpam-2688	11	11	the	the	DET
ejpam-2688	11	12	genetic	genetic	ADJ
ejpam-2688	11	13	algorithm	algorithm	NOUN
ejpam-2688	11	14	,	,	PUNCT
ejpam-2688	11	15	does	do	VERB
ejpam-2688	11	16	this	this	PRON
ejpam-2688	11	17	by	by	ADP
ejpam-2688	11	18	optimizing	optimize	VERB
ejpam-2688	11	19	a	a	DET
ejpam-2688	11	20	function	function	NOUN
ejpam-2688	11	21	that	that	PRON
ejpam-2688	11	22	rewards	reward	VERB
ejpam-2688	11	23	correct	correct	ADJ
ejpam-2688	11	24	classification	classification	NOUN
ejpam-2688	11	25	while	while	SCONJ
ejpam-2688	11	26	penalizing	penalize	VERB
ejpam-2688	11	27	model	model	NOUN
ejpam-2688	11	28	complexity	complexity	NOUN
ejpam-2688	11	29	and	and	CCONJ
ejpam-2688	11	30	misclassification	misclassification	NOUN
ejpam-2688	11	31	.	.	PUNCT
ejpam-2688	12	1	we	we	PRON
ejpam-2688	12	2	report	report	VERB
ejpam-2688	12	3	results	result	NOUN
ejpam-2688	12	4	on	on	ADP
ejpam-2688	12	5	three	three	NUM
ejpam-2688	12	6	real	real	ADJ
ejpam-2688	12	7	datasets	dataset	NOUN
ejpam-2688	12	8	,	,	PUNCT
ejpam-2688	12	9	including	include	VERB
ejpam-2688	12	10	data	datum	NOUN
ejpam-2688	12	11	from	from	ADP
ejpam-2688	12	12	a	a	DET
ejpam-2688	12	13	medical	medical	ADJ
ejpam-2688	12	14	imaging	imaging	NOUN
ejpam-2688	12	15	study	study	NOUN
ejpam-2688	12	16	.	.	PUNCT
ejpam-2688	13	1	for	for	ADP
ejpam-2688	13	2	the	the	DET
ejpam-2688	13	3	latter	latter	ADJ
ejpam-2688	13	4	,	,	PUNCT
ejpam-2688	13	5	we	we	PRON
ejpam-2688	13	6	obtained	obtain	VERB
ejpam-2688	13	7	an	an	DET
ejpam-2688	13	8	impressively	impressively	ADV
ejpam-2688	13	9	low	low	ADJ
ejpam-2688	13	10	misclassification	misclassification	NOUN
ejpam-2688	13	11	rate	rate	NOUN
ejpam-2688	13	12	of	of	ADP
ejpam-2688	13	13	0.3	0.3	NUM
ejpam-2688	13	14	%	%	NOUN
ejpam-2688	13	15	,	,	PUNCT
ejpam-2688	13	16	while	while	SCONJ
ejpam-2688	13	17	reducing	reduce	VERB
ejpam-2688	13	18	the	the	DET
ejpam-2688	13	19	number	number	NOUN
ejpam-2688	13	20	of	of	ADP
ejpam-2688	13	21	features	feature	NOUN
ejpam-2688	13	22	from	from	ADP
ejpam-2688	13	23	p	p	NOUN
ejpam-2688	13	24	=	=	NOUN
ejpam-2688	13	25	20	20	NUM
ejpam-2688	13	26	to	to	PART
ejpam-2688	13	27	p∗	p∗	VERB
ejpam-2688	13	28	=	=	SYM
ejpam-2688	13	29	6	6	NUM
ejpam-2688	13	30	.	.	X
ejpam-2688	13	31	2010	2010	NUM
ejpam-2688	13	32	mathematics	mathematic	NOUN
ejpam-2688	13	33	subject	subject	NOUN
ejpam-2688	13	34	classifications	classification	NOUN
ejpam-2688	13	35	:	:	PUNCT
ejpam-2688	13	36	62h30	62h30	NUM
ejpam-2688	13	37	,	,	PUNCT
ejpam-2688	13	38	68t10	68t10	NUM
ejpam-2688	13	39	key	key	ADJ
ejpam-2688	13	40	words	word	NOUN
ejpam-2688	13	41	and	and	CCONJ
ejpam-2688	13	42	phrases	phrase	NOUN
ejpam-2688	13	43	:	:	PUNCT
ejpam-2688	13	44	supervised	supervise	VERB
ejpam-2688	13	45	classification	classification	NOUN
ejpam-2688	13	46	,	,	PUNCT
ejpam-2688	13	47	discriminant	discriminant	ADJ
ejpam-2688	13	48	analysis	analysis	NOUN
ejpam-2688	13	49	,	,	PUNCT
ejpam-2688	13	50	support	support	NOUN
ejpam-2688	13	51	vectors	vector	NOUN
ejpam-2688	13	52	,	,	PUNCT
ejpam-2688	13	53	information	information	NOUN
ejpam-2688	13	54	criteria	criterion	NOUN
ejpam-2688	13	55	,	,	PUNCT
ejpam-2688	13	56	feature	feature	NOUN
ejpam-2688	13	57	selection	selection	NOUN
ejpam-2688	13	58	,	,	PUNCT
ejpam-2688	13	59	stochastic	stochastic	ADJ
ejpam-2688	13	60	optimization	optimization	NOUN
ejpam-2688	13	61	,	,	PUNCT
ejpam-2688	13	62	reproducing	reproduce	VERB
ejpam-2688	13	63	kernel	kernel	PROPN
ejpam-2688	13	64	hilbert	hilbert	PROPN
ejpam-2688	13	65	space	space	NOUN
ejpam-2688	13	66	,	,	PUNCT
ejpam-2688	13	67	machine	machine	NOUN
ejpam-2688	13	68	learning	learning	NOUN
ejpam-2688	13	69	∗corresponding	∗corresponde	VERB
ejpam-2688	13	70	author	author	NOUN
ejpam-2688	13	71	.	.	PUNCT
ejpam-2688	14	1	email	email	NOUN
ejpam-2688	14	2	addresses	address	NOUN
ejpam-2688	14	3	:	:	PUNCT
ejpam-2688	14	4	ahowe42@gmail.com	ahowe42@gmail.com	PROPN
ejpam-2688	14	5	(	(	PUNCT
ejpam-2688	14	6	j.	j.	PROPN
ejpam-2688	14	7	howe	howe	PROPN
ejpam-2688	14	8	)	)	PUNCT
ejpam-2688	14	9	,	,	PUNCT
ejpam-2688	14	10	bozdogan@utk.edu	bozdogan@utk.edu	PROPN
ejpam-2688	14	11	(	(	PUNCT
ejpam-2688	14	12	h.	h.	PROPN
ejpam-2688	14	13	bozdogan	bozdogan	PROPN
ejpam-2688	14	14	)	)	PUNCT
ejpam-2688	14	15	http://www.ejpam.com	http://www.ejpam.com	X
ejpam-2688	15	1	216	216	NUM
ejpam-2688	15	2	c	c	X
ejpam-2688	15	3	©	©	PROPN
ejpam-2688	15	4	2016	2016	NUM
ejpam-2688	15	5	ejpam	ejpam	VERB
ejpam-2688	15	6	all	all	DET
ejpam-2688	15	7	rights	right	NOUN
ejpam-2688	15	8	reserved	reserve	VERB
ejpam-2688	15	9	.	.	PUNCT
ejpam-2688	16	1	european	european	ADJ
ejpam-2688	16	2	journal	journal	PROPN
ejpam-2688	16	3	of	of	ADP
ejpam-2688	16	4	pure	pure	ADJ
ejpam-2688	16	5	and	and	CCONJ
ejpam-2688	16	6	applied	apply	VERB
ejpam-2688	16	7	mathematics	mathematic	NOUN
ejpam-2688	16	8	vol	vol	NOUN
ejpam-2688	16	9	.	.	PROPN
ejpam-2688	17	1	9	9	NUM
ejpam-2688	17	2	,	,	PUNCT
ejpam-2688	17	3	no	no	INTJ
ejpam-2688	17	4	.	.	NOUN
ejpam-2688	17	5	2	2	NUM
ejpam-2688	17	6	,	,	PUNCT
ejpam-2688	17	7	2016	2016	NUM
ejpam-2688	17	8	,	,	PUNCT
ejpam-2688	17	9	216	216	NUM
ejpam-2688	17	10	-	-	SYM
ejpam-2688	17	11	230	230	NUM
ejpam-2688	17	12	issn	issn	PROPN
ejpam-2688	17	13	1307	1307	NUM
ejpam-2688	17	14	-	-	SYM
ejpam-2688	17	15	5543	5543	NUM
ejpam-2688	17	16	–	–	PUNCT
ejpam-2688	17	17	www.ejpam.com	www.ejpam.com	X
ejpam-2688	17	18	j.	j.	PROPN
ejpam-2688	17	19	howe	howe	PROPN
ejpam-2688	17	20	,	,	PUNCT
ejpam-2688	17	21	h.	h.	PROPN
ejpam-2688	17	22	bozdogan	bozdogan	PROPN
ejpam-2688	17	23	/	/	SYM
ejpam-2688	17	24	eur	eur	PROPN
ejpam-2688	17	25	.	.	PUNCT
ejpam-2688	18	1	j.	j.	PROPN
ejpam-2688	18	2	pure	pure	PROPN
ejpam-2688	18	3	appl	appl	PROPN
ejpam-2688	18	4	.	.	PROPN
ejpam-2688	18	5	math	math	PROPN
ejpam-2688	18	6	,	,	PUNCT
ejpam-2688	18	7	9	9	NUM
ejpam-2688	18	8	(	(	PUNCT
ejpam-2688	18	9	2016	2016	NUM
ejpam-2688	18	10	)	)	PUNCT
ejpam-2688	18	11	,	,	PUNCT
ejpam-2688	18	12	216	216	NUM
ejpam-2688	18	13	-	-	SYM
ejpam-2688	18	14	230	230	NUM
ejpam-2688	18	15	217	217	NUM
ejpam-2688	18	16	1	1	NUM
ejpam-2688	18	17	.	.	PUNCT
ejpam-2688	19	1	introduction	introduction	NOUN
ejpam-2688	19	2	logistic	logistic	ADJ
ejpam-2688	19	3	regression	regression	NOUN
ejpam-2688	19	4	is	be	AUX
ejpam-2688	19	5	a	a	DET
ejpam-2688	19	6	well	well	ADV
ejpam-2688	19	7	-	-	PUNCT
ejpam-2688	19	8	known	know	VERB
ejpam-2688	19	9	form	form	NOUN
ejpam-2688	19	10	of	of	ADP
ejpam-2688	19	11	nonlinear	nonlinear	ADJ
ejpam-2688	19	12	regression	regression	NOUN
ejpam-2688	19	13	in	in	ADP
ejpam-2688	19	14	which	which	PRON
ejpam-2688	19	15	responses	response	NOUN
ejpam-2688	19	16	can	can	AUX
ejpam-2688	19	17	take	take	VERB
ejpam-2688	19	18	on	on	ADP
ejpam-2688	19	19	values	value	NOUN
ejpam-2688	19	20	of	of	ADP
ejpam-2688	19	21	0	0	NUM
ejpam-2688	19	22	or	or	CCONJ
ejpam-2688	19	23	1	1	NUM
ejpam-2688	19	24	(	(	PUNCT
ejpam-2688	19	25	or	or	CCONJ
ejpam-2688	19	26	any	any	DET
ejpam-2688	19	27	binary	binary	ADJ
ejpam-2688	19	28	format	format	NOUN
ejpam-2688	19	29	)	)	PUNCT
ejpam-2688	19	30	.	.	PUNCT
ejpam-2688	20	1	from	from	ADP
ejpam-2688	20	2	a	a	DET
ejpam-2688	20	3	different	different	ADJ
ejpam-2688	20	4	perspective	perspective	NOUN
ejpam-2688	20	5	,	,	PUNCT
ejpam-2688	20	6	we	we	PRON
ejpam-2688	20	7	can	can	AUX
ejpam-2688	20	8	see	see	VERB
ejpam-2688	20	9	the	the	DET
ejpam-2688	20	10	binary	binary	ADJ
ejpam-2688	20	11	responses	response	NOUN
ejpam-2688	20	12	as	as	ADP
ejpam-2688	20	13	class	class	NOUN
ejpam-2688	20	14	labels	label	NOUN
ejpam-2688	20	15	for	for	ADP
ejpam-2688	20	16	data	datum	NOUN
ejpam-2688	20	17	from	from	ADP
ejpam-2688	20	18	two	two	NUM
ejpam-2688	20	19	groups	group	NOUN
ejpam-2688	20	20	.	.	PUNCT
ejpam-2688	21	1	this	this	PRON
ejpam-2688	21	2	leads	lead	VERB
ejpam-2688	21	3	us	we	PRON
ejpam-2688	21	4	to	to	ADP
ejpam-2688	21	5	the	the	DET
ejpam-2688	21	6	concept	concept	NOUN
ejpam-2688	21	7	of	of	ADP
ejpam-2688	21	8	discriminant	discriminant	ADJ
ejpam-2688	21	9	analysis	analysis	NOUN
ejpam-2688	21	10	,	,	PUNCT
ejpam-2688	21	11	which	which	PRON
ejpam-2688	21	12	is	be	AUX
ejpam-2688	21	13	closely	closely	ADV
ejpam-2688	21	14	related	relate	VERB
ejpam-2688	21	15	to	to	ADP
ejpam-2688	21	16	logistic	logistic	ADJ
ejpam-2688	21	17	regression	regression	NOUN
ejpam-2688	21	18	.	.	PUNCT
ejpam-2688	22	1	in	in	ADP
ejpam-2688	22	2	general	general	ADJ
ejpam-2688	22	3	,	,	PUNCT
ejpam-2688	22	4	the	the	DET
ejpam-2688	22	5	goal	goal	NOUN
ejpam-2688	22	6	of	of	ADP
ejpam-2688	22	7	discriminant	discriminant	ADJ
ejpam-2688	22	8	analysis	analysis	NOUN
ejpam-2688	22	9	is	be	AUX
ejpam-2688	22	10	to	to	PART
ejpam-2688	22	11	determine	determine	VERB
ejpam-2688	22	12	data	datum	NOUN
ejpam-2688	22	13	groupings	grouping	NOUN
ejpam-2688	22	14	that	that	PRON
ejpam-2688	22	15	minimize	minimize	VERB
ejpam-2688	22	16	the	the	DET
ejpam-2688	22	17	variability	variability	NOUN
ejpam-2688	22	18	within	within	ADP
ejpam-2688	22	19	the	the	DET
ejpam-2688	22	20	groups	group	NOUN
ejpam-2688	22	21	and	and	CCONJ
ejpam-2688	22	22	maximize	maximize	VERB
ejpam-2688	22	23	the	the	DET
ejpam-2688	22	24	variability	variability	NOUN
ejpam-2688	22	25	between	between	ADP
ejpam-2688	22	26	the	the	DET
ejpam-2688	22	27	groups	group	NOUN
ejpam-2688	22	28	.	.	PUNCT
ejpam-2688	23	1	differently	differently	ADV
ejpam-2688	23	2	put	put	VERB
ejpam-2688	23	3	,	,	PUNCT
ejpam-2688	23	4	given	give	VERB
ejpam-2688	23	5	known	know	VERB
ejpam-2688	23	6	class	class	NOUN
ejpam-2688	23	7	labels	label	NOUN
ejpam-2688	23	8	for	for	ADP
ejpam-2688	23	9	the	the	DET
ejpam-2688	23	10	data	datum	NOUN
ejpam-2688	23	11	,	,	PUNCT
ejpam-2688	23	12	the	the	DET
ejpam-2688	23	13	goal	goal	NOUN
ejpam-2688	23	14	is	be	AUX
ejpam-2688	23	15	to	to	PART
ejpam-2688	23	16	minimize	minimize	VERB
ejpam-2688	23	17	the	the	DET
ejpam-2688	23	18	probability	probability	NOUN
ejpam-2688	23	19	of	of	ADP
ejpam-2688	23	20	misclassification	misclassification	NOUN
ejpam-2688	23	21	it	it	PRON
ejpam-2688	23	22	is	be	AUX
ejpam-2688	23	23	a	a	DET
ejpam-2688	23	24	method	method	NOUN
ejpam-2688	23	25	of	of	ADP
ejpam-2688	23	26	supervised	supervised	ADJ
ejpam-2688	23	27	learning	learning	NOUN
ejpam-2688	23	28	.	.	PUNCT
ejpam-2688	24	1	when	when	SCONJ
ejpam-2688	24	2	we	we	PRON
ejpam-2688	24	3	perform	perform	VERB
ejpam-2688	24	4	kernel	kernel	PROPN
ejpam-2688	24	5	discriminant	discriminant	ADJ
ejpam-2688	24	6	analysis	analysis	NOUN
ejpam-2688	24	7	(	(	PUNCT
ejpam-2688	24	8	kda	kda	NOUN
ejpam-2688	24	9	)	)	PUNCT
ejpam-2688	24	10	,	,	PUNCT
ejpam-2688	24	11	this	this	PRON
ejpam-2688	24	12	does	do	AUX
ejpam-2688	24	13	not	not	PART
ejpam-2688	24	14	change	change	VERB
ejpam-2688	24	15	.	.	PUNCT
ejpam-2688	25	1	to	to	PART
ejpam-2688	25	2	use	use	VERB
ejpam-2688	25	3	kernel	kernel	PROPN
ejpam-2688	25	4	discriminant	discriminant	PROPN
ejpam-2688	25	5	analysis	analysis	NOUN
ejpam-2688	25	6	,	,	PUNCT
ejpam-2688	25	7	one	one	PRON
ejpam-2688	25	8	merely	merely	ADV
ejpam-2688	25	9	has	have	VERB
ejpam-2688	25	10	to	to	PART
ejpam-2688	25	11	apply	apply	VERB
ejpam-2688	25	12	a	a	DET
ejpam-2688	25	13	kernel	kernel	NOUN
ejpam-2688	25	14	function	function	NOUN
ejpam-2688	25	15	to	to	ADP
ejpam-2688	25	16	the	the	DET
ejpam-2688	25	17	data	datum	NOUN
ejpam-2688	25	18	,	,	PUNCT
ejpam-2688	25	19	then	then	ADV
ejpam-2688	25	20	perform	perform	VERB
ejpam-2688	25	21	the	the	DET
ejpam-2688	25	22	usual	usual	ADJ
ejpam-2688	25	23	analysis	analysis	NOUN
ejpam-2688	25	24	.	.	PUNCT
ejpam-2688	26	1	this	this	PRON
ejpam-2688	26	2	does	do	AUX
ejpam-2688	26	3	,	,	PUNCT
ejpam-2688	26	4	however	however	ADV
ejpam-2688	26	5	,	,	PUNCT
ejpam-2688	26	6	present	present	ADJ
ejpam-2688	26	7	two	two	NUM
ejpam-2688	26	8	issues	issue	NOUN
ejpam-2688	26	9	which	which	PRON
ejpam-2688	26	10	we	we	PRON
ejpam-2688	26	11	address	address	VERB
ejpam-2688	26	12	in	in	ADP
ejpam-2688	26	13	this	this	DET
ejpam-2688	26	14	research	research	NOUN
ejpam-2688	26	15	.	.	PUNCT
ejpam-2688	27	1	•	•	ADV
ejpam-2688	27	2	there	there	PRON
ejpam-2688	27	3	are	be	VERB
ejpam-2688	27	4	many	many	ADJ
ejpam-2688	27	5	possible	possible	ADJ
ejpam-2688	27	6	kernel	kernel	NOUN
ejpam-2688	27	7	functions	function	NOUN
ejpam-2688	27	8	that	that	PRON
ejpam-2688	27	9	can	can	AUX
ejpam-2688	27	10	be	be	AUX
ejpam-2688	27	11	applied	apply	VERB
ejpam-2688	27	12	to	to	PART
ejpam-2688	27	13	perform	perform	VERB
ejpam-2688	27	14	the	the	DET
ejpam-2688	27	15	nonlinear	nonlinear	ADJ
ejpam-2688	27	16	map	map	NOUN
ejpam-2688	27	17	into	into	ADP
ejpam-2688	27	18	higher	high	ADJ
ejpam-2688	27	19	-	-	PUNCT
ejpam-2688	27	20	dimensional	dimensional	ADJ
ejpam-2688	27	21	feature	feature	NOUN
ejpam-2688	27	22	space	space	NOUN
ejpam-2688	27	23	.	.	PUNCT
ejpam-2688	28	1	the	the	DET
ejpam-2688	28	2	choice	choice	NOUN
ejpam-2688	28	3	of	of	ADP
ejpam-2688	28	4	the	the	DET
ejpam-2688	28	5	kernel	kernel	PROPN
ejpam-2688	28	6	function	function	NOUN
ejpam-2688	28	7	can	can	AUX
ejpam-2688	28	8	have	have	VERB
ejpam-2688	28	9	a	a	DET
ejpam-2688	28	10	substantial	substantial	ADJ
ejpam-2688	28	11	impact	impact	NOUN
ejpam-2688	28	12	on	on	ADP
ejpam-2688	28	13	the	the	DET
ejpam-2688	28	14	analytical	analytical	ADJ
ejpam-2688	28	15	results	result	NOUN
ejpam-2688	28	16	.	.	PUNCT
ejpam-2688	29	1	for	for	ADP
ejpam-2688	29	2	example	example	NOUN
ejpam-2688	29	3	,	,	PUNCT
ejpam-2688	29	4	use	use	NOUN
ejpam-2688	29	5	of	of	ADP
ejpam-2688	29	6	a	a	DET
ejpam-2688	29	7	linear	linear	ADJ
ejpam-2688	29	8	kernel	kernel	NOUN
ejpam-2688	29	9	on	on	ADP
ejpam-2688	29	10	data	datum	NOUN
ejpam-2688	29	11	that	that	PRON
ejpam-2688	29	12	is	be	AUX
ejpam-2688	29	13	inherently	inherently	ADV
ejpam-2688	29	14	nonlinear	nonlinear	ADJ
ejpam-2688	29	15	will	will	AUX
ejpam-2688	29	16	likely	likely	ADV
ejpam-2688	29	17	inflate	inflate	VERB
ejpam-2688	29	18	the	the	DET
ejpam-2688	29	19	classification	classification	NOUN
ejpam-2688	29	20	error	error	NOUN
ejpam-2688	29	21	.	.	PUNCT
ejpam-2688	30	1	for	for	ADP
ejpam-2688	30	2	univariate	univariate	ADJ
ejpam-2688	30	3	or	or	CCONJ
ejpam-2688	30	4	bivariate	bivariate	ADJ
ejpam-2688	30	5	data	datum	NOUN
ejpam-2688	30	6	,	,	PUNCT
ejpam-2688	30	7	it	it	PRON
ejpam-2688	30	8	may	may	AUX
ejpam-2688	30	9	be	be	AUX
ejpam-2688	30	10	easy	easy	ADJ
ejpam-2688	30	11	to	to	PART
ejpam-2688	30	12	determine	determine	VERB
ejpam-2688	30	13	nonlinearity	nonlinearity	NOUN
ejpam-2688	30	14	,	,	PUNCT
ejpam-2688	30	15	but	but	CCONJ
ejpam-2688	30	16	what	what	PRON
ejpam-2688	30	17	of	of	ADP
ejpam-2688	30	18	ten	ten	NUM
ejpam-2688	30	19	variables	variable	NOUN
ejpam-2688	30	20	?	?	PUNCT
ejpam-2688	31	1	in	in	ADP
ejpam-2688	31	2	most	most	ADV
ejpam-2688	31	3	relevant	relevant	ADJ
ejpam-2688	31	4	research	research	NOUN
ejpam-2688	31	5	with	with	ADP
ejpam-2688	31	6	kernel	kernel	PROPN
ejpam-2688	31	7	methods	method	NOUN
ejpam-2688	31	8	,	,	PUNCT
ejpam-2688	31	9	the	the	DET
ejpam-2688	31	10	kernel	kernel	NOUN
ejpam-2688	31	11	function	function	NOUN
ejpam-2688	31	12	is	be	AUX
ejpam-2688	31	13	either	either	CCONJ
ejpam-2688	31	14	selected	select	VERB
ejpam-2688	31	15	a	a	DET
ejpam-2688	31	16	priori	priori	NOUN
ejpam-2688	31	17	or	or	CCONJ
ejpam-2688	31	18	using	use	VERB
ejpam-2688	31	19	cross	cross	NOUN
ejpam-2688	31	20	-	-	NOUN
ejpam-2688	31	21	validation	validation	NOUN
ejpam-2688	31	22	to	to	PART
ejpam-2688	31	23	minimize	minimize	VERB
ejpam-2688	31	24	the	the	DET
ejpam-2688	31	25	testing	testing	NOUN
ejpam-2688	31	26	classification	classification	NOUN
ejpam-2688	31	27	error	error	NOUN
ejpam-2688	31	28	.	.	PUNCT
ejpam-2688	32	1	how	how	SCONJ
ejpam-2688	32	2	do	do	AUX
ejpam-2688	32	3	we	we	PRON
ejpam-2688	32	4	choose	choose	VERB
ejpam-2688	32	5	the	the	DET
ejpam-2688	32	6	"	"	PUNCT
ejpam-2688	32	7	best	good	ADJ
ejpam-2688	32	8	"	"	PUNCT
ejpam-2688	32	9	kernel	kernel	NOUN
ejpam-2688	32	10	function	function	VERB
ejpam-2688	32	11	consistent	consistent	ADJ
ejpam-2688	32	12	with	with	ADP
ejpam-2688	32	13	the	the	DET
ejpam-2688	32	14	principal	principal	NOUN
ejpam-2688	32	15	of	of	ADP
ejpam-2688	32	16	occam	occam	PROPN
ejpam-2688	32	17	’s	’s	PART
ejpam-2688	32	18	razor	razor	NOUN
ejpam-2688	32	19	?	?	PUNCT
ejpam-2688	33	1	•	•	NUM
ejpam-2688	33	2	for	for	ADP
ejpam-2688	33	3	any	any	DET
ejpam-2688	33	4	classification	classification	NOUN
ejpam-2688	33	5	method	method	NOUN
ejpam-2688	33	6	,	,	PUNCT
ejpam-2688	33	7	there	there	PRON
ejpam-2688	33	8	is	be	VERB
ejpam-2688	33	9	often	often	ADV
ejpam-2688	33	10	value	value	NOUN
ejpam-2688	33	11	in	in	ADP
ejpam-2688	33	12	knowing	know	VERB
ejpam-2688	33	13	which	which	PRON
ejpam-2688	33	14	variables	variable	NOUN
ejpam-2688	33	15	contribute	contribute	VERB
ejpam-2688	33	16	most	most	ADJ
ejpam-2688	33	17	to	to	ADP
ejpam-2688	33	18	the	the	DET
ejpam-2688	33	19	separation	separation	NOUN
ejpam-2688	33	20	of	of	ADP
ejpam-2688	33	21	the	the	DET
ejpam-2688	33	22	classes	class	NOUN
ejpam-2688	33	23	.	.	PUNCT
ejpam-2688	34	1	of	of	ADP
ejpam-2688	34	2	course	course	ADV
ejpam-2688	34	3	,	,	PUNCT
ejpam-2688	34	4	this	this	PRON
ejpam-2688	34	5	is	be	AUX
ejpam-2688	34	6	generically	generically	ADV
ejpam-2688	34	7	true	true	ADJ
ejpam-2688	34	8	about	about	ADP
ejpam-2688	34	9	all	all	DET
ejpam-2688	34	10	statistical	statistical	ADJ
ejpam-2688	34	11	data	datum	NOUN
ejpam-2688	34	12	mining	mining	NOUN
ejpam-2688	34	13	/	/	SYM
ejpam-2688	34	14	machine	machine	NOUN
ejpam-2688	34	15	learning	learn	VERB
ejpam-2688	34	16	techniques	technique	NOUN
ejpam-2688	34	17	.	.	PUNCT
ejpam-2688	35	1	however	however	ADV
ejpam-2688	35	2	,	,	PUNCT
ejpam-2688	35	3	with	with	ADP
ejpam-2688	35	4	kernel	kernel	PROPN
ejpam-2688	35	5	methods	method	NOUN
ejpam-2688	35	6	,	,	PUNCT
ejpam-2688	35	7	after	after	SCONJ
ejpam-2688	35	8	we	we	PRON
ejpam-2688	35	9	apply	apply	VERB
ejpam-2688	35	10	the	the	DET
ejpam-2688	35	11	kernel	kernel	PROPN
ejpam-2688	35	12	function	function	NOUN
ejpam-2688	35	13	,	,	PUNCT
ejpam-2688	35	14	it	it	PRON
ejpam-2688	35	15	is	be	AUX
ejpam-2688	35	16	impossible	impossible	ADJ
ejpam-2688	35	17	to	to	PART
ejpam-2688	35	18	perform	perform	VERB
ejpam-2688	35	19	any	any	DET
ejpam-2688	35	20	meaningful	meaningful	ADJ
ejpam-2688	35	21	feature	feature	NOUN
ejpam-2688	35	22	selection	selection	NOUN
ejpam-2688	35	23	analysis	analysis	NOUN
ejpam-2688	35	24	.	.	PUNCT
ejpam-2688	36	1	perhaps	perhaps	ADV
ejpam-2688	36	2	we	we	PRON
ejpam-2688	36	3	are	be	AUX
ejpam-2688	36	4	making	make	VERB
ejpam-2688	36	5	ten	ten	NUM
ejpam-2688	36	6	hopefully	hopefully	ADV
ejpam-2688	36	7	predictive	predictive	ADJ
ejpam-2688	36	8	,	,	PUNCT
ejpam-2688	36	9	and	and	CCONJ
ejpam-2688	36	10	costly	costly	ADJ
ejpam-2688	36	11	,	,	PUNCT
ejpam-2688	36	12	measurements	measurement	NOUN
ejpam-2688	36	13	on	on	ADP
ejpam-2688	36	14	a	a	DET
ejpam-2688	36	15	process	process	NOUN
ejpam-2688	36	16	but	but	CCONJ
ejpam-2688	36	17	we	we	PRON
ejpam-2688	36	18	can	can	AUX
ejpam-2688	36	19	get	get	VERB
ejpam-2688	36	20	very	very	ADV
ejpam-2688	36	21	low	low	ADJ
ejpam-2688	36	22	classification	classification	NOUN
ejpam-2688	36	23	errors	error	NOUN
ejpam-2688	36	24	only	only	ADV
ejpam-2688	36	25	using	use	VERB
ejpam-2688	36	26	three	three	NUM
ejpam-2688	36	27	of	of	ADP
ejpam-2688	36	28	them	they	PRON
ejpam-2688	36	29	?	?	PUNCT
ejpam-2688	37	1	why	why	SCONJ
ejpam-2688	37	2	take	take	VERB
ejpam-2688	37	3	unnecessary	unnecessary	ADJ
ejpam-2688	37	4	measurements	measurement	NOUN
ejpam-2688	37	5	for	for	ADP
ejpam-2688	37	6	a	a	DET
ejpam-2688	37	7	model	model	NOUN
ejpam-2688	37	8	that	that	PRON
ejpam-2688	37	9	is	be	AUX
ejpam-2688	37	10	overly	overly	ADV
ejpam-2688	37	11	complex	complex	ADJ
ejpam-2688	37	12	when	when	SCONJ
ejpam-2688	37	13	we	we	PRON
ejpam-2688	37	14	can	can	AUX
ejpam-2688	37	15	have	have	VERB
ejpam-2688	37	16	a	a	DET
ejpam-2688	37	17	model	model	NOUN
ejpam-2688	37	18	that	that	PRON
ejpam-2688	37	19	is	be	AUX
ejpam-2688	37	20	both	both	CCONJ
ejpam-2688	37	21	accurate	accurate	ADJ
ejpam-2688	37	22	and	and	CCONJ
ejpam-2688	37	23	parsimonious	parsimonious	ADJ
ejpam-2688	37	24	?	?	PUNCT
ejpam-2688	38	1	how	how	SCONJ
ejpam-2688	38	2	do	do	AUX
ejpam-2688	38	3	we	we	PRON
ejpam-2688	38	4	determine	determine	VERB
ejpam-2688	38	5	which	which	PRON
ejpam-2688	38	6	variables	variable	NOUN
ejpam-2688	38	7	are	be	AUX
ejpam-2688	38	8	contributing	contribute	VERB
ejpam-2688	38	9	the	the	DET
ejpam-2688	38	10	most	most	ADJ
ejpam-2688	38	11	to	to	ADP
ejpam-2688	38	12	our	our	PRON
ejpam-2688	38	13	discriminant	discriminant	ADJ
ejpam-2688	38	14	functions	function	NOUN
ejpam-2688	38	15	in	in	ADP
ejpam-2688	38	16	the	the	DET
ejpam-2688	38	17	kernel	kernel	PROPN
ejpam-2688	38	18	space	space	NOUN
ejpam-2688	38	19	?	?	PUNCT
ejpam-2688	39	1	here	here	ADV
ejpam-2688	39	2	we	we	PRON
ejpam-2688	39	3	propose	propose	VERB
ejpam-2688	39	4	a	a	DET
ejpam-2688	39	5	hybrid	hybrid	ADJ
ejpam-2688	39	6	optimization	optimization	NOUN
ejpam-2688	39	7	algorithm	algorithm	NOUN
ejpam-2688	39	8	to	to	PART
ejpam-2688	39	9	simultaneously	simultaneously	ADV
ejpam-2688	39	10	perform	perform	VERB
ejpam-2688	39	11	kernel	kernel	NOUN
ejpam-2688	39	12	selection	selection	NOUN
ejpam-2688	39	13	and	and	CCONJ
ejpam-2688	39	14	feature	feature	NOUN
ejpam-2688	39	15	selection	selection	NOUN
ejpam-2688	39	16	.	.	PUNCT
ejpam-2688	40	1	our	our	PRON
ejpam-2688	40	2	algorithm	algorithm	NOUN
ejpam-2688	40	3	uses	use	VERB
ejpam-2688	40	4	a	a	DET
ejpam-2688	40	5	combination	combination	NOUN
ejpam-2688	40	6	of	of	ADP
ejpam-2688	40	7	cross	cross	NOUN
ejpam-2688	40	8	-	-	NOUN
ejpam-2688	40	9	validation	validation	NOUN
ejpam-2688	40	10	with	with	ADP
ejpam-2688	40	11	the	the	DET
ejpam-2688	40	12	genetic	genetic	ADJ
ejpam-2688	40	13	algorithm	algorithm	NOUN
ejpam-2688	40	14	.	.	PUNCT
ejpam-2688	41	1	the	the	DET
ejpam-2688	41	2	optimization	optimization	NOUN
ejpam-2688	41	3	objective	objective	NOUN
ejpam-2688	41	4	is	be	AUX
ejpam-2688	41	5	a	a	DET
ejpam-2688	41	6	special	special	ADJ
ejpam-2688	41	7	form	form	NOUN
ejpam-2688	41	8	of	of	ADP
ejpam-2688	41	9	bozdogan	bozdogan	PROPN
ejpam-2688	41	10	’s	’s	PART
ejpam-2688	41	11	icom	icom	PROPN
ejpam-2688	41	12	p	p	PROPN
ejpam-2688	42	1	[	[	X
ejpam-2688	42	2	12	12	NUM
ejpam-2688	42	3	]	]	PUNCT
ejpam-2688	42	4	developed	develop	VERB
ejpam-2688	42	5	for	for	ADP
ejpam-2688	42	6	sparse	sparse	ADJ
ejpam-2688	42	7	classification	classification	NOUN
ejpam-2688	42	8	methods	method	NOUN
ejpam-2688	42	9	such	such	ADJ
ejpam-2688	42	10	as	as	ADP
ejpam-2688	42	11	kda	kda	NOUN
ejpam-2688	42	12	.	.	PUNCT
ejpam-2688	43	1	following	follow	VERB
ejpam-2688	43	2	this	this	DET
ejpam-2688	43	3	introduction	introduction	NOUN
ejpam-2688	43	4	,	,	PUNCT
ejpam-2688	43	5	we	we	PRON
ejpam-2688	43	6	provide	provide	VERB
ejpam-2688	43	7	background	background	NOUN
ejpam-2688	43	8	details	detail	NOUN
ejpam-2688	43	9	of	of	ADP
ejpam-2688	43	10	regularized	regularize	VERB
ejpam-2688	43	11	kda	kda	NOUN
ejpam-2688	43	12	with	with	ADP
ejpam-2688	43	13	support	support	NOUN
ejpam-2688	43	14	vector	vector	NOUN
ejpam-2688	43	15	machines	machine	NOUN
ejpam-2688	43	16	.	.	PUNCT
ejpam-2688	44	1	section	section	NOUN
ejpam-2688	44	2	3	3	NUM
ejpam-2688	44	3	describes	describe	VERB
ejpam-2688	44	4	our	our	PRON
ejpam-2688	44	5	hybrid	hybrid	ADJ
ejpam-2688	44	6	algorithm	algorithm	NOUN
ejpam-2688	44	7	,	,	PUNCT
ejpam-2688	44	8	and	and	CCONJ
ejpam-2688	44	9	numerical	numerical	ADJ
ejpam-2688	44	10	results	result	NOUN
ejpam-2688	44	11	on	on	ADP
ejpam-2688	44	12	real	real	ADJ
ejpam-2688	44	13	datasets	dataset	NOUN
ejpam-2688	44	14	are	be	AUX
ejpam-2688	44	15	shown	show	VERB
ejpam-2688	44	16	in	in	ADP
ejpam-2688	44	17	section	section	NOUN
ejpam-2688	44	18	4	4	NUM
ejpam-2688	44	19	.	.	PUNCT
ejpam-2688	45	1	we	we	PRON
ejpam-2688	45	2	finish	finish	VERB
ejpam-2688	45	3	with	with	ADP
ejpam-2688	45	4	some	some	DET
ejpam-2688	45	5	final	final	ADJ
ejpam-2688	45	6	thoughts	thought	NOUN
ejpam-2688	45	7	in	in	ADP
ejpam-2688	45	8	section	section	NOUN
ejpam-2688	45	9	5	5	NUM
ejpam-2688	45	10	.	.	PUNCT
ejpam-2688	46	1	j.	j.	PROPN
ejpam-2688	46	2	howe	howe	PROPN
ejpam-2688	46	3	,	,	PUNCT
ejpam-2688	46	4	h.	h.	PROPN
ejpam-2688	46	5	bozdogan	bozdogan	PROPN
ejpam-2688	46	6	/	/	SYM
ejpam-2688	46	7	eur	eur	PROPN
ejpam-2688	46	8	.	.	PUNCT
ejpam-2688	47	1	j.	j.	PROPN
ejpam-2688	47	2	pure	pure	PROPN
ejpam-2688	47	3	appl	appl	PROPN
ejpam-2688	47	4	.	.	PROPN
ejpam-2688	47	5	math	math	PROPN
ejpam-2688	47	6	,	,	PUNCT
ejpam-2688	47	7	9	9	NUM
ejpam-2688	47	8	(	(	PUNCT
ejpam-2688	47	9	2016	2016	NUM
ejpam-2688	47	10	)	)	PUNCT
ejpam-2688	47	11	,	,	PUNCT
ejpam-2688	47	12	216	216	NUM
ejpam-2688	47	13	-	-	SYM
ejpam-2688	47	14	230	230	NUM
ejpam-2688	47	15	218	218	NUM
ejpam-2688	47	16	2	2	NUM
ejpam-2688	47	17	.	.	PUNCT
ejpam-2688	47	18	regularized	regularize	VERB
ejpam-2688	47	19	kernel	kernel	NOUN
ejpam-2688	47	20	discriminant	discriminant	ADJ
ejpam-2688	47	21	analysis	analysis	NOUN
ejpam-2688	47	22	with	with	ADP
ejpam-2688	47	23	support	support	NOUN
ejpam-2688	47	24	vectors	vector	NOUN
ejpam-2688	47	25	2.1	2.1	NUM
ejpam-2688	47	26	.	.	PUNCT
ejpam-2688	48	1	kernels	kernel	NOUN
ejpam-2688	48	2	reproducing	reproduce	VERB
ejpam-2688	48	3	kernel	kernel	PROPN
ejpam-2688	48	4	hilbert	hilbert	PROPN
ejpam-2688	48	5	spaces	space	NOUN
ejpam-2688	48	6	were	be	AUX
ejpam-2688	48	7	initially	initially	ADV
ejpam-2688	48	8	developed	develop	VERB
ejpam-2688	48	9	by	by	ADP
ejpam-2688	48	10	the	the	DET
ejpam-2688	48	11	mathematician	mathematician	ADJ
ejpam-2688	48	12	aronszajn	aronszajn	NOUN
ejpam-2688	49	1	[	[	X
ejpam-2688	49	2	2	2	NUM
ejpam-2688	49	3	]	]	PUNCT
ejpam-2688	49	4	.	.	PUNCT
ejpam-2688	50	1	assuming	assume	VERB
ejpam-2688	50	2	they	they	PRON
ejpam-2688	50	3	meet	meet	VERB
ejpam-2688	50	4	mercer	mercer	PROPN
ejpam-2688	50	5	’s	’s	PART
ejpam-2688	50	6	conditions	condition	NOUN
ejpam-2688	50	7	,	,	PUNCT
ejpam-2688	50	8	kernel	kernel	PROPN
ejpam-2688	50	9	functions	function	NOUN
ejpam-2688	50	10	correspond	correspond	VERB
ejpam-2688	50	11	to	to	ADP
ejpam-2688	50	12	a	a	DET
ejpam-2688	50	13	nonlinear	nonlinear	ADJ
ejpam-2688	50	14	map	map	NOUN
ejpam-2688	50	15	into	into	ADP
ejpam-2688	50	16	a	a	DET
ejpam-2688	50	17	higher	high	ADJ
ejpam-2688	50	18	dimensional	dimensional	ADJ
ejpam-2688	50	19	feature	feature	NOUN
ejpam-2688	50	20	space	space	NOUN
ejpam-2688	50	21	f	f	NOUN
ejpam-2688	50	22	and	and	CCONJ
ejpam-2688	50	23	then	then	ADV
ejpam-2688	50	24	taking	take	VERB
ejpam-2688	50	25	the	the	DET
ejpam-2688	50	26	dot	dot	NOUN
ejpam-2688	50	27	product	product	NOUN
ejpam-2688	50	28	in	in	ADP
ejpam-2688	50	29	this	this	DET
ejpam-2688	50	30	space	space	NOUN
ejpam-2688	50	31	.	.	PUNCT
ejpam-2688	51	1	as	as	ADP
ejpam-2688	51	2	an	an	DET
ejpam-2688	51	3	example	example	NOUN
ejpam-2688	51	4	,	,	PUNCT
ejpam-2688	51	5	consider	consider	VERB
ejpam-2688	51	6	the	the	DET
ejpam-2688	51	7	map	map	NOUN
ejpam-2688	51	8	φ	φ	X
ejpam-2688	51	9	:	:	PUNCT
ejpam-2688	51	10	r2→	r2→	NOUN
ejpam-2688	51	11	r3	r3	PROPN
ejpam-2688	51	12	,	,	PUNCT
ejpam-2688	51	13	defined	define	VERB
ejpam-2688	51	14	as	as	ADP
ejpam-2688	51	15	φ	φ	PROPN
ejpam-2688	51	16	�	�	PROPN
ejpam-2688	51	17	�	�	PROPN
ejpam-2688	51	18	x1	x1	PROPN
ejpam-2688	51	19	,	,	PUNCT
ejpam-2688	51	20	x2	x2	PROPN
ejpam-2688	51	21	�	�	PROPN
ejpam-2688	51	22	′	′	NUM
ejpam-2688	51	23	�	�	PROPN
ejpam-2688	51	24	=	=	SYM
ejpam-2688	51	25	�	�	PROPN
ejpam-2688	51	26	x2	x2	PROPN
ejpam-2688	51	27	2	2	NUM
ejpam-2688	51	28	,	,	PUNCT
ejpam-2688	51	29	p	p	NOUN
ejpam-2688	51	30	2x1	2x1	NUM
ejpam-2688	51	31	x2	x2	NOUN
ejpam-2688	51	32	,	,	PUNCT
ejpam-2688	51	33	x2	x2	PROPN
ejpam-2688	51	34	2	2	NUM
ejpam-2688	51	35	�	�	NOUN
ejpam-2688	51	36	′	′	NUM
ejpam-2688	51	37	.	.	PUNCT
ejpam-2688	52	1	for	for	ADP
ejpam-2688	52	2	two	two	NUM
ejpam-2688	52	3	vectors	vector	NOUN
ejpam-2688	52	4	x	x	PUNCT
ejpam-2688	52	5	i	i	PRON
ejpam-2688	52	6	and	and	CCONJ
ejpam-2688	52	7	x	x	PROPN
ejpam-2688	52	8	j	j	PROPN
ejpam-2688	52	9	,	,	PUNCT
ejpam-2688	52	10	we	we	PRON
ejpam-2688	52	11	have	have	VERB
ejpam-2688	52	12	φ	φ	PROPN
ejpam-2688	52	13	�	�	PROPN
ejpam-2688	53	1	x	x	PROPN
ejpam-2688	54	1	i	i	PRON
ejpam-2688	54	2	�	�	PROPN
ejpam-2688	54	3	′	′	NUM
ejpam-2688	54	4	φ	φ	PROPN
ejpam-2688	54	5	�	�	PROPN
ejpam-2688	54	6	x	x	PROPN
ejpam-2688	54	7	j	j	PROPN
ejpam-2688	54	8	�	�	PROPN
ejpam-2688	54	9	=	=	SYM
ejpam-2688	54	10	�	�	PROPN
ejpam-2688	54	11	x2	x2	PROPN
ejpam-2688	54	12	i2	i2	PROPN
ejpam-2688	54	13	,	,	PUNCT
ejpam-2688	54	14	p	p	X
ejpam-2688	54	15	2x	2x	NUM
ejpam-2688	54	16	i1	i1	PROPN
ejpam-2688	54	17	x	x	PROPN
ejpam-2688	54	18	i2	i2	PROPN
ejpam-2688	54	19	,	,	PUNCT
ejpam-2688	54	20	x2	x2	PROPN
ejpam-2688	54	21	i2	i2	PROPN
ejpam-2688	54	22	�	�	PROPN
ejpam-2688	54	23	�	�	PROPN
ejpam-2688	54	24	x2	x2	PROPN
ejpam-2688	54	25	j2	j2	PROPN
ejpam-2688	54	26	,	,	PUNCT
ejpam-2688	54	27	p	p	X
ejpam-2688	54	28	2x	2x	NUM
ejpam-2688	54	29	j1	j1	PROPN
ejpam-2688	54	30	x	x	SYM
ejpam-2688	54	31	j2	j2	PROPN
ejpam-2688	54	32	,	,	PUNCT
ejpam-2688	54	33	x2	x2	PROPN
ejpam-2688	54	34	j2	j2	PROPN
ejpam-2688	54	35	�	�	PROPN
ejpam-2688	54	36	′	′	VERB
ejpam-2688	54	37	=	=	SYM
ejpam-2688	54	38	�	�	PROPN
ejpam-2688	54	39	x2	x2	PROPN
ejpam-2688	54	40	i2	i2	PROPN
ejpam-2688	54	41	x2	x2	PROPN
ejpam-2688	54	42	j2	j2	PROPN
ejpam-2688	54	43	,	,	PUNCT
ejpam-2688	54	44	2x	2x	PROPN
ejpam-2688	54	45	i1	i1	PROPN
ejpam-2688	54	46	x	x	PROPN
ejpam-2688	54	47	i2	i2	PROPN
ejpam-2688	54	48	x	x	PROPN
ejpam-2688	54	49	j1	j1	PROPN
ejpam-2688	54	50	x	x	SYM
ejpam-2688	54	51	j2	j2	PROPN
ejpam-2688	54	52	,	,	PUNCT
ejpam-2688	54	53	x2	x2	PROPN
ejpam-2688	54	54	i2	i2	PROPN
ejpam-2688	54	55	x2	x2	PROPN
ejpam-2688	54	56	j2	j2	PROPN
ejpam-2688	54	57	�	�	PROPN
ejpam-2688	54	58	=	=	SYM
ejpam-2688	54	59	�	�	PROPN
ejpam-2688	54	60	x	x	SYM
ejpam-2688	54	61	′i	′i	NOUN
ejpam-2688	54	62	x	x	SYM
ejpam-2688	54	63	j	j	PROPN
ejpam-2688	54	64	�	�	PROPN
ejpam-2688	54	65	2	2	NUM
ejpam-2688	54	66	this	this	DET
ejpam-2688	54	67	last	last	ADJ
ejpam-2688	54	68	equality	equality	NOUN
ejpam-2688	54	69	is	be	AUX
ejpam-2688	54	70	called	call	VERB
ejpam-2688	54	71	the	the	DET
ejpam-2688	54	72	quadratic	quadratic	ADJ
ejpam-2688	54	73	kernel	kernel	NOUN
ejpam-2688	54	74	(	(	PUNCT
ejpam-2688	54	75	with	with	ADP
ejpam-2688	54	76	no	no	DET
ejpam-2688	54	77	intercept	intercept	NOUN
ejpam-2688	54	78	)	)	PUNCT
ejpam-2688	54	79	,	,	PUNCT
ejpam-2688	54	80	which	which	PRON
ejpam-2688	54	81	we	we	PRON
ejpam-2688	54	82	may	may	AUX
ejpam-2688	54	83	denote	denote	VERB
ejpam-2688	54	84	as	as	ADP
ejpam-2688	54	85	k	k	PROPN
ejpam-2688	54	86	�	�	PROPN
ejpam-2688	54	87	x	x	PROPN
ejpam-2688	55	1	i	i	INTJ
ejpam-2688	55	2	,	,	PUNCT
ejpam-2688	55	3	x	x	PROPN
ejpam-2688	55	4	j	j	PROPN
ejpam-2688	55	5	�	�	PROPN
ejpam-2688	55	6	;	;	PUNCT
ejpam-2688	55	7	by	by	ADP
ejpam-2688	55	8	computing	compute	VERB
ejpam-2688	55	9	the	the	DET
ejpam-2688	55	10	quadratic	quadratic	ADJ
ejpam-2688	55	11	kernel	kernel	NOUN
ejpam-2688	55	12	function	function	NOUN
ejpam-2688	55	13	,	,	PUNCT
ejpam-2688	55	14	we	we	PRON
ejpam-2688	55	15	avoid	avoid	VERB
ejpam-2688	55	16	performing	perform	VERB
ejpam-2688	55	17	the	the	DET
ejpam-2688	55	18	map	map	NOUN
ejpam-2688	55	19	.	.	PUNCT
ejpam-2688	56	1	this	this	PRON
ejpam-2688	56	2	is	be	AUX
ejpam-2688	56	3	called	call	VERB
ejpam-2688	56	4	the	the	DET
ejpam-2688	56	5	kernel	kernel	NOUN
ejpam-2688	56	6	trick	trick	NOUN
ejpam-2688	56	7	.	.	PUNCT
ejpam-2688	57	1	for	for	ADP
ejpam-2688	57	2	a	a	DET
ejpam-2688	57	3	dataset	dataset	NOUN
ejpam-2688	57	4	x	x	PUNCT
ejpam-2688	57	5	with	with	ADP
ejpam-2688	57	6	n	n	CCONJ
ejpam-2688	57	7	rows	row	NOUN
ejpam-2688	57	8	and	and	CCONJ
ejpam-2688	57	9	p	p	NOUN
ejpam-2688	57	10	variables	variable	NOUN
ejpam-2688	57	11	,	,	PUNCT
ejpam-2688	57	12	the	the	DET
ejpam-2688	57	13	data	data	NOUN
ejpam-2688	57	14	is	be	AUX
ejpam-2688	57	15	translated	translate	VERB
ejpam-2688	57	16	into	into	ADP
ejpam-2688	57	17	a	a	DET
ejpam-2688	57	18	square	square	ADJ
ejpam-2688	57	19	matrix	matrix	NOUN
ejpam-2688	57	20	of	of	ADP
ejpam-2688	57	21	size	size	NOUN
ejpam-2688	57	22	n	n	CCONJ
ejpam-2688	57	23	in	in	ADP
ejpam-2688	57	24	the	the	DET
ejpam-2688	57	25	feature	feature	NOUN
ejpam-2688	57	26	space	space	NOUN
ejpam-2688	57	27	,	,	PUNCT
ejpam-2688	57	28	in	in	ADP
ejpam-2688	57	29	which	which	PRON
ejpam-2688	57	30	every	every	DET
ejpam-2688	57	31	possible	possible	ADJ
ejpam-2688	57	32	pair	pair	NOUN
ejpam-2688	57	33	of	of	ADP
ejpam-2688	57	34	points	point	NOUN
ejpam-2688	57	35	is	be	AUX
ejpam-2688	57	36	evaluated	evaluate	VERB
ejpam-2688	57	37	.	.	PUNCT
ejpam-2688	58	1	note	note	VERB
ejpam-2688	58	2	that	that	SCONJ
ejpam-2688	58	3	this	this	DET
ejpam-2688	58	4	translation	translation	NOUN
ejpam-2688	58	5	is	be	AUX
ejpam-2688	58	6	neither	neither	CCONJ
ejpam-2688	58	7	one	one	NUM
ejpam-2688	58	8	-	-	PUNCT
ejpam-2688	58	9	to	to	ADP
ejpam-2688	58	10	-	-	PUNCT
ejpam-2688	58	11	one	one	NUM
ejpam-2688	58	12	,	,	PUNCT
ejpam-2688	58	13	nor	nor	CCONJ
ejpam-2688	58	14	onto	onto	ADP
ejpam-2688	58	15	application	application	NOUN
ejpam-2688	58	16	of	of	ADP
ejpam-2688	58	17	a	a	DET
ejpam-2688	58	18	kernel	kernel	NOUN
ejpam-2688	58	19	function	function	NOUN
ejpam-2688	58	20	is	be	AUX
ejpam-2688	58	21	an	an	DET
ejpam-2688	58	22	non	non	ADJ
ejpam-2688	58	23	-	-	ADJ
ejpam-2688	58	24	invertible	invertible	ADJ
ejpam-2688	58	25	process	process	NOUN
ejpam-2688	58	26	.	.	PUNCT
ejpam-2688	59	1	once	once	SCONJ
ejpam-2688	59	2	the	the	DET
ejpam-2688	59	3	data	data	NOUN
ejpam-2688	59	4	has	have	AUX
ejpam-2688	59	5	been	be	AUX
ejpam-2688	59	6	classified	classify	VERB
ejpam-2688	59	7	in	in	ADP
ejpam-2688	59	8	the	the	DET
ejpam-2688	59	9	feature	feature	NOUN
ejpam-2688	59	10	space	space	NOUN
ejpam-2688	59	11	,	,	PUNCT
ejpam-2688	59	12	we	we	PRON
ejpam-2688	59	13	have	have	VERB
ejpam-2688	59	14	no	no	DET
ejpam-2688	59	15	way	way	NOUN
ejpam-2688	59	16	to	to	PART
ejpam-2688	59	17	go	go	VERB
ejpam-2688	59	18	back	back	ADV
ejpam-2688	59	19	to	to	ADP
ejpam-2688	59	20	the	the	DET
ejpam-2688	59	21	original	original	ADJ
ejpam-2688	59	22	data	datum	NOUN
ejpam-2688	59	23	space	space	NOUN
ejpam-2688	59	24	and	and	CCONJ
ejpam-2688	59	25	judge	judge	VERB
ejpam-2688	59	26	the	the	DET
ejpam-2688	59	27	value	value	NOUN
ejpam-2688	59	28	of	of	ADP
ejpam-2688	59	29	individual	individual	ADJ
ejpam-2688	59	30	variables	variable	NOUN
ejpam-2688	59	31	.	.	PUNCT
ejpam-2688	60	1	while	while	SCONJ
ejpam-2688	60	2	kernel	kernel	PROPN
ejpam-2688	60	3	functions	function	NOUN
ejpam-2688	60	4	execute	execute	VERB
ejpam-2688	60	5	a	a	DET
ejpam-2688	60	6	non	non	ADJ
ejpam-2688	60	7	-	-	ADJ
ejpam-2688	60	8	intuitive	intuitive	ADJ
ejpam-2688	60	9	process	process	NOUN
ejpam-2688	60	10	of	of	ADP
ejpam-2688	60	11	dimensional	dimensional	ADJ
ejpam-2688	60	12	inflation	inflation	NOUN
ejpam-2688	60	13	,	,	PUNCT
ejpam-2688	60	14	the	the	DET
ejpam-2688	60	15	frequent	frequent	ADJ
ejpam-2688	60	16	superior	superior	ADJ
ejpam-2688	60	17	performance	performance	NOUN
ejpam-2688	60	18	of	of	ADP
ejpam-2688	60	19	analysis	analysis	NOUN
ejpam-2688	60	20	with	with	ADP
ejpam-2688	60	21	kernels	kernel	NOUN
ejpam-2688	60	22	is	be	AUX
ejpam-2688	60	23	well	well	ADV
ejpam-2688	60	24	documented	document	VERB
ejpam-2688	60	25	in	in	ADP
ejpam-2688	60	26	a	a	DET
ejpam-2688	60	27	variety	variety	NOUN
ejpam-2688	60	28	of	of	ADP
ejpam-2688	60	29	methods	method	NOUN
ejpam-2688	60	30	(	(	PUNCT
ejpam-2688	60	31	kda	kda	PROPN
ejpam-2688	60	32	,	,	PUNCT
ejpam-2688	60	33	kpca	kpca	PROPN
ejpam-2688	60	34	,	,	PUNCT
ejpam-2688	60	35	klr	klr	PROPN
ejpam-2688	60	36	,	,	PUNCT
ejpam-2688	60	37	.	.	PUNCT
ejpam-2688	60	38	.	.	PUNCT
ejpam-2688	60	39	.	.	PUNCT
ejpam-2688	60	40	)	)	PUNCT
ejpam-2688	60	41	.	.	PUNCT
ejpam-2688	61	1	at	at	ADP
ejpam-2688	61	2	least	least	ADJ
ejpam-2688	61	3	part	part	NOUN
ejpam-2688	61	4	of	of	ADP
ejpam-2688	61	5	this	this	DET
ejpam-2688	61	6	success	success	NOUN
ejpam-2688	61	7	is	be	AUX
ejpam-2688	61	8	due	due	ADJ
ejpam-2688	61	9	to	to	ADP
ejpam-2688	61	10	the	the	DET
ejpam-2688	61	11	way	way	NOUN
ejpam-2688	61	12	functions	function	NOUN
ejpam-2688	61	13	of	of	ADP
ejpam-2688	61	14	distances	distance	NOUN
ejpam-2688	61	15	between	between	ADP
ejpam-2688	61	16	all	all	DET
ejpam-2688	61	17	pairs	pair	NOUN
ejpam-2688	61	18	of	of	ADP
ejpam-2688	61	19	observations	observation	NOUN
ejpam-2688	61	20	end	end	VERB
ejpam-2688	61	21	up	up	ADP
ejpam-2688	61	22	as	as	ADP
ejpam-2688	61	23	observations	observation	NOUN
ejpam-2688	61	24	in	in	ADP
ejpam-2688	61	25	the	the	DET
ejpam-2688	61	26	feature	feature	NOUN
ejpam-2688	61	27	space	space	NOUN
ejpam-2688	61	28	.	.	PUNCT
ejpam-2688	62	1	this	this	PRON
ejpam-2688	62	2	has	have	VERB
ejpam-2688	62	3	the	the	DET
ejpam-2688	62	4	effect	effect	NOUN
ejpam-2688	62	5	of	of	ADP
ejpam-2688	62	6	extracting	extract	VERB
ejpam-2688	62	7	much	much	ADV
ejpam-2688	62	8	more	more	ADJ
ejpam-2688	62	9	information	information	NOUN
ejpam-2688	62	10	from	from	ADP
ejpam-2688	62	11	the	the	DET
ejpam-2688	62	12	data	datum	NOUN
ejpam-2688	62	13	.	.	PUNCT
ejpam-2688	63	1	related	related	ADJ
ejpam-2688	63	2	data	datum	NOUN
ejpam-2688	63	3	tends	tend	VERB
ejpam-2688	63	4	to	to	PART
ejpam-2688	63	5	become	become	VERB
ejpam-2688	63	6	more	more	ADV
ejpam-2688	63	7	closely	closely	ADV
ejpam-2688	63	8	compacted	compact	VERB
ejpam-2688	63	9	,	,	PUNCT
ejpam-2688	63	10	and	and	CCONJ
ejpam-2688	63	11	unrelated	unrelated	ADJ
ejpam-2688	63	12	data	datum	NOUN
ejpam-2688	63	13	tends	tend	VERB
ejpam-2688	63	14	to	to	PART
ejpam-2688	63	15	become	become	VERB
ejpam-2688	63	16	more	more	ADV
ejpam-2688	63	17	separated	separated	ADJ
ejpam-2688	63	18	.	.	PUNCT
ejpam-2688	64	1	visualization	visualization	NOUN
ejpam-2688	64	2	of	of	ADP
ejpam-2688	64	3	this	this	DET
ejpam-2688	64	4	fact	fact	NOUN
ejpam-2688	64	5	can	can	AUX
ejpam-2688	64	6	be	be	AUX
ejpam-2688	64	7	seen	see	VERB
ejpam-2688	64	8	in	in	ADP
ejpam-2688	64	9	figure	figure	NOUN
ejpam-2688	64	10	1	1	NUM
ejpam-2688	64	11	.	.	PUNCT
ejpam-2688	65	1	in	in	ADP
ejpam-2688	65	2	the	the	DET
ejpam-2688	65	3	right	right	ADJ
ejpam-2688	65	4	pane	pane	NOUN
ejpam-2688	65	5	,	,	PUNCT
ejpam-2688	65	6	note	note	VERB
ejpam-2688	65	7	how	how	SCONJ
ejpam-2688	65	8	the	the	DET
ejpam-2688	65	9	confounding	confounding	NOUN
ejpam-2688	65	10	between	between	ADP
ejpam-2688	65	11	the	the	DET
ejpam-2688	65	12	versicolor	versicolor	NOUN
ejpam-2688	65	13	and	and	CCONJ
ejpam-2688	65	14	virginica	virginica	NOUN
ejpam-2688	65	15	observations	observation	NOUN
ejpam-2688	65	16	is	be	AUX
ejpam-2688	65	17	lessened	lessen	VERB
ejpam-2688	65	18	,	,	PUNCT
ejpam-2688	65	19	and	and	CCONJ
ejpam-2688	65	20	how	how	SCONJ
ejpam-2688	65	21	the	the	DET
ejpam-2688	65	22	setosa	setosa	PROPN
ejpam-2688	65	23	group	group	NOUN
ejpam-2688	65	24	has	have	AUX
ejpam-2688	65	25	pulled	pull	VERB
ejpam-2688	65	26	away	away	ADV
ejpam-2688	65	27	from	from	ADP
ejpam-2688	65	28	the	the	DET
ejpam-2688	65	29	others	other	NOUN
ejpam-2688	65	30	.	.	PUNCT
ejpam-2688	66	1	j.	j.	PROPN
ejpam-2688	66	2	howe	howe	PROPN
ejpam-2688	66	3	,	,	PUNCT
ejpam-2688	66	4	h.	h.	PROPN
ejpam-2688	66	5	bozdogan	bozdogan	PROPN
ejpam-2688	66	6	/	/	SYM
ejpam-2688	66	7	eur	eur	PROPN
ejpam-2688	66	8	.	.	PUNCT
ejpam-2688	67	1	j.	j.	PROPN
ejpam-2688	67	2	pure	pure	PROPN
ejpam-2688	67	3	appl	appl	PROPN
ejpam-2688	67	4	.	.	PROPN
ejpam-2688	67	5	math	math	PROPN
ejpam-2688	67	6	,	,	PUNCT
ejpam-2688	67	7	9	9	NUM
ejpam-2688	67	8	(	(	PUNCT
ejpam-2688	67	9	2016	2016	NUM
ejpam-2688	67	10	)	)	PUNCT
ejpam-2688	67	11	,	,	PUNCT
ejpam-2688	67	12	216	216	NUM
ejpam-2688	67	13	-	-	SYM
ejpam-2688	67	14	230	230	NUM
ejpam-2688	67	15	219	219	NUM
ejpam-2688	67	16	petal	petal	ADJ
ejpam-2688	67	17	length	length	NOUN
ejpam-2688	67	18	s	s	PART
ejpam-2688	68	1	ep	ep	PROPN
ejpam-2688	68	2	al	al	PROPN
ejpam-2688	68	3	w	w	PROPN
ejpam-2688	69	1	i	i	PROPN
ejpam-2688	70	1	d	d	PROPN
ejpam-2688	70	2	th	th	X
ejpam-2688	70	3	(	(	PUNCT
ejpam-2688	70	4	a	a	PRON
ejpam-2688	70	5	)	)	PUNCT
ejpam-2688	70	6	iris	iris	NOUN
ejpam-2688	70	7	data	datum	NOUN
ejpam-2688	70	8	(	(	PUNCT
ejpam-2688	70	9	b	b	NOUN
ejpam-2688	70	10	)	)	PUNCT
ejpam-2688	70	11	1st	1st	NOUN
ejpam-2688	70	12	two	two	NUM
ejpam-2688	70	13	variables	variable	NOUN
ejpam-2688	70	14	after	after	ADP
ejpam-2688	70	15	kernel	kernel	PROPN
ejpam-2688	70	16	trick	trick	NOUN
ejpam-2688	70	17	figure	figure	NOUN
ejpam-2688	70	18	1	1	NUM
ejpam-2688	70	19	:	:	PUNCT
ejpam-2688	70	20	demonstrating	demonstrate	VERB
ejpam-2688	70	21	separation	separation	NOUN
ejpam-2688	70	22	in	in	ADP
ejpam-2688	70	23	kernel	kernel	PROPN
ejpam-2688	70	24	space	space	NOUN
ejpam-2688	70	25	;	;	PUNCT
ejpam-2688	70	26	x	x	X
ejpam-2688	70	27	is	be	AUX
ejpam-2688	70	28	setosa	setosa	ADJ
ejpam-2688	70	29	,	,	PUNCT
ejpam-2688	70	30	o	o	PROPN
ejpam-2688	70	31	is	be	AUX
ejpam-2688	70	32	versicolor	versicolor	NOUN
ejpam-2688	70	33	,	,	PUNCT
ejpam-2688	70	34	and	and	CCONJ
ejpam-2688	70	35	∗	∗	NOUN
ejpam-2688	70	36	is	be	AUX
ejpam-2688	70	37	virginica	virginica	NOUN
ejpam-2688	70	38	.	.	PUNCT
ejpam-2688	71	1	the	the	DET
ejpam-2688	71	2	set	set	NOUN
ejpam-2688	71	3	of	of	ADP
ejpam-2688	71	4	kernel	kernel	PROPN
ejpam-2688	71	5	functions	function	NOUN
ejpam-2688	71	6	which	which	PRON
ejpam-2688	71	7	we	we	PRON
ejpam-2688	71	8	use	use	VERB
ejpam-2688	71	9	in	in	ADP
ejpam-2688	71	10	this	this	DET
ejpam-2688	71	11	research	research	NOUN
ejpam-2688	71	12	is	be	AUX
ejpam-2688	71	13	composed	compose	VERB
ejpam-2688	71	14	of	of	ADP
ejpam-2688	71	15	the	the	DET
ejpam-2688	71	16	nine	nine	NUM
ejpam-2688	71	17	most	most	ADV
ejpam-2688	71	18	common	common	ADJ
ejpam-2688	71	19	,	,	PUNCT
ejpam-2688	71	20	as	as	SCONJ
ejpam-2688	71	21	listed	list	VERB
ejpam-2688	71	22	in	in	ADP
ejpam-2688	71	23	table	table	NOUN
ejpam-2688	71	24	1	1	NUM
ejpam-2688	71	25	.	.	PUNCT
ejpam-2688	72	1	for	for	ADP
ejpam-2688	72	2	each	each	DET
ejpam-2688	72	3	kernel	kernel	NOUN
ejpam-2688	72	4	,	,	PUNCT
ejpam-2688	72	5	we	we	PRON
ejpam-2688	72	6	indicate	indicate	VERB
ejpam-2688	72	7	the	the	DET
ejpam-2688	72	8	parameters	parameter	NOUN
ejpam-2688	72	9	we	we	PRON
ejpam-2688	72	10	used	use	VERB
ejpam-2688	72	11	.	.	PUNCT
ejpam-2688	73	1	it	it	PRON
ejpam-2688	73	2	is	be	AUX
ejpam-2688	73	3	generally	generally	ADV
ejpam-2688	73	4	table	table	NOUN
ejpam-2688	73	5	1	1	NUM
ejpam-2688	73	6	:	:	PUNCT
ejpam-2688	73	7	kernel	kernel	NOUN
ejpam-2688	73	8	functions	function	NOUN
ejpam-2688	73	9	available	available	ADJ
ejpam-2688	73	10	.	.	PUNCT
ejpam-2688	74	1	function	function	NOUN
ejpam-2688	74	2	form	form	NOUN
ejpam-2688	74	3	parameters	parameter	NOUN
ejpam-2688	74	4	binary	binary	PROPN
ejpam-2688	74	5	linear	linear	PROPN
ejpam-2688	74	6	polynomial	polynomial	PROPN
ejpam-2688	74	7	�	�	PROPN
ejpam-2688	74	8	x	x	PUNCT
ejpam-2688	74	9	x	x	X
ejpam-2688	75	1	′	′	NUM
ejpam-2688	76	1	+	+	CCONJ
ejpam-2688	76	2	b	b	AUX
ejpam-2688	76	3	�	�	PROPN
ejpam-2688	76	4	a	a	DET
ejpam-2688	76	5	a	a	PRON
ejpam-2688	76	6	=	=	SYM
ejpam-2688	76	7	1	1	NUM
ejpam-2688	76	8	,	,	PUNCT
ejpam-2688	76	9	b	b	X
ejpam-2688	76	10	=	=	SYM
ejpam-2688	76	11	0	0	NUM
ejpam-2688	76	12	0001	0001	NUM
ejpam-2688	76	13	quadratic	quadratic	ADJ
ejpam-2688	76	14	polynomial	polynomial	ADJ
ejpam-2688	76	15	�	�	NOUN
ejpam-2688	76	16	x	x	PUNCT
ejpam-2688	76	17	x	x	X
ejpam-2688	76	18	′	′	NUM
ejpam-2688	77	1	+	+	CCONJ
ejpam-2688	77	2	b	b	X
ejpam-2688	77	3	�	�	PROPN
ejpam-2688	77	4	a	a	PRON
ejpam-2688	77	5	a	a	PRON
ejpam-2688	77	6	=	=	SYM
ejpam-2688	77	7	2	2	NUM
ejpam-2688	77	8	,	,	PUNCT
ejpam-2688	77	9	b	b	X
ejpam-2688	77	10	=	=	SYM
ejpam-2688	77	11	1	1	NUM
ejpam-2688	77	12	0010	0010	NUM
ejpam-2688	77	13	cubic	cubic	ADJ
ejpam-2688	77	14	polynomial	polynomial	ADJ
ejpam-2688	77	15	�	�	PROPN
ejpam-2688	77	16	x	x	PUNCT
ejpam-2688	77	17	x	x	X
ejpam-2688	78	1	′	′	NUM
ejpam-2688	79	1	+	+	CCONJ
ejpam-2688	79	2	b	b	X
ejpam-2688	79	3	�	�	PROPN
ejpam-2688	79	4	a	a	PRON
ejpam-2688	79	5	a	a	PRON
ejpam-2688	79	6	=	=	SYM
ejpam-2688	79	7	3	3	NUM
ejpam-2688	79	8	,	,	PUNCT
ejpam-2688	79	9	b	b	X
ejpam-2688	79	10	=	=	SYM
ejpam-2688	79	11	1	1	NUM
ejpam-2688	79	12	0011	0011	NUM
ejpam-2688	79	13	exponential	exponential	ADJ
ejpam-2688	79	14	exp	exp	X
ejpam-2688	79	15	�	�	PROPN
ejpam-2688	79	16	−	−	PROPN
ejpam-2688	79	17	1	1	NUM
ejpam-2688	79	18	2a2	2a2	NUM
ejpam-2688	80	1	æ	æ	NOUN
ejpam-2688	80	2	‖x	‖x	NOUN
ejpam-2688	80	3	−	−	PROPN
ejpam-2688	80	4	x‖2	x‖2	PROPN
ejpam-2688	81	1	�	�	PROPN
ejpam-2688	81	2	a	a	PRON
ejpam-2688	81	3	=	=	NOUN
ejpam-2688	81	4	1	1	NUM
ejpam-2688	81	5	0100	0100	NUM
ejpam-2688	81	6	gaussian	gaussian	NOUN
ejpam-2688	81	7	exp	exp	X
ejpam-2688	81	8	�	�	PROPN
ejpam-2688	81	9	−	−	PROPN
ejpam-2688	81	10	�	�	PROPN
ejpam-2688	81	11	1	1	NUM
ejpam-2688	81	12	ab	ab	PROPN
ejpam-2688	81	13	‖x	‖x	NOUN
ejpam-2688	81	14	−	−	PROPN
ejpam-2688	81	15	x‖2	x‖2	PROPN
ejpam-2688	81	16	�	�	PROPN
ejpam-2688	81	17	c	c	PROPN
ejpam-2688	81	18	�	�	PROPN
ejpam-2688	81	19	a	a	DET
ejpam-2688	81	20	=	=	SYM
ejpam-2688	81	21	2	2	NUM
ejpam-2688	81	22	,	,	PUNCT
ejpam-2688	81	23	b	b	NOUN
ejpam-2688	82	1	=	=	SYM
ejpam-2688	82	2	c	c	NOUN
ejpam-2688	82	3	=	=	SYM
ejpam-2688	82	4	1	1	NUM
ejpam-2688	82	5	0101	0101	NUM
ejpam-2688	82	6	homogenous	homogenous	ADJ
ejpam-2688	82	7	poly	poly	NOUN
ejpam-2688	82	8	.	.	PUNCT
ejpam-2688	83	1	(	(	PUNCT
ejpam-2688	83	2	homo	homo	NOUN
ejpam-2688	83	3	)	)	PUNCT
ejpam-2688	83	4	�	�	PROPN
ejpam-2688	83	5	1	1	NUM
ejpam-2688	83	6	a2	a2	PROPN
ejpam-2688	83	7	x	x	SYM
ejpam-2688	83	8	x	x	SYM
ejpam-2688	83	9	′	′	NUM
ejpam-2688	83	10	�	�	PROPN
ejpam-2688	83	11	b	b	PROPN
ejpam-2688	83	12	a	a	PRON
ejpam-2688	83	13	=	=	SYM
ejpam-2688	83	14	1	1	NUM
ejpam-2688	83	15	,	,	PUNCT
ejpam-2688	83	16	b	b	NOUN
ejpam-2688	83	17	=	=	SYM
ejpam-2688	83	18	2	2	NUM
ejpam-2688	83	19	0110	0110	NUM
ejpam-2688	83	20	laplace	laplace	NOUN
ejpam-2688	83	21	exp	exp	NOUN
ejpam-2688	83	22	�	�	PROPN
ejpam-2688	83	23	−	−	PROPN
ejpam-2688	83	24	q	q	PROPN
ejpam-2688	83	25	1	1	NUM
ejpam-2688	83	26	a2	a2	PROPN
ejpam-2688	83	27	‖x	‖x	NOUN
ejpam-2688	83	28	−	−	PROPN
ejpam-2688	83	29	x‖2	x‖2	PROPN
ejpam-2688	84	1	�	�	PROPN
ejpam-2688	85	1	a	a	DET
ejpam-2688	85	2	=	=	SYM
ejpam-2688	85	3	1	1	NUM
ejpam-2688	85	4	0111	0111	NUM
ejpam-2688	85	5	cauchy	cauchy	PROPN
ejpam-2688	85	6	�	�	PROPN
ejpam-2688	85	7	1	1	NUM
ejpam-2688	85	8	+	+	NUM
ejpam-2688	85	9	1	1	NUM
ejpam-2688	85	10	a	a	PRON
ejpam-2688	85	11	‖x	‖x	NOUN
ejpam-2688	85	12	−	−	PROPN
ejpam-2688	85	13	x‖2	x‖2	PROPN
ejpam-2688	85	14	�	�	PROPN
ejpam-2688	85	15	−1	−1	NOUN
ejpam-2688	85	16	a	a	DET
ejpam-2688	85	17	=	=	SYM
ejpam-2688	85	18	1	1	NUM
ejpam-2688	85	19	1000	1000	NUM
ejpam-2688	85	20	inverse	inverse	NOUN
ejpam-2688	85	21	multi	multi	ADJ
ejpam-2688	85	22	-	-	ADJ
ejpam-2688	85	23	quadric	quadric	ADJ
ejpam-2688	85	24	�	�	NOUN
ejpam-2688	85	25	‖x	‖x	NOUN
ejpam-2688	85	26	−	−	PROPN
ejpam-2688	85	27	x‖2	x‖2	PUNCT
ejpam-2688	86	1	+	+	NUM
ejpam-2688	86	2	a2	a2	PROPN
ejpam-2688	86	3	�	�	PROPN
ejpam-2688	86	4	−	−	PROPN
ejpam-2688	86	5	1	1	NUM
ejpam-2688	86	6	2	2	NUM
ejpam-2688	86	7	a	a	DET
ejpam-2688	86	8	=	=	SYM
ejpam-2688	86	9	1	1	NUM
ejpam-2688	86	10	1001	1001	NUM
ejpam-2688	86	11	difficult	difficult	ADJ
ejpam-2688	86	12	to	to	PART
ejpam-2688	86	13	know	know	VERB
ejpam-2688	86	14	a	a	DET
ejpam-2688	86	15	priori	priori	ADJ
ejpam-2688	86	16	which	which	DET
ejpam-2688	86	17	kernel	kernel	NOUN
ejpam-2688	86	18	is	be	AUX
ejpam-2688	86	19	best	good	ADJ
ejpam-2688	86	20	.	.	PUNCT
ejpam-2688	87	1	yet	yet	ADV
ejpam-2688	87	2	,	,	PUNCT
ejpam-2688	87	3	this	this	PRON
ejpam-2688	87	4	is	be	AUX
ejpam-2688	87	5	one	one	NUM
ejpam-2688	87	6	decision	decision	NOUN
ejpam-2688	87	7	that	that	PRON
ejpam-2688	87	8	can	can	AUX
ejpam-2688	87	9	have	have	VERB
ejpam-2688	87	10	a	a	DET
ejpam-2688	87	11	large	large	ADJ
ejpam-2688	87	12	impact	impact	NOUN
ejpam-2688	87	13	on	on	ADP
ejpam-2688	87	14	the	the	DET
ejpam-2688	87	15	performance	performance	NOUN
ejpam-2688	87	16	of	of	ADP
ejpam-2688	87	17	kda	kda	NOUN
ejpam-2688	87	18	.	.	PUNCT
ejpam-2688	88	1	some	some	DET
ejpam-2688	88	2	researchers	researcher	NOUN
ejpam-2688	88	3	simply	simply	ADV
ejpam-2688	88	4	select	select	VERB
ejpam-2688	88	5	a	a	DET
ejpam-2688	88	6	kernel	kernel	NOUN
ejpam-2688	88	7	function	function	VERB
ejpam-2688	88	8	a	a	DET
ejpam-2688	88	9	priori	priori	ADV
ejpam-2688	88	10	.	.	PUNCT
ejpam-2688	89	1	the	the	DET
ejpam-2688	89	2	more	more	ADV
ejpam-2688	89	3	usual	usual	ADJ
ejpam-2688	89	4	approach	approach	NOUN
ejpam-2688	89	5	is	be	AUX
ejpam-2688	89	6	to	to	PART
ejpam-2688	89	7	simply	simply	ADV
ejpam-2688	89	8	apply	apply	VERB
ejpam-2688	89	9	kda	kda	NOUN
ejpam-2688	89	10	with	with	ADP
ejpam-2688	89	11	a	a	DET
ejpam-2688	89	12	variety	variety	NOUN
ejpam-2688	89	13	of	of	ADP
ejpam-2688	89	14	kernel	kernel	NOUN
ejpam-2688	89	15	functions	function	NOUN
ejpam-2688	89	16	and	and	CCONJ
ejpam-2688	89	17	select	select	VERB
ejpam-2688	89	18	whichever	whichever	PRON
ejpam-2688	89	19	gives	give	VERB
ejpam-2688	89	20	best	good	ADJ
ejpam-2688	89	21	results	result	NOUN
ejpam-2688	89	22	on	on	ADP
ejpam-2688	89	23	the	the	DET
ejpam-2688	89	24	sample	sample	NOUN
ejpam-2688	89	25	data	datum	NOUN
ejpam-2688	89	26	.	.	PUNCT
ejpam-2688	90	1	cross	cross	ADJ
ejpam-2688	90	2	-	-	ADJ
ejpam-2688	90	3	validation	validation	ADJ
ejpam-2688	90	4	sampling	sampling	NOUN
ejpam-2688	90	5	is	be	AUX
ejpam-2688	90	6	used	use	VERB
ejpam-2688	90	7	to	to	PART
ejpam-2688	90	8	limit	limit	VERB
ejpam-2688	90	9	the	the	DET
ejpam-2688	90	10	risk	risk	NOUN
ejpam-2688	90	11	of	of	ADP
ejpam-2688	90	12	fitting	fit	VERB
ejpam-2688	90	13	to	to	ADP
ejpam-2688	90	14	random	random	ADJ
ejpam-2688	90	15	noise	noise	NOUN
ejpam-2688	90	16	in	in	ADP
ejpam-2688	90	17	specific	specific	ADJ
ejpam-2688	90	18	subsets	subset	NOUN
ejpam-2688	90	19	.	.	PUNCT
ejpam-2688	91	1	however	however	ADV
ejpam-2688	91	2	,	,	PUNCT
ejpam-2688	91	3	this	this	DET
ejpam-2688	91	4	approach	approach	NOUN
ejpam-2688	91	5	only	only	ADV
ejpam-2688	91	6	considers	consider	VERB
ejpam-2688	91	7	classification	classification	NOUN
ejpam-2688	91	8	performance	performance	NOUN
ejpam-2688	91	9	,	,	PUNCT
ejpam-2688	91	10	and	and	CCONJ
ejpam-2688	91	11	ignores	ignore	VERB
ejpam-2688	91	12	model	model	NOUN
ejpam-2688	91	13	complexity	complexity	NOUN
ejpam-2688	91	14	.	.	PUNCT
ejpam-2688	92	1	optimal	optimal	ADJ
ejpam-2688	92	2	selection	selection	NOUN
ejpam-2688	92	3	of	of	ADP
ejpam-2688	92	4	the	the	DET
ejpam-2688	92	5	parameters	parameter	NOUN
ejpam-2688	92	6	is	be	AUX
ejpam-2688	92	7	another	another	DET
ejpam-2688	92	8	important	important	ADJ
ejpam-2688	92	9	consideration	consideration	NOUN
ejpam-2688	92	10	in	in	ADP
ejpam-2688	92	11	kda	kda	PROPN
ejpam-2688	92	12	.	.	PUNCT
ejpam-2688	93	1	liberati	liberati	PROPN
ejpam-2688	93	2	et	et	PROPN
ejpam-2688	93	3	al	al	PROPN
ejpam-2688	93	4	.	.	PUNCT
ejpam-2688	94	1	[	[	X
ejpam-2688	94	2	12	12	NUM
ejpam-2688	94	3	]	]	PUNCT
ejpam-2688	94	4	proposed	propose	VERB
ejpam-2688	94	5	a	a	DET
ejpam-2688	94	6	data	data	NOUN
ejpam-2688	94	7	-	-	PUNCT
ejpam-2688	94	8	based	base	VERB
ejpam-2688	94	9	technique	technique	NOUN
ejpam-2688	94	10	to	to	PART
ejpam-2688	94	11	simultaneously	simultaneously	ADV
ejpam-2688	94	12	optimize	optimize	VERB
ejpam-2688	94	13	selection	selection	NOUN
ejpam-2688	94	14	and	and	CCONJ
ejpam-2688	94	15	parametrization	parametrization	NOUN
ejpam-2688	94	16	of	of	ADP
ejpam-2688	94	17	the	the	DET
ejpam-2688	94	18	kernel	kernel	PROPN
ejpam-2688	94	19	function	function	NOUN
ejpam-2688	94	20	.	.	PUNCT
ejpam-2688	95	1	in	in	ADP
ejpam-2688	95	2	this	this	DET
ejpam-2688	95	3	research	research	NOUN
ejpam-2688	95	4	,	,	PUNCT
ejpam-2688	95	5	we	we	PRON
ejpam-2688	95	6	have	have	AUX
ejpam-2688	95	7	opted	opt	VERB
ejpam-2688	95	8	not	not	PART
ejpam-2688	95	9	to	to	PART
ejpam-2688	95	10	attempt	attempt	VERB
ejpam-2688	95	11	to	to	PART
ejpam-2688	95	12	optimize	optimize	VERB
ejpam-2688	95	13	the	the	DET
ejpam-2688	95	14	parameters	parameter	NOUN
ejpam-2688	95	15	.	.	PUNCT
ejpam-2688	96	1	j.	j.	PROPN
ejpam-2688	96	2	howe	howe	PROPN
ejpam-2688	96	3	,	,	PUNCT
ejpam-2688	96	4	h.	h.	PROPN
ejpam-2688	96	5	bozdogan	bozdogan	PROPN
ejpam-2688	96	6	/	/	SYM
ejpam-2688	96	7	eur	eur	PROPN
ejpam-2688	96	8	.	.	PUNCT
ejpam-2688	97	1	j.	j.	PROPN
ejpam-2688	97	2	pure	pure	PROPN
ejpam-2688	97	3	appl	appl	PROPN
ejpam-2688	97	4	.	.	PROPN
ejpam-2688	97	5	math	math	PROPN
ejpam-2688	97	6	,	,	PUNCT
ejpam-2688	97	7	9	9	NUM
ejpam-2688	97	8	(	(	PUNCT
ejpam-2688	97	9	2016	2016	NUM
ejpam-2688	97	10	)	)	PUNCT
ejpam-2688	97	11	,	,	PUNCT
ejpam-2688	97	12	216	216	NUM
ejpam-2688	97	13	-	-	SYM
ejpam-2688	97	14	230	230	NUM
ejpam-2688	97	15	220	220	NUM
ejpam-2688	97	16	2.2	2.2	NUM
ejpam-2688	97	17	.	.	PUNCT
ejpam-2688	98	1	binary	binary	ADJ
ejpam-2688	98	2	discriminant	discriminant	PROPN
ejpam-2688	98	3	analysis	analysis	VERB
ejpam-2688	98	4	our	our	PRON
ejpam-2688	98	5	data	datum	NOUN
ejpam-2688	98	6	x	x	VERB
ejpam-2688	98	7	is	be	AUX
ejpam-2688	98	8	composed	compose	VERB
ejpam-2688	98	9	of	of	ADP
ejpam-2688	98	10	n	n	DET
ejpam-2688	98	11	realizations	realization	NOUN
ejpam-2688	98	12	of	of	ADP
ejpam-2688	98	13	p	p	NOUN
ejpam-2688	98	14	continuous	continuous	ADJ
ejpam-2688	98	15	measurements	measurement	NOUN
ejpam-2688	98	16	.	.	PUNCT
ejpam-2688	99	1	accompanying	accompany	VERB
ejpam-2688	99	2	x	x	SYM
ejpam-2688	99	3	is	be	AUX
ejpam-2688	99	4	a	a	DET
ejpam-2688	99	5	vector	vector	NOUN
ejpam-2688	99	6	of	of	ADP
ejpam-2688	99	7	class	class	NOUN
ejpam-2688	99	8	assignments	assignment	NOUN
ejpam-2688	99	9	y	y	PROPN
ejpam-2688	99	10	∈	∈	PROPN
ejpam-2688	100	1	[	[	X
ejpam-2688	100	2	1,2	1,2	NUM
ejpam-2688	100	3	]	]	PUNCT
ejpam-2688	100	4	.	.	PUNCT
ejpam-2688	101	1	having	have	VERB
ejpam-2688	101	2	yi	yi	NOUN
ejpam-2688	101	3	=	=	SYM
ejpam-2688	101	4	1	1	NUM
ejpam-2688	101	5	indicates	indicate	VERB
ejpam-2688	101	6	that	that	SCONJ
ejpam-2688	101	7	x	x	PUNCT
ejpam-2688	101	8	i	i	PRON
ejpam-2688	101	9	is	be	AUX
ejpam-2688	101	10	an	an	DET
ejpam-2688	101	11	element	element	NOUN
ejpam-2688	101	12	of	of	ADP
ejpam-2688	101	13	the	the	DET
ejpam-2688	101	14	first	first	ADJ
ejpam-2688	101	15	group	group	NOUN
ejpam-2688	101	16	.	.	PUNCT
ejpam-2688	102	1	after	after	ADP
ejpam-2688	102	2	mapping	map	VERB
ejpam-2688	102	3	the	the	DET
ejpam-2688	102	4	data	datum	NOUN
ejpam-2688	102	5	into	into	ADP
ejpam-2688	102	6	the	the	DET
ejpam-2688	102	7	feature	feature	NOUN
ejpam-2688	102	8	space	space	NOUN
ejpam-2688	102	9	f	f	NOUN
ejpam-2688	102	10	,	,	PUNCT
ejpam-2688	102	11	the	the	DET
ejpam-2688	102	12	goal	goal	NOUN
ejpam-2688	102	13	is	be	AUX
ejpam-2688	102	14	to	to	PART
ejpam-2688	102	15	find	find	VERB
ejpam-2688	102	16	a	a	DET
ejpam-2688	102	17	direction	direction	NOUN
ejpam-2688	102	18	ψ=	ψ=	NOUN
ejpam-2688	103	1	n∑	n∑	PROPN
ejpam-2688	103	2	i=1	i=1	PROPN
ejpam-2688	103	3	αiφ	αiφ	ADJ
ejpam-2688	103	4	�	�	PROPN
ejpam-2688	103	5	x	x	PUNCT
ejpam-2688	103	6	i	i	PRON
ejpam-2688	103	7	�	�	PROPN
ejpam-2688	103	8	=	=	SYM
ejpam-2688	103	9	α	α	PROPN
ejpam-2688	103	10	,	,	PUNCT
ejpam-2688	103	11	x	x	PROPN
ejpam-2688	103	12	i	i	PRON
ejpam-2688	103	13	�	�	PROPN
ejpam-2688	103	14	(	(	PUNCT
ejpam-2688	103	15	1	1	NUM
ejpam-2688	103	16	)	)	PUNCT
ejpam-2688	103	17	with	with	ADP
ejpam-2688	103	18	weight	weight	NOUN
ejpam-2688	103	19	vector	vector	NOUN
ejpam-2688	103	20	α	α	NOUN
ejpam-2688	103	21	that	that	PRON
ejpam-2688	103	22	maximizes	maximize	VERB
ejpam-2688	103	23	the	the	DET
ejpam-2688	103	24	fisher	fisher	PROPN
ejpam-2688	103	25	criterion	criterion	NOUN
ejpam-2688	103	26	jf	jf	PROPN
ejpam-2688	103	27	(	(	PUNCT
ejpam-2688	103	28	α	α	NOUN
ejpam-2688	103	29	)	)	PUNCT
ejpam-2688	103	30	=	=	NOUN
ejpam-2688	103	31	α′σ̂bα	α′σ̂bα	PROPN
ejpam-2688	103	32	α′σ̂wα	α′σ̂wα	PROPN
ejpam-2688	103	33	.	.	PUNCT
ejpam-2688	104	1	(	(	PUNCT
ejpam-2688	104	2	2	2	X
ejpam-2688	104	3	)	)	PUNCT
ejpam-2688	104	4	σ̂b	σ̂b	NOUN
ejpam-2688	104	5	indicates	indicate	VERB
ejpam-2688	104	6	the	the	DET
ejpam-2688	104	7	between	between	ADP
ejpam-2688	104	8	-	-	PUNCT
ejpam-2688	104	9	group	group	NOUN
ejpam-2688	104	10	covariance	covariance	NOUN
ejpam-2688	104	11	matrix	matrix	NOUN
ejpam-2688	104	12	,	,	PUNCT
ejpam-2688	104	13	and	and	CCONJ
ejpam-2688	104	14	σ̂w	σ̂w	NOUN
ejpam-2688	104	15	is	be	AUX
ejpam-2688	104	16	the	the	DET
ejpam-2688	104	17	within	within	ADP
ejpam-2688	104	18	-	-	PUNCT
ejpam-2688	104	19	group	group	NOUN
ejpam-2688	104	20	covariance	covariance	NOUN
ejpam-2688	104	21	matrix	matrix	NOUN
ejpam-2688	104	22	,	,	PUNCT
ejpam-2688	104	23	shown	show	VERB
ejpam-2688	104	24	in	in	ADP
ejpam-2688	104	25	(	(	PUNCT
ejpam-2688	104	26	3	3	NUM
ejpam-2688	104	27	)	)	PUNCT
ejpam-2688	104	28	and	and	CCONJ
ejpam-2688	104	29	(	(	PUNCT
ejpam-2688	104	30	4	4	NUM
ejpam-2688	104	31	)	)	PUNCT
ejpam-2688	104	32	,	,	PUNCT
ejpam-2688	104	33	respectively	respectively	ADV
ejpam-2688	104	34	.	.	PUNCT
ejpam-2688	105	1	σ̂b	σ̂b	X
ejpam-2688	105	2	=	=	SYM
ejpam-2688	105	3	�	�	PROPN
ejpam-2688	106	1	x1	x1	NUM
ejpam-2688	106	2	−	−	PROPN
ejpam-2688	106	3	x2	x2	PROPN
ejpam-2688	106	4	�	�	PROPN
ejpam-2688	106	5	′	′	PROPN
ejpam-2688	106	6	�	�	PROPN
ejpam-2688	107	1	x1	x1	PRON
ejpam-2688	107	2	−	−	PROPN
ejpam-2688	107	3	x2	x2	PROPN
ejpam-2688	107	4	�	�	PROPN
ejpam-2688	107	5	(	(	PUNCT
ejpam-2688	107	6	3	3	NUM
ejpam-2688	107	7	)	)	PUNCT
ejpam-2688	107	8	σ̂w	σ̂w	NOUN
ejpam-2688	107	9	=	=	SYM
ejpam-2688	107	10	1	1	NUM
ejpam-2688	107	11	n	n	NOUN
ejpam-2688	107	12	w	w	NOUN
ejpam-2688	107	13	=	=	SYM
ejpam-2688	107	14	1	1	NUM
ejpam-2688	107	15	n	n	NUM
ejpam-2688	107	16	2∑	2∑	NOUN
ejpam-2688	107	17	k=1	k=1	PUNCT
ejpam-2688	108	1	i	i	PRON
ejpam-2688	108	2	yi	yi	X
ejpam-2688	109	1	=	=	PROPN
ejpam-2688	109	2	k	k	PROPN
ejpam-2688	109	3	�	�	PROPN
ejpam-2688	109	4	x	x	PUNCT
ejpam-2688	109	5	−	−	PROPN
ejpam-2688	109	6	xk	xk	PROPN
ejpam-2688	109	7	�	�	PROPN
ejpam-2688	109	8	′	′	PROPN
ejpam-2688	109	9	�	�	PROPN
ejpam-2688	109	10	x	x	PUNCT
ejpam-2688	109	11	−	−	PROPN
ejpam-2688	109	12	xk	xk	PROPN
ejpam-2688	109	13	�	�	PROPN
ejpam-2688	109	14	(	(	PUNCT
ejpam-2688	109	15	4	4	NUM
ejpam-2688	109	16	)	)	PUNCT
ejpam-2688	109	17	xk	xk	PROPN
ejpam-2688	109	18	is	be	AUX
ejpam-2688	109	19	the	the	DET
ejpam-2688	109	20	mean	mean	NOUN
ejpam-2688	109	21	of	of	ADP
ejpam-2688	109	22	observations	observation	NOUN
ejpam-2688	109	23	belonging	belong	VERB
ejpam-2688	109	24	to	to	ADP
ejpam-2688	109	25	class	class	NOUN
ejpam-2688	109	26	k	k	PROPN
ejpam-2688	109	27	,	,	PUNCT
ejpam-2688	109	28	and	and	CCONJ
ejpam-2688	110	1	i	i	PRON
ejpam-2688	110	2	y	y	PROPN
ejpam-2688	110	3	=	=	ADJ
ejpam-2688	110	4	k	k	PROPN
ejpam-2688	110	5	is	be	AUX
ejpam-2688	110	6	an	an	DET
ejpam-2688	110	7	indicator	indicator	NOUN
ejpam-2688	110	8	function	function	NOUN
ejpam-2688	110	9	which	which	PRON
ejpam-2688	110	10	takes	take	VERB
ejpam-2688	110	11	on	on	ADP
ejpam-2688	110	12	the	the	DET
ejpam-2688	110	13	value	value	NOUN
ejpam-2688	110	14	1	1	NUM
ejpam-2688	110	15	when	when	SCONJ
ejpam-2688	110	16	the	the	DET
ejpam-2688	110	17	specific	specific	ADJ
ejpam-2688	110	18	datapoint	datapoint	NOUN
ejpam-2688	110	19	is	be	AUX
ejpam-2688	110	20	in	in	ADP
ejpam-2688	110	21	group	group	NOUN
ejpam-2688	110	22	k	k	PROPN
ejpam-2688	110	23	(	(	PUNCT
ejpam-2688	110	24	0	0	NUM
ejpam-2688	110	25	otherwise	otherwise	ADV
ejpam-2688	110	26	)	)	PUNCT
ejpam-2688	110	27	.	.	PUNCT
ejpam-2688	111	1	the	the	DET
ejpam-2688	111	2	binary	binary	PROPN
ejpam-2688	111	3	kernel	kernel	PROPN
ejpam-2688	111	4	discriminant	discriminant	PROPN
ejpam-2688	111	5	function	function	NOUN
ejpam-2688	111	6	and	and	CCONJ
ejpam-2688	111	7	classifier	classifier	NOUN
ejpam-2688	111	8	are	be	AUX
ejpam-2688	111	9	:	:	PUNCT
ejpam-2688	111	10	f	f	X
ejpam-2688	111	11	�	�	PROPN
ejpam-2688	111	12	x	x	PUNCT
ejpam-2688	111	13	i	i	PRON
ejpam-2688	111	14	�	�	PROPN
ejpam-2688	111	15	=	=	SYM
ejpam-2688	111	16	α	α	PROPN
ejpam-2688	111	17	,	,	PUNCT
ejpam-2688	111	18	k	k	PROPN
ejpam-2688	111	19	�	�	PROPN
ejpam-2688	111	20	x	x	INTJ
ejpam-2688	111	21	i	i	PRON
ejpam-2688	111	22	,	,	PUNCT
ejpam-2688	111	23	x	x	PROPN
ejpam-2688	111	24	�	�	PROPN
ejpam-2688	111	25	�	�	PROPN
ejpam-2688	111	26	+	+	SYM
ejpam-2688	111	27	b	b	PROPN
ejpam-2688	111	28	,	,	PUNCT
ejpam-2688	111	29	and	and	CCONJ
ejpam-2688	111	30	(	(	PUNCT
ejpam-2688	111	31	5	5	X
ejpam-2688	111	32	)	)	PUNCT
ejpam-2688	111	33	q	q	NOUN
ejpam-2688	111	34	�	�	PROPN
ejpam-2688	111	35	x	x	PUNCT
ejpam-2688	111	36	i	i	PRON
ejpam-2688	111	37	�	�	PROPN
ejpam-2688	111	38	=	=	SYM
ejpam-2688	111	39	¨	¨	NOUN
ejpam-2688	111	40	1	1	NUM
ejpam-2688	111	41	f	f	PROPN
ejpam-2688	111	42	�	�	PROPN
ejpam-2688	111	43	x	x	SYM
ejpam-2688	112	1	i	i	NOUN
ejpam-2688	112	2	�	�	VERB
ejpam-2688	112	3	≥	≥	NOUN
ejpam-2688	112	4	0	0	NUM
ejpam-2688	112	5	2	2	NUM
ejpam-2688	112	6	f	f	PROPN
ejpam-2688	112	7	�	�	PROPN
ejpam-2688	112	8	x	x	PUNCT
ejpam-2688	112	9	i	i	PRON
ejpam-2688	112	10	�	�	X
ejpam-2688	112	11	<	<	X
ejpam-2688	112	12	0	0	PROPN
ejpam-2688	112	13	.	.	PUNCT
ejpam-2688	113	1	(	(	PUNCT
ejpam-2688	113	2	6	6	NUM
ejpam-2688	113	3	)	)	PUNCT
ejpam-2688	113	4	where	where	SCONJ
ejpam-2688	113	5	the	the	DET
ejpam-2688	113	6	vector	vector	NOUN
ejpam-2688	113	7	α	α	NOUN
ejpam-2688	113	8	is	be	AUX
ejpam-2688	113	9	obtained	obtain	VERB
ejpam-2688	113	10	by	by	ADP
ejpam-2688	113	11	solving	solve	VERB
ejpam-2688	113	12	(	(	PUNCT
ejpam-2688	113	13	2	2	NUM
ejpam-2688	113	14	)	)	PUNCT
ejpam-2688	113	15	,	,	PUNCT
ejpam-2688	113	16	and	and	CCONJ
ejpam-2688	113	17	b	b	X
ejpam-2688	113	18	is	be	AUX
ejpam-2688	113	19	the	the	DET
ejpam-2688	113	20	intercept	intercept	NOUN
ejpam-2688	113	21	of	of	ADP
ejpam-2688	113	22	the	the	DET
ejpam-2688	113	23	separating	separate	VERB
ejpam-2688	113	24	hyperplane	hyperplane	NOUN
ejpam-2688	113	25	,	,	PUNCT
ejpam-2688	113	26	which	which	PRON
ejpam-2688	113	27	passes	pass	VERB
ejpam-2688	113	28	through	through	ADP
ejpam-2688	113	29	the	the	DET
ejpam-2688	113	30	midpoint	midpoint	NOUN
ejpam-2688	113	31	of	of	ADP
ejpam-2688	113	32	the	the	DET
ejpam-2688	113	33	class	class	NOUN
ejpam-2688	113	34	centroids	centroid	NOUN
ejpam-2688	113	35	.	.	PUNCT
ejpam-2688	114	1	2.3	2.3	NUM
ejpam-2688	114	2	.	.	PUNCT
ejpam-2688	114	3	binary	binary	ADJ
ejpam-2688	114	4	support	support	NOUN
ejpam-2688	114	5	vectors	vector	NOUN
ejpam-2688	114	6	generalizing	generalize	VERB
ejpam-2688	114	7	this	this	PRON
ejpam-2688	114	8	further	far	ADV
ejpam-2688	114	9	,	,	PUNCT
ejpam-2688	114	10	we	we	PRON
ejpam-2688	114	11	can	can	AUX
ejpam-2688	114	12	rewrite	rewrite	VERB
ejpam-2688	114	13	(	(	PUNCT
ejpam-2688	114	14	5	5	NUM
ejpam-2688	114	15	)	)	PUNCT
ejpam-2688	114	16	as	as	ADP
ejpam-2688	114	17	f	f	PROPN
ejpam-2688	114	18	�	�	PROPN
ejpam-2688	114	19	x	x	PROPN
ejpam-2688	114	20	i	i	PRON
ejpam-2688	114	21	�	�	PROPN
ejpam-2688	114	22	=	=	SYM
ejpam-2688	114	23	α∗	α∗	PROPN
ejpam-2688	114	24	,	,	PUNCT
ejpam-2688	114	25	ks	ks	X
ejpam-2688	114	26	�	�	PROPN
ejpam-2688	114	27	x	x	PROPN
ejpam-2688	114	28	i	i	NOUN
ejpam-2688	114	29	�	�	VERB
ejpam-2688	114	30	�	�	PROPN
ejpam-2688	114	31	+	+	CCONJ
ejpam-2688	114	32	b∗	b∗	ADJ
ejpam-2688	114	33	,	,	PUNCT
ejpam-2688	114	34	where	where	SCONJ
ejpam-2688	114	35	ks	ks	PROPN
ejpam-2688	114	36	�	�	PROPN
ejpam-2688	114	37	x	x	PROPN
ejpam-2688	114	38	i	i	PRON
ejpam-2688	114	39	�	�	PROPN
ejpam-2688	114	40	=	=	SYM
ejpam-2688	114	41	�	�	PROPN
ejpam-2688	114	42	k	k	PROPN
ejpam-2688	114	43	�	�	PROPN
ejpam-2688	115	1	x	x	PROPN
ejpam-2688	115	2	i	i	NOUN
ejpam-2688	115	3	,	,	PUNCT
ejpam-2688	115	4	s1	s1	PROPN
ejpam-2688	115	5	�	�	PROPN
ejpam-2688	115	6	,	,	PUNCT
ejpam-2688	115	7	k	k	PROPN
ejpam-2688	115	8	�	�	PROPN
ejpam-2688	115	9	x	x	PROPN
ejpam-2688	115	10	i	i	PROPN
ejpam-2688	115	11	,	,	PUNCT
ejpam-2688	115	12	s2	s2	PROPN
ejpam-2688	115	13	�	�	PROPN
ejpam-2688	115	14	,	,	PUNCT
ejpam-2688	115	15	.	.	PUNCT
ejpam-2688	115	16	.	.	PUNCT
ejpam-2688	115	17	.	.	PUNCT
ejpam-2688	116	1	,	,	PUNCT
ejpam-2688	116	2	k	k	PROPN
ejpam-2688	116	3	�	�	PROPN
ejpam-2688	116	4	x	x	PROPN
ejpam-2688	116	5	i	i	PROPN
ejpam-2688	116	6	,	,	PUNCT
ejpam-2688	116	7	sm	sm	PROPN
ejpam-2688	116	8	�	�	PROPN
ejpam-2688	116	9	�	�	PROPN
ejpam-2688	116	10	is	be	AUX
ejpam-2688	116	11	the	the	DET
ejpam-2688	116	12	vector	vector	NOUN
ejpam-2688	116	13	of	of	ADP
ejpam-2688	116	14	the	the	DET
ejpam-2688	116	15	ith	ith	PROPN
ejpam-2688	116	16	datapoint	datapoint	PROPN
ejpam-2688	116	17	evaluated	evaluate	VERB
ejpam-2688	116	18	at	at	ADP
ejpam-2688	116	19	the	the	DET
ejpam-2688	116	20	m	m	PROPN
ejpam-2688	116	21	support	support	NOUN
ejpam-2688	116	22	vectors	vector	NOUN
ejpam-2688	116	23	,	,	PUNCT
ejpam-2688	116	24	which	which	PRON
ejpam-2688	116	25	form	form	VERB
ejpam-2688	116	26	a	a	DET
ejpam-2688	116	27	subset	subset	NOUN
ejpam-2688	116	28	of	of	ADP
ejpam-2688	116	29	the	the	DET
ejpam-2688	116	30	data	datum	NOUN
ejpam-2688	116	31	.	.	PUNCT
ejpam-2688	117	1	this	this	PRON
ejpam-2688	117	2	is	be	AUX
ejpam-2688	117	3	the	the	DET
ejpam-2688	117	4	support	support	NOUN
ejpam-2688	117	5	vector	vector	NOUN
ejpam-2688	117	6	machine	machine	NOUN
ejpam-2688	117	7	(	(	PUNCT
ejpam-2688	117	8	svm	svm	PROPN
ejpam-2688	117	9	)	)	PUNCT
ejpam-2688	117	10	.	.	PUNCT
ejpam-2688	118	1	thus	thus	ADV
ejpam-2688	118	2	,	,	PUNCT
ejpam-2688	118	3	optimization	optimization	NOUN
ejpam-2688	118	4	of	of	ADP
ejpam-2688	118	5	the	the	DET
ejpam-2688	118	6	weights	weight	NOUN
ejpam-2688	118	7	and	and	CCONJ
ejpam-2688	118	8	intercept	intercept	NOUN
ejpam-2688	118	9	becomes	become	VERB
ejpam-2688	118	10	the	the	DET
ejpam-2688	118	11	quadratic	quadratic	ADJ
ejpam-2688	118	12	programming	programming	NOUN
ejpam-2688	118	13	problem	problem	NOUN
ejpam-2688	118	14	shown	show	VERB
ejpam-2688	118	15	here	here	ADV
ejpam-2688	118	16	.	.	PUNCT
ejpam-2688	119	1	(	(	PUNCT
ejpam-2688	119	2	α∗	α∗	NOUN
ejpam-2688	119	3	,	,	PUNCT
ejpam-2688	119	4	b∗	b∗	ADJ
ejpam-2688	119	5	)	)	PUNCT
ejpam-2688	120	1	=	=	NOUN
ejpam-2688	120	2	min	min	NOUN
ejpam-2688	120	3	α	α	NOUN
ejpam-2688	120	4	,	,	PUNCT
ejpam-2688	120	5	b	b	PROPN
ejpam-2688	120	6	�	�	PROPN
ejpam-2688	120	7	1	1	NUM
ejpam-2688	120	8	2	2	NUM
ejpam-2688	120	9	‖α‖2	‖α‖2	NOUN
ejpam-2688	120	10	+	+	CCONJ
ejpam-2688	120	11	c	c	PROPN
ejpam-2688	120	12	n∑	n∑	NOUN
ejpam-2688	120	13	i=1	i=1	X
ejpam-2688	120	14	ξd	ξd	PROPN
ejpam-2688	121	1	i	i	PRON
ejpam-2688	121	2	�	�	PROPN
ejpam-2688	121	3	,	,	PUNCT
ejpam-2688	121	4	subject	subject	ADJ
ejpam-2688	121	5	to	to	ADP
ejpam-2688	121	6	j.	j.	PROPN
ejpam-2688	121	7	howe	howe	PROPN
ejpam-2688	121	8	,	,	PUNCT
ejpam-2688	121	9	h.	h.	PROPN
ejpam-2688	121	10	bozdogan	bozdogan	PROPN
ejpam-2688	121	11	/	/	SYM
ejpam-2688	121	12	eur	eur	PROPN
ejpam-2688	121	13	.	.	PUNCT
ejpam-2688	122	1	j.	j.	PROPN
ejpam-2688	122	2	pure	pure	PROPN
ejpam-2688	122	3	appl	appl	PROPN
ejpam-2688	122	4	.	.	PROPN
ejpam-2688	122	5	math	math	PROPN
ejpam-2688	122	6	,	,	PUNCT
ejpam-2688	122	7	9	9	NUM
ejpam-2688	122	8	(	(	PUNCT
ejpam-2688	122	9	2016	2016	NUM
ejpam-2688	122	10	)	)	PUNCT
ejpam-2688	122	11	,	,	PUNCT
ejpam-2688	122	12	216	216	NUM
ejpam-2688	122	13	-	-	SYM
ejpam-2688	122	14	230	230	NUM
ejpam-2688	122	15	221	221	NUM
ejpam-2688	122	16	α	α	NOUN
ejpam-2688	122	17	,	,	PUNCT
ejpam-2688	122	18	x	x	PROPN
ejpam-2688	122	19	i	i	PRON
ejpam-2688	122	20	�	�	PROPN
ejpam-2688	123	1	+	+	CCONJ
ejpam-2688	123	2	b	b	NOUN
ejpam-2688	123	3	≥	≥	NOUN
ejpam-2688	123	4	1−	1−	NUM
ejpam-2688	123	5	ξi	ξi	NOUN
ejpam-2688	123	6	,	,	PUNCT
ejpam-2688	123	7	i	i	PROPN
ejpam-2688	123	8	∈	∈	PROPN
ejpam-2688	123	9	i1	i1	PROPN
ejpam-2688	123	10	,	,	PUNCT
ejpam-2688	123	11	α	α	X
ejpam-2688	123	12	,	,	PUNCT
ejpam-2688	123	13	x	x	PROPN
ejpam-2688	123	14	i	i	PRON
ejpam-2688	123	15	�	�	PROPN
ejpam-2688	123	16	+	+	CCONJ
ejpam-2688	123	17	b	b	X
ejpam-2688	123	18	≤	≤	NUM
ejpam-2688	123	19	−1	−1	NOUN
ejpam-2688	123	20	+	+	CCONJ
ejpam-2688	123	21	ξi	ξi	NOUN
ejpam-2688	123	22	,	,	PUNCT
ejpam-2688	123	23	i	i	PROPN
ejpam-2688	123	24	∈	∈	PROPN
ejpam-2688	123	25	i2	i2	PROPN
ejpam-2688	123	26	,	,	PUNCT
ejpam-2688	123	27	c	c	PROPN
ejpam-2688	123	28	>	>	X
ejpam-2688	123	29	0,ξi	0,ξi	PROPN
ejpam-2688	123	30	≥	≥	NOUN
ejpam-2688	123	31	0	0	NUM
ejpam-2688	123	32	,	,	PUNCT
ejpam-2688	123	33	i	i	PROPN
ejpam-2688	123	34	∈	∈	PROPN
ejpam-2688	123	35	i1	i1	PROPN
ejpam-2688	123	36	⋃	⋃	PROPN
ejpam-2688	123	37	i2	i2	PROPN
ejpam-2688	123	38	when	when	SCONJ
ejpam-2688	123	39	d	d	PROPN
ejpam-2688	123	40	=	=	SYM
ejpam-2688	123	41	1	1	NUM
ejpam-2688	123	42	,	,	PUNCT
ejpam-2688	123	43	we	we	PRON
ejpam-2688	123	44	say	say	VERB
ejpam-2688	123	45	the	the	DET
ejpam-2688	123	46	svm	svm	PROPN
ejpam-2688	123	47	is	be	AUX
ejpam-2688	123	48	l1	l1	PROPN
ejpam-2688	123	49	soft	soft	ADJ
ejpam-2688	123	50	margin	margin	NOUN
ejpam-2688	123	51	trained	train	VERB
ejpam-2688	123	52	,	,	PUNCT
ejpam-2688	123	53	otherwise	otherwise	ADV
ejpam-2688	123	54	,	,	PUNCT
ejpam-2688	123	55	it	it	PRON
ejpam-2688	123	56	’s	’	VERB
ejpam-2688	123	57	l2	l2	VERB
ejpam-2688	123	58	soft	soft	ADJ
ejpam-2688	123	59	margin	margin	NOUN
ejpam-2688	123	60	trained	train	VERB
ejpam-2688	123	61	.	.	PUNCT
ejpam-2688	124	1	c	c	PROPN
ejpam-2688	124	2	is	be	AUX
ejpam-2688	124	3	a	a	DET
ejpam-2688	124	4	regularization	regularization	NOUN
ejpam-2688	124	5	constant	constant	ADJ
ejpam-2688	124	6	,	,	PUNCT
ejpam-2688	124	7	and	and	CCONJ
ejpam-2688	124	8	i1	i1	PROPN
ejpam-2688	124	9	and	and	CCONJ
ejpam-2688	124	10	i2	i2	PROPN
ejpam-2688	124	11	are	be	AUX
ejpam-2688	124	12	slack	slack	NOUN
ejpam-2688	124	13	variables	variable	NOUN
ejpam-2688	124	14	used	use	VERB
ejpam-2688	124	15	to	to	PART
ejpam-2688	124	16	relax	relax	VERB
ejpam-2688	124	17	the	the	DET
ejpam-2688	124	18	inequalities	inequality	NOUN
ejpam-2688	124	19	for	for	ADP
ejpam-2688	124	20	non	non	ADJ
ejpam-2688	124	21	-	-	ADJ
ejpam-2688	124	22	separable	separable	ADJ
ejpam-2688	124	23	data	datum	NOUN
ejpam-2688	124	24	.	.	PUNCT
ejpam-2688	125	1	2.4	2.4	NUM
ejpam-2688	125	2	.	.	PUNCT
ejpam-2688	126	1	multi	multi	ADJ
ejpam-2688	126	2	-	-	ADJ
ejpam-2688	126	3	class	class	ADJ
ejpam-2688	126	4	svm	svm	NOUN
ejpam-2688	126	5	for	for	ADP
ejpam-2688	126	6	data	datum	NOUN
ejpam-2688	126	7	composed	compose	VERB
ejpam-2688	126	8	of	of	ADP
ejpam-2688	126	9	k	k	PROPN
ejpam-2688	126	10	>	>	SYM
ejpam-2688	126	11	2	2	NUM
ejpam-2688	126	12	classes	class	NOUN
ejpam-2688	126	13	indexed	index	VERB
ejpam-2688	126	14	by	by	ADP
ejpam-2688	126	15	k	k	PROPN
ejpam-2688	126	16	,	,	PUNCT
ejpam-2688	126	17	we	we	PRON
ejpam-2688	126	18	consider	consider	VERB
ejpam-2688	126	19	a	a	DET
ejpam-2688	126	20	set	set	NOUN
ejpam-2688	126	21	of	of	ADP
ejpam-2688	126	22	discriminant	discriminant	ADJ
ejpam-2688	126	23	functions	function	NOUN
ejpam-2688	126	24	fk	fk	INTJ
ejpam-2688	126	25	�	�	PROPN
ejpam-2688	126	26	x	x	PUNCT
ejpam-2688	126	27	i	i	PRON
ejpam-2688	126	28	�	�	PROPN
ejpam-2688	126	29	=	=	SYM
ejpam-2688	126	30	αk	αk	PROPN
ejpam-2688	126	31	,	,	PUNCT
ejpam-2688	126	32	ks	ks	X
ejpam-2688	126	33	�	�	PROPN
ejpam-2688	126	34	x	x	PROPN
ejpam-2688	126	35	i	i	NOUN
ejpam-2688	126	36	�	�	VERB
ejpam-2688	126	37	�	�	PROPN
ejpam-2688	126	38	+	+	CCONJ
ejpam-2688	126	39	bk	bk	NOUN
ejpam-2688	126	40	.	.	PUNCT
ejpam-2688	127	1	there	there	PRON
ejpam-2688	127	2	are	be	VERB
ejpam-2688	127	3	several	several	ADJ
ejpam-2688	127	4	ways	way	NOUN
ejpam-2688	127	5	to	to	PART
ejpam-2688	127	6	decompose	decompose	VERB
ejpam-2688	127	7	the	the	DET
ejpam-2688	127	8	multi	multi	ADJ
ejpam-2688	127	9	-	-	ADJ
ejpam-2688	127	10	class	class	ADJ
ejpam-2688	127	11	svm	svm	NOUN
ejpam-2688	127	12	,	,	PUNCT
ejpam-2688	127	13	including	include	VERB
ejpam-2688	127	14	one	one	NUM
ejpam-2688	127	15	-	-	PUNCT
ejpam-2688	127	16	against	against	ADP
ejpam-2688	127	17	all	all	PRON
ejpam-2688	127	18	(	(	PUNCT
ejpam-2688	127	19	oaa	oaa	PROPN
ejpam-2688	127	20	)	)	PUNCT
ejpam-2688	127	21	and	and	CCONJ
ejpam-2688	127	22	one	one	NUM
ejpam-2688	127	23	-	-	PUNCT
ejpam-2688	127	24	against	against	ADP
ejpam-2688	127	25	-	-	PUNCT
ejpam-2688	127	26	one	one	NUM
ejpam-2688	127	27	(	(	PUNCT
ejpam-2688	127	28	oao	oao	PROPN
ejpam-2688	127	29	)	)	PUNCT
ejpam-2688	127	30	see	see	VERB
ejpam-2688	127	31	[	[	X
ejpam-2688	127	32	11	11	NUM
ejpam-2688	127	33	]	]	PUNCT
ejpam-2688	127	34	.	.	PUNCT
ejpam-2688	128	1	the	the	DET
ejpam-2688	128	2	oaa	oaa	NOUN
ejpam-2688	128	3	decomposition	decomposition	NOUN
ejpam-2688	128	4	works	work	VERB
ejpam-2688	128	5	by	by	ADP
ejpam-2688	128	6	trading	trade	VERB
ejpam-2688	128	7	the	the	DET
ejpam-2688	128	8	single	single	ADJ
ejpam-2688	128	9	multi	multi	ADJ
ejpam-2688	128	10	-	-	ADJ
ejpam-2688	128	11	class	class	ADJ
ejpam-2688	128	12	problem	problem	NOUN
ejpam-2688	128	13	for	for	ADP
ejpam-2688	128	14	k	k	PROPN
ejpam-2688	128	15	binary	binary	PROPN
ejpam-2688	128	16	svm	svm	PROPN
ejpam-2688	128	17	problems	problem	NOUN
ejpam-2688	128	18	,	,	PUNCT
ejpam-2688	128	19	where	where	SCONJ
ejpam-2688	128	20	the	the	DET
ejpam-2688	128	21	binary	binary	ADJ
ejpam-2688	128	22	state	state	PROPN
ejpam-2688	128	23	vector	vector	NOUN
ejpam-2688	128	24	y	y	PROPN
ejpam-2688	128	25	′	′	NUM
ejpam-2688	129	1	k	k	PROPN
ejpam-2688	129	2	is	be	AUX
ejpam-2688	129	3	y	y	NOUN
ejpam-2688	129	4	′	′	NUM
ejpam-2688	129	5	k	k	NOUN
ejpam-2688	130	1	=	=	PUNCT
ejpam-2688	130	2	¨	¨	NOUN
ejpam-2688	130	3	1	1	NUM
ejpam-2688	130	4	for	for	ADP
ejpam-2688	130	5	y	y	PROPN
ejpam-2688	130	6	=	=	SYM
ejpam-2688	130	7	yk	yk	PROPN
ejpam-2688	130	8	2	2	NUM
ejpam-2688	130	9	for	for	ADP
ejpam-2688	130	10	y	y	PROPN
ejpam-2688	130	11	6=	6=	PROPN
ejpam-2688	130	12	yk	yk	PROPN
ejpam-2688	130	13	.	.	PUNCT
ejpam-2688	131	1	for	for	ADP
ejpam-2688	131	2	example	example	NOUN
ejpam-2688	131	3	,	,	PUNCT
ejpam-2688	131	4	if	if	SCONJ
ejpam-2688	131	5	we	we	PRON
ejpam-2688	131	6	had	have	VERB
ejpam-2688	131	7	k	k	NOUN
ejpam-2688	131	8	=	=	SYM
ejpam-2688	131	9	4	4	NUM
ejpam-2688	131	10	classes	class	NOUN
ejpam-2688	131	11	a	a	DET
ejpam-2688	131	12	,	,	PUNCT
ejpam-2688	131	13	b	b	NOUN
ejpam-2688	131	14	,	,	PUNCT
ejpam-2688	131	15	c	c	NOUN
ejpam-2688	131	16	,	,	PUNCT
ejpam-2688	131	17	and	and	CCONJ
ejpam-2688	131	18	d	d	X
ejpam-2688	131	19	,	,	PUNCT
ejpam-2688	131	20	oaa	oaa	PROPN
ejpam-2688	131	21	would	would	AUX
ejpam-2688	131	22	solve	solve	VERB
ejpam-2688	131	23	four	four	NUM
ejpam-2688	131	24	binary	binary	ADJ
ejpam-2688	131	25	problems	problem	NOUN
ejpam-2688	131	26	:	:	PUNCT
ejpam-2688	131	27	a	a	DET
ejpam-2688	131	28	vs	vs	ADP
ejpam-2688	131	29	bcd	bcd	PROPN
ejpam-2688	131	30	,	,	PUNCT
ejpam-2688	131	31	b	b	PROPN
ejpam-2688	131	32	vs	vs	ADP
ejpam-2688	131	33	acd	acd	NOUN
ejpam-2688	131	34	,	,	PUNCT
ejpam-2688	131	35	c	c	PROPN
ejpam-2688	131	36	vs	vs	ADP
ejpam-2688	131	37	abd	abd	PROPN
ejpam-2688	131	38	,	,	PUNCT
ejpam-2688	131	39	d	d	PROPN
ejpam-2688	131	40	vs	vs	ADP
ejpam-2688	131	41	abc	abc	PROPN
ejpam-2688	131	42	the	the	DET
ejpam-2688	131	43	multi	multi	ADJ
ejpam-2688	131	44	-	-	ADJ
ejpam-2688	131	45	class	class	ADJ
ejpam-2688	131	46	classification	classification	NOUN
ejpam-2688	131	47	rule	rule	NOUN
ejpam-2688	131	48	used	use	VERB
ejpam-2688	131	49	is	be	AUX
ejpam-2688	131	50	then	then	ADV
ejpam-2688	131	51	q	q	PROPN
ejpam-2688	131	52	�	�	PROPN
ejpam-2688	131	53	x	x	PUNCT
ejpam-2688	131	54	i	i	PRON
ejpam-2688	131	55	�	�	PROPN
ejpam-2688	131	56	=	=	SYM
ejpam-2688	131	57	max	max	PROPN
ejpam-2688	131	58	k=1,2,	k=1,2,	PROPN
ejpam-2688	131	59	...	...	PUNCT
ejpam-2688	131	60	,k	,k	PUNCT
ejpam-2688	131	61	fk	fk	INTJ
ejpam-2688	131	62	�	�	PROPN
ejpam-2688	132	1	x	x	PUNCT
ejpam-2688	132	2	i	i	PRON
ejpam-2688	132	3	�	�	PROPN
ejpam-2688	132	4	.	.	PUNCT
ejpam-2688	133	1	(	(	PUNCT
ejpam-2688	133	2	7	7	X
ejpam-2688	133	3	)	)	PUNCT
ejpam-2688	133	4	oao	oao	PROPN
ejpam-2688	133	5	,	,	PUNCT
ejpam-2688	133	6	on	on	ADP
ejpam-2688	133	7	the	the	DET
ejpam-2688	133	8	other	other	ADJ
ejpam-2688	133	9	hand	hand	NOUN
ejpam-2688	133	10	,	,	PUNCT
ejpam-2688	133	11	solves	solve	VERB
ejpam-2688	133	12	the	the	DET
ejpam-2688	133	13	multi	multi	ADJ
ejpam-2688	133	14	-	-	ADJ
ejpam-2688	133	15	class	class	ADJ
ejpam-2688	133	16	problem	problem	NOUN
ejpam-2688	133	17	by	by	ADP
ejpam-2688	133	18	solving	solve	VERB
ejpam-2688	133	19	k	k	NOUN
ejpam-2688	133	20	′	′	NUM
ejpam-2688	134	1	=	=	PUNCT
ejpam-2688	134	2	k	k	PROPN
ejpam-2688	134	3	(	(	PUNCT
ejpam-2688	134	4	k	k	PROPN
ejpam-2688	134	5	−	−	PROPN
ejpam-2688	134	6	1)/2	1)/2	NUM
ejpam-2688	134	7	binary	binary	ADJ
ejpam-2688	134	8	svm	svm	PROPN
ejpam-2688	134	9	problems	problem	NOUN
ejpam-2688	134	10	,	,	PUNCT
ejpam-2688	134	11	in	in	ADP
ejpam-2688	134	12	which	which	PRON
ejpam-2688	134	13	all	all	DET
ejpam-2688	134	14	pairs	pair	NOUN
ejpam-2688	134	15	of	of	ADP
ejpam-2688	134	16	classes	class	NOUN
ejpam-2688	134	17	are	be	AUX
ejpam-2688	134	18	considered	consider	VERB
ejpam-2688	134	19	.	.	PUNCT
ejpam-2688	135	1	the	the	DET
ejpam-2688	135	2	majority	majority	NOUN
ejpam-2688	135	3	voting	voting	NOUN
ejpam-2688	135	4	strategy	strategy	NOUN
ejpam-2688	135	5	shown	show	VERB
ejpam-2688	135	6	in	in	ADP
ejpam-2688	135	7	(	(	PUNCT
ejpam-2688	135	8	8)	8)	NUM
ejpam-2688	135	9	is	be	AUX
ejpam-2688	135	10	used	use	VERB
ejpam-2688	135	11	to	to	PART
ejpam-2688	135	12	select	select	VERB
ejpam-2688	135	13	the	the	DET
ejpam-2688	135	14	final	final	ADJ
ejpam-2688	135	15	class	class	NOUN
ejpam-2688	135	16	assignments	assignment	NOUN
ejpam-2688	135	17	.	.	PUNCT
ejpam-2688	136	1	the	the	DET
ejpam-2688	136	2	vector	vector	NOUN
ejpam-2688	136	3	vote	vote	NOUN
ejpam-2688	136	4	�	�	PROPN
ejpam-2688	136	5	x	x	PRON
ejpam-2688	136	6	i	i	PRON
ejpam-2688	136	7	�	�	PROPN
ejpam-2688	136	8	indicates	indicate	VERB
ejpam-2688	136	9	the	the	DET
ejpam-2688	136	10	frequency	frequency	NOUN
ejpam-2688	136	11	with	with	ADP
ejpam-2688	136	12	which	which	PRON
ejpam-2688	136	13	,	,	PUNCT
ejpam-2688	136	14	from	from	ADP
ejpam-2688	136	15	all	all	PRON
ejpam-2688	136	16	k	k	PROPN
ejpam-2688	136	17	′	′	NUM
ejpam-2688	136	18	binary	binary	ADJ
ejpam-2688	136	19	svm	svm	PROPN
ejpam-2688	136	20	results	result	NOUN
ejpam-2688	136	21	,	,	PUNCT
ejpam-2688	136	22	the	the	DET
ejpam-2688	136	23	ith	ith	PROPN
ejpam-2688	136	24	datapoint	datapoint	NOUN
ejpam-2688	136	25	was	be	AUX
ejpam-2688	136	26	classified	classify	VERB
ejpam-2688	136	27	into	into	ADP
ejpam-2688	136	28	each	each	DET
ejpam-2688	136	29	group	group	NOUN
ejpam-2688	136	30	.	.	PUNCT
ejpam-2688	137	1	vote	vote	NOUN
ejpam-2688	137	2	�	�	PROPN
ejpam-2688	137	3	x	x	PUNCT
ejpam-2688	137	4	i	i	PRON
ejpam-2688	137	5	�	�	PROPN
ejpam-2688	137	6	=	=	SYM
ejpam-2688	137	7	�	�	PROPN
ejpam-2688	137	8	v1	v1	PROPN
ejpam-2688	137	9	�	�	PROPN
ejpam-2688	138	1	x	x	PUNCT
ejpam-2688	138	2	i	i	PRON
ejpam-2688	138	3	�	�	PROPN
ejpam-2688	138	4	,	,	PUNCT
ejpam-2688	138	5	v2	v2	PROPN
ejpam-2688	138	6	�	�	PROPN
ejpam-2688	138	7	x	x	PUNCT
ejpam-2688	138	8	i	i	PRON
ejpam-2688	138	9	�	�	PROPN
ejpam-2688	138	10	,	,	PUNCT
ejpam-2688	138	11	.	.	PUNCT
ejpam-2688	138	12	.	.	PUNCT
ejpam-2688	138	13	.	.	PUNCT
ejpam-2688	139	1	,	,	PUNCT
ejpam-2688	139	2	vk	vk	INTJ
ejpam-2688	139	3	′	′	NUM
ejpam-2688	139	4	�	�	PROPN
ejpam-2688	139	5	x	x	VERB
ejpam-2688	140	1	i	i	PROPN
ejpam-2688	140	2	�	�	PROPN
ejpam-2688	140	3	�	�	PROPN
ejpam-2688	140	4	q	q	PROPN
ejpam-2688	140	5	�	�	PROPN
ejpam-2688	140	6	x	x	PUNCT
ejpam-2688	140	7	i	i	PRON
ejpam-2688	140	8	�	�	PROPN
ejpam-2688	140	9	=	=	SYM
ejpam-2688	141	1	max	max	PROPN
ejpam-2688	141	2	y	y	PROPN
ejpam-2688	141	3	′	′	NUM
ejpam-2688	141	4	i	i	PRON
ejpam-2688	142	1	=	=	NOUN
ejpam-2688	143	1	1,2,	1,2,	NUM
ejpam-2688	143	2	...	...	PUNCT
ejpam-2688	143	3	,k	,k	PUNCT
ejpam-2688	143	4	′	′	NUM
ejpam-2688	143	5	vote	vote	NOUN
ejpam-2688	143	6	�	�	PROPN
ejpam-2688	143	7	x	x	PUNCT
ejpam-2688	143	8	i	i	PRON
ejpam-2688	143	9	�	�	PROPN
ejpam-2688	143	10	(	(	PUNCT
ejpam-2688	143	11	8)	8)	NUM
ejpam-2688	143	12	using	use	VERB
ejpam-2688	143	13	the	the	DET
ejpam-2688	143	14	same	same	ADJ
ejpam-2688	143	15	groups	group	NOUN
ejpam-2688	143	16	a	a	DET
ejpam-2688	143	17	,	,	PUNCT
ejpam-2688	143	18	b	b	PROPN
ejpam-2688	143	19	,	,	PUNCT
ejpam-2688	143	20	c	c	NOUN
ejpam-2688	143	21	,	,	PUNCT
ejpam-2688	143	22	and	and	CCONJ
ejpam-2688	143	23	d	d	NOUN
ejpam-2688	143	24	,	,	PUNCT
ejpam-2688	143	25	oao	oao	PROPN
ejpam-2688	143	26	solves	solve	VERB
ejpam-2688	143	27	the	the	DET
ejpam-2688	143	28	six	six	NUM
ejpam-2688	143	29	binary	binary	ADJ
ejpam-2688	143	30	svms	svms	NOUN
ejpam-2688	143	31	a	a	DET
ejpam-2688	143	32	vs	vs	ADP
ejpam-2688	143	33	b	b	PROPN
ejpam-2688	143	34	,	,	PUNCT
ejpam-2688	143	35	a	a	DET
ejpam-2688	143	36	vs	vs	ADP
ejpam-2688	143	37	c	c	PROPN
ejpam-2688	143	38	,	,	PUNCT
ejpam-2688	143	39	a	a	DET
ejpam-2688	143	40	vs	vs	ADP
ejpam-2688	143	41	d	d	PROPN
ejpam-2688	143	42	,	,	PUNCT
ejpam-2688	143	43	b	b	PROPN
ejpam-2688	143	44	vs	vs	ADP
ejpam-2688	143	45	c	c	PROPN
ejpam-2688	143	46	,	,	PUNCT
ejpam-2688	143	47	b	b	PROPN
ejpam-2688	143	48	vs	vs	ADP
ejpam-2688	143	49	d	d	PROPN
ejpam-2688	143	50	,	,	PUNCT
ejpam-2688	143	51	c	c	PROPN
ejpam-2688	143	52	vs	vs	ADP
ejpam-2688	143	53	d	d	PROPN
ejpam-2688	143	54	j.	j.	PROPN
ejpam-2688	143	55	howe	howe	PROPN
ejpam-2688	143	56	,	,	PUNCT
ejpam-2688	143	57	h.	h.	PROPN
ejpam-2688	143	58	bozdogan	bozdogan	PROPN
ejpam-2688	143	59	/	/	SYM
ejpam-2688	143	60	eur	eur	PROPN
ejpam-2688	143	61	.	.	PUNCT
ejpam-2688	144	1	j.	j.	PROPN
ejpam-2688	144	2	pure	pure	PROPN
ejpam-2688	144	3	appl	appl	PROPN
ejpam-2688	144	4	.	.	PROPN
ejpam-2688	144	5	math	math	PROPN
ejpam-2688	144	6	,	,	PUNCT
ejpam-2688	144	7	9	9	NUM
ejpam-2688	144	8	(	(	PUNCT
ejpam-2688	144	9	2016	2016	NUM
ejpam-2688	144	10	)	)	PUNCT
ejpam-2688	144	11	,	,	PUNCT
ejpam-2688	144	12	216	216	NUM
ejpam-2688	144	13	-	-	SYM
ejpam-2688	144	14	230	230	NUM
ejpam-2688	144	15	222	222	NUM
ejpam-2688	144	16	2.5	2.5	NUM
ejpam-2688	144	17	.	.	PUNCT
ejpam-2688	145	1	hybridized	hybridize	VERB
ejpam-2688	145	2	covariance	covariance	NOUN
ejpam-2688	145	3	estimation	estimation	NOUN
ejpam-2688	145	4	in	in	ADP
ejpam-2688	145	5	broad	broad	ADJ
ejpam-2688	145	6	terms	term	NOUN
ejpam-2688	145	7	,	,	PUNCT
ejpam-2688	145	8	kda	kda	PROPN
ejpam-2688	145	9	means	mean	VERB
ejpam-2688	145	10	applying	apply	VERB
ejpam-2688	145	11	the	the	DET
ejpam-2688	145	12	appropriate	appropriate	ADJ
ejpam-2688	145	13	calculations	calculation	NOUN
ejpam-2688	145	14	in	in	ADP
ejpam-2688	145	15	sections	section	NOUN
ejpam-2688	145	16	2.2	2.2	NUM
ejpam-2688	145	17	through	through	ADP
ejpam-2688	145	18	2.4	2.4	NUM
ejpam-2688	145	19	after	after	ADP
ejpam-2688	145	20	application	application	NOUN
ejpam-2688	145	21	of	of	ADP
ejpam-2688	145	22	the	the	DET
ejpam-2688	145	23	kernel	kernel	NOUN
ejpam-2688	145	24	trick	trick	NOUN
ejpam-2688	145	25	.	.	PUNCT
ejpam-2688	146	1	when	when	SCONJ
ejpam-2688	146	2	performing	perform	VERB
ejpam-2688	146	3	kda	kda	NOUN
ejpam-2688	146	4	,	,	PUNCT
ejpam-2688	146	5	it	it	PRON
ejpam-2688	146	6	can	can	AUX
ejpam-2688	146	7	be	be	AUX
ejpam-2688	146	8	usually	usually	ADV
ejpam-2688	146	9	expected	expect	VERB
ejpam-2688	146	10	that	that	SCONJ
ejpam-2688	146	11	the	the	DET
ejpam-2688	146	12	within	within	ADP
ejpam-2688	146	13	-	-	PUNCT
ejpam-2688	146	14	group	group	NOUN
ejpam-2688	146	15	covariance	covariance	NOUN
ejpam-2688	146	16	matrix	matrix	NOUN
ejpam-2688	146	17	(	(	PUNCT
ejpam-2688	146	18	4	4	NUM
ejpam-2688	146	19	)	)	PUNCT
ejpam-2688	146	20	wo	will	AUX
ejpam-2688	146	21	n’t	not	PART
ejpam-2688	146	22	be	be	AUX
ejpam-2688	146	23	nonsingular	nonsingular	ADJ
ejpam-2688	146	24	or	or	CCONJ
ejpam-2688	146	25	positive	positive	ADJ
ejpam-2688	146	26	definite	definite	ADJ
ejpam-2688	146	27	.	.	PUNCT
ejpam-2688	147	1	singularity	singularity	NOUN
ejpam-2688	147	2	of	of	ADP
ejpam-2688	147	3	this	this	DET
ejpam-2688	147	4	kernel	kernel	NOUN
ejpam-2688	147	5	covariance	covariance	NOUN
ejpam-2688	147	6	matrix	matrix	NOUN
ejpam-2688	147	7	is	be	AUX
ejpam-2688	147	8	a	a	DET
ejpam-2688	147	9	problem	problem	NOUN
ejpam-2688	147	10	that	that	PRON
ejpam-2688	147	11	has	have	AUX
ejpam-2688	147	12	attracted	attract	VERB
ejpam-2688	147	13	many	many	ADJ
ejpam-2688	147	14	researchers	researcher	NOUN
ejpam-2688	147	15	,	,	PUNCT
ejpam-2688	147	16	and	and	CCONJ
ejpam-2688	147	17	many	many	ADJ
ejpam-2688	147	18	methods	method	NOUN
ejpam-2688	147	19	have	have	AUX
ejpam-2688	147	20	been	be	AUX
ejpam-2688	147	21	proposed	propose	VERB
ejpam-2688	147	22	to	to	PART
ejpam-2688	147	23	make	make	VERB
ejpam-2688	147	24	the	the	DET
ejpam-2688	147	25	matrix	matrix	NOUN
ejpam-2688	147	26	well	well	ADV
ejpam-2688	147	27	-	-	PUNCT
ejpam-2688	147	28	conditioned	condition	VERB
ejpam-2688	147	29	.	.	PUNCT
ejpam-2688	148	1	in	in	ADP
ejpam-2688	148	2	[	[	X
ejpam-2688	148	3	12	12	NUM
ejpam-2688	148	4	]	]	PUNCT
ejpam-2688	148	5	,	,	PUNCT
ejpam-2688	148	6	liberati	liberati	PROPN
ejpam-2688	148	7	et	et	PROPN
ejpam-2688	148	8	al	al	PROPN
ejpam-2688	148	9	.	.	PROPN
ejpam-2688	148	10	introduced	introduce	VERB
ejpam-2688	148	11	a	a	DET
ejpam-2688	148	12	hybridized	hybridize	VERB
ejpam-2688	148	13	covariance	covariance	NOUN
ejpam-2688	148	14	estimator	estimator	NOUN
ejpam-2688	148	15	σ̂sta_cse	σ̂sta_cse	PROPN
ejpam-2688	148	16	that	that	PRON
ejpam-2688	148	17	joins	join	VERB
ejpam-2688	148	18	the	the	DET
ejpam-2688	148	19	stabilization	stabilization	NOUN
ejpam-2688	148	20	technique	technique	NOUN
ejpam-2688	148	21	of	of	ADP
ejpam-2688	148	22	thomaz	thomaz	PROPN
ejpam-2688	148	23	[	[	X
ejpam-2688	148	24	15	15	NUM
ejpam-2688	148	25	]	]	PUNCT
ejpam-2688	148	26	with	with	ADP
ejpam-2688	148	27	the	the	DET
ejpam-2688	148	28	convex	convex	ADJ
ejpam-2688	148	29	sum	sum	NOUN
ejpam-2688	148	30	covariance	covariance	NOUN
ejpam-2688	148	31	estimator	estimator	NOUN
ejpam-2688	148	32	shrinkage	shrinkage	NOUN
ejpam-2688	148	33	technique	technique	NOUN
ejpam-2688	148	34	of	of	ADP
ejpam-2688	148	35	press	press	NOUN
ejpam-2688	148	36	[	[	X
ejpam-2688	148	37	14	14	NUM
ejpam-2688	148	38	]	]	PUNCT
ejpam-2688	148	39	and	and	CCONJ
ejpam-2688	148	40	chen	chen	PROPN
ejpam-2688	149	1	[	[	X
ejpam-2688	149	2	6	6	NUM
ejpam-2688	149	3	]	]	PUNCT
ejpam-2688	149	4	.	.	PUNCT
ejpam-2688	150	1	there	there	PRON
ejpam-2688	150	2	is	be	VERB
ejpam-2688	150	3	an	an	DET
ejpam-2688	150	4	optional	optional	ADJ
ejpam-2688	150	5	third	third	ADJ
ejpam-2688	150	6	step	step	NOUN
ejpam-2688	150	7	,	,	PUNCT
ejpam-2688	150	8	which	which	PRON
ejpam-2688	150	9	we	we	PRON
ejpam-2688	150	10	apply	apply	VERB
ejpam-2688	150	11	to	to	PART
ejpam-2688	150	12	help	help	VERB
ejpam-2688	150	13	regularize	regularize	VERB
ejpam-2688	150	14	especially	especially	ADV
ejpam-2688	150	15	sparse	sparse	ADJ
ejpam-2688	150	16	and	and	CCONJ
ejpam-2688	150	17	/	/	SYM
ejpam-2688	150	18	or	or	CCONJ
ejpam-2688	150	19	singular	singular	ADJ
ejpam-2688	150	20	matrices	matrix	NOUN
ejpam-2688	150	21	.	.	PUNCT
ejpam-2688	151	1	after	after	ADP
ejpam-2688	151	2	computing	compute	VERB
ejpam-2688	151	3	the	the	DET
ejpam-2688	151	4	hybrid	hybrid	NOUN
ejpam-2688	151	5	stabilized	stabilize	VERB
ejpam-2688	151	6	kernel	kernel	NOUN
ejpam-2688	151	7	matrix	matrix	NOUN
ejpam-2688	151	8	,	,	PUNCT
ejpam-2688	151	9	we	we	PRON
ejpam-2688	151	10	compute	compute	VERB
ejpam-2688	151	11	its	its	PRON
ejpam-2688	151	12	singular	singular	ADJ
ejpam-2688	151	13	values	value	NOUN
ejpam-2688	151	14	.	.	PUNCT
ejpam-2688	152	1	σ̂sta_cse	σ̂sta_cse	NOUN
ejpam-2688	152	2	is	be	AUX
ejpam-2688	152	3	then	then	ADV
ejpam-2688	152	4	replaced	replace	VERB
ejpam-2688	152	5	with	with	ADP
ejpam-2688	152	6	a	a	DET
ejpam-2688	152	7	diagonal	diagonal	ADJ
ejpam-2688	152	8	matrix	matrix	NOUN
ejpam-2688	152	9	of	of	ADP
ejpam-2688	152	10	some	some	DET
ejpam-2688	152	11	subset	subset	NOUN
ejpam-2688	152	12	of	of	ADP
ejpam-2688	152	13	the	the	DET
ejpam-2688	152	14	largest	large	ADJ
ejpam-2688	152	15	singular	singular	ADJ
ejpam-2688	152	16	values	value	NOUN
ejpam-2688	152	17	as	as	ADP
ejpam-2688	152	18	a	a	DET
ejpam-2688	152	19	reduced	reduced	ADJ
ejpam-2688	152	20	rank	rank	NOUN
ejpam-2688	152	21	approximation	approximation	NOUN
ejpam-2688	152	22	σ̂∗sta_cse	σ̂∗sta_cse	PROPN
ejpam-2688	152	23	.	.	PUNCT
ejpam-2688	153	1	for	for	ADP
ejpam-2688	153	2	the	the	DET
ejpam-2688	153	3	real	real	ADJ
ejpam-2688	153	4	datasets	dataset	NOUN
ejpam-2688	153	5	analyzed	analyze	VERB
ejpam-2688	153	6	in	in	ADP
ejpam-2688	153	7	this	this	DET
ejpam-2688	153	8	research	research	NOUN
ejpam-2688	153	9	,	,	PUNCT
ejpam-2688	153	10	we	we	PRON
ejpam-2688	153	11	kept	keep	VERB
ejpam-2688	153	12	the	the	DET
ejpam-2688	153	13	top	top	ADJ
ejpam-2688	153	14	25	25	NUM
ejpam-2688	153	15	when	when	SCONJ
ejpam-2688	153	16	further	further	ADJ
ejpam-2688	153	17	regularization	regularization	NOUN
ejpam-2688	153	18	was	be	AUX
ejpam-2688	153	19	necessary	necessary	ADJ
ejpam-2688	153	20	.	.	PUNCT
ejpam-2688	154	1	3	3	X
ejpam-2688	154	2	.	.	X
ejpam-2688	154	3	cross	cross	ADJ
ejpam-2688	154	4	-	-	ADJ
ejpam-2688	154	5	validation	validation	ADJ
ejpam-2688	154	6	genetic	genetic	ADJ
ejpam-2688	154	7	algorithm	algorithm	NOUN
ejpam-2688	154	8	for	for	ADP
ejpam-2688	154	9	optimization	optimization	NOUN
ejpam-2688	154	10	the	the	DET
ejpam-2688	154	11	genetic	genetic	ADJ
ejpam-2688	154	12	algorithm	algorithm	NOUN
ejpam-2688	154	13	(	(	PUNCT
ejpam-2688	154	14	ga	ga	NOUN
ejpam-2688	154	15	)	)	PUNCT
ejpam-2688	154	16	is	be	AUX
ejpam-2688	154	17	a	a	DET
ejpam-2688	154	18	stochastic	stochastic	ADJ
ejpam-2688	154	19	search	search	NOUN
ejpam-2688	154	20	algorithm	algorithm	NOUN
ejpam-2688	154	21	that	that	PRON
ejpam-2688	154	22	borrows	borrow	VERB
ejpam-2688	154	23	concepts	concept	NOUN
ejpam-2688	154	24	from	from	ADP
ejpam-2688	154	25	biological	biological	ADJ
ejpam-2688	154	26	evolution	evolution	NOUN
ejpam-2688	155	1	[	[	X
ejpam-2688	155	2	7–10	7–10	X
ejpam-2688	155	3	]	]	X
ejpam-2688	155	4	;	;	PUNCT
ejpam-2688	155	5	it	it	PRON
ejpam-2688	155	6	has	have	AUX
ejpam-2688	155	7	been	be	AUX
ejpam-2688	155	8	used	use	VERB
ejpam-2688	155	9	successfully	successfully	ADV
ejpam-2688	155	10	in	in	ADP
ejpam-2688	155	11	a	a	DET
ejpam-2688	155	12	wide	wide	ADJ
ejpam-2688	155	13	range	range	NOUN
ejpam-2688	155	14	of	of	ADP
ejpam-2688	155	15	statistical	statistical	ADJ
ejpam-2688	155	16	modeling	modeling	NOUN
ejpam-2688	155	17	applications	application	NOUN
ejpam-2688	155	18	.	.	PUNCT
ejpam-2688	156	1	the	the	DET
ejpam-2688	156	2	solution	solution	NOUN
ejpam-2688	156	3	space	space	NOUN
ejpam-2688	156	4	for	for	ADP
ejpam-2688	156	5	a	a	DET
ejpam-2688	156	6	problem	problem	NOUN
ejpam-2688	156	7	is	be	AUX
ejpam-2688	156	8	explored	explore	VERB
ejpam-2688	156	9	via	via	ADP
ejpam-2688	156	10	an	an	DET
ejpam-2688	156	11	ensemble	ensemble	NOUN
ejpam-2688	156	12	of	of	ADP
ejpam-2688	156	13	strings	string	NOUN
ejpam-2688	156	14	which	which	PRON
ejpam-2688	156	15	represent	represent	VERB
ejpam-2688	156	16	possible	possible	ADJ
ejpam-2688	156	17	solutions	solution	NOUN
ejpam-2688	156	18	.	.	PUNCT
ejpam-2688	157	1	in	in	ADP
ejpam-2688	157	2	the	the	DET
ejpam-2688	157	3	parlance	parlance	NOUN
ejpam-2688	157	4	of	of	ADP
ejpam-2688	157	5	the	the	DET
ejpam-2688	157	6	ga	ga	PROPN
ejpam-2688	157	7	,	,	PUNCT
ejpam-2688	157	8	these	these	DET
ejpam-2688	157	9	solution	solution	NOUN
ejpam-2688	157	10	strings	string	NOUN
ejpam-2688	157	11	are	be	AUX
ejpam-2688	157	12	called	call	VERB
ejpam-2688	157	13	chromosomes	chromosome	NOUN
ejpam-2688	157	14	.	.	PUNCT
ejpam-2688	158	1	chromosomes	chromosome	NOUN
ejpam-2688	158	2	are	be	AUX
ejpam-2688	158	3	created	create	VERB
ejpam-2688	158	4	by	by	ADP
ejpam-2688	158	5	encoding	encode	VERB
ejpam-2688	158	6	solutions	solution	NOUN
ejpam-2688	158	7	using	use	VERB
ejpam-2688	158	8	a	a	DET
ejpam-2688	158	9	fixed	fix	VERB
ejpam-2688	158	10	,	,	PUNCT
ejpam-2688	158	11	finite	finite	ADJ
ejpam-2688	158	12	-	-	ADJ
ejpam-2688	158	13	length	length	ADJ
ejpam-2688	158	14	alphabet	alphabet	NOUN
ejpam-2688	158	15	of	of	ADP
ejpam-2688	158	16	symbols	symbol	NOUN
ejpam-2688	158	17	.	.	PUNCT
ejpam-2688	159	1	solutions	solution	NOUN
ejpam-2688	159	2	for	for	ADP
ejpam-2688	159	3	the	the	DET
ejpam-2688	159	4	ga	ga	PROPN
ejpam-2688	159	5	are	be	AUX
ejpam-2688	159	6	most	most	ADV
ejpam-2688	159	7	typically	typically	ADV
ejpam-2688	159	8	coded	code	VERB
ejpam-2688	159	9	as	as	ADP
ejpam-2688	159	10	binary	binary	ADJ
ejpam-2688	159	11	strings	string	NOUN
ejpam-2688	159	12	.	.	PUNCT
ejpam-2688	160	1	individual	individual	ADJ
ejpam-2688	160	2	chromosomes	chromosome	NOUN
ejpam-2688	160	3	are	be	AUX
ejpam-2688	160	4	allowed	allow	VERB
ejpam-2688	160	5	to	to	PART
ejpam-2688	160	6	compete	compete	VERB
ejpam-2688	160	7	with	with	ADP
ejpam-2688	160	8	each	each	DET
ejpam-2688	160	9	other	other	ADJ
ejpam-2688	160	10	a	a	DET
ejpam-2688	160	11	la	la	X
ejpam-2688	160	12	natural	natural	ADJ
ejpam-2688	160	13	selection	selection	NOUN
ejpam-2688	160	14	,	,	PUNCT
ejpam-2688	160	15	to	to	PART
ejpam-2688	160	16	create	create	VERB
ejpam-2688	160	17	better	well	ADJ
ejpam-2688	160	18	solutions	solution	NOUN
ejpam-2688	160	19	,	,	PUNCT
ejpam-2688	160	20	with	with	ADP
ejpam-2688	160	21	the	the	DET
ejpam-2688	160	22	goal	goal	NOUN
ejpam-2688	160	23	to	to	PART
ejpam-2688	160	24	optimize	optimize	VERB
ejpam-2688	160	25	some	some	DET
ejpam-2688	160	26	objective	objective	ADJ
ejpam-2688	160	27	function	function	NOUN
ejpam-2688	160	28	.	.	PUNCT
ejpam-2688	161	1	operational	operational	ADJ
ejpam-2688	161	2	details	detail	NOUN
ejpam-2688	161	3	of	of	ADP
ejpam-2688	161	4	the	the	DET
ejpam-2688	161	5	ga	ga	PROPN
ejpam-2688	161	6	can	can	AUX
ejpam-2688	161	7	be	be	AUX
ejpam-2688	161	8	found	find	VERB
ejpam-2688	161	9	in	in	ADP
ejpam-2688	161	10	the	the	DET
ejpam-2688	161	11	above	above	ADV
ejpam-2688	161	12	-	-	PUNCT
ejpam-2688	161	13	mentioned	mention	VERB
ejpam-2688	161	14	sources	source	NOUN
ejpam-2688	161	15	,	,	PUNCT
ejpam-2688	161	16	or	or	CCONJ
ejpam-2688	161	17	any	any	DET
ejpam-2688	161	18	number	number	NOUN
ejpam-2688	161	19	of	of	ADP
ejpam-2688	161	20	others	other	NOUN
ejpam-2688	161	21	.	.	PUNCT
ejpam-2688	162	1	for	for	ADP
ejpam-2688	162	2	the	the	DET
ejpam-2688	162	3	problem	problem	NOUN
ejpam-2688	162	4	of	of	ADP
ejpam-2688	162	5	selecting	select	VERB
ejpam-2688	162	6	a	a	DET
ejpam-2688	162	7	subset	subset	NOUN
ejpam-2688	162	8	of	of	ADP
ejpam-2688	162	9	p	p	PROPN
ejpam-2688	162	10	variables	variable	NOUN
ejpam-2688	162	11	,	,	PUNCT
ejpam-2688	162	12	a	a	DET
ejpam-2688	162	13	chromosome	chromosome	NOUN
ejpam-2688	162	14	is	be	AUX
ejpam-2688	162	15	a	a	DET
ejpam-2688	162	16	p	p	ADJ
ejpam-2688	162	17	-	-	PUNCT
ejpam-2688	162	18	length	length	NOUN
ejpam-2688	162	19	vector	vector	NOUN
ejpam-2688	162	20	such	such	ADJ
ejpam-2688	162	21	that	that	SCONJ
ejpam-2688	162	22	each	each	DET
ejpam-2688	162	23	element	element	NOUN
ejpam-2688	162	24	represents	represent	VERB
ejpam-2688	162	25	the	the	DET
ejpam-2688	162	26	presence	presence	NOUN
ejpam-2688	162	27	(	(	PUNCT
ejpam-2688	162	28	1	1	NUM
ejpam-2688	162	29	)	)	PUNCT
ejpam-2688	162	30	or	or	CCONJ
ejpam-2688	162	31	absence	absence	NOUN
ejpam-2688	162	32	(	(	PUNCT
ejpam-2688	162	33	0	0	NUM
ejpam-2688	162	34	)	)	PUNCT
ejpam-2688	162	35	of	of	ADP
ejpam-2688	162	36	a	a	DET
ejpam-2688	162	37	specific	specific	ADJ
ejpam-2688	162	38	variable	variable	NOUN
ejpam-2688	162	39	.	.	PUNCT
ejpam-2688	163	1	an	an	DET
ejpam-2688	163	2	example	example	NOUN
ejpam-2688	163	3	chromosome	chromosome	NOUN
ejpam-2688	163	4	may	may	AUX
ejpam-2688	163	5	be	be	AUX
ejpam-2688	163	6	[	[	X
ejpam-2688	163	7	10011001	10011001	NUM
ejpam-2688	163	8	]	]	PUNCT
ejpam-2688	163	9	;	;	PUNCT
ejpam-2688	163	10	in	in	ADP
ejpam-2688	163	11	this	this	DET
ejpam-2688	163	12	case	case	NOUN
ejpam-2688	163	13	,	,	PUNCT
ejpam-2688	163	14	predictors	predictor	NOUN
ejpam-2688	163	15	1,4,5,8	1,4,5,8	NUM
ejpam-2688	163	16	are	be	AUX
ejpam-2688	163	17	selected	select	VERB
ejpam-2688	163	18	while	while	SCONJ
ejpam-2688	163	19	2,3,6,7	2,3,6,7	NUM
ejpam-2688	163	20	are	be	AUX
ejpam-2688	163	21	not	not	PART
ejpam-2688	163	22	.	.	PUNCT
ejpam-2688	164	1	our	our	PRON
ejpam-2688	164	2	algorithm	algorithm	NOUN
ejpam-2688	164	3	uses	use	VERB
ejpam-2688	164	4	the	the	DET
ejpam-2688	164	5	ga	ga	PROPN
ejpam-2688	164	6	to	to	PART
ejpam-2688	164	7	simultaneously	simultaneously	ADV
ejpam-2688	164	8	determine	determine	VERB
ejpam-2688	164	9	the	the	DET
ejpam-2688	164	10	best	good	ADJ
ejpam-2688	164	11	subset	subset	NOUN
ejpam-2688	164	12	of	of	ADP
ejpam-2688	164	13	variables	variable	NOUN
ejpam-2688	164	14	and	and	CCONJ
ejpam-2688	164	15	the	the	DET
ejpam-2688	164	16	best	good	ADJ
ejpam-2688	164	17	kernel	kernel	NOUN
ejpam-2688	164	18	function	function	NOUN
ejpam-2688	164	19	.	.	PUNCT
ejpam-2688	165	1	we	we	PRON
ejpam-2688	165	2	do	do	VERB
ejpam-2688	165	3	this	this	PRON
ejpam-2688	165	4	by	by	ADP
ejpam-2688	165	5	coding	code	VERB
ejpam-2688	165	6	the	the	DET
ejpam-2688	165	7	different	different	ADJ
ejpam-2688	165	8	kernel	kernel	NOUN
ejpam-2688	165	9	functions	function	NOUN
ejpam-2688	165	10	into	into	ADP
ejpam-2688	165	11	a	a	DET
ejpam-2688	165	12	binary	binary	ADJ
ejpam-2688	165	13	string	string	NOUN
ejpam-2688	165	14	,	,	PUNCT
ejpam-2688	165	15	and	and	CCONJ
ejpam-2688	165	16	appending	append	VERB
ejpam-2688	165	17	this	this	PRON
ejpam-2688	165	18	onto	onto	ADP
ejpam-2688	165	19	the	the	DET
ejpam-2688	165	20	feature	feature	NOUN
ejpam-2688	165	21	selection	selection	NOUN
ejpam-2688	165	22	string	string	NOUN
ejpam-2688	165	23	.	.	PUNCT
ejpam-2688	166	1	we	we	PRON
ejpam-2688	166	2	have	have	VERB
ejpam-2688	166	3	9	9	NUM
ejpam-2688	166	4	kernels	kernel	NOUN
ejpam-2688	166	5	to	to	PART
ejpam-2688	166	6	choose	choose	VERB
ejpam-2688	166	7	from	from	ADP
ejpam-2688	166	8	;	;	PUNCT
ejpam-2688	166	9	9	9	NUM
ejpam-2688	166	10	in	in	ADP
ejpam-2688	166	11	binary	binary	ADJ
ejpam-2688	166	12	representation	representation	NOUN
ejpam-2688	166	13	requires	require	VERB
ejpam-2688	166	14	4	4	NUM
ejpam-2688	166	15	bits	bit	NOUN
ejpam-2688	166	16	.	.	PUNCT
ejpam-2688	167	1	hence	hence	ADV
ejpam-2688	167	2	,	,	PUNCT
ejpam-2688	167	3	the	the	DET
ejpam-2688	167	4	kernels	kernel	NOUN
ejpam-2688	167	5	are	be	AUX
ejpam-2688	167	6	represented	represent	VERB
ejpam-2688	167	7	by	by	ADP
ejpam-2688	167	8	binary	binary	ADJ
ejpam-2688	167	9	strings	string	NOUN
ejpam-2688	167	10	from	from	ADP
ejpam-2688	167	11	[	[	X
ejpam-2688	167	12	0000	0000	NUM
ejpam-2688	167	13	]	]	PUNCT
ejpam-2688	167	14	(	(	PUNCT
ejpam-2688	167	15	linear	linear	NOUN
ejpam-2688	167	16	polynomial	polynomial	NOUN
ejpam-2688	167	17	)	)	PUNCT
ejpam-2688	167	18	to	to	ADP
ejpam-2688	167	19	[	[	X
ejpam-2688	167	20	1001	1001	NUM
ejpam-2688	167	21	]	]	X
ejpam-2688	167	22	(	(	PUNCT
ejpam-2688	167	23	inverse	inverse	NOUN
ejpam-2688	167	24	multi	multi	NOUN
ejpam-2688	167	25	-	-	ADJ
ejpam-2688	167	26	quadric	quadric	ADJ
ejpam-2688	167	27	)	)	PUNCT
ejpam-2688	167	28	.	.	PUNCT
ejpam-2688	168	1	the	the	DET
ejpam-2688	168	2	allowed	allow	VERB
ejpam-2688	168	3	kernel	kernel	PROPN
ejpam-2688	168	4	binary	binary	PROPN
ejpam-2688	168	5	codes	code	NOUN
ejpam-2688	168	6	are	be	AUX
ejpam-2688	168	7	shown	show	VERB
ejpam-2688	168	8	along	along	ADP
ejpam-2688	168	9	with	with	ADP
ejpam-2688	168	10	the	the	DET
ejpam-2688	168	11	kernel	kernel	NOUN
ejpam-2688	168	12	functions	function	NOUN
ejpam-2688	168	13	in	in	ADP
ejpam-2688	168	14	table	table	NOUN
ejpam-2688	168	15	1	1	NUM
ejpam-2688	168	16	.	.	PUNCT
ejpam-2688	169	1	an	an	DET
ejpam-2688	169	2	obvious	obvious	ADJ
ejpam-2688	169	3	issue	issue	NOUN
ejpam-2688	169	4	is	be	AUX
ejpam-2688	169	5	that	that	SCONJ
ejpam-2688	169	6	four	four	NUM
ejpam-2688	169	7	binary	binary	ADJ
ejpam-2688	169	8	digits	digit	NOUN
ejpam-2688	169	9	can	can	AUX
ejpam-2688	169	10	be	be	AUX
ejpam-2688	169	11	used	use	VERB
ejpam-2688	169	12	to	to	PART
ejpam-2688	169	13	represent	represent	VERB
ejpam-2688	169	14	all	all	DET
ejpam-2688	169	15	the	the	DET
ejpam-2688	169	16	counting	counting	NOUN
ejpam-2688	169	17	numbers	number	NOUN
ejpam-2688	169	18	up	up	ADP
ejpam-2688	169	19	to	to	PART
ejpam-2688	169	20	fifteen	fifteen	NUM
ejpam-2688	169	21	,	,	PUNCT
ejpam-2688	169	22	and	and	CCONJ
ejpam-2688	169	23	yet	yet	ADV
ejpam-2688	169	24	we	we	PRON
ejpam-2688	169	25	only	only	ADV
ejpam-2688	169	26	have	have	VERB
ejpam-2688	169	27	nine	nine	NUM
ejpam-2688	169	28	kernels	kernel	NOUN
ejpam-2688	169	29	.	.	PUNCT
ejpam-2688	170	1	hence	hence	ADV
ejpam-2688	170	2	,	,	PUNCT
ejpam-2688	170	3	the	the	DET
ejpam-2688	170	4	ga	ga	PROPN
ejpam-2688	170	5	’s	’s	PART
ejpam-2688	170	6	crossover	crossover	NOUN
ejpam-2688	170	7	and	and	CCONJ
ejpam-2688	170	8	mutation	mutation	NOUN
ejpam-2688	170	9	operators	operator	NOUN
ejpam-2688	170	10	can	can	AUX
ejpam-2688	170	11	both	both	PRON
ejpam-2688	170	12	generate	generate	VERB
ejpam-2688	170	13	illegal	illegal	ADJ
ejpam-2688	170	14	strings	string	NOUN
ejpam-2688	170	15	representing	represent	VERB
ejpam-2688	170	16	kernels	kernel	NOUN
ejpam-2688	170	17	that	that	PRON
ejpam-2688	170	18	we	we	PRON
ejpam-2688	170	19	do	do	AUX
ejpam-2688	170	20	n’t	not	PART
ejpam-2688	170	21	have	have	VERB
ejpam-2688	170	22	.	.	PUNCT
ejpam-2688	171	1	when	when	SCONJ
ejpam-2688	171	2	this	this	PRON
ejpam-2688	171	3	occurs	occur	VERB
ejpam-2688	171	4	,	,	PUNCT
ejpam-2688	171	5	we	we	PRON
ejpam-2688	171	6	apply	apply	VERB
ejpam-2688	171	7	modular	modular	ADJ
ejpam-2688	171	8	arithmetic	arithmetic	ADJ
ejpam-2688	171	9	to	to	PART
ejpam-2688	171	10	scale	scale	VERB
ejpam-2688	171	11	back	back	ADP
ejpam-2688	171	12	the	the	DET
ejpam-2688	171	13	offending	offending	ADJ
ejpam-2688	171	14	binary	binary	ADJ
ejpam-2688	171	15	string	string	NOUN
ejpam-2688	171	16	.	.	PUNCT
ejpam-2688	172	1	for	for	ADP
ejpam-2688	172	2	example	example	NOUN
ejpam-2688	172	3	,	,	PUNCT
ejpam-2688	172	4	say	say	VERB
ejpam-2688	172	5	the	the	DET
ejpam-2688	172	6	kernel	kernel	PROPN
ejpam-2688	172	7	portion	portion	NOUN
ejpam-2688	172	8	of	of	ADP
ejpam-2688	172	9	a	a	DET
ejpam-2688	172	10	chromosome	chromosome	NOUN
ejpam-2688	172	11	is	be	AUX
ejpam-2688	172	12	[	[	X
ejpam-2688	172	13	1100	1100	NUM
ejpam-2688	172	14	]	]	PUNCT
ejpam-2688	172	15	,	,	PUNCT
ejpam-2688	172	16	encoding	encode	VERB
ejpam-2688	172	17	the	the	DET
ejpam-2688	172	18	nonexistent	nonexistent	ADJ
ejpam-2688	172	19	twelfth	twelfth	ADJ
ejpam-2688	172	20	kernel	kernel	NOUN
ejpam-2688	172	21	.	.	PUNCT
ejpam-2688	173	1	applying	apply	VERB
ejpam-2688	173	2	modular	modular	ADJ
ejpam-2688	173	3	arithmetic	arithmetic	ADJ
ejpam-2688	173	4	,	,	PUNCT
ejpam-2688	173	5	we	we	PRON
ejpam-2688	173	6	have	have	VERB
ejpam-2688	173	7	mod(12,9	mod(12,9	NOUN
ejpam-2688	173	8	)	)	PUNCT
ejpam-2688	174	1	=	=	SYM
ejpam-2688	174	2	3	3	NUM
ejpam-2688	174	3	=	=	SYM
ejpam-2688	175	1	[	[	X
ejpam-2688	175	2	0011	0011	NUM
ejpam-2688	175	3	]	]	PUNCT
ejpam-2688	175	4	.	.	PUNCT
ejpam-2688	176	1	thus	thus	ADV
ejpam-2688	176	2	,	,	PUNCT
ejpam-2688	176	3	we	we	PRON
ejpam-2688	176	4	replace	replace	VERB
ejpam-2688	176	5	a	a	DET
ejpam-2688	176	6	string	string	NOUN
ejpam-2688	176	7	that	that	PRON
ejpam-2688	176	8	is	be	AUX
ejpam-2688	176	9	too	too	ADV
ejpam-2688	176	10	large	large	ADJ
ejpam-2688	176	11	with	with	ADP
ejpam-2688	176	12	its	its	PRON
ejpam-2688	176	13	remainder	remainder	NOUN
ejpam-2688	176	14	when	when	SCONJ
ejpam-2688	176	15	divided	divide	VERB
ejpam-2688	176	16	by	by	ADP
ejpam-2688	176	17	[	[	X
ejpam-2688	176	18	1001	1001	NUM
ejpam-2688	176	19	]	]	PUNCT
ejpam-2688	176	20	.	.	PUNCT
ejpam-2688	177	1	this	this	DET
ejpam-2688	177	2	repair	repair	NOUN
ejpam-2688	177	3	mechanism	mechanism	NOUN
ejpam-2688	177	4	will	will	AUX
ejpam-2688	177	5	impart	impart	VERB
ejpam-2688	177	6	a	a	DET
ejpam-2688	177	7	slight	slight	ADJ
ejpam-2688	177	8	bias	bias	NOUN
ejpam-2688	177	9	to	to	ADP
ejpam-2688	177	10	the	the	DET
ejpam-2688	177	11	six	six	NUM
ejpam-2688	177	12	simplest	simple	ADJ
ejpam-2688	177	13	kernel	kernel	NOUN
ejpam-2688	177	14	functions	function	NOUN
ejpam-2688	177	15	,	,	PUNCT
ejpam-2688	177	16	but	but	CCONJ
ejpam-2688	177	17	does	do	AUX
ejpam-2688	177	18	not	not	PART
ejpam-2688	177	19	seem	seem	VERB
ejpam-2688	177	20	to	to	ADP
ejpam-2688	177	21	j.	j.	PROPN
ejpam-2688	177	22	howe	howe	PROPN
ejpam-2688	177	23	,	,	PUNCT
ejpam-2688	177	24	h.	h.	PROPN
ejpam-2688	177	25	bozdogan	bozdogan	PROPN
ejpam-2688	177	26	/	/	SYM
ejpam-2688	177	27	eur	eur	PROPN
ejpam-2688	177	28	.	.	PUNCT
ejpam-2688	178	1	j.	j.	PROPN
ejpam-2688	178	2	pure	pure	PROPN
ejpam-2688	178	3	appl	appl	PROPN
ejpam-2688	178	4	.	.	PROPN
ejpam-2688	178	5	math	math	PROPN
ejpam-2688	178	6	,	,	PUNCT
ejpam-2688	178	7	9	9	NUM
ejpam-2688	178	8	(	(	PUNCT
ejpam-2688	178	9	2016	2016	NUM
ejpam-2688	178	10	)	)	PUNCT
ejpam-2688	178	11	,	,	PUNCT
ejpam-2688	178	12	216	216	NUM
ejpam-2688	178	13	-	-	SYM
ejpam-2688	178	14	230	230	NUM
ejpam-2688	178	15	223	223	NUM
ejpam-2688	178	16	be	be	AUX
ejpam-2688	178	17	have	have	VERB
ejpam-2688	178	18	any	any	DET
ejpam-2688	178	19	systemic	systemic	ADJ
ejpam-2688	178	20	effect	effect	NOUN
ejpam-2688	178	21	.	.	PUNCT
ejpam-2688	179	1	hence	hence	ADV
ejpam-2688	179	2	,	,	PUNCT
ejpam-2688	179	3	a	a	DET
ejpam-2688	179	4	chromosome	chromosome	NOUN
ejpam-2688	179	5	in	in	ADP
ejpam-2688	179	6	our	our	PRON
ejpam-2688	179	7	algorithm	algorithm	NOUN
ejpam-2688	179	8	is	be	AUX
ejpam-2688	179	9	a	a	DET
ejpam-2688	179	10	p+4	p+4	ADJ
ejpam-2688	179	11	-	-	PUNCT
ejpam-2688	179	12	length	length	NOUN
ejpam-2688	179	13	binary	binary	ADJ
ejpam-2688	179	14	string	string	NOUN
ejpam-2688	179	15	representing	represent	VERB
ejpam-2688	179	16	a	a	DET
ejpam-2688	179	17	specific	specific	ADJ
ejpam-2688	179	18	subset	subset	NOUN
ejpam-2688	179	19	of	of	ADP
ejpam-2688	179	20	features	feature	NOUN
ejpam-2688	179	21	and	and	CCONJ
ejpam-2688	179	22	kernel	kernel	PROPN
ejpam-2688	179	23	function	function	PROPN
ejpam-2688	179	24	.	.	PUNCT
ejpam-2688	180	1	the	the	DET
ejpam-2688	180	2	genetic	genetic	ADJ
ejpam-2688	180	3	algorithm	algorithm	NOUN
ejpam-2688	180	4	is	be	AUX
ejpam-2688	180	5	allowed	allow	VERB
ejpam-2688	180	6	to	to	PART
ejpam-2688	180	7	progress	progress	VERB
ejpam-2688	180	8	for	for	ADP
ejpam-2688	180	9	twenty	twenty	NUM
ejpam-2688	180	10	generations	generation	NOUN
ejpam-2688	180	11	,	,	PUNCT
ejpam-2688	180	12	operating	operate	VERB
ejpam-2688	180	13	on	on	ADP
ejpam-2688	180	14	an	an	DET
ejpam-2688	180	15	ensemble	ensemble	NOUN
ejpam-2688	180	16	of	of	ADP
ejpam-2688	180	17	twenty	twenty	NUM
ejpam-2688	180	18	of	of	ADP
ejpam-2688	180	19	these	these	DET
ejpam-2688	180	20	solutions	solution	NOUN
ejpam-2688	180	21	,	,	PUNCT
ejpam-2688	180	22	with	with	ADP
ejpam-2688	180	23	the	the	DET
ejpam-2688	180	24	goal	goal	NOUN
ejpam-2688	180	25	to	to	PART
ejpam-2688	180	26	minimize	minimize	VERB
ejpam-2688	180	27	the	the	DET
ejpam-2688	180	28	objective	objective	ADJ
ejpam-2688	180	29	function	function	NOUN
ejpam-2688	180	30	icom	icom	PROPN
ejpam-2688	180	31	pperf	pperf	PROPN
ejpam-2688	180	32	.	.	PUNCT
ejpam-2688	181	1	3.1	3.1	NUM
ejpam-2688	181	2	.	.	PUNCT
ejpam-2688	181	3	information	information	NOUN
ejpam-2688	181	4	complexity	complexity	NOUN
ejpam-2688	181	5	criteria	criterion	NOUN
ejpam-2688	181	6	for	for	ADP
ejpam-2688	181	7	supervised	supervised	ADJ
ejpam-2688	181	8	classification	classification	NOUN
ejpam-2688	181	9	a	a	DET
ejpam-2688	181	10	logical	logical	ADJ
ejpam-2688	181	11	next	next	ADJ
ejpam-2688	181	12	step	step	NOUN
ejpam-2688	181	13	from	from	ADP
ejpam-2688	181	14	information	information	NOUN
ejpam-2688	181	15	theoretic	theoretic	NOUN
ejpam-2688	181	16	model	model	NOUN
ejpam-2688	181	17	selection	selection	NOUN
ejpam-2688	181	18	criteria	criterion	NOUN
ejpam-2688	181	19	such	such	ADJ
ejpam-2688	181	20	as	as	ADP
ejpam-2688	181	21	akaike	akaike	ADJ
ejpam-2688	181	22	’s	’s	PART
ejpam-2688	181	23	aic	aic	PROPN
ejpam-2688	181	24	and	and	CCONJ
ejpam-2688	181	25	schwartz	schwartz	PROPN
ejpam-2688	181	26	’s	’s	PART
ejpam-2688	181	27	sbc	sbc	PROPN
ejpam-2688	181	28	,	,	PUNCT
ejpam-2688	181	29	bozdogan	bozdogan	NOUN
ejpam-2688	181	30	introduced	introduce	VERB
ejpam-2688	181	31	and	and	CCONJ
ejpam-2688	181	32	developed	develop	VERB
ejpam-2688	181	33	his	his	PRON
ejpam-2688	181	34	information	information	NOUN
ejpam-2688	181	35	complexity	complexity	NOUN
ejpam-2688	181	36	criteria	criterion	NOUN
ejpam-2688	181	37	icom	icom	X
ejpam-2688	181	38	p	p	NOUN
ejpam-2688	181	39	in	in	ADP
ejpam-2688	181	40	[	[	X
ejpam-2688	181	41	4	4	NUM
ejpam-2688	181	42	,	,	PUNCT
ejpam-2688	181	43	5	5	NUM
ejpam-2688	181	44	,	,	PUNCT
ejpam-2688	181	45	(	(	PUNCT
ejpam-2688	181	46	and	and	CCONJ
ejpam-2688	181	47	others	other	NOUN
ejpam-2688	181	48	)	)	PUNCT
ejpam-2688	181	49	]	]	PUNCT
ejpam-2688	181	50	.	.	PUNCT
ejpam-2688	182	1	icom	icom	PROPN
ejpam-2688	182	2	p	p	PROPN
ejpam-2688	182	3	typically	typically	ADV
ejpam-2688	182	4	penalizes	penalize	VERB
ejpam-2688	182	5	models	model	NOUN
ejpam-2688	182	6	based	base	VERB
ejpam-2688	182	7	on	on	ADP
ejpam-2688	182	8	the	the	DET
ejpam-2688	182	9	maximal	maximal	ADJ
ejpam-2688	182	10	entropic	entropic	ADJ
ejpam-2688	182	11	complexity	complexity	NOUN
ejpam-2688	182	12	c1	c1	NOUN
ejpam-2688	182	13	of	of	ADP
ejpam-2688	182	14	the	the	DET
ejpam-2688	182	15	model	model	NOUN
ejpam-2688	182	16	covariance	covariance	NOUN
ejpam-2688	182	17	matrix	matrix	NOUN
ejpam-2688	182	18	[	[	X
ejpam-2688	182	19	3	3	NUM
ejpam-2688	182	20	]	]	PUNCT
ejpam-2688	182	21	,	,	PUNCT
ejpam-2688	182	22	as	as	SCONJ
ejpam-2688	182	23	opposed	oppose	VERB
ejpam-2688	182	24	to	to	ADP
ejpam-2688	182	25	functions	function	NOUN
ejpam-2688	182	26	of	of	ADP
ejpam-2688	182	27	the	the	DET
ejpam-2688	182	28	number	number	NOUN
ejpam-2688	182	29	parameters	parameter	NOUN
ejpam-2688	182	30	estimated	estimate	VERB
ejpam-2688	182	31	.	.	PUNCT
ejpam-2688	183	1	this	this	DET
ejpam-2688	183	2	penalty	penalty	NOUN
ejpam-2688	183	3	allows	allow	VERB
ejpam-2688	183	4	icom	icom	PROPN
ejpam-2688	183	5	p	p	PROPN
ejpam-2688	183	6	,	,	PUNCT
ejpam-2688	183	7	shown	show	VERB
ejpam-2688	183	8	in	in	ADP
ejpam-2688	183	9	(	(	PUNCT
ejpam-2688	183	10	9	9	NUM
ejpam-2688	183	11	)	)	PUNCT
ejpam-2688	183	12	,	,	PUNCT
ejpam-2688	183	13	to	to	PART
ejpam-2688	183	14	simultaneously	simultaneously	ADV
ejpam-2688	183	15	penalize	penalize	VERB
ejpam-2688	183	16	a	a	DET
ejpam-2688	183	17	model	model	NOUN
ejpam-2688	183	18	based	base	VERB
ejpam-2688	183	19	on	on	ADP
ejpam-2688	183	20	lack	lack	NOUN
ejpam-2688	183	21	-	-	PUNCT
ejpam-2688	183	22	of	of	ADP
ejpam-2688	183	23	-	-	PUNCT
ejpam-2688	183	24	fit	fit	ADJ
ejpam-2688	183	25	,	,	PUNCT
ejpam-2688	183	26	lack	lack	NOUN
ejpam-2688	183	27	-	-	PUNCT
ejpam-2688	183	28	of	of	ADP
ejpam-2688	183	29	-	-	PUNCT
ejpam-2688	183	30	parsimony	parsimony	NOUN
ejpam-2688	183	31	and	and	CCONJ
ejpam-2688	183	32	profusion	profusion	NOUN
ejpam-2688	183	33	-	-	PUNCT
ejpam-2688	183	34	of	of	ADP
ejpam-2688	183	35	-	-	PUNCT
ejpam-2688	183	36	complexity	complexity	NOUN
ejpam-2688	183	37	.	.	PUNCT
ejpam-2688	184	1	icom	icom	PROPN
ejpam-2688	184	2	p(f̂−1	p(f̂−1	PROPN
ejpam-2688	184	3	)	)	PUNCT
ejpam-2688	184	4	=	=	SYM
ejpam-2688	185	1	−2	−2	NOUN
ejpam-2688	185	2	log	log	NOUN
ejpam-2688	185	3	l(θ̂	l(θ̂	PROPN
ejpam-2688	185	4	|	|	ADV
ejpam-2688	185	5	x	x	X
ejpam-2688	185	6	)	)	PUNCT
ejpam-2688	185	7	lack	lack	NOUN
ejpam-2688	185	8	-	-	PUNCT
ejpam-2688	185	9	of	of	ADP
ejpam-2688	185	10	-	-	PUNCT
ejpam-2688	185	11	fit	fit	ADJ
ejpam-2688	185	12	+	+	CCONJ
ejpam-2688	185	13	2c1(f̂−1	2c1(f̂−1	NUM
ejpam-2688	185	14	)	)	PUNCT
ejpam-2688	185	15	complex	complex	NOUN
ejpam-2688	186	1	i	i	PRON
ejpam-2688	186	2	t	t	PROPN
ejpam-2688	186	3	y	y	PROPN
ejpam-2688	186	4	(	(	PUNCT
ejpam-2688	186	5	9	9	X
ejpam-2688	186	6	)	)	PUNCT
ejpam-2688	186	7	several	several	ADJ
ejpam-2688	186	8	versions	version	NOUN
ejpam-2688	186	9	of	of	ADP
ejpam-2688	186	10	icom	icom	PROPN
ejpam-2688	186	11	p	p	PROPN
ejpam-2688	186	12	have	have	AUX
ejpam-2688	186	13	been	be	AUX
ejpam-2688	186	14	developed	develop	VERB
ejpam-2688	186	15	for	for	ADP
ejpam-2688	186	16	various	various	ADJ
ejpam-2688	186	17	model	model	NOUN
ejpam-2688	186	18	selection	selection	NOUN
ejpam-2688	186	19	problems	problem	NOUN
ejpam-2688	186	20	.	.	PUNCT
ejpam-2688	187	1	for	for	ADP
ejpam-2688	187	2	the	the	DET
ejpam-2688	187	3	problem	problem	NOUN
ejpam-2688	187	4	of	of	ADP
ejpam-2688	187	5	kernel	kernel	NOUN
ejpam-2688	187	6	-	-	PUNCT
ejpam-2688	187	7	based	base	VERB
ejpam-2688	187	8	supervised	supervised	ADJ
ejpam-2688	187	9	learning	learning	NOUN
ejpam-2688	187	10	,	,	PUNCT
ejpam-2688	187	11	liberati	liberati	PROPN
ejpam-2688	187	12	et	et	PROPN
ejpam-2688	187	13	al	al	PROPN
ejpam-2688	187	14	.	.	PUNCT
ejpam-2688	188	1	[	[	X
ejpam-2688	188	2	12	12	NUM
ejpam-2688	188	3	]	]	PUNCT
ejpam-2688	188	4	introduced	introduce	VERB
ejpam-2688	188	5	icom	icom	PROPN
ejpam-2688	188	6	pperf	pperf	PROPN
ejpam-2688	188	7	.	.	PUNCT
ejpam-2688	189	1	this	this	DET
ejpam-2688	189	2	form	form	NOUN
ejpam-2688	189	3	of	of	ADP
ejpam-2688	189	4	icom	icom	PROPN
ejpam-2688	189	5	p	p	PROPN
ejpam-2688	189	6	is	be	AUX
ejpam-2688	189	7	conceptually	conceptually	ADV
ejpam-2688	189	8	based	base	VERB
ejpam-2688	189	9	on	on	ADP
ejpam-2688	189	10	the	the	DET
ejpam-2688	189	11	regression	regression	NOUN
ejpam-2688	189	12	-	-	PUNCT
ejpam-2688	189	13	basis	basis	NOUN
ejpam-2688	189	14	of	of	ADP
ejpam-2688	189	15	discriminant	discriminant	ADJ
ejpam-2688	189	16	analysis	analysis	NOUN
ejpam-2688	189	17	:	:	PUNCT
ejpam-2688	189	18	icom	icom	PROPN
ejpam-2688	189	19	pperf	pperf	PROPN
ejpam-2688	189	20	=	=	SYM
ejpam-2688	189	21	n	n	CCONJ
ejpam-2688	189	22	log	log	VERB
ejpam-2688	189	23	2π+	2π+	NUM
ejpam-2688	189	24	n	n	CCONJ
ejpam-2688	189	25	log	log	VERB
ejpam-2688	189	26	σ̂2	σ̂2	PROPN
ejpam-2688	190	1	+	+	CCONJ
ejpam-2688	190	2	n	n	CCONJ
ejpam-2688	190	3	︸	︸	X
ejpam-2688	190	4	︷︷	︷︷	NOUN
ejpam-2688	190	5	︸	︸	VERB
ejpam-2688	191	1	lack−o	lack−o	PROPN
ejpam-2688	191	2	f	f	PROPN
ejpam-2688	192	1	−	−	PROPN
ejpam-2688	193	1	f	f	PROPN
ejpam-2688	194	1	i	i	PRON
ejpam-2688	194	2	t	t	PROPN
ejpam-2688	194	3	+	+	CCONJ
ejpam-2688	194	4	2c1f	2c1f	NUM
ejpam-2688	194	5	�	�	PROPN
ejpam-2688	194	6	σ̂∗sta_cse	σ̂∗sta_cse	PROPN
ejpam-2688	194	7	�	�	PROPN
ejpam-2688	194	8	︸	︸	ADP
ejpam-2688	195	1	︷︷	︷︷	PROPN
ejpam-2688	195	2	︸	︸	PUNCT
ejpam-2688	196	1	complex	complex	ADJ
ejpam-2688	197	1	i	i	PRON
ejpam-2688	197	2	t	t	PROPN
ejpam-2688	197	3	y	y	PROPN
ejpam-2688	197	4	,	,	PUNCT
ejpam-2688	197	5	(	(	PUNCT
ejpam-2688	197	6	10	10	NUM
ejpam-2688	197	7	)	)	PUNCT
ejpam-2688	198	1	where	where	SCONJ
ejpam-2688	198	2	σ̂2	σ̂2	PROPN
ejpam-2688	198	3	=	=	SYM
ejpam-2688	198	4	1	1	NUM
ejpam-2688	198	5	n	n	PRON
ejpam-2688	198	6	∑n	∑n	PROPN
ejpam-2688	198	7	i=1	i=1	PROPN
ejpam-2688	198	8	�	�	PROPN
ejpam-2688	198	9	yi	yi	PROPN
ejpam-2688	198	10	−	−	PROPN
ejpam-2688	198	11	ŷi	ŷi	PROPN
ejpam-2688	198	12	�	�	PROPN
ejpam-2688	198	13	2	2	NUM
ejpam-2688	199	1	.	.	PUNCT
ejpam-2688	200	1	the	the	DET
ejpam-2688	200	2	yi	yi	PROPN
ejpam-2688	200	3	are	be	AUX
ejpam-2688	200	4	the	the	DET
ejpam-2688	200	5	actual	actual	ADJ
ejpam-2688	200	6	known	know	VERB
ejpam-2688	200	7	group	group	NOUN
ejpam-2688	200	8	labels	label	NOUN
ejpam-2688	200	9	,	,	PUNCT
ejpam-2688	200	10	and	and	CCONJ
ejpam-2688	200	11	the	the	DET
ejpam-2688	200	12	ŷi	ŷi	PROPN
ejpam-2688	200	13	are	be	AUX
ejpam-2688	200	14	the	the	DET
ejpam-2688	200	15	group	group	NOUN
ejpam-2688	200	16	labels	label	NOUN
ejpam-2688	200	17	predicted	predict	VERB
ejpam-2688	200	18	with	with	ADP
ejpam-2688	200	19	kda	kda	PROPN
ejpam-2688	200	20	.	.	PUNCT
ejpam-2688	201	1	the	the	DET
ejpam-2688	201	2	kernel	kernel	PROPN
ejpam-2688	201	3	methods	method	NOUN
ejpam-2688	201	4	used	use	VERB
ejpam-2688	201	5	in	in	ADP
ejpam-2688	201	6	kda	kda	NOUN
ejpam-2688	201	7	lead	lead	NOUN
ejpam-2688	201	8	to	to	ADP
ejpam-2688	201	9	orthogonal	orthogonal	ADJ
ejpam-2688	201	10	and	and	CCONJ
ejpam-2688	201	11	highly	highly	ADV
ejpam-2688	201	12	sparse	sparse	ADJ
ejpam-2688	201	13	matrices	matrix	NOUN
ejpam-2688	201	14	,	,	PUNCT
ejpam-2688	201	15	which	which	PRON
ejpam-2688	201	16	can	can	AUX
ejpam-2688	201	17	cause	cause	VERB
ejpam-2688	201	18	problems	problem	NOUN
ejpam-2688	201	19	for	for	ADP
ejpam-2688	201	20	the	the	DET
ejpam-2688	201	21	c1	c1	PROPN
ejpam-2688	201	22	measure	measure	NOUN
ejpam-2688	201	23	of	of	ADP
ejpam-2688	201	24	complexity	complexity	NOUN
ejpam-2688	201	25	.	.	PUNCT
ejpam-2688	202	1	accordingly	accordingly	ADV
ejpam-2688	202	2	,	,	PUNCT
ejpam-2688	202	3	icom	icom	PROPN
ejpam-2688	202	4	pperf	pperf	PROPN
ejpam-2688	202	5	uses	use	VERB
ejpam-2688	202	6	a	a	DET
ejpam-2688	202	7	modified	modify	VERB
ejpam-2688	202	8	measure	measure	NOUN
ejpam-2688	202	9	of	of	ADP
ejpam-2688	202	10	complexity	complexity	NOUN
ejpam-2688	202	11	based	base	VERB
ejpam-2688	202	12	on	on	ADP
ejpam-2688	202	13	the	the	DET
ejpam-2688	202	14	frobenius	frobenius	ADJ
ejpam-2688	202	15	norm	norm	NOUN
ejpam-2688	202	16	characterization	characterization	NOUN
ejpam-2688	202	17	of	of	ADP
ejpam-2688	202	18	the	the	DET
ejpam-2688	202	19	entropic	entropic	ADJ
ejpam-2688	202	20	complexity	complexity	NOUN
ejpam-2688	202	21	cf	cf	NOUN
ejpam-2688	202	22	,	,	PUNCT
ejpam-2688	202	23	shown	show	VERB
ejpam-2688	202	24	in	in	ADP
ejpam-2688	202	25	(	(	PUNCT
ejpam-2688	202	26	11	11	NUM
ejpam-2688	202	27	)	)	PUNCT
ejpam-2688	202	28	as	as	ADP
ejpam-2688	202	29	a	a	DET
ejpam-2688	202	30	function	function	NOUN
ejpam-2688	202	31	of	of	ADP
ejpam-2688	202	32	the	the	DET
ejpam-2688	202	33	eigenvalues	eigenvalue	NOUN
ejpam-2688	202	34	of	of	ADP
ejpam-2688	202	35	the	the	DET
ejpam-2688	202	36	matrix	matrix	NOUN
ejpam-2688	202	37	.	.	PUNCT
ejpam-2688	203	1	c1f	c1f	PROPN
ejpam-2688	203	2	(	(	PUNCT
ejpam-2688	203	3	·	·	PUNCT
ejpam-2688	203	4	)	)	PUNCT
ejpam-2688	203	5	=	=	SYM
ejpam-2688	204	1	1	1	NUM
ejpam-2688	204	2	4λ	4λ	NUM
ejpam-2688	204	3	2	2	NUM
ejpam-2688	204	4	p∑	p∑	NOUN
ejpam-2688	204	5	i=1	i=1	PROPN
ejpam-2688	204	6	�	�	PROPN
ejpam-2688	204	7	λi	λi	NUM
ejpam-2688	204	8	−λ	−λ	PROPN
ejpam-2688	204	9	�	�	PROPN
ejpam-2688	204	10	2	2	NUM
ejpam-2688	204	11	(	(	PUNCT
ejpam-2688	204	12	11	11	NUM
ejpam-2688	204	13	)	)	PUNCT
ejpam-2688	204	14	by	by	ADP
ejpam-2688	204	15	minimizing	minimize	VERB
ejpam-2688	204	16	icom	icom	PROPN
ejpam-2688	204	17	pperf	pperf	NOUN
ejpam-2688	204	18	,	,	PUNCT
ejpam-2688	204	19	our	our	PRON
ejpam-2688	204	20	algorithm	algorithm	NOUN
ejpam-2688	204	21	can	can	AUX
ejpam-2688	204	22	simultaneously	simultaneously	ADV
ejpam-2688	204	23	minimize	minimize	VERB
ejpam-2688	204	24	classification	classification	NOUN
ejpam-2688	204	25	error	error	NOUN
ejpam-2688	204	26	,	,	PUNCT
ejpam-2688	204	27	maximize	maximize	VERB
ejpam-2688	204	28	fit	fit	ADJ
ejpam-2688	204	29	,	,	PUNCT
ejpam-2688	204	30	and	and	CCONJ
ejpam-2688	204	31	minimize	minimize	VERB
ejpam-2688	204	32	model	model	NOUN
ejpam-2688	204	33	complexity	complexity	NOUN
ejpam-2688	204	34	.	.	PUNCT
ejpam-2688	205	1	3.2	3.2	NUM
ejpam-2688	205	2	.	.	PUNCT
ejpam-2688	206	1	cross	cross	NOUN
ejpam-2688	206	2	-	-	NOUN
ejpam-2688	206	3	validation	validation	NOUN
ejpam-2688	206	4	within	within	ADP
ejpam-2688	206	5	the	the	DET
ejpam-2688	206	6	ga	ga	PROPN
ejpam-2688	206	7	:	:	PUNCT
ejpam-2688	206	8	cvga	cvga	PROPN
ejpam-2688	206	9	cross	cross	NOUN
ejpam-2688	206	10	-	-	NOUN
ejpam-2688	206	11	validation	validation	ADJ
ejpam-2688	206	12	(	(	PUNCT
ejpam-2688	206	13	cv	cv	NOUN
ejpam-2688	206	14	)	)	PUNCT
ejpam-2688	206	15	partitioning	partitioning	NOUN
ejpam-2688	206	16	of	of	ADP
ejpam-2688	206	17	datasets	dataset	NOUN
ejpam-2688	206	18	is	be	AUX
ejpam-2688	206	19	commonly	commonly	ADV
ejpam-2688	206	20	used	use	VERB
ejpam-2688	206	21	in	in	ADP
ejpam-2688	206	22	machine	machine	NOUN
ejpam-2688	206	23	learning	learn	VERB
ejpam-2688	206	24	to	to	PART
ejpam-2688	206	25	assess	assess	VERB
ejpam-2688	206	26	the	the	DET
ejpam-2688	206	27	predictive	predictive	ADJ
ejpam-2688	206	28	power	power	NOUN
ejpam-2688	206	29	of	of	ADP
ejpam-2688	206	30	models	model	NOUN
ejpam-2688	206	31	.	.	PUNCT
ejpam-2688	207	1	the	the	DET
ejpam-2688	207	2	model	model	NOUN
ejpam-2688	207	3	is	be	AUX
ejpam-2688	207	4	estimated	estimate	VERB
ejpam-2688	207	5	based	base	VERB
ejpam-2688	207	6	on	on	ADP
ejpam-2688	207	7	a	a	DET
ejpam-2688	207	8	training	training	NOUN
ejpam-2688	207	9	set	set	NOUN
ejpam-2688	207	10	of	of	ADP
ejpam-2688	207	11	the	the	DET
ejpam-2688	207	12	data	datum	NOUN
ejpam-2688	207	13	,	,	PUNCT
ejpam-2688	207	14	then	then	ADV
ejpam-2688	207	15	the	the	DET
ejpam-2688	207	16	model	model	NOUN
ejpam-2688	207	17	is	be	AUX
ejpam-2688	207	18	used	use	VERB
ejpam-2688	207	19	to	to	PART
ejpam-2688	207	20	classify	classify	VERB
ejpam-2688	207	21	a	a	DET
ejpam-2688	207	22	testing	testing	NOUN
ejpam-2688	207	23	set	set	VERB
ejpam-2688	207	24	.	.	PUNCT
ejpam-2688	208	1	classification	classification	NOUN
ejpam-2688	208	2	rates	rate	NOUN
ejpam-2688	208	3	are	be	AUX
ejpam-2688	208	4	reported	report	VERB
ejpam-2688	208	5	from	from	ADP
ejpam-2688	208	6	the	the	DET
ejpam-2688	208	7	testing	testing	NOUN
ejpam-2688	208	8	set	set	NOUN
ejpam-2688	208	9	.	.	PUNCT
ejpam-2688	209	1	observations	observation	NOUN
ejpam-2688	209	2	are	be	AUX
ejpam-2688	209	3	randomly	randomly	ADV
ejpam-2688	209	4	grouped	group	VERB
ejpam-2688	209	5	into	into	ADP
ejpam-2688	209	6	training	training	NOUN
ejpam-2688	209	7	and	and	CCONJ
ejpam-2688	209	8	testing	testing	NOUN
ejpam-2688	209	9	sets	set	NOUN
ejpam-2688	209	10	based	base	VERB
ejpam-2688	209	11	on	on	ADP
ejpam-2688	209	12	a	a	DET
ejpam-2688	209	13	specified	specified	ADJ
ejpam-2688	209	14	percentage	percentage	NOUN
ejpam-2688	209	15	(	(	PUNCT
ejpam-2688	209	16	in	in	ADP
ejpam-2688	209	17	this	this	DET
ejpam-2688	209	18	research	research	NOUN
ejpam-2688	209	19	,	,	PUNCT
ejpam-2688	209	20	we	we	PRON
ejpam-2688	209	21	use	use	VERB
ejpam-2688	209	22	20	20	NUM
ejpam-2688	209	23	%	%	NOUN
ejpam-2688	209	24	for	for	ADP
ejpam-2688	209	25	training	training	NOUN
ejpam-2688	209	26	,	,	PUNCT
ejpam-2688	209	27	with	with	ADP
ejpam-2688	209	28	the	the	DET
ejpam-2688	209	29	remaining	remain	VERB
ejpam-2688	209	30	80	80	NUM
ejpam-2688	209	31	%	%	NOUN
ejpam-2688	209	32	for	for	ADP
ejpam-2688	209	33	testing	testing	NOUN
ejpam-2688	209	34	)	)	PUNCT
ejpam-2688	209	35	.	.	PUNCT
ejpam-2688	210	1	j.	j.	PROPN
ejpam-2688	210	2	howe	howe	PROPN
ejpam-2688	210	3	,	,	PUNCT
ejpam-2688	210	4	h.	h.	PROPN
ejpam-2688	210	5	bozdogan	bozdogan	PROPN
ejpam-2688	210	6	/	/	SYM
ejpam-2688	210	7	eur	eur	PROPN
ejpam-2688	210	8	.	.	PUNCT
ejpam-2688	211	1	j.	j.	PROPN
ejpam-2688	211	2	pure	pure	PROPN
ejpam-2688	211	3	appl	appl	PROPN
ejpam-2688	211	4	.	.	PROPN
ejpam-2688	211	5	math	math	PROPN
ejpam-2688	211	6	,	,	PUNCT
ejpam-2688	211	7	9	9	NUM
ejpam-2688	211	8	(	(	PUNCT
ejpam-2688	211	9	2016	2016	NUM
ejpam-2688	211	10	)	)	PUNCT
ejpam-2688	211	11	,	,	PUNCT
ejpam-2688	211	12	216	216	NUM
ejpam-2688	211	13	-	-	SYM
ejpam-2688	211	14	230	230	NUM
ejpam-2688	211	15	224	224	NUM
ejpam-2688	211	16	to	to	PART
ejpam-2688	211	17	avoid	avoid	VERB
ejpam-2688	211	18	bias	bias	NOUN
ejpam-2688	211	19	due	due	ADP
ejpam-2688	211	20	to	to	ADP
ejpam-2688	211	21	the	the	DET
ejpam-2688	211	22	randomized	randomized	ADJ
ejpam-2688	211	23	partitioning	partitioning	NOUN
ejpam-2688	211	24	,	,	PUNCT
ejpam-2688	211	25	we	we	PRON
ejpam-2688	211	26	could	could	AUX
ejpam-2688	211	27	run	run	VERB
ejpam-2688	211	28	the	the	DET
ejpam-2688	211	29	ga	ga	NOUN
ejpam-2688	211	30	many	many	ADJ
ejpam-2688	211	31	times	time	NOUN
ejpam-2688	211	32	(	(	PUNCT
ejpam-2688	211	33	called	call	VERB
ejpam-2688	211	34	replications	replication	NOUN
ejpam-2688	211	35	)	)	PUNCT
ejpam-2688	211	36	,	,	PUNCT
ejpam-2688	211	37	each	each	DET
ejpam-2688	211	38	time	time	NOUN
ejpam-2688	211	39	with	with	ADP
ejpam-2688	211	40	a	a	DET
ejpam-2688	211	41	new	new	ADJ
ejpam-2688	211	42	cv	cv	PROPN
ejpam-2688	211	43	sample	sample	NOUN
ejpam-2688	211	44	,	,	PUNCT
ejpam-2688	211	45	but	but	CCONJ
ejpam-2688	211	46	it	it	PRON
ejpam-2688	211	47	would	would	AUX
ejpam-2688	211	48	be	be	AUX
ejpam-2688	211	49	very	very	ADV
ejpam-2688	211	50	time	time	NOUN
ejpam-2688	211	51	consuming	consume	VERB
ejpam-2688	211	52	to	to	PART
ejpam-2688	211	53	do	do	VERB
ejpam-2688	211	54	this	this	PRON
ejpam-2688	211	55	on	on	ADP
ejpam-2688	211	56	top	top	NOUN
ejpam-2688	211	57	of	of	ADP
ejpam-2688	211	58	the	the	DET
ejpam-2688	211	59	ga	ga	PROPN
ejpam-2688	211	60	.	.	PROPN
ejpam-2688	212	1	at	at	ADP
ejpam-2688	212	2	the	the	DET
ejpam-2688	212	3	end	end	NOUN
ejpam-2688	212	4	,	,	PUNCT
ejpam-2688	212	5	we	we	PRON
ejpam-2688	212	6	’d	’d	NOUN
ejpam-2688	212	7	need	need	VERB
ejpam-2688	212	8	to	to	PART
ejpam-2688	212	9	combine	combine	VERB
ejpam-2688	212	10	the	the	DET
ejpam-2688	212	11	results	result	NOUN
ejpam-2688	212	12	from	from	ADP
ejpam-2688	212	13	all	all	DET
ejpam-2688	212	14	the	the	DET
ejpam-2688	212	15	replications	replication	NOUN
ejpam-2688	212	16	to	to	PART
ejpam-2688	212	17	determine	determine	VERB
ejpam-2688	212	18	the	the	DET
ejpam-2688	212	19	optimal	optimal	ADJ
ejpam-2688	212	20	model	model	NOUN
ejpam-2688	212	21	.	.	PUNCT
ejpam-2688	213	1	instead	instead	ADV
ejpam-2688	213	2	,	,	PUNCT
ejpam-2688	213	3	we	we	PRON
ejpam-2688	213	4	propose	propose	VERB
ejpam-2688	213	5	a	a	DET
ejpam-2688	213	6	hybrid	hybrid	ADJ
ejpam-2688	213	7	algorithm	algorithm	NOUN
ejpam-2688	213	8	that	that	PRON
ejpam-2688	213	9	combines	combine	VERB
ejpam-2688	213	10	the	the	DET
ejpam-2688	213	11	ga	ga	NOUN
ejpam-2688	213	12	with	with	ADP
ejpam-2688	213	13	cross	cross	NOUN
ejpam-2688	213	14	-	-	ADJ
ejpam-2688	213	15	validation	validation	ADJ
ejpam-2688	213	16	,	,	PUNCT
ejpam-2688	213	17	called	call	VERB
ejpam-2688	213	18	cvga	cvga	PROPN
ejpam-2688	213	19	.	.	PUNCT
ejpam-2688	214	1	cvga	cvga	PROPN
ejpam-2688	214	2	adds	add	VERB
ejpam-2688	214	3	an	an	DET
ejpam-2688	214	4	extra	extra	ADJ
ejpam-2688	214	5	layer	layer	NOUN
ejpam-2688	214	6	of	of	ADP
ejpam-2688	214	7	randomness	randomness	NOUN
ejpam-2688	214	8	to	to	ADP
ejpam-2688	214	9	the	the	DET
ejpam-2688	214	10	ga	ga	PROPN
ejpam-2688	214	11	in	in	ADP
ejpam-2688	214	12	that	that	PRON
ejpam-2688	214	13	every	every	DET
ejpam-2688	214	14	time	time	NOUN
ejpam-2688	214	15	the	the	DET
ejpam-2688	214	16	fitness	fitness	NOUN
ejpam-2688	214	17	of	of	ADP
ejpam-2688	214	18	a	a	DET
ejpam-2688	214	19	chromosome	chromosome	NOUN
ejpam-2688	214	20	is	be	AUX
ejpam-2688	214	21	evaluated	evaluate	VERB
ejpam-2688	214	22	,	,	PUNCT
ejpam-2688	214	23	it	it	PRON
ejpam-2688	214	24	is	be	AUX
ejpam-2688	214	25	based	base	VERB
ejpam-2688	214	26	on	on	ADP
ejpam-2688	214	27	a	a	DET
ejpam-2688	214	28	new	new	ADJ
ejpam-2688	214	29	cross	cross	ADJ
ejpam-2688	214	30	-	-	ADJ
ejpam-2688	214	31	validation	validation	ADJ
ejpam-2688	214	32	sample	sample	NOUN
ejpam-2688	214	33	.	.	PUNCT
ejpam-2688	215	1	instead	instead	ADV
ejpam-2688	215	2	of	of	ADP
ejpam-2688	215	3	nesting	nest	VERB
ejpam-2688	215	4	the	the	DET
ejpam-2688	215	5	ga	ga	PROPN
ejpam-2688	215	6	within	within	ADP
ejpam-2688	215	7	cv	cv	PROPN
ejpam-2688	215	8	,	,	PUNCT
ejpam-2688	215	9	cv	cv	PROPN
ejpam-2688	215	10	is	be	AUX
ejpam-2688	215	11	nested	nest	VERB
ejpam-2688	215	12	within	within	ADP
ejpam-2688	215	13	the	the	DET
ejpam-2688	215	14	ga	ga	PROPN
ejpam-2688	215	15	.	.	PUNCT
ejpam-2688	216	1	this	this	PRON
ejpam-2688	216	2	allows	allow	VERB
ejpam-2688	216	3	us	we	PRON
ejpam-2688	216	4	to	to	PART
ejpam-2688	216	5	score	score	VERB
ejpam-2688	216	6	solutions	solution	NOUN
ejpam-2688	216	7	during	during	ADP
ejpam-2688	216	8	optimization	optimization	NOUN
ejpam-2688	216	9	with	with	ADP
ejpam-2688	216	10	no	no	DET
ejpam-2688	216	11	concern	concern	NOUN
ejpam-2688	216	12	that	that	SCONJ
ejpam-2688	216	13	our	our	PRON
ejpam-2688	216	14	partitioning	partitioning	NOUN
ejpam-2688	216	15	into	into	ADP
ejpam-2688	216	16	training	training	NOUN
ejpam-2688	216	17	/	/	SYM
ejpam-2688	216	18	testing	testing	NOUN
ejpam-2688	216	19	for	for	ADP
ejpam-2688	216	20	the	the	DET
ejpam-2688	216	21	ga	ga	PROPN
ejpam-2688	216	22	was	be	AUX
ejpam-2688	216	23	somehow	somehow	ADV
ejpam-2688	216	24	not	not	PART
ejpam-2688	216	25	representative	representative	ADJ
ejpam-2688	216	26	.	.	PUNCT
ejpam-2688	217	1	however	however	ADV
ejpam-2688	217	2	,	,	PUNCT
ejpam-2688	217	3	the	the	DET
ejpam-2688	217	4	extra	extra	ADJ
ejpam-2688	217	5	randomness	randomness	NOUN
ejpam-2688	217	6	within	within	ADP
ejpam-2688	217	7	the	the	DET
ejpam-2688	217	8	cvga	cvga	NOUN
ejpam-2688	217	9	does	do	AUX
ejpam-2688	217	10	present	present	VERB
ejpam-2688	217	11	a	a	DET
ejpam-2688	217	12	challenge	challenge	NOUN
ejpam-2688	217	13	.	.	PUNCT
ejpam-2688	218	1	suppose	suppose	VERB
ejpam-2688	218	2	in	in	ADP
ejpam-2688	218	3	one	one	NUM
ejpam-2688	218	4	iteration	iteration	NOUN
ejpam-2688	218	5	of	of	ADP
ejpam-2688	218	6	the	the	DET
ejpam-2688	218	7	cvga	cvga	NOUN
ejpam-2688	218	8	,	,	PUNCT
ejpam-2688	218	9	we	we	PRON
ejpam-2688	218	10	find	find	VERB
ejpam-2688	218	11	the	the	DET
ejpam-2688	218	12	best	good	ADJ
ejpam-2688	218	13	solution	solution	NOUN
ejpam-2688	218	14	to	to	PART
ejpam-2688	218	15	use	use	VERB
ejpam-2688	218	16	variables	variable	NOUN
ejpam-2688	218	17	1	1	NUM
ejpam-2688	218	18	and	and	CCONJ
ejpam-2688	218	19	2	2	NUM
ejpam-2688	218	20	and	and	CCONJ
ejpam-2688	218	21	the	the	DET
ejpam-2688	218	22	gaussian	gaussian	ADJ
ejpam-2688	218	23	kernel	kernel	NOUN
ejpam-2688	218	24	,	,	PUNCT
ejpam-2688	218	25	with	with	ADP
ejpam-2688	218	26	a	a	DET
ejpam-2688	218	27	score	score	NOUN
ejpam-2688	218	28	of	of	ADP
ejpam-2688	218	29	−67	−67	PROPN
ejpam-2688	218	30	.	.	PUNCT
ejpam-2688	219	1	in	in	ADP
ejpam-2688	219	2	a	a	DET
ejpam-2688	219	3	later	later	ADJ
ejpam-2688	219	4	generation	generation	NOUN
ejpam-2688	219	5	,	,	PUNCT
ejpam-2688	219	6	the	the	DET
ejpam-2688	219	7	same	same	ADJ
ejpam-2688	219	8	solution	solution	NOUN
ejpam-2688	219	9	could	could	AUX
ejpam-2688	219	10	result	result	VERB
ejpam-2688	219	11	in	in	ADP
ejpam-2688	219	12	a	a	DET
ejpam-2688	219	13	score	score	NOUN
ejpam-2688	219	14	of	of	ADP
ejpam-2688	219	15	−23	−23	PROPN
ejpam-2688	219	16	,	,	PUNCT
ejpam-2688	219	17	and	and	CCONJ
ejpam-2688	219	18	not	not	PART
ejpam-2688	219	19	be	be	AUX
ejpam-2688	219	20	the	the	DET
ejpam-2688	219	21	best	good	ADJ
ejpam-2688	219	22	for	for	ADP
ejpam-2688	219	23	that	that	DET
ejpam-2688	219	24	iteration	iteration	NOUN
ejpam-2688	219	25	.	.	PUNCT
ejpam-2688	220	1	this	this	DET
ejpam-2688	220	2	variability	variability	NOUN
ejpam-2688	220	3	is	be	AUX
ejpam-2688	220	4	obviously	obviously	ADV
ejpam-2688	220	5	due	due	ADJ
ejpam-2688	220	6	to	to	ADP
ejpam-2688	220	7	the	the	DET
ejpam-2688	220	8	fact	fact	NOUN
ejpam-2688	220	9	that	that	SCONJ
ejpam-2688	220	10	the	the	DET
ejpam-2688	220	11	fitness	fitness	NOUN
ejpam-2688	220	12	of	of	ADP
ejpam-2688	220	13	each	each	DET
ejpam-2688	220	14	chromosome	chromosome	NOUN
ejpam-2688	220	15	is	be	AUX
ejpam-2688	220	16	evaluated	evaluate	VERB
ejpam-2688	220	17	on	on	ADP
ejpam-2688	220	18	different	different	ADJ
ejpam-2688	220	19	data	datum	NOUN
ejpam-2688	220	20	.	.	PUNCT
ejpam-2688	221	1	we	we	PRON
ejpam-2688	221	2	have	have	AUX
ejpam-2688	221	3	implemented	implement	VERB
ejpam-2688	221	4	a	a	DET
ejpam-2688	221	5	two	two	NUM
ejpam-2688	221	6	-	-	PUNCT
ejpam-2688	221	7	stage	stage	NOUN
ejpam-2688	221	8	process	process	NOUN
ejpam-2688	221	9	to	to	PART
ejpam-2688	221	10	smooth	smooth	VERB
ejpam-2688	221	11	out	out	ADP
ejpam-2688	221	12	this	this	DET
ejpam-2688	221	13	variation	variation	NOUN
ejpam-2688	221	14	.	.	PUNCT
ejpam-2688	222	1	first	first	ADV
ejpam-2688	222	2	,	,	PUNCT
ejpam-2688	222	3	in	in	ADP
ejpam-2688	222	4	summarizing	summarize	VERB
ejpam-2688	222	5	the	the	DET
ejpam-2688	222	6	results	result	NOUN
ejpam-2688	222	7	from	from	ADP
ejpam-2688	222	8	the	the	DET
ejpam-2688	222	9	ga	ga	PROPN
ejpam-2688	222	10	,	,	PUNCT
ejpam-2688	222	11	we	we	PRON
ejpam-2688	222	12	store	store	VERB
ejpam-2688	222	13	the	the	DET
ejpam-2688	222	14	median	median	PROPN
ejpam-2688	222	15	icom	icom	PROPN
ejpam-2688	222	16	pperf	pperf	PROPN
ejpam-2688	222	17	and	and	CCONJ
ejpam-2688	222	18	testing	testing	NOUN
ejpam-2688	222	19	/	/	SYM
ejpam-2688	222	20	training	training	NOUN
ejpam-2688	222	21	classification	classification	NOUN
ejpam-2688	222	22	error	error	NOUN
ejpam-2688	222	23	rates	rate	NOUN
ejpam-2688	222	24	for	for	ADP
ejpam-2688	222	25	every	every	DET
ejpam-2688	222	26	unique	unique	ADJ
ejpam-2688	222	27	solution	solution	NOUN
ejpam-2688	222	28	(	(	PUNCT
ejpam-2688	222	29	since	since	SCONJ
ejpam-2688	222	30	good	good	ADJ
ejpam-2688	222	31	solutions	solution	NOUN
ejpam-2688	222	32	will	will	AUX
ejpam-2688	222	33	tend	tend	VERB
ejpam-2688	222	34	to	to	PART
ejpam-2688	222	35	be	be	AUX
ejpam-2688	222	36	occur	occur	VERB
ejpam-2688	222	37	multiple	multiple	ADJ
ejpam-2688	222	38	times	time	NOUN
ejpam-2688	222	39	)	)	PUNCT
ejpam-2688	222	40	.	.	PUNCT
ejpam-2688	223	1	the	the	DET
ejpam-2688	223	2	median	median	NOUN
ejpam-2688	223	3	is	be	AUX
ejpam-2688	223	4	used	use	VERB
ejpam-2688	223	5	instead	instead	ADV
ejpam-2688	223	6	of	of	ADP
ejpam-2688	223	7	the	the	DET
ejpam-2688	223	8	average	average	NOUN
ejpam-2688	223	9	to	to	PART
ejpam-2688	223	10	ensure	ensure	VERB
ejpam-2688	223	11	that	that	SCONJ
ejpam-2688	223	12	the	the	DET
ejpam-2688	223	13	optimal	optimal	ADJ
ejpam-2688	223	14	solution	solution	NOUN
ejpam-2688	223	15	selected	select	VERB
ejpam-2688	223	16	at	at	ADP
ejpam-2688	223	17	the	the	DET
ejpam-2688	223	18	end	end	NOUN
ejpam-2688	223	19	of	of	ADP
ejpam-2688	223	20	the	the	DET
ejpam-2688	223	21	process	process	NOUN
ejpam-2688	223	22	is	be	AUX
ejpam-2688	223	23	robust	robust	ADJ
ejpam-2688	223	24	against	against	ADP
ejpam-2688	223	25	cross	cross	NOUN
ejpam-2688	223	26	-	-	NOUN
ejpam-2688	223	27	validations	validation	NOUN
ejpam-2688	223	28	with	with	ADP
ejpam-2688	223	29	outlying	outlying	ADJ
ejpam-2688	223	30	performances	performance	NOUN
ejpam-2688	223	31	.	.	PUNCT
ejpam-2688	224	1	secondly	secondly	ADV
ejpam-2688	224	2	,	,	PUNCT
ejpam-2688	224	3	we	we	PRON
ejpam-2688	224	4	actually	actually	ADV
ejpam-2688	224	5	run	run	VERB
ejpam-2688	224	6	the	the	DET
ejpam-2688	224	7	ga	ga	PROPN
ejpam-2688	224	8	100	100	NUM
ejpam-2688	224	9	times	time	NOUN
ejpam-2688	224	10	,	,	PUNCT
ejpam-2688	224	11	for	for	ADP
ejpam-2688	224	12	a	a	DET
ejpam-2688	224	13	maximum	maximum	NOUN
ejpam-2688	224	14	of	of	ADP
ejpam-2688	224	15	100	100	NUM
ejpam-2688	224	16	×	×	NOUN
ejpam-2688	224	17	20	20	NUM
ejpam-2688	224	18	×	×	NOUN
ejpam-2688	224	19	20=	20=	NUM
ejpam-2688	224	20	40,000	40,000	NUM
ejpam-2688	224	21	unique	unique	ADJ
ejpam-2688	224	22	solutions	solution	NOUN
ejpam-2688	224	23	evaluated	evaluate	VERB
ejpam-2688	224	24	.	.	PUNCT
ejpam-2688	225	1	the	the	DET
ejpam-2688	225	2	median	median	PROPN
ejpam-2688	225	3	icom	icom	PROPN
ejpam-2688	225	4	pperf	pperf	PROPN
ejpam-2688	225	5	for	for	ADP
ejpam-2688	225	6	each	each	DET
ejpam-2688	225	7	solution	solution	NOUN
ejpam-2688	225	8	evaluated	evaluate	VERB
ejpam-2688	225	9	is	be	AUX
ejpam-2688	225	10	then	then	ADV
ejpam-2688	225	11	averaged	average	VERB
ejpam-2688	225	12	over	over	ADP
ejpam-2688	225	13	all	all	DET
ejpam-2688	225	14	100	100	NUM
ejpam-2688	225	15	replications	replication	NOUN
ejpam-2688	225	16	,	,	PUNCT
ejpam-2688	225	17	and	and	CCONJ
ejpam-2688	225	18	we	we	PRON
ejpam-2688	225	19	compute	compute	VERB
ejpam-2688	225	20	the	the	DET
ejpam-2688	225	21	95	95	NUM
ejpam-2688	225	22	%	%	NOUN
ejpam-2688	225	23	empirical	empirical	ADJ
ejpam-2688	225	24	confidence	confidence	NOUN
ejpam-2688	225	25	intervals	interval	NOUN
ejpam-2688	225	26	for	for	ADP
ejpam-2688	225	27	the	the	DET
ejpam-2688	225	28	misclassification	misclassification	NOUN
ejpam-2688	225	29	rates	rate	NOUN
ejpam-2688	225	30	.	.	PUNCT
ejpam-2688	226	1	in	in	ADP
ejpam-2688	226	2	summary	summary	NOUN
ejpam-2688	226	3	,	,	PUNCT
ejpam-2688	226	4	computing	compute	VERB
ejpam-2688	226	5	the	the	DET
ejpam-2688	226	6	fitness	fitness	NOUN
ejpam-2688	226	7	for	for	ADP
ejpam-2688	226	8	each	each	DET
ejpam-2688	226	9	chromosome	chromosome	NOUN
ejpam-2688	226	10	follows	follow	VERB
ejpam-2688	226	11	these	these	DET
ejpam-2688	226	12	steps	step	NOUN
ejpam-2688	226	13	:	:	PUNCT
ejpam-2688	226	14	(	(	PUNCT
ejpam-2688	226	15	i	i	NOUN
ejpam-2688	226	16	)	)	PUNCT
ejpam-2688	226	17	randomly	randomly	ADV
ejpam-2688	226	18	partition	partition	VERB
ejpam-2688	226	19	the	the	DET
ejpam-2688	226	20	data	datum	NOUN
ejpam-2688	226	21	into	into	ADP
ejpam-2688	226	22	training	training	NOUN
ejpam-2688	226	23	and	and	CCONJ
ejpam-2688	226	24	testing	testing	NOUN
ejpam-2688	226	25	sets	set	NOUN
ejpam-2688	226	26	,	,	PUNCT
ejpam-2688	226	27	keeping	keep	VERB
ejpam-2688	226	28	only	only	ADV
ejpam-2688	226	29	the	the	DET
ejpam-2688	226	30	features	feature	NOUN
ejpam-2688	226	31	selected	select	VERB
ejpam-2688	226	32	by	by	ADP
ejpam-2688	226	33	the	the	DET
ejpam-2688	226	34	chromosome	chromosome	NOUN
ejpam-2688	226	35	(	(	PUNCT
ejpam-2688	226	36	ii	ii	NOUN
ejpam-2688	226	37	)	)	PUNCT
ejpam-2688	226	38	perform	perform	VERB
ejpam-2688	226	39	kda	kda	NOUN
ejpam-2688	226	40	on	on	ADP
ejpam-2688	226	41	the	the	DET
ejpam-2688	226	42	training	training	NOUN
ejpam-2688	226	43	set	set	NOUN
ejpam-2688	226	44	,	,	PUNCT
ejpam-2688	226	45	measuring	measure	VERB
ejpam-2688	226	46	the	the	DET
ejpam-2688	226	47	classification	classification	NOUN
ejpam-2688	226	48	error	error	NOUN
ejpam-2688	226	49	,	,	PUNCT
ejpam-2688	226	50	and	and	CCONJ
ejpam-2688	226	51	the	the	DET
ejpam-2688	226	52	complexity	complexity	NOUN
ejpam-2688	226	53	of	of	ADP
ejpam-2688	226	54	the	the	DET
ejpam-2688	226	55	reduced	reduce	VERB
ejpam-2688	226	56	rank	rank	NOUN
ejpam-2688	226	57	hybrid	hybrid	NOUN
ejpam-2688	226	58	stabilized	stabilize	VERB
ejpam-2688	226	59	kernel	kernel	NOUN
ejpam-2688	226	60	matrix	matrix	NOUN
ejpam-2688	226	61	;	;	PUNCT
ejpam-2688	226	62	this	this	PRON
ejpam-2688	226	63	is	be	AUX
ejpam-2688	226	64	for	for	ADP
ejpam-2688	226	65	the	the	DET
ejpam-2688	226	66	complexity	complexity	NOUN
ejpam-2688	226	67	term	term	NOUN
ejpam-2688	226	68	of	of	ADP
ejpam-2688	226	69	icom	icom	PROPN
ejpam-2688	226	70	pperf	pperf	PROPN
ejpam-2688	226	71	in	in	ADP
ejpam-2688	226	72	(	(	PUNCT
ejpam-2688	226	73	10	10	NUM
ejpam-2688	226	74	)	)	PUNCT
ejpam-2688	226	75	(	(	PUNCT
ejpam-2688	226	76	iii	iii	X
ejpam-2688	226	77	)	)	PUNCT
ejpam-2688	226	78	use	use	VERB
ejpam-2688	226	79	the	the	DET
ejpam-2688	226	80	kda	kda	NOUN
ejpam-2688	226	81	model	model	NOUN
ejpam-2688	226	82	to	to	PART
ejpam-2688	226	83	classify	classify	VERB
ejpam-2688	226	84	the	the	DET
ejpam-2688	226	85	data	datum	NOUN
ejpam-2688	226	86	in	in	ADP
ejpam-2688	226	87	the	the	DET
ejpam-2688	226	88	testing	testing	NOUN
ejpam-2688	226	89	set	set	NOUN
ejpam-2688	226	90	,	,	PUNCT
ejpam-2688	226	91	measuring	measure	VERB
ejpam-2688	226	92	the	the	DET
ejpam-2688	226	93	classification	classification	NOUN
ejpam-2688	226	94	error	error	NOUN
ejpam-2688	226	95	,	,	PUNCT
ejpam-2688	226	96	and	and	CCONJ
ejpam-2688	226	97	the	the	DET
ejpam-2688	226	98	negative	negative	ADJ
ejpam-2688	226	99	maximized	maximized	ADJ
ejpam-2688	226	100	likelihood	likelihood	NOUN
ejpam-2688	226	101	;	;	PUNCT
ejpam-2688	226	102	this	this	PRON
ejpam-2688	226	103	is	be	AUX
ejpam-2688	226	104	for	for	SCONJ
ejpam-2688	226	105	the	the	DET
ejpam-2688	226	106	lack	lack	NOUN
ejpam-2688	226	107	-	-	PUNCT
ejpam-2688	226	108	of	of	ADP
ejpam-2688	226	109	-	-	PUNCT
ejpam-2688	226	110	fit	fit	ADJ
ejpam-2688	226	111	term	term	NOUN
ejpam-2688	226	112	in	in	ADP
ejpam-2688	226	113	(	(	PUNCT
ejpam-2688	226	114	10	10	NUM
ejpam-2688	226	115	)	)	PUNCT
ejpam-2688	226	116	(	(	PUNCT
ejpam-2688	226	117	iv	iv	X
ejpam-2688	226	118	)	)	PUNCT
ejpam-2688	226	119	join	join	VERB
ejpam-2688	226	120	the	the	DET
ejpam-2688	226	121	two	two	NUM
ejpam-2688	226	122	parts	part	NOUN
ejpam-2688	226	123	of	of	ADP
ejpam-2688	226	124	icom	icom	PROPN
ejpam-2688	226	125	pperf	pperf	PROPN
ejpam-2688	226	126	together	together	ADV
ejpam-2688	226	127	4	4	NUM
ejpam-2688	226	128	.	.	PUNCT
ejpam-2688	226	129	numerical	numerical	ADJ
ejpam-2688	226	130	results	result	NOUN
ejpam-2688	226	131	4.1	4.1	NUM
ejpam-2688	226	132	.	.	PUNCT
ejpam-2688	227	1	x	x	X
ejpam-2688	227	2	-	-	PUNCT
ejpam-2688	227	3	ray	ray	NOUN
ejpam-2688	227	4	burst	burst	NOUN
ejpam-2688	227	5	event	event	NOUN
ejpam-2688	227	6	data	data	VERB
ejpam-2688	227	7	our	our	PRON
ejpam-2688	227	8	first	first	ADJ
ejpam-2688	227	9	example	example	NOUN
ejpam-2688	227	10	is	be	AUX
ejpam-2688	227	11	an	an	DET
ejpam-2688	227	12	easy	easy	ADJ
ejpam-2688	227	13	2	2	NUM
ejpam-2688	227	14	-	-	PUNCT
ejpam-2688	227	15	dimensional	dimensional	ADJ
ejpam-2688	227	16	dataset	dataset	NOUN
ejpam-2688	227	17	regarding	regard	VERB
ejpam-2688	227	18	x	x	NOUN
ejpam-2688	227	19	-	-	NOUN
ejpam-2688	227	20	ray	ray	NOUN
ejpam-2688	227	21	bursts	burst	NOUN
ejpam-2688	227	22	as	as	SCONJ
ejpam-2688	227	23	gathered	gather	VERB
ejpam-2688	227	24	by	by	ADP
ejpam-2688	227	25	the	the	DET
ejpam-2688	227	26	phebus	phebus	ADJ
ejpam-2688	227	27	instrument	instrument	NOUN
ejpam-2688	227	28	on	on	ADP
ejpam-2688	227	29	the	the	DET
ejpam-2688	227	30	granat	granat	NOUN
ejpam-2688	227	31	satellite	satellite	NOUN
ejpam-2688	227	32	.	.	PUNCT
ejpam-2688	228	1	this	this	DET
ejpam-2688	228	2	data	datum	NOUN
ejpam-2688	228	3	was	be	AUX
ejpam-2688	228	4	gathered	gather	VERB
ejpam-2688	228	5	with	with	ADP
ejpam-2688	228	6	the	the	DET
ejpam-2688	228	7	purpose	purpose	NOUN
ejpam-2688	228	8	of	of	ADP
ejpam-2688	228	9	predicting	predict	VERB
ejpam-2688	228	10	the	the	DET
ejpam-2688	228	11	effects	effect	NOUN
ejpam-2688	228	12	of	of	ADP
ejpam-2688	228	13	x	x	NOUN
ejpam-2688	228	14	-	-	NOUN
ejpam-2688	228	15	ray	ray	NOUN
ejpam-2688	228	16	bursts	burst	NOUN
ejpam-2688	228	17	on	on	ADP
ejpam-2688	228	18	weather	weather	NOUN
ejpam-2688	228	19	.	.	PUNCT
ejpam-2688	229	1	there	there	PRON
ejpam-2688	229	2	are	be	VERB
ejpam-2688	229	3	two	two	NUM
ejpam-2688	229	4	classes	class	NOUN
ejpam-2688	229	5	of	of	ADP
ejpam-2688	229	6	data	datum	NOUN
ejpam-2688	229	7	:	:	PUNCT
ejpam-2688	229	8	the	the	DET
ejpam-2688	229	9	first	first	ADJ
ejpam-2688	229	10	class	class	NOUN
ejpam-2688	229	11	j.	j.	PROPN
ejpam-2688	229	12	howe	howe	PROPN
ejpam-2688	229	13	,	,	PUNCT
ejpam-2688	229	14	h.	h.	PROPN
ejpam-2688	229	15	bozdogan	bozdogan	PROPN
ejpam-2688	229	16	/	/	SYM
ejpam-2688	229	17	eur	eur	PROPN
ejpam-2688	229	18	.	.	PUNCT
ejpam-2688	230	1	j.	j.	PROPN
ejpam-2688	230	2	pure	pure	PROPN
ejpam-2688	230	3	appl	appl	PROPN
ejpam-2688	230	4	.	.	PROPN
ejpam-2688	230	5	math	math	PROPN
ejpam-2688	230	6	,	,	PUNCT
ejpam-2688	230	7	9	9	NUM
ejpam-2688	230	8	(	(	PUNCT
ejpam-2688	230	9	2016	2016	NUM
ejpam-2688	230	10	)	)	PUNCT
ejpam-2688	230	11	,	,	PUNCT
ejpam-2688	230	12	216	216	NUM
ejpam-2688	230	13	-	-	SYM
ejpam-2688	230	14	230	230	NUM
ejpam-2688	230	15	225	225	NUM
ejpam-2688	230	16	with	with	ADP
ejpam-2688	230	17	n1	n1	PROPN
ejpam-2688	230	18	=	=	SYM
ejpam-2688	230	19	132	132	NUM
ejpam-2688	230	20	observations	observation	NOUN
ejpam-2688	230	21	,	,	PUNCT
ejpam-2688	230	22	and	and	CCONJ
ejpam-2688	230	23	the	the	DET
ejpam-2688	230	24	second	second	ADJ
ejpam-2688	230	25	with	with	ADP
ejpam-2688	230	26	the	the	DET
ejpam-2688	230	27	remaining	remain	VERB
ejpam-2688	230	28	n2	n2	NOUN
ejpam-2688	230	29	=	=	SYM
ejpam-2688	230	30	42	42	NUM
ejpam-2688	230	31	.	.	PUNCT
ejpam-2688	230	32	table	table	NOUN
ejpam-2688	230	33	2	2	NUM
ejpam-2688	230	34	displays	display	VERB
ejpam-2688	230	35	the	the	DET
ejpam-2688	230	36	four	four	NUM
ejpam-2688	230	37	unique	unique	ADJ
ejpam-2688	230	38	solutions	solution	NOUN
ejpam-2688	230	39	chosen	choose	VERB
ejpam-2688	230	40	across	across	ADP
ejpam-2688	230	41	by	by	ADP
ejpam-2688	230	42	the	the	DET
ejpam-2688	230	43	cvga	cvga	NOUN
ejpam-2688	230	44	.	.	PUNCT
ejpam-2688	231	1	table	table	NOUN
ejpam-2688	231	2	2	2	NUM
ejpam-2688	231	3	:	:	PUNCT
ejpam-2688	231	4	models	model	NOUN
ejpam-2688	231	5	selected	select	VERB
ejpam-2688	231	6	for	for	ADP
ejpam-2688	231	7	the	the	DET
ejpam-2688	231	8	x	x	ADJ
ejpam-2688	231	9	-	-	NOUN
ejpam-2688	231	10	ray	ray	NOUN
ejpam-2688	231	11	burst	burst	ADJ
ejpam-2688	231	12	data	datum	NOUN
ejpam-2688	231	13	.	.	PUNCT
ejpam-2688	232	1	subset	subset	PROPN
ejpam-2688	232	2	kernel	kernel	PROPN
ejpam-2688	232	3	icom	icom	PROPN
ejpam-2688	232	4	pperf	pperf	PROPN
ejpam-2688	232	5	training	training	NOUN
ejpam-2688	232	6	err	err	PROPN
ejpam-2688	232	7	.	.	PUNCT
ejpam-2688	233	1	ci	ci	PROPN
ejpam-2688	233	2	testing	testing	PROPN
ejpam-2688	233	3	err	err	PROPN
ejpam-2688	233	4	.	.	PUNCT
ejpam-2688	234	1	ci	ci	PROPN
ejpam-2688	234	2	ga	ga	PROPN
ejpam-2688	234	3	.	.	PROPN
ejpam-2688	234	4	freq	freq	PROPN
ejpam-2688	234	5	.	.	PUNCT
ejpam-2688	235	1	{	{	PUNCT
ejpam-2688	235	2	1,2	1,2	NUM
ejpam-2688	235	3	}	}	PUNCT
ejpam-2688	235	4	laplace	laplace	NOUN
ejpam-2688	235	5	-77.78	-77.78	PROPN
ejpam-2688	236	1	[	[	X
ejpam-2688	236	2	0.00,0.00	0.00,0.00	X
ejpam-2688	236	3	]	]	X
ejpam-2688	236	4	[	[	X
ejpam-2688	236	5	0.72,0.72	0.72,0.72	NOUN
ejpam-2688	236	6	]	]	X
ejpam-2688	236	7	86	86	NUM
ejpam-2688	236	8	{	{	PUNCT
ejpam-2688	236	9	1,2	1,2	NUM
ejpam-2688	236	10	}	}	PUNCT
ejpam-2688	236	11	exponential	exponential	NOUN
ejpam-2688	236	12	-71.81	-71.81	PUNCT
ejpam-2688	237	1	[	[	X
ejpam-2688	237	2	0.00,0.00	0.00,0.00	X
ejpam-2688	237	3	]	]	X
ejpam-2688	237	4	[	[	X
ejpam-2688	237	5	0.57,0.89	0.57,0.89	X
ejpam-2688	237	6	]	]	X
ejpam-2688	237	7	10	10	NUM
ejpam-2688	237	8	{	{	PUNCT
ejpam-2688	237	9	1,2	1,2	NUM
ejpam-2688	237	10	}	}	PUNCT
ejpam-2688	237	11	inv	inv	VERB
ejpam-2688	237	12	.	.	PUNCT
ejpam-2688	238	1	multi	multi	ADJ
ejpam-2688	238	2	-	-	ADJ
ejpam-2688	238	3	quadric	quadric	ADJ
ejpam-2688	238	4	-55.2	-55.2	PROPN
ejpam-2688	239	1	[	[	X
ejpam-2688	239	2	0.00,0.00	0.00,0.00	X
ejpam-2688	239	3	]	]	X
ejpam-2688	239	4	[	[	X
ejpam-2688	239	5	0.33,1.29	0.33,1.29	X
ejpam-2688	239	6	]	]	X
ejpam-2688	239	7	1	1	NUM
ejpam-2688	239	8	{	{	PUNCT
ejpam-2688	239	9	1	1	NUM
ejpam-2688	239	10	}	}	PUNCT
ejpam-2688	239	11	laplace	laplace	NOUN
ejpam-2688	240	1	9.12	9.12	NUM
ejpam-2688	240	2	[	[	NOUN
ejpam-2688	240	3	0.00,2.62	0.00,2.62	X
ejpam-2688	240	4	]	]	X
ejpam-2688	240	5	[	[	X
ejpam-2688	240	6	0.45,2.33	0.45,2.33	X
ejpam-2688	240	7	]	]	SYM
ejpam-2688	240	8	3	3	NUM
ejpam-2688	240	9	not	not	PART
ejpam-2688	240	10	only	only	ADV
ejpam-2688	240	11	was	be	AUX
ejpam-2688	240	12	the	the	DET
ejpam-2688	240	13	best	good	ADJ
ejpam-2688	240	14	solution	solution	NOUN
ejpam-2688	240	15	selected	select	VERB
ejpam-2688	240	16	by	by	ADP
ejpam-2688	240	17	86	86	NUM
ejpam-2688	240	18	%	%	NOUN
ejpam-2688	240	19	of	of	ADP
ejpam-2688	240	20	the	the	DET
ejpam-2688	240	21	replications	replication	NOUN
ejpam-2688	240	22	,	,	PUNCT
ejpam-2688	240	23	more	more	ADJ
ejpam-2688	240	24	than	than	ADP
ejpam-2688	240	25	half	half	NOUN
ejpam-2688	240	26	of	of	ADP
ejpam-2688	240	27	the	the	DET
ejpam-2688	240	28	total	total	ADJ
ejpam-2688	240	29	generations	generation	NOUN
ejpam-2688	240	30	selected	select	VERB
ejpam-2688	240	31	it	it	PRON
ejpam-2688	240	32	.	.	PUNCT
ejpam-2688	241	1	using	use	VERB
ejpam-2688	241	2	the	the	DET
ejpam-2688	241	3	laplace	laplace	NOUN
ejpam-2688	241	4	kernel	kernel	PROPN
ejpam-2688	241	5	function	function	NOUN
ejpam-2688	241	6	on	on	ADP
ejpam-2688	241	7	both	both	DET
ejpam-2688	241	8	variables	variable	NOUN
ejpam-2688	241	9	of	of	ADP
ejpam-2688	241	10	this	this	DET
ejpam-2688	241	11	data	data	NOUN
ejpam-2688	241	12	is	be	AUX
ejpam-2688	241	13	a	a	DET
ejpam-2688	241	14	very	very	ADV
ejpam-2688	241	15	clear	clear	ADJ
ejpam-2688	241	16	winner	winner	NOUN
ejpam-2688	241	17	with	with	ADP
ejpam-2688	241	18	a	a	DET
ejpam-2688	241	19	0.72	0.72	NUM
ejpam-2688	241	20	%	%	NOUN
ejpam-2688	241	21	probability	probability	NOUN
ejpam-2688	241	22	of	of	ADP
ejpam-2688	241	23	misclassification	misclassification	NOUN
ejpam-2688	241	24	,	,	PUNCT
ejpam-2688	241	25	not	not	PART
ejpam-2688	241	26	that	that	SCONJ
ejpam-2688	241	27	any	any	PRON
ejpam-2688	241	28	of	of	ADP
ejpam-2688	241	29	these	these	DET
ejpam-2688	241	30	four	four	NUM
ejpam-2688	241	31	models	model	NOUN
ejpam-2688	241	32	had	have	VERB
ejpam-2688	241	33	unreasonable	unreasonable	ADJ
ejpam-2688	241	34	error	error	NOUN
ejpam-2688	241	35	rates	rate	NOUN
ejpam-2688	241	36	.	.	PUNCT
ejpam-2688	242	1	figure	figure	NOUN
ejpam-2688	242	2	2	2	NUM
ejpam-2688	242	3	has	have	VERB
ejpam-2688	242	4	the	the	DET
ejpam-2688	242	5	scatter	scatter	NOUN
ejpam-2688	242	6	plots	plot	NOUN
ejpam-2688	242	7	plus	plus	CCONJ
ejpam-2688	242	8	the	the	DET
ejpam-2688	242	9	contours	contours	NOUN
ejpam-2688	242	10	for	for	ADP
ejpam-2688	242	11	the	the	DET
ejpam-2688	242	12	top	top	ADJ
ejpam-2688	242	13	two	two	NUM
ejpam-2688	242	14	solutions	solution	NOUN
ejpam-2688	242	15	.	.	PUNCT
ejpam-2688	243	1	note	note	VERB
ejpam-2688	243	2	the	the	DET
ejpam-2688	243	3	clear	clear	ADJ
ejpam-2688	243	4	separation	separation	NOUN
ejpam-2688	243	5	boundary	boundary	ADJ
ejpam-2688	243	6	between	between	ADP
ejpam-2688	243	7	each	each	DET
ejpam-2688	243	8	group	group	NOUN
ejpam-2688	243	9	hence	hence	ADV
ejpam-2688	243	10	the	the	DET
ejpam-2688	243	11	low	low	ADJ
ejpam-2688	243	12	misclassification	misclassification	NOUN
ejpam-2688	243	13	rates	rate	NOUN
ejpam-2688	243	14	are	be	AUX
ejpam-2688	243	15	not	not	PART
ejpam-2688	243	16	unexpected	unexpected	ADJ
ejpam-2688	243	17	.	.	PUNCT
ejpam-2688	244	1	both	both	DET
ejpam-2688	244	2	models	model	NOUN
ejpam-2688	244	3	used	use	VERB
ejpam-2688	244	4	a	a	DET
ejpam-2688	244	5	small	small	ADJ
ejpam-2688	244	6	number	number	NOUN
ejpam-2688	244	7	of	of	ADP
ejpam-2688	244	8	support	support	NOUN
ejpam-2688	244	9	vectors	vector	NOUN
ejpam-2688	244	10	14	14	NUM
ejpam-2688	244	11	and	and	CCONJ
ejpam-2688	244	12	11	11	NUM
ejpam-2688	244	13	,	,	PUNCT
ejpam-2688	244	14	respectively	respectively	ADV
ejpam-2688	244	15	.	.	PUNCT
ejpam-2688	245	1	less	less	ADJ
ejpam-2688	245	2	than	than	ADP
ejpam-2688	245	3	10	10	NUM
ejpam-2688	245	4	%	%	NOUN
ejpam-2688	245	5	of	of	ADP
ejpam-2688	245	6	the	the	DET
ejpam-2688	245	7	observations	observation	NOUN
ejpam-2688	245	8	was	be	AUX
ejpam-2688	245	9	needed	need	VERB
ejpam-2688	245	10	,	,	PUNCT
ejpam-2688	245	11	which	which	PRON
ejpam-2688	245	12	shows	show	VERB
ejpam-2688	245	13	the	the	DET
ejpam-2688	245	14	efficiency	efficiency	NOUN
ejpam-2688	245	15	of	of	ADP
ejpam-2688	245	16	support	support	NOUN
ejpam-2688	245	17	vector	vector	NOUN
ejpam-2688	245	18	classification	classification	NOUN
ejpam-2688	245	19	.	.	PUNCT
ejpam-2688	246	1	clearly	clearly	ADV
ejpam-2688	246	2	the	the	DET
ejpam-2688	246	3	full	full	PROPN
ejpam-2688	246	4	ga	ga	PROPN
ejpam-2688	246	5	with	with	ADP
ejpam-2688	246	6	cross	cross	ADJ
ejpam-2688	246	7	-	-	ADJ
ejpam-2688	246	8	validation	validation	ADJ
ejpam-2688	246	9	model	model	NOUN
ejpam-2688	246	10	was	be	AUX
ejpam-2688	246	11	overkill	overkill	NOUN
ejpam-2688	246	12	for	for	ADP
ejpam-2688	246	13	this	this	DET
ejpam-2688	246	14	dataset	dataset	NOUN
ejpam-2688	246	15	,	,	PUNCT
ejpam-2688	246	16	as	as	SCONJ
ejpam-2688	246	17	complete	complete	ADJ
ejpam-2688	246	18	enumeration	enumeration	NOUN
ejpam-2688	246	19	would	would	AUX
ejpam-2688	246	20	only	only	ADV
ejpam-2688	246	21	need	need	VERB
ejpam-2688	246	22	to	to	PART
ejpam-2688	246	23	evaluate	evaluate	VERB
ejpam-2688	246	24	27	27	NUM
ejpam-2688	246	25	solutions	solution	NOUN
ejpam-2688	246	26	.	.	PUNCT
ejpam-2688	247	1	it	it	PRON
ejpam-2688	247	2	has	have	AUX
ejpam-2688	247	3	been	be	AUX
ejpam-2688	247	4	included	include	VERB
ejpam-2688	247	5	here	here	ADV
ejpam-2688	247	6	purely	purely	ADV
ejpam-2688	247	7	for	for	ADP
ejpam-2688	247	8	the	the	DET
ejpam-2688	247	9	visualization	visualization	NOUN
ejpam-2688	247	10	the	the	DET
ejpam-2688	247	11	support	support	NOUN
ejpam-2688	247	12	-	-	PUNCT
ejpam-2688	247	13	vector	vector	NOUN
ejpam-2688	247	14	-	-	PUNCT
ejpam-2688	247	15	based	base	VERB
ejpam-2688	247	16	separation	separation	NOUN
ejpam-2688	247	17	areas	area	NOUN
ejpam-2688	247	18	,	,	PUNCT
ejpam-2688	247	19	which	which	PRON
ejpam-2688	247	20	will	will	AUX
ejpam-2688	247	21	not	not	PART
ejpam-2688	247	22	be	be	AUX
ejpam-2688	247	23	possible	possible	ADJ
ejpam-2688	247	24	for	for	ADP
ejpam-2688	247	25	the	the	DET
ejpam-2688	247	26	other	other	ADJ
ejpam-2688	247	27	examples	example	NOUN
ejpam-2688	247	28	.	.	PUNCT
ejpam-2688	248	1	(	(	PUNCT
ejpam-2688	248	2	a	a	X
ejpam-2688	248	3	)	)	PUNCT
ejpam-2688	248	4	with	with	ADP
ejpam-2688	248	5	laplace	laplace	NOUN
ejpam-2688	248	6	kernel	kernel	PROPN
ejpam-2688	248	7	(	(	PUNCT
ejpam-2688	248	8	b	b	NOUN
ejpam-2688	248	9	)	)	PUNCT
ejpam-2688	248	10	with	with	ADP
ejpam-2688	248	11	exponential	exponential	ADJ
ejpam-2688	248	12	kernel	kernel	NOUN
ejpam-2688	248	13	figure	figure	NOUN
ejpam-2688	248	14	2	2	NUM
ejpam-2688	248	15	:	:	PUNCT
ejpam-2688	248	16	demonstrating	demonstrate	VERB
ejpam-2688	248	17	separation	separation	NOUN
ejpam-2688	248	18	with	with	ADP
ejpam-2688	248	19	the	the	DET
ejpam-2688	248	20	two	two	NUM
ejpam-2688	248	21	best	good	ADJ
ejpam-2688	248	22	kda	kda	NOUN
ejpam-2688	248	23	models	model	NOUN
ejpam-2688	248	24	.	.	PUNCT
ejpam-2688	249	1	the	the	DET
ejpam-2688	249	2	classes	class	NOUN
ejpam-2688	249	3	are	be	AUX
ejpam-2688	249	4	marked	mark	VERB
ejpam-2688	249	5	by	by	ADP
ejpam-2688	249	6	"	"	PUNCT
ejpam-2688	249	7	x	x	NOUN
ejpam-2688	249	8	"	"	PUNCT
ejpam-2688	249	9	and	and	CCONJ
ejpam-2688	249	10	"	"	PUNCT
ejpam-2688	249	11	+	+	ADJ
ejpam-2688	249	12	"	"	PUNCT
ejpam-2688	249	13	,	,	PUNCT
ejpam-2688	249	14	and	and	CCONJ
ejpam-2688	249	15	"	"	PUNCT
ejpam-2688	249	16	o	o	NOUN
ejpam-2688	249	17	"	"	PUNCT
ejpam-2688	249	18	indicates	indicate	VERB
ejpam-2688	249	19	the	the	DET
ejpam-2688	249	20	support	support	NOUN
ejpam-2688	249	21	vectors	vector	NOUN
ejpam-2688	249	22	.	.	PUNCT
ejpam-2688	250	1	j.	j.	PROPN
ejpam-2688	250	2	howe	howe	PROPN
ejpam-2688	250	3	,	,	PUNCT
ejpam-2688	250	4	h.	h.	PROPN
ejpam-2688	250	5	bozdogan	bozdogan	PROPN
ejpam-2688	250	6	/	/	SYM
ejpam-2688	250	7	eur	eur	PROPN
ejpam-2688	250	8	.	.	PUNCT
ejpam-2688	251	1	j.	j.	PROPN
ejpam-2688	251	2	pure	pure	PROPN
ejpam-2688	251	3	appl	appl	PROPN
ejpam-2688	251	4	.	.	PROPN
ejpam-2688	251	5	math	math	PROPN
ejpam-2688	251	6	,	,	PUNCT
ejpam-2688	251	7	9	9	NUM
ejpam-2688	251	8	(	(	PUNCT
ejpam-2688	251	9	2016	2016	NUM
ejpam-2688	251	10	)	)	PUNCT
ejpam-2688	251	11	,	,	PUNCT
ejpam-2688	251	12	216	216	NUM
ejpam-2688	251	13	-	-	SYM
ejpam-2688	251	14	230	230	NUM
ejpam-2688	251	15	226	226	NUM
ejpam-2688	251	16	4.2	4.2	NUM
ejpam-2688	251	17	.	.	PUNCT
ejpam-2688	252	1	wine	wine	NOUN
ejpam-2688	252	2	composition	composition	NOUN
ejpam-2688	252	3	data	datum	NOUN
ejpam-2688	252	4	our	our	PRON
ejpam-2688	252	5	next	next	ADJ
ejpam-2688	252	6	example	example	NOUN
ejpam-2688	252	7	is	be	AUX
ejpam-2688	252	8	the	the	DET
ejpam-2688	252	9	wine	wine	NOUN
ejpam-2688	252	10	recognition	recognition	NOUN
ejpam-2688	252	11	dataset	dataset	NOUN
ejpam-2688	252	12	of	of	ADP
ejpam-2688	252	13	m.	m.	PROPN
ejpam-2688	252	14	fiorina	fiorina	PROPN
ejpam-2688	252	15	,	,	PUNCT
ejpam-2688	252	16	et	et	PROPN
ejpam-2688	252	17	al	al	PROPN
ejpam-2688	252	18	.	.	PROPN
ejpam-2688	252	19	,	,	PUNCT
ejpam-2688	252	20	used	use	VERB
ejpam-2688	252	21	in	in	ADP
ejpam-2688	252	22	[	[	X
ejpam-2688	252	23	1	1	NUM
ejpam-2688	252	24	]	]	PUNCT
ejpam-2688	252	25	.	.	PUNCT
ejpam-2688	253	1	these	these	DET
ejpam-2688	253	2	data	datum	NOUN
ejpam-2688	253	3	are	be	AUX
ejpam-2688	253	4	the	the	DET
ejpam-2688	253	5	results	result	NOUN
ejpam-2688	253	6	of	of	ADP
ejpam-2688	253	7	a	a	DET
ejpam-2688	253	8	chemical	chemical	ADJ
ejpam-2688	253	9	analysis	analysis	NOUN
ejpam-2688	253	10	of	of	ADP
ejpam-2688	253	11	n	n	NOUN
ejpam-2688	253	12	=	=	SYM
ejpam-2688	253	13	178	178	NUM
ejpam-2688	253	14	wines	wine	NOUN
ejpam-2688	253	15	grown	grow	VERB
ejpam-2688	253	16	in	in	ADP
ejpam-2688	253	17	the	the	DET
ejpam-2688	253	18	same	same	ADJ
ejpam-2688	253	19	region	region	NOUN
ejpam-2688	253	20	in	in	ADP
ejpam-2688	253	21	italy	italy	PROPN
ejpam-2688	253	22	but	but	CCONJ
ejpam-2688	253	23	derived	derive	VERB
ejpam-2688	253	24	from	from	ADP
ejpam-2688	253	25	k	k	PROPN
ejpam-2688	253	26	=	=	SYM
ejpam-2688	253	27	3	3	NUM
ejpam-2688	253	28	different	different	ADJ
ejpam-2688	253	29	cultivars	cultivar	NOUN
ejpam-2688	253	30	(	(	PUNCT
ejpam-2688	253	31	n1	n1	NOUN
ejpam-2688	253	32	=	=	SYM
ejpam-2688	253	33	59	59	NUM
ejpam-2688	253	34	,	,	PUNCT
ejpam-2688	253	35	n2	n2	NOUN
ejpam-2688	253	36	=	=	SYM
ejpam-2688	253	37	71	71	NUM
ejpam-2688	253	38	,	,	PUNCT
ejpam-2688	253	39	n3	n3	NOUN
ejpam-2688	253	40	=	=	SYM
ejpam-2688	253	41	48	48	NUM
ejpam-2688	253	42	)	)	PUNCT
ejpam-2688	253	43	.	.	PUNCT
ejpam-2688	254	1	the	the	DET
ejpam-2688	254	2	analysis	analysis	NOUN
ejpam-2688	254	3	determined	determine	VERB
ejpam-2688	254	4	the	the	DET
ejpam-2688	254	5	quantities	quantity	NOUN
ejpam-2688	254	6	of	of	ADP
ejpam-2688	254	7	p	p	NOUN
ejpam-2688	254	8	=	=	SYM
ejpam-2688	254	9	13	13	NUM
ejpam-2688	254	10	chemical	chemical	NOUN
ejpam-2688	254	11	constituents	constituent	NOUN
ejpam-2688	254	12	found	find	VERB
ejpam-2688	254	13	in	in	ADP
ejpam-2688	254	14	each	each	PRON
ejpam-2688	254	15	of	of	ADP
ejpam-2688	254	16	the	the	DET
ejpam-2688	254	17	three	three	NUM
ejpam-2688	254	18	types	type	NOUN
ejpam-2688	254	19	of	of	ADP
ejpam-2688	254	20	wines	wine	NOUN
ejpam-2688	254	21	.	.	PUNCT
ejpam-2688	255	1	the	the	DET
ejpam-2688	255	2	variables	variable	NOUN
ejpam-2688	255	3	are	be	AUX
ejpam-2688	255	4	shown	show	VERB
ejpam-2688	255	5	in	in	ADP
ejpam-2688	255	6	table	table	NOUN
ejpam-2688	255	7	3	3	NUM
ejpam-2688	255	8	.	.	PUNCT
ejpam-2688	255	9	table	table	NOUN
ejpam-2688	255	10	3	3	NUM
ejpam-2688	255	11	:	:	PUNCT
ejpam-2688	255	12	wine	wine	NOUN
ejpam-2688	255	13	data	datum	NOUN
ejpam-2688	255	14	variables	variable	NOUN
ejpam-2688	255	15	.	.	PUNCT
ejpam-2688	256	1	variable	variable	ADJ
ejpam-2688	256	2	variable	variable	NOUN
ejpam-2688	256	3	x1	x1	PROPN
ejpam-2688	256	4	alcohol	alcohol	PROPN
ejpam-2688	256	5	x8	x8	PROPN
ejpam-2688	256	6	non	non	ADJ
ejpam-2688	256	7	-	-	ADJ
ejpam-2688	256	8	flavonoid	flavonoid	ADJ
ejpam-2688	256	9	phenols	phenol	NOUN
ejpam-2688	256	10	x2	x2	PROPN
ejpam-2688	256	11	malic	malic	PROPN
ejpam-2688	256	12	acid	acid	PROPN
ejpam-2688	256	13	x9	x9	PROPN
ejpam-2688	256	14	proanthocyanins	proanthocyanin	NOUN
ejpam-2688	256	15	x3	x3	VERB
ejpam-2688	256	16	ash	ash	NOUN
ejpam-2688	256	17	x10	x10	ADP
ejpam-2688	256	18	color	color	NOUN
ejpam-2688	256	19	intensity	intensity	NOUN
ejpam-2688	257	1	x4	x4	PROPN
ejpam-2688	257	2	alkalinity	alkalinity	NOUN
ejpam-2688	257	3	of	of	ADP
ejpam-2688	257	4	ash	ash	NOUN
ejpam-2688	257	5	x11	x11	NOUN
ejpam-2688	257	6	hue	hue	NOUN
ejpam-2688	257	7	x5	x5	PROPN
ejpam-2688	257	8	magnesium	magnesium	NOUN
ejpam-2688	257	9	x12	x12	NUM
ejpam-2688	257	10	od280	od280	PROPN
ejpam-2688	257	11	/	/	SYM
ejpam-2688	257	12	od315	od315	PROPN
ejpam-2688	257	13	of	of	ADP
ejpam-2688	257	14	diluted	dilute	VERB
ejpam-2688	257	15	wines	wine	NOUN
ejpam-2688	257	16	x6	x6	PROPN
ejpam-2688	257	17	total	total	ADJ
ejpam-2688	257	18	phenols	phenol	NOUN
ejpam-2688	257	19	x13	x13	NOUN
ejpam-2688	257	20	proline	proline	NOUN
ejpam-2688	257	21	x7	x7	NOUN
ejpam-2688	257	22	total	total	ADJ
ejpam-2688	257	23	flavonoids	flavonoid	NOUN
ejpam-2688	257	24	with	with	ADP
ejpam-2688	257	25	this	this	DET
ejpam-2688	257	26	dataset	dataset	NOUN
ejpam-2688	257	27	,	,	PUNCT
ejpam-2688	257	28	there	there	PRON
ejpam-2688	257	29	are	be	VERB
ejpam-2688	257	30	9×	9×	NUM
ejpam-2688	257	31	�	�	NOUN
ejpam-2688	257	32	213	213	NUM
ejpam-2688	257	33	−	−	NUM
ejpam-2688	257	34	1	1	NUM
ejpam-2688	257	35	�	�	NOUN
ejpam-2688	257	36	=	=	NOUN
ejpam-2688	257	37	73,719	73,719	NUM
ejpam-2688	257	38	possible	possible	ADJ
ejpam-2688	257	39	nontrivial	nontrivial	ADJ
ejpam-2688	257	40	solutions	solution	NOUN
ejpam-2688	257	41	;	;	PUNCT
ejpam-2688	257	42	the	the	DET
ejpam-2688	257	43	cvga	cvga	NOUN
ejpam-2688	257	44	with	with	ADP
ejpam-2688	257	45	100	100	NUM
ejpam-2688	257	46	replications	replication	NOUN
ejpam-2688	257	47	of	of	ADP
ejpam-2688	257	48	the	the	DET
ejpam-2688	257	49	ga	ga	PROPN
ejpam-2688	257	50	explored	explore	VERB
ejpam-2688	257	51	nearly	nearly	ADV
ejpam-2688	257	52	half	half	NOUN
ejpam-2688	257	53	of	of	ADP
ejpam-2688	257	54	the	the	DET
ejpam-2688	257	55	solution	solution	NOUN
ejpam-2688	257	56	space	space	NOUN
ejpam-2688	257	57	.	.	PUNCT
ejpam-2688	258	1	none	none	NOUN
ejpam-2688	258	2	of	of	ADP
ejpam-2688	258	3	the	the	DET
ejpam-2688	258	4	generations	generation	NOUN
ejpam-2688	258	5	selected	select	VERB
ejpam-2688	258	6	the	the	DET
ejpam-2688	258	7	saturated	saturate	VERB
ejpam-2688	258	8	model	model	NOUN
ejpam-2688	258	9	with	with	ADP
ejpam-2688	258	10	all	all	DET
ejpam-2688	258	11	features	feature	NOUN
ejpam-2688	258	12	as	as	ADP
ejpam-2688	258	13	the	the	DET
ejpam-2688	258	14	best	good	ADJ
ejpam-2688	258	15	;	;	PUNCT
ejpam-2688	258	16	the	the	DET
ejpam-2688	258	17	most	most	ADV
ejpam-2688	258	18	frequently	frequently	ADV
ejpam-2688	258	19	selected	select	VERB
ejpam-2688	258	20	kernel	kernel	NOUN
ejpam-2688	258	21	functions	function	NOUN
ejpam-2688	258	22	were	be	AUX
ejpam-2688	258	23	the	the	DET
ejpam-2688	258	24	quadratic	quadratic	ADJ
ejpam-2688	258	25	(	(	PUNCT
ejpam-2688	258	26	25	25	NUM
ejpam-2688	258	27	%	%	NOUN
ejpam-2688	258	28	)	)	PUNCT
ejpam-2688	258	29	and	and	CCONJ
ejpam-2688	258	30	exponential	exponential	ADJ
ejpam-2688	258	31	(	(	PUNCT
ejpam-2688	258	32	18	18	NUM
ejpam-2688	258	33	%	%	NOUN
ejpam-2688	258	34	)	)	PUNCT
ejpam-2688	258	35	.	.	PUNCT
ejpam-2688	259	1	in	in	ADP
ejpam-2688	259	2	table	table	NOUN
ejpam-2688	259	3	4	4	NUM
ejpam-2688	259	4	,	,	PUNCT
ejpam-2688	259	5	we	we	PRON
ejpam-2688	259	6	report	report	VERB
ejpam-2688	259	7	the	the	DET
ejpam-2688	259	8	best	good	ADJ
ejpam-2688	259	9	6	6	NUM
ejpam-2688	259	10	models	model	NOUN
ejpam-2688	259	11	with	with	ADP
ejpam-2688	259	12	their	their	PRON
ejpam-2688	259	13	classification	classification	NOUN
ejpam-2688	259	14	results	result	NOUN
ejpam-2688	259	15	.	.	PUNCT
ejpam-2688	260	1	the	the	DET
ejpam-2688	260	2	top	top	ADJ
ejpam-2688	260	3	6	6	NUM
ejpam-2688	260	4	,	,	PUNCT
ejpam-2688	260	5	as	as	SCONJ
ejpam-2688	260	6	opposed	oppose	VERB
ejpam-2688	260	7	to	to	ADP
ejpam-2688	260	8	a	a	DET
ejpam-2688	260	9	round	round	ADJ
ejpam-2688	260	10	number	number	NOUN
ejpam-2688	260	11	,	,	PUNCT
ejpam-2688	260	12	were	be	AUX
ejpam-2688	260	13	chosen	choose	VERB
ejpam-2688	260	14	,	,	PUNCT
ejpam-2688	260	15	since	since	SCONJ
ejpam-2688	260	16	they	they	PRON
ejpam-2688	260	17	had	have	AUX
ejpam-2688	260	18	identically	identically	ADV
ejpam-2688	260	19	perfect	perfect	VERB
ejpam-2688	260	20	training	training	NOUN
ejpam-2688	260	21	errors	error	NOUN
ejpam-2688	260	22	.	.	PUNCT
ejpam-2688	261	1	table	table	NOUN
ejpam-2688	261	2	4	4	NUM
ejpam-2688	261	3	:	:	PUNCT
ejpam-2688	261	4	top	top	ADJ
ejpam-2688	261	5	6	6	NUM
ejpam-2688	261	6	models	model	NOUN
ejpam-2688	261	7	selected	select	VERB
ejpam-2688	261	8	for	for	ADP
ejpam-2688	261	9	wine	wine	NOUN
ejpam-2688	261	10	data	datum	NOUN
ejpam-2688	261	11	.	.	PUNCT
ejpam-2688	262	1	subset	subset	PROPN
ejpam-2688	262	2	kernel	kernel	PROPN
ejpam-2688	262	3	icom	icom	PROPN
ejpam-2688	262	4	pperf	pperf	PROPN
ejpam-2688	262	5	training	training	NOUN
ejpam-2688	262	6	error	error	NOUN
ejpam-2688	262	7	testing	testing	NOUN
ejpam-2688	262	8	error	error	NOUN
ejpam-2688	262	9	{	{	PUNCT
ejpam-2688	262	10	1−	1−	NUM
ejpam-2688	262	11	4,7,8,11−	4,7,8,11−	NUM
ejpam-2688	262	12	13	13	NUM
ejpam-2688	262	13	}	}	PUNCT
ejpam-2688	262	14	quadratic	quadratic	ADJ
ejpam-2688	262	15	-229.61	-229.61	NOUN
ejpam-2688	262	16	0.00	0.00	NUM
ejpam-2688	262	17	%	%	NOUN
ejpam-2688	262	18	0.70	0.70	NUM
ejpam-2688	262	19	%	%	NOUN
ejpam-2688	262	20	{	{	PUNCT
ejpam-2688	262	21	1,3,7,11,13	1,3,7,11,13	NUM
ejpam-2688	262	22	}	}	PUNCT
ejpam-2688	262	23	cubic	cubic	ADJ
ejpam-2688	262	24	-222.45	-222.45	PROPN
ejpam-2688	262	25	0.00	0.00	NUM
ejpam-2688	262	26	%	%	NOUN
ejpam-2688	262	27	0.70	0.70	NUM
ejpam-2688	262	28	%	%	NOUN
ejpam-2688	262	29	{	{	PUNCT
ejpam-2688	262	30	1,3,6−	1,3,6−	PROPN
ejpam-2688	262	31	8,11−	8,11−	NUM
ejpam-2688	262	32	13	13	NUM
ejpam-2688	262	33	}	}	PUNCT
ejpam-2688	262	34	quadratic	quadratic	ADJ
ejpam-2688	262	35	-145.87	-145.87	PROPN
ejpam-2688	262	36	0.00	0.00	NUM
ejpam-2688	262	37	%	%	NOUN
ejpam-2688	262	38	1.41	1.41	NUM
ejpam-2688	262	39	%	%	NOUN
ejpam-2688	262	40	{	{	PUNCT
ejpam-2688	262	41	1,3,4,7,8,9,11,12	1,3,4,7,8,9,11,12	NUM
ejpam-2688	262	42	}	}	PUNCT
ejpam-2688	262	43	quadratic	quadratic	ADJ
ejpam-2688	262	44	-127.64	-127.64	PROPN
ejpam-2688	262	45	0.00	0.00	NUM
ejpam-2688	262	46	%	%	NOUN
ejpam-2688	262	47	1.41	1.41	NUM
ejpam-2688	262	48	%	%	NOUN
ejpam-2688	262	49	{	{	PUNCT
ejpam-2688	262	50	1−	1−	NUM
ejpam-2688	262	51	3,7,10,13	3,7,10,13	NUM
ejpam-2688	262	52	}	}	PUNCT
ejpam-2688	262	53	quadratic	quadratic	ADJ
ejpam-2688	262	54	-125.01	-125.01	PROPN
ejpam-2688	262	55	0.00	0.00	NUM
ejpam-2688	262	56	%	%	NOUN
ejpam-2688	262	57	1.41	1.41	NUM
ejpam-2688	262	58	%	%	NOUN
ejpam-2688	262	59	{	{	PUNCT
ejpam-2688	262	60	1,4,6,9−	1,4,6,9−	NUM
ejpam-2688	262	61	13	13	NUM
ejpam-2688	262	62	}	}	PUNCT
ejpam-2688	262	63	quadratic	quadratic	ADJ
ejpam-2688	262	64	-123.36	-123.36	PROPN
ejpam-2688	262	65	0.00	0.00	NUM
ejpam-2688	262	66	%	%	NOUN
ejpam-2688	262	67	1.41	1.41	NUM
ejpam-2688	262	68	%	%	NOUN
ejpam-2688	262	69	all	all	DET
ejpam-2688	262	70	the	the	DET
ejpam-2688	262	71	subset	subset	NOUN
ejpam-2688	262	72	models	model	NOUN
ejpam-2688	262	73	shown	show	VERB
ejpam-2688	262	74	here	here	ADV
ejpam-2688	262	75	exhibit	exhibit	VERB
ejpam-2688	262	76	substantial	substantial	ADJ
ejpam-2688	262	77	overlap	overlap	NOUN
ejpam-2688	262	78	almost	almost	ADV
ejpam-2688	262	79	all	all	PRON
ejpam-2688	262	80	include	include	VERB
ejpam-2688	262	81	at	at	ADP
ejpam-2688	262	82	least	least	ADJ
ejpam-2688	262	83	the	the	DET
ejpam-2688	262	84	first	first	ADJ
ejpam-2688	262	85	,	,	PUNCT
ejpam-2688	262	86	third	third	ADJ
ejpam-2688	262	87	,	,	PUNCT
ejpam-2688	262	88	and	and	CCONJ
ejpam-2688	262	89	thirteenth	thirteenth	ADJ
ejpam-2688	262	90	features	feature	NOUN
ejpam-2688	262	91	.	.	PUNCT
ejpam-2688	263	1	in	in	ADP
ejpam-2688	263	2	considering	consider	VERB
ejpam-2688	263	3	the	the	DET
ejpam-2688	263	4	classification	classification	NOUN
ejpam-2688	263	5	errors	error	NOUN
ejpam-2688	263	6	,	,	PUNCT
ejpam-2688	263	7	there	there	PRON
ejpam-2688	263	8	’s	’	VERB
ejpam-2688	263	9	no	no	DET
ejpam-2688	263	10	difference	difference	NOUN
ejpam-2688	263	11	between	between	ADP
ejpam-2688	263	12	the	the	DET
ejpam-2688	263	13	best	good	ADJ
ejpam-2688	263	14	two	two	NUM
ejpam-2688	263	15	models	model	NOUN
ejpam-2688	263	16	.	.	PUNCT
ejpam-2688	264	1	additionally	additionally	ADV
ejpam-2688	264	2	,	,	PUNCT
ejpam-2688	264	3	since	since	SCONJ
ejpam-2688	264	4	the	the	DET
ejpam-2688	264	5	icom	icom	PROPN
ejpam-2688	264	6	pperf	pperf	PROPN
ejpam-2688	264	7	scores	score	NOUN
ejpam-2688	264	8	are	be	AUX
ejpam-2688	264	9	so	so	ADV
ejpam-2688	264	10	close	close	ADJ
ejpam-2688	264	11	,	,	PUNCT
ejpam-2688	264	12	it	it	PRON
ejpam-2688	264	13	’s	’	VERB
ejpam-2688	264	14	likely	likely	ADJ
ejpam-2688	264	15	,	,	PUNCT
ejpam-2688	264	16	due	due	ADP
ejpam-2688	264	17	to	to	ADP
ejpam-2688	264	18	the	the	DET
ejpam-2688	264	19	random	random	ADJ
ejpam-2688	264	20	variation	variation	NOUN
ejpam-2688	264	21	from	from	ADP
ejpam-2688	264	22	cross	cross	NOUN
ejpam-2688	264	23	validation	validation	NOUN
ejpam-2688	264	24	,	,	PUNCT
ejpam-2688	264	25	that	that	SCONJ
ejpam-2688	264	26	the	the	DET
ejpam-2688	264	27	scores	score	NOUN
ejpam-2688	264	28	are	be	AUX
ejpam-2688	264	29	not	not	PART
ejpam-2688	264	30	significantly	significantly	ADV
ejpam-2688	264	31	different	different	ADJ
ejpam-2688	264	32	.	.	PUNCT
ejpam-2688	265	1	however	however	ADV
ejpam-2688	265	2	,	,	PUNCT
ejpam-2688	265	3	the	the	DET
ejpam-2688	265	4	first	first	ADJ
ejpam-2688	265	5	model	model	NOUN
ejpam-2688	265	6	uses	use	VERB
ejpam-2688	265	7	nine	nine	NUM
ejpam-2688	265	8	variables	variable	NOUN
ejpam-2688	265	9	,	,	PUNCT
ejpam-2688	265	10	while	while	SCONJ
ejpam-2688	265	11	the	the	DET
ejpam-2688	265	12	second	second	NOUN
ejpam-2688	265	13	,	,	PUNCT
ejpam-2688	265	14	which	which	PRON
ejpam-2688	265	15	achieves	achieve	VERB
ejpam-2688	265	16	the	the	DET
ejpam-2688	265	17	same	same	ADJ
ejpam-2688	265	18	low	low	ADJ
ejpam-2688	265	19	error	error	NOUN
ejpam-2688	265	20	,	,	PUNCT
ejpam-2688	265	21	uses	use	VERB
ejpam-2688	265	22	only	only	ADV
ejpam-2688	265	23	five	five	NUM
ejpam-2688	265	24	.	.	PUNCT
ejpam-2688	266	1	hence	hence	ADV
ejpam-2688	266	2	,	,	PUNCT
ejpam-2688	266	3	the	the	DET
ejpam-2688	266	4	principle	principle	NOUN
ejpam-2688	266	5	of	of	ADP
ejpam-2688	266	6	parsimony	parsimony	NOUN
ejpam-2688	266	7	drives	drive	VERB
ejpam-2688	266	8	us	we	PRON
ejpam-2688	266	9	to	to	PART
ejpam-2688	266	10	prefer	prefer	VERB
ejpam-2688	266	11	the	the	DET
ejpam-2688	266	12	subset	subset	NOUN
ejpam-2688	266	13	{	{	PUNCT
ejpam-2688	266	14	1,3,7,11,13	1,3,7,11,13	NUM
ejpam-2688	266	15	}	}	PUNCT
ejpam-2688	266	16	.	.	PUNCT
ejpam-2688	267	1	j.	j.	PROPN
ejpam-2688	267	2	howe	howe	PROPN
ejpam-2688	267	3	,	,	PUNCT
ejpam-2688	267	4	h.	h.	PROPN
ejpam-2688	267	5	bozdogan	bozdogan	PROPN
ejpam-2688	267	6	/	/	SYM
ejpam-2688	267	7	eur	eur	PROPN
ejpam-2688	267	8	.	.	PUNCT
ejpam-2688	268	1	j.	j.	PROPN
ejpam-2688	268	2	pure	pure	PROPN
ejpam-2688	268	3	appl	appl	PROPN
ejpam-2688	268	4	.	.	PROPN
ejpam-2688	268	5	math	math	PROPN
ejpam-2688	268	6	,	,	PUNCT
ejpam-2688	268	7	9	9	NUM
ejpam-2688	268	8	(	(	PUNCT
ejpam-2688	268	9	2016	2016	NUM
ejpam-2688	268	10	)	)	PUNCT
ejpam-2688	268	11	,	,	PUNCT
ejpam-2688	268	12	216	216	NUM
ejpam-2688	268	13	-	-	SYM
ejpam-2688	268	14	230	230	NUM
ejpam-2688	268	15	227	227	NUM
ejpam-2688	268	16	in	in	ADP
ejpam-2688	268	17	figure	figure	NOUN
ejpam-2688	268	18	3	3	NUM
ejpam-2688	268	19	,	,	PUNCT
ejpam-2688	268	20	we	we	PRON
ejpam-2688	268	21	show	show	VERB
ejpam-2688	268	22	3	3	NUM
ejpam-2688	268	23	-	-	PUNCT
ejpam-2688	268	24	way	way	NOUN
ejpam-2688	268	25	scatterplots	scatterplot	NOUN
ejpam-2688	268	26	for	for	ADP
ejpam-2688	268	27	two	two	NUM
ejpam-2688	268	28	of	of	ADP
ejpam-2688	268	29	the	the	DET
ejpam-2688	268	30	possible	possible	ADJ
ejpam-2688	268	31	ten	ten	NUM
ejpam-2688	268	32	combinations	combination	NOUN
ejpam-2688	268	33	of	of	ADP
ejpam-2688	268	34	these	these	DET
ejpam-2688	268	35	five	five	NUM
ejpam-2688	268	36	variables	variable	NOUN
ejpam-2688	268	37	.	.	PUNCT
ejpam-2688	269	1	the	the	DET
ejpam-2688	269	2	plots	plot	NOUN
ejpam-2688	269	3	selected	select	VERB
ejpam-2688	269	4	were	be	AUX
ejpam-2688	269	5	fairly	fairly	ADV
ejpam-2688	269	6	representative	representative	ADJ
ejpam-2688	269	7	of	of	ADP
ejpam-2688	269	8	all	all	DET
ejpam-2688	269	9	10	10	NUM
ejpam-2688	269	10	there	there	PRON
ejpam-2688	269	11	were	be	VERB
ejpam-2688	269	12	no	no	DET
ejpam-2688	269	13	3	3	NUM
ejpam-2688	269	14	-	-	PUNCT
ejpam-2688	269	15	way	way	NOUN
ejpam-2688	269	16	plots	plot	NOUN
ejpam-2688	269	17	with	with	ADP
ejpam-2688	269	18	clear	clear	ADJ
ejpam-2688	269	19	separation	separation	NOUN
ejpam-2688	269	20	of	of	ADP
ejpam-2688	269	21	all	all	DET
ejpam-2688	269	22	classes	class	NOUN
ejpam-2688	269	23	in	in	ADP
ejpam-2688	269	24	the	the	DET
ejpam-2688	269	25	original	original	ADJ
ejpam-2688	269	26	data	data	NOUN
ejpam-2688	269	27	space	space	NOUN
ejpam-2688	269	28	.	.	PUNCT
ejpam-2688	270	1	this	this	PRON
ejpam-2688	270	2	suggests	suggest	VERB
ejpam-2688	270	3	that	that	SCONJ
ejpam-2688	270	4	the	the	DET
ejpam-2688	270	5	kernel	kernel	PROPN
ejpam-2688	270	6	methods	method	NOUN
ejpam-2688	270	7	boosted	boost	VERB
ejpam-2688	270	8	classification	classification	NOUN
ejpam-2688	270	9	performance	performance	NOUN
ejpam-2688	270	10	as	as	SCONJ
ejpam-2688	270	11	we	we	PRON
ejpam-2688	270	12	expect	expect	VERB
ejpam-2688	270	13	.	.	PUNCT
ejpam-2688	271	1	x	x	SYM
ejpam-2688	271	2	1	1	NUM
ejpam-2688	271	3	x	x	SYM
ejpam-2688	271	4	3	3	NUM
ejpam-2688	271	5	x	x	SYM
ejpam-2688	271	6	11	11	NUM
ejpam-2688	271	7	(	(	PUNCT
ejpam-2688	271	8	a	a	NOUN
ejpam-2688	271	9	)	)	PUNCT
ejpam-2688	271	10	features	feature	VERB
ejpam-2688	271	11	1×	1×	NUM
ejpam-2688	271	12	3×	3×	NUM
ejpam-2688	271	13	11	11	NUM
ejpam-2688	271	14	x	x	SYM
ejpam-2688	271	15	3	3	NUM
ejpam-2688	271	16	x	x	SYM
ejpam-2688	271	17	7	7	NUM
ejpam-2688	271	18	x	x	SYM
ejpam-2688	271	19	13	13	NUM
ejpam-2688	271	20	(	(	PUNCT
ejpam-2688	271	21	b	b	NOUN
ejpam-2688	271	22	)	)	PUNCT
ejpam-2688	271	23	features	feature	VERB
ejpam-2688	271	24	3×	3×	NUM
ejpam-2688	271	25	7×	7×	NUM
ejpam-2688	271	26	13	13	NUM
ejpam-2688	271	27	figure	figure	NOUN
ejpam-2688	271	28	3	3	NUM
ejpam-2688	271	29	:	:	PUNCT
ejpam-2688	271	30	trivariate	trivariate	NOUN
ejpam-2688	271	31	grouped	group	VERB
ejpam-2688	271	32	scatterplots	scatterplot	NOUN
ejpam-2688	271	33	for	for	ADP
ejpam-2688	271	34	the	the	DET
ejpam-2688	271	35	best	good	ADJ
ejpam-2688	271	36	wine	wine	NOUN
ejpam-2688	271	37	subset	subset	NOUN
ejpam-2688	271	38	.	.	PUNCT
ejpam-2688	272	1	4.3	4.3	NUM
ejpam-2688	272	2	.	.	PUNCT
ejpam-2688	273	1	aorta	aorta	PROPN
ejpam-2688	273	2	nuclear	nuclear	ADJ
ejpam-2688	273	3	resonance	resonance	NOUN
ejpam-2688	273	4	image	image	NOUN
ejpam-2688	273	5	data	data	VERB
ejpam-2688	273	6	our	our	PRON
ejpam-2688	273	7	final	final	ADJ
ejpam-2688	273	8	example	example	NOUN
ejpam-2688	273	9	is	be	AUX
ejpam-2688	273	10	by	by	ADP
ejpam-2688	273	11	application	application	NOUN
ejpam-2688	273	12	to	to	ADP
ejpam-2688	273	13	medical	medical	ADJ
ejpam-2688	273	14	imaging	imaging	NOUN
ejpam-2688	273	15	data	datum	NOUN
ejpam-2688	273	16	from	from	ADP
ejpam-2688	273	17	a	a	DET
ejpam-2688	273	18	study	study	NOUN
ejpam-2688	273	19	of	of	ADP
ejpam-2688	273	20	heart	heart	NOUN
ejpam-2688	273	21	tissue	tissue	NOUN
ejpam-2688	273	22	.	.	PUNCT
ejpam-2688	274	1	hardening	harden	VERB
ejpam-2688	274	2	of	of	ADP
ejpam-2688	274	3	the	the	DET
ejpam-2688	274	4	arteries	artery	NOUN
ejpam-2688	274	5	is	be	AUX
ejpam-2688	274	6	a	a	DET
ejpam-2688	274	7	leading	lead	VERB
ejpam-2688	274	8	cause	cause	NOUN
ejpam-2688	274	9	of	of	ADP
ejpam-2688	274	10	death	death	NOUN
ejpam-2688	274	11	and	and	CCONJ
ejpam-2688	274	12	debility	debility	NOUN
ejpam-2688	274	13	in	in	ADP
ejpam-2688	274	14	the	the	DET
ejpam-2688	274	15	industrial	industrial	ADJ
ejpam-2688	274	16	world	world	NOUN
ejpam-2688	274	17	.	.	PUNCT
ejpam-2688	275	1	in	in	ADP
ejpam-2688	275	2	the	the	DET
ejpam-2688	275	3	u.s	u.s	PROPN
ejpam-2688	275	4	.	.	PROPN
ejpam-2688	275	5	alone	alone	ADJ
ejpam-2688	275	6	13	13	NUM
ejpam-2688	275	7	million	million	NUM
ejpam-2688	275	8	americans	americans	PROPN
ejpam-2688	275	9	suffer	suffer	VERB
ejpam-2688	275	10	from	from	ADP
ejpam-2688	275	11	heart	heart	NOUN
ejpam-2688	275	12	attacks	attack	NOUN
ejpam-2688	275	13	,	,	PUNCT
ejpam-2688	275	14	and	and	CCONJ
ejpam-2688	275	15	90,000	90,000	NUM
ejpam-2688	275	16	people	people	NOUN
ejpam-2688	275	17	die	die	VERB
ejpam-2688	275	18	from	from	ADP
ejpam-2688	275	19	heart	heart	NOUN
ejpam-2688	275	20	disease	disease	NOUN
ejpam-2688	275	21	annually	annually	ADV
ejpam-2688	275	22	.	.	PUNCT
ejpam-2688	276	1	nuclear	nuclear	ADJ
ejpam-2688	276	2	magnetic	magnetic	ADJ
ejpam-2688	276	3	resonance	resonance	NOUN
ejpam-2688	276	4	(	(	PUNCT
ejpam-2688	276	5	nmr	nmr	NOUN
ejpam-2688	276	6	)	)	PUNCT
ejpam-2688	276	7	imaging	imaging	NOUN
ejpam-2688	276	8	has	have	AUX
ejpam-2688	276	9	been	be	AUX
ejpam-2688	276	10	used	use	VERB
ejpam-2688	276	11	to	to	PART
ejpam-2688	276	12	aid	aid	VERB
ejpam-2688	276	13	clinical	clinical	ADJ
ejpam-2688	276	14	identification	identification	NOUN
ejpam-2688	276	15	of	of	ADP
ejpam-2688	276	16	fatty	fatty	ADJ
ejpam-2688	276	17	tissues	tissue	NOUN
ejpam-2688	276	18	in	in	ADP
ejpam-2688	276	19	the	the	DET
ejpam-2688	276	20	arteries	artery	NOUN
ejpam-2688	276	21	to	to	PART
ejpam-2688	276	22	aid	aid	VERB
ejpam-2688	276	23	in	in	ADP
ejpam-2688	276	24	early	early	ADJ
ejpam-2688	276	25	detection	detection	NOUN
ejpam-2688	276	26	of	of	ADP
ejpam-2688	276	27	heart	heart	NOUN
ejpam-2688	276	28	attacks	attack	NOUN
ejpam-2688	276	29	.	.	PUNCT
ejpam-2688	277	1	the	the	DET
ejpam-2688	277	2	aorta	aorta	PROPN
ejpam-2688	277	3	data	datum	NOUN
ejpam-2688	277	4	analyzed	analyze	VERB
ejpam-2688	277	5	here	here	ADV
ejpam-2688	277	6	was	be	AUX
ejpam-2688	277	7	collected	collect	VERB
ejpam-2688	277	8	by	by	ADP
ejpam-2688	277	9	pearlman	pearlman	NOUN
ejpam-2688	277	10	[	[	X
ejpam-2688	277	11	13	13	NUM
ejpam-2688	277	12	]	]	PUNCT
ejpam-2688	277	13	at	at	ADP
ejpam-2688	277	14	the	the	DET
ejpam-2688	277	15	medical	medical	ADJ
ejpam-2688	277	16	school	school	NOUN
ejpam-2688	277	17	of	of	ADP
ejpam-2688	277	18	the	the	DET
ejpam-2688	277	19	university	university	PROPN
ejpam-2688	277	20	of	of	ADP
ejpam-2688	277	21	virginia	virginia	PROPN
ejpam-2688	277	22	.	.	PUNCT
ejpam-2688	278	1	there	there	PRON
ejpam-2688	278	2	are	be	VERB
ejpam-2688	278	3	observations	observation	NOUN
ejpam-2688	278	4	from	from	ADP
ejpam-2688	278	5	n	n	NOUN
ejpam-2688	278	6	=	=	SYM
ejpam-2688	278	7	418	418	NUM
ejpam-2688	278	8	patients	patient	NOUN
ejpam-2688	278	9	on	on	ADP
ejpam-2688	278	10	16	16	NUM
ejpam-2688	278	11	different	different	ADJ
ejpam-2688	278	12	image	image	NOUN
ejpam-2688	278	13	acquisition	acquisition	NOUN
ejpam-2688	278	14	variables	variable	NOUN
ejpam-2688	278	15	.	.	PUNCT
ejpam-2688	279	1	including	include	VERB
ejpam-2688	279	2	direction	direction	NOUN
ejpam-2688	279	3	and	and	CCONJ
ejpam-2688	279	4	orientation	orientation	NOUN
ejpam-2688	279	5	variables	variable	NOUN
ejpam-2688	279	6	,	,	PUNCT
ejpam-2688	279	7	we	we	PRON
ejpam-2688	279	8	have	have	VERB
ejpam-2688	279	9	p	p	NOUN
ejpam-2688	279	10	=	=	SYM
ejpam-2688	279	11	20	20	NUM
ejpam-2688	279	12	variables	variable	NOUN
ejpam-2688	279	13	.	.	PUNCT
ejpam-2688	280	1	the	the	DET
ejpam-2688	280	2	first	first	ADJ
ejpam-2688	280	3	n1	n1	PROPN
ejpam-2688	280	4	=	=	SYM
ejpam-2688	280	5	194	194	NUM
ejpam-2688	280	6	patients	patient	NOUN
ejpam-2688	280	7	exhibited	exhibit	VERB
ejpam-2688	280	8	early	early	ADJ
ejpam-2688	280	9	atheroma	atheroma	NOUN
ejpam-2688	280	10	,	,	PUNCT
ejpam-2688	280	11	and	and	CCONJ
ejpam-2688	280	12	the	the	DET
ejpam-2688	280	13	remaining	remain	VERB
ejpam-2688	280	14	n2	n2	NOUN
ejpam-2688	280	15	=	=	NOUN
ejpam-2688	280	16	224	224	NUM
ejpam-2688	280	17	patients	patient	NOUN
ejpam-2688	280	18	were	be	AUX
ejpam-2688	280	19	clinically	clinically	ADV
ejpam-2688	280	20	deemed	deem	VERB
ejpam-2688	280	21	healthy	healthy	ADJ
ejpam-2688	280	22	.	.	PUNCT
ejpam-2688	281	1	for	for	ADP
ejpam-2688	281	2	this	this	DET
ejpam-2688	281	3	dataset	dataset	NOUN
ejpam-2688	281	4	which	which	PRON
ejpam-2688	281	5	exhibits	exhibit	VERB
ejpam-2688	281	6	marked	mark	VERB
ejpam-2688	281	7	non	non	ADJ
ejpam-2688	281	8	-	-	ADJ
ejpam-2688	281	9	normality	normality	ADJ
ejpam-2688	281	10	,	,	PUNCT
ejpam-2688	281	11	there	there	PRON
ejpam-2688	281	12	are	be	VERB
ejpam-2688	281	13	9,437,175	9,437,175	NUM
ejpam-2688	281	14	possible	possible	ADJ
ejpam-2688	281	15	subset+kernel	subset+kernel	PROPN
ejpam-2688	281	16	combinations	combination	NOUN
ejpam-2688	281	17	.	.	PUNCT
ejpam-2688	282	1	the	the	DET
ejpam-2688	282	2	cvga	cvga	PROPN
ejpam-2688	282	3	ran	run	VERB
ejpam-2688	282	4	100	100	NUM
ejpam-2688	282	5	replications	replication	NOUN
ejpam-2688	282	6	of	of	ADP
ejpam-2688	282	7	the	the	DET
ejpam-2688	282	8	genetic	genetic	ADJ
ejpam-2688	282	9	algorithm	algorithm	NOUN
ejpam-2688	282	10	,	,	PUNCT
ejpam-2688	282	11	with	with	ADP
ejpam-2688	282	12	each	each	PRON
ejpam-2688	282	13	running	run	VERB
ejpam-2688	282	14	for	for	ADP
ejpam-2688	282	15	twenty	twenty	NUM
ejpam-2688	282	16	generations	generation	NOUN
ejpam-2688	282	17	with	with	ADP
ejpam-2688	282	18	a	a	DET
ejpam-2688	282	19	population	population	NOUN
ejpam-2688	282	20	size	size	NOUN
ejpam-2688	282	21	of	of	ADP
ejpam-2688	282	22	twenty	twenty	NUM
ejpam-2688	282	23	-	-	PUNCT
ejpam-2688	282	24	five	five	NUM
ejpam-2688	282	25	.	.	PUNCT
ejpam-2688	283	1	with	with	SCONJ
ejpam-2688	283	2	the	the	DET
ejpam-2688	283	3	elitism	elitism	NOUN
ejpam-2688	283	4	rule	rule	NOUN
ejpam-2688	283	5	turned	turn	VERB
ejpam-2688	283	6	on	on	ADP
ejpam-2688	283	7	,	,	PUNCT
ejpam-2688	283	8	our	our	PRON
ejpam-2688	283	9	modeling	modeling	NOUN
ejpam-2688	283	10	process	process	NOUN
ejpam-2688	283	11	evaluated	evaluate	VERB
ejpam-2688	283	12	at	at	ADP
ejpam-2688	283	13	most	most	ADV
ejpam-2688	283	14	69,000	69,000	NUM
ejpam-2688	283	15	unique	unique	ADJ
ejpam-2688	283	16	solutions	solution	NOUN
ejpam-2688	283	17	0.73	0.73	NUM
ejpam-2688	283	18	%	%	NOUN
ejpam-2688	283	19	of	of	ADP
ejpam-2688	283	20	the	the	DET
ejpam-2688	283	21	solution	solution	NOUN
ejpam-2688	283	22	space	space	NOUN
ejpam-2688	283	23	.	.	PUNCT
ejpam-2688	284	1	when	when	SCONJ
ejpam-2688	284	2	sorted	sort	VERB
ejpam-2688	284	3	by	by	ADP
ejpam-2688	284	4	the	the	DET
ejpam-2688	284	5	icom	icom	PROPN
ejpam-2688	284	6	pperf	pperf	PROPN
ejpam-2688	284	7	score	score	NOUN
ejpam-2688	284	8	,	,	PUNCT
ejpam-2688	284	9	the	the	DET
ejpam-2688	284	10	top	top	ADJ
ejpam-2688	284	11	forty	forty	NUM
ejpam-2688	284	12	solutions	solution	NOUN
ejpam-2688	284	13	used	use	VERB
ejpam-2688	284	14	the	the	DET
ejpam-2688	284	15	cauchy	cauchy	ADJ
ejpam-2688	284	16	kernel	kernel	NOUN
ejpam-2688	284	17	,	,	PUNCT
ejpam-2688	284	18	had	have	VERB
ejpam-2688	284	19	indistinguishable	indistinguishable	ADJ
ejpam-2688	284	20	scores	score	NOUN
ejpam-2688	284	21	,	,	PUNCT
ejpam-2688	284	22	with	with	ADP
ejpam-2688	284	23	identical	identical	ADJ
ejpam-2688	284	24	testing	testing	NOUN
ejpam-2688	284	25	error	error	NOUN
ejpam-2688	284	26	rates	rate	NOUN
ejpam-2688	284	27	of	of	ADP
ejpam-2688	284	28	0.30	0.30	NUM
ejpam-2688	284	29	%	%	NOUN
ejpam-2688	284	30	and	and	CCONJ
ejpam-2688	284	31	varying	vary	VERB
ejpam-2688	284	32	subsets	subset	NOUN
ejpam-2688	284	33	of	of	ADP
ejpam-2688	284	34	features	feature	NOUN
ejpam-2688	284	35	.	.	PUNCT
ejpam-2688	285	1	none	none	NOUN
ejpam-2688	285	2	of	of	ADP
ejpam-2688	285	3	the	the	DET
ejpam-2688	285	4	generations	generation	NOUN
ejpam-2688	285	5	selected	select	VERB
ejpam-2688	285	6	the	the	DET
ejpam-2688	285	7	fully	fully	ADV
ejpam-2688	285	8	saturated	saturate	VERB
ejpam-2688	285	9	model	model	NOUN
ejpam-2688	285	10	.	.	PUNCT
ejpam-2688	286	1	among	among	ADP
ejpam-2688	286	2	the	the	DET
ejpam-2688	286	3	indistinguishable	indistinguishable	ADJ
ejpam-2688	286	4	(	(	PUNCT
ejpam-2688	286	5	by	by	ADP
ejpam-2688	286	6	score	score	NOUN
ejpam-2688	286	7	and	and	CCONJ
ejpam-2688	286	8	testing	testing	NOUN
ejpam-2688	286	9	error	error	NOUN
ejpam-2688	286	10	)	)	PUNCT
ejpam-2688	286	11	solutions	solution	NOUN
ejpam-2688	286	12	,	,	PUNCT
ejpam-2688	286	13	the	the	DET
ejpam-2688	286	14	only	only	ADJ
ejpam-2688	286	15	kernels	kernel	NOUN
ejpam-2688	286	16	selected	select	VERB
ejpam-2688	286	17	were	be	AUX
ejpam-2688	286	18	the	the	DET
ejpam-2688	286	19	cauchy	cauchy	ADJ
ejpam-2688	286	20	and	and	CCONJ
ejpam-2688	286	21	inverse	inverse	ADJ
ejpam-2688	286	22	multi	multi	ADJ
ejpam-2688	286	23	-	-	ADJ
ejpam-2688	286	24	quadric	quadric	ADJ
ejpam-2688	286	25	kernels	kernel	NOUN
ejpam-2688	286	26	.	.	PUNCT
ejpam-2688	287	1	j.	j.	PROPN
ejpam-2688	287	2	howe	howe	PROPN
ejpam-2688	287	3	,	,	PUNCT
ejpam-2688	287	4	h.	h.	PROPN
ejpam-2688	287	5	bozdogan	bozdogan	PROPN
ejpam-2688	287	6	/	/	SYM
ejpam-2688	287	7	eur	eur	PROPN
ejpam-2688	287	8	.	.	PUNCT
ejpam-2688	288	1	j.	j.	PROPN
ejpam-2688	288	2	pure	pure	PROPN
ejpam-2688	288	3	appl	appl	PROPN
ejpam-2688	288	4	.	.	PROPN
ejpam-2688	288	5	math	math	PROPN
ejpam-2688	288	6	,	,	PUNCT
ejpam-2688	288	7	9	9	NUM
ejpam-2688	288	8	(	(	PUNCT
ejpam-2688	288	9	2016	2016	NUM
ejpam-2688	288	10	)	)	PUNCT
ejpam-2688	288	11	,	,	PUNCT
ejpam-2688	288	12	216	216	NUM
ejpam-2688	288	13	-	-	SYM
ejpam-2688	288	14	230	230	NUM
ejpam-2688	288	15	228	228	NUM
ejpam-2688	288	16	before	before	ADP
ejpam-2688	288	17	running	run	VERB
ejpam-2688	288	18	the	the	DET
ejpam-2688	288	19	full	full	ADJ
ejpam-2688	288	20	modeling	modeling	NOUN
ejpam-2688	288	21	procedure	procedure	NOUN
ejpam-2688	289	1	,	,	PUNCT
ejpam-2688	289	2	we	we	PRON
ejpam-2688	289	3	performed	perform	VERB
ejpam-2688	289	4	some	some	DET
ejpam-2688	289	5	exploratory	exploratory	ADJ
ejpam-2688	289	6	data	datum	NOUN
ejpam-2688	289	7	analysis	analysis	NOUN
ejpam-2688	289	8	using	use	VERB
ejpam-2688	289	9	the	the	DET
ejpam-2688	289	10	full	full	ADJ
ejpam-2688	289	11	set	set	NOUN
ejpam-2688	289	12	of	of	ADP
ejpam-2688	289	13	features	feature	NOUN
ejpam-2688	289	14	.	.	PUNCT
ejpam-2688	290	1	in	in	ADP
ejpam-2688	290	2	this	this	DET
ejpam-2688	290	3	analysis	analysis	NOUN
ejpam-2688	290	4	,	,	PUNCT
ejpam-2688	290	5	we	we	PRON
ejpam-2688	290	6	generated	generate	VERB
ejpam-2688	290	7	100	100	NUM
ejpam-2688	290	8	training	training	NOUN
ejpam-2688	290	9	/	/	SYM
ejpam-2688	290	10	testing	testing	NOUN
ejpam-2688	290	11	crossvalidation	crossvalidation	NOUN
ejpam-2688	290	12	samples	sample	NOUN
ejpam-2688	290	13	,	,	PUNCT
ejpam-2688	290	14	and	and	CCONJ
ejpam-2688	290	15	fit	fit	VERB
ejpam-2688	290	16	each	each	PRON
ejpam-2688	290	17	of	of	ADP
ejpam-2688	290	18	the	the	DET
ejpam-2688	290	19	9	9	NUM
ejpam-2688	290	20	kernels	kernel	NOUN
ejpam-2688	290	21	to	to	ADP
ejpam-2688	290	22	all	all	PRON
ejpam-2688	290	23	.	.	PUNCT
ejpam-2688	291	1	with	with	ADP
ejpam-2688	291	2	the	the	DET
ejpam-2688	291	3	full	full	ADJ
ejpam-2688	291	4	dataset	dataset	NOUN
ejpam-2688	291	5	,	,	PUNCT
ejpam-2688	291	6	the	the	DET
ejpam-2688	291	7	95	95	NUM
ejpam-2688	291	8	%	%	NOUN
ejpam-2688	291	9	confidence	confidence	NOUN
ejpam-2688	291	10	interval	interval	NOUN
ejpam-2688	291	11	of	of	ADP
ejpam-2688	291	12	the	the	DET
ejpam-2688	291	13	testing	testing	NOUN
ejpam-2688	291	14	error	error	NOUN
ejpam-2688	291	15	rates	rate	NOUN
ejpam-2688	291	16	with	with	ADP
ejpam-2688	291	17	the	the	DET
ejpam-2688	291	18	cauchy	cauchy	NOUN
ejpam-2688	291	19	was	be	AUX
ejpam-2688	291	20	abysmal	abysmal	ADJ
ejpam-2688	291	21	:	:	PUNCT
ejpam-2688	292	1	[	[	X
ejpam-2688	292	2	43.80%,47.65	43.80%,47.65	X
ejpam-2688	292	3	%	%	NOUN
ejpam-2688	292	4	]	]	X
ejpam-2688	292	5	.	.	PUNCT
ejpam-2688	293	1	this	this	PRON
ejpam-2688	293	2	once	once	ADV
ejpam-2688	293	3	again	again	ADV
ejpam-2688	293	4	demonstrates	demonstrate	VERB
ejpam-2688	293	5	the	the	DET
ejpam-2688	293	6	clear	clear	ADJ
ejpam-2688	293	7	benefit	benefit	NOUN
ejpam-2688	293	8	of	of	ADP
ejpam-2688	293	9	optimal	optimal	ADJ
ejpam-2688	293	10	feature	feature	NOUN
ejpam-2688	293	11	selection	selection	NOUN
ejpam-2688	293	12	.	.	PUNCT
ejpam-2688	294	1	table	table	NOUN
ejpam-2688	294	2	5	5	NUM
ejpam-2688	294	3	show	show	NOUN
ejpam-2688	294	4	five	five	NUM
ejpam-2688	294	5	of	of	ADP
ejpam-2688	294	6	the	the	DET
ejpam-2688	294	7	best	good	ADJ
ejpam-2688	294	8	models	model	NOUN
ejpam-2688	294	9	.	.	PUNCT
ejpam-2688	295	1	while	while	SCONJ
ejpam-2688	295	2	the	the	DET
ejpam-2688	295	3	cauchy	cauchy	ADJ
ejpam-2688	295	4	kernel	kernel	PROPN
ejpam-2688	295	5	appears	appear	VERB
ejpam-2688	295	6	superior	superior	ADJ
ejpam-2688	295	7	for	for	ADP
ejpam-2688	295	8	this	this	DET
ejpam-2688	295	9	data	datum	NOUN
ejpam-2688	295	10	,	,	PUNCT
ejpam-2688	295	11	it	it	PRON
ejpam-2688	295	12	seems	seem	VERB
ejpam-2688	295	13	there	there	PRON
ejpam-2688	295	14	is	be	VERB
ejpam-2688	295	15	no	no	DET
ejpam-2688	295	16	clear	clear	ADJ
ejpam-2688	295	17	best	good	ADJ
ejpam-2688	295	18	set	set	NOUN
ejpam-2688	295	19	of	of	ADP
ejpam-2688	295	20	features	feature	NOUN
ejpam-2688	295	21	,	,	PUNCT
ejpam-2688	295	22	since	since	SCONJ
ejpam-2688	295	23	all	all	PRON
ejpam-2688	295	24	of	of	ADP
ejpam-2688	295	25	the	the	DET
ejpam-2688	295	26	top	top	ADJ
ejpam-2688	295	27	five	five	NUM
ejpam-2688	295	28	performed	perform	VERB
ejpam-2688	295	29	nearly	nearly	ADV
ejpam-2688	295	30	perfectly	perfectly	ADV
ejpam-2688	295	31	.	.	PUNCT
ejpam-2688	296	1	the	the	DET
ejpam-2688	296	2	top	top	ADJ
ejpam-2688	296	3	model	model	NOUN
ejpam-2688	296	4	with	with	ADP
ejpam-2688	296	5	the	the	DET
ejpam-2688	296	6	cauchy	cauchy	ADJ
ejpam-2688	296	7	kernel	kernel	PROPN
ejpam-2688	296	8	has	have	AUX
ejpam-2688	296	9	dramatically	dramatically	ADV
ejpam-2688	296	10	reduced	reduce	VERB
ejpam-2688	296	11	the	the	DET
ejpam-2688	296	12	dimensionality	dimensionality	NOUN
ejpam-2688	296	13	of	of	ADP
ejpam-2688	296	14	the	the	DET
ejpam-2688	296	15	data	datum	NOUN
ejpam-2688	296	16	,	,	PUNCT
ejpam-2688	296	17	from	from	ADP
ejpam-2688	296	18	p	p	NOUN
ejpam-2688	296	19	=	=	NUM
ejpam-2688	296	20	20	20	NUM
ejpam-2688	296	21	variables	variable	NOUN
ejpam-2688	296	22	down	down	ADV
ejpam-2688	296	23	to	to	ADP
ejpam-2688	296	24	p∗	p∗	NOUN
ejpam-2688	296	25	=	=	SYM
ejpam-2688	296	26	6	6	X
ejpam-2688	296	27	.	.	PUNCT
ejpam-2688	296	28	figure	figure	VERB
ejpam-2688	296	29	4	4	NUM
ejpam-2688	296	30	displays	display	VERB
ejpam-2688	296	31	the	the	DET
ejpam-2688	296	32	poor	poor	ADJ
ejpam-2688	296	33	separation	separation	NOUN
ejpam-2688	296	34	in	in	ADP
ejpam-2688	296	35	the	the	DET
ejpam-2688	296	36	original	original	ADJ
ejpam-2688	296	37	data	data	NOUN
ejpam-2688	296	38	space	space	NOUN
ejpam-2688	296	39	for	for	ADP
ejpam-2688	296	40	two	two	NUM
ejpam-2688	296	41	sets	set	NOUN
ejpam-2688	296	42	of	of	ADP
ejpam-2688	296	43	pairs	pair	NOUN
ejpam-2688	296	44	of	of	ADP
ejpam-2688	296	45	the	the	DET
ejpam-2688	296	46	original	original	ADJ
ejpam-2688	296	47	features	feature	NOUN
ejpam-2688	296	48	.	.	PUNCT
ejpam-2688	297	1	table	table	NOUN
ejpam-2688	297	2	5	5	NUM
ejpam-2688	297	3	:	:	SYM
ejpam-2688	297	4	5	5	NUM
ejpam-2688	297	5	of	of	ADP
ejpam-2688	297	6	the	the	DET
ejpam-2688	297	7	best	good	ADJ
ejpam-2688	297	8	models	model	NOUN
ejpam-2688	297	9	selected	select	VERB
ejpam-2688	297	10	for	for	ADP
ejpam-2688	297	11	aorta	aorta	NOUN
ejpam-2688	297	12	data	datum	NOUN
ejpam-2688	297	13	.	.	PUNCT
ejpam-2688	298	1	subset	subset	PROPN
ejpam-2688	298	2	kernel	kernel	PROPN
ejpam-2688	298	3	icom	icom	PROPN
ejpam-2688	298	4	pperf	pperf	PROPN
ejpam-2688	298	5	training	training	NOUN
ejpam-2688	298	6	error	error	NOUN
ejpam-2688	298	7	testing	testing	NOUN
ejpam-2688	298	8	error	error	NOUN
ejpam-2688	298	9	{	{	PUNCT
ejpam-2688	298	10	5,7,8,11,12,15	5,7,8,11,12,15	NUM
ejpam-2688	298	11	}	}	PUNCT
ejpam-2688	298	12	cauchy	cauchy	ADJ
ejpam-2688	298	13	-530.05	-530.05	NOUN
ejpam-2688	298	14	0.00	0.00	NUM
ejpam-2688	298	15	%	%	NOUN
ejpam-2688	298	16	0.30	0.30	NUM
ejpam-2688	298	17	%	%	NOUN
ejpam-2688	298	18	{	{	PUNCT
ejpam-2688	298	19	4,5,8,9,11,16,18	4,5,8,9,11,16,18	NOUN
ejpam-2688	298	20	}	}	PUNCT
ejpam-2688	298	21	cauchy	cauchy	ADJ
ejpam-2688	298	22	-530.05	-530.05	NOUN
ejpam-2688	298	23	0.00	0.00	NUM
ejpam-2688	298	24	%	%	NOUN
ejpam-2688	298	25	0.30	0.30	NUM
ejpam-2688	298	26	%	%	NOUN
ejpam-2688	298	27	{	{	PUNCT
ejpam-2688	298	28	4,7−	4,7−	NUM
ejpam-2688	298	29	9,11−	9,11−	NUM
ejpam-2688	298	30	13,15,18	13,15,18	NUM
ejpam-2688	298	31	}	}	PUNCT
ejpam-2688	298	32	linear	linear	PROPN
ejpam-2688	298	33	-440.22	-440.22	PROPN
ejpam-2688	298	34	0.00	0.00	NUM
ejpam-2688	298	35	%	%	NOUN
ejpam-2688	298	36	0.30	0.30	NUM
ejpam-2688	298	37	%	%	NOUN
ejpam-2688	298	38	{	{	PUNCT
ejpam-2688	298	39	3,−5,7,9,12−	3,−5,7,9,12−	NUM
ejpam-2688	298	40	16,19	16,19	ADJ
ejpam-2688	298	41	}	}	PUNCT
ejpam-2688	298	42	cubic	cubic	ADJ
ejpam-2688	298	43	-145.87	-145.87	PROPN
ejpam-2688	298	44	0.00	0.00	NUM
ejpam-2688	298	45	%	%	NOUN
ejpam-2688	298	46	0.30	0.30	NUM
ejpam-2688	298	47	%	%	NOUN
ejpam-2688	298	48	{	{	PUNCT
ejpam-2688	298	49	2−	2−	NUM
ejpam-2688	298	50	7,9,10,12,14,15,17,19	7,9,10,12,14,15,17,19	NUM
ejpam-2688	298	51	}	}	PUNCT
ejpam-2688	298	52	homogenous	homogenous	ADJ
ejpam-2688	298	53	poly	poly	ADJ
ejpam-2688	298	54	-127.64	-127.64	PROPN
ejpam-2688	298	55	0.00	0.00	NUM
ejpam-2688	298	56	%	%	NOUN
ejpam-2688	298	57	0.30	0.30	NUM
ejpam-2688	298	58	%	%	NOUN
ejpam-2688	298	59	(	(	PUNCT
ejpam-2688	298	60	a	a	NOUN
ejpam-2688	298	61	)	)	PUNCT
ejpam-2688	298	62	features	feature	VERB
ejpam-2688	298	63	11×	11×	NUM
ejpam-2688	298	64	15	15	NUM
ejpam-2688	298	65	(	(	PUNCT
ejpam-2688	298	66	b	b	NOUN
ejpam-2688	298	67	)	)	PUNCT
ejpam-2688	298	68	features	feature	VERB
ejpam-2688	298	69	12×	12×	NUM
ejpam-2688	298	70	15	15	NUM
ejpam-2688	298	71	figure	figure	NOUN
ejpam-2688	298	72	4	4	NUM
ejpam-2688	298	73	:	:	PUNCT
ejpam-2688	298	74	bivariate	bivariate	ADJ
ejpam-2688	298	75	grouped	group	VERB
ejpam-2688	298	76	scatterplots	scatterplot	NOUN
ejpam-2688	298	77	for	for	ADP
ejpam-2688	298	78	aorta	aorta	NOUN
ejpam-2688	298	79	data	datum	NOUN
ejpam-2688	298	80	showing	show	VERB
ejpam-2688	298	81	poor	poor	ADJ
ejpam-2688	298	82	separation	separation	NOUN
ejpam-2688	298	83	.	.	PUNCT
ejpam-2688	299	1	5	5	X
ejpam-2688	299	2	.	.	X
ejpam-2688	299	3	concluding	conclude	VERB
ejpam-2688	299	4	remarks	remark	NOUN
ejpam-2688	299	5	in	in	ADP
ejpam-2688	299	6	summary	summary	NOUN
ejpam-2688	299	7	,	,	PUNCT
ejpam-2688	299	8	we	we	PRON
ejpam-2688	299	9	have	have	AUX
ejpam-2688	299	10	developed	develop	VERB
ejpam-2688	299	11	and	and	CCONJ
ejpam-2688	299	12	applied	apply	VERB
ejpam-2688	299	13	a	a	DET
ejpam-2688	299	14	new	new	ADJ
ejpam-2688	299	15	hybrid	hybrid	ADJ
ejpam-2688	299	16	stochastic	stochastic	ADJ
ejpam-2688	299	17	algorithm	algorithm	NOUN
ejpam-2688	299	18	,	,	PUNCT
ejpam-2688	299	19	cvga	cvga	PROPN
ejpam-2688	299	20	,	,	PUNCT
ejpam-2688	299	21	which	which	PRON
ejpam-2688	299	22	combines	combine	VERB
ejpam-2688	299	23	the	the	DET
ejpam-2688	299	24	strengths	strength	NOUN
ejpam-2688	299	25	of	of	ADP
ejpam-2688	299	26	cross	cross	NOUN
ejpam-2688	299	27	-	-	NOUN
ejpam-2688	299	28	validation	validation	NOUN
ejpam-2688	299	29	and	and	CCONJ
ejpam-2688	299	30	the	the	DET
ejpam-2688	299	31	genetic	genetic	ADJ
ejpam-2688	299	32	algorithm	algorithm	NOUN
ejpam-2688	299	33	.	.	PUNCT
ejpam-2688	300	1	within	within	ADP
ejpam-2688	300	2	the	the	DET
ejpam-2688	300	3	ga	ga	PROPN
ejpam-2688	300	4	,	,	PUNCT
ejpam-2688	300	5	we	we	PRON
ejpam-2688	300	6	’ve	’ve	AUX
ejpam-2688	300	7	used	use	VERB
ejpam-2688	300	8	a	a	DET
ejpam-2688	300	9	novel	novel	NOUN
ejpam-2688	300	10	encoding	encoding	NOUN
ejpam-2688	300	11	strategy	strategy	NOUN
ejpam-2688	300	12	to	to	PART
ejpam-2688	300	13	create	create	VERB
ejpam-2688	300	14	chromosomes	chromosome	NOUN
ejpam-2688	300	15	which	which	PRON
ejpam-2688	300	16	simultaneously	simultaneously	ADV
ejpam-2688	300	17	encode	encode	VERB
ejpam-2688	300	18	for	for	ADP
ejpam-2688	300	19	feature	feature	NOUN
ejpam-2688	300	20	selection	selection	NOUN
ejpam-2688	300	21	and	and	CCONJ
ejpam-2688	300	22	kernel	kernel	PROPN
ejpam-2688	300	23	selection	selection	NOUN
ejpam-2688	300	24	.	.	PUNCT
ejpam-2688	301	1	we	we	PRON
ejpam-2688	301	2	’ve	’ve	AUX
ejpam-2688	301	3	applied	apply	VERB
ejpam-2688	301	4	the	the	DET
ejpam-2688	301	5	cvga	cvga	NOUN
ejpam-2688	301	6	to	to	PART
ejpam-2688	301	7	regularized	regularize	VERB
ejpam-2688	301	8	support	support	NOUN
ejpam-2688	301	9	vector	vector	NOUN
ejpam-2688	301	10	references	reference	NOUN
ejpam-2688	301	11	229	229	NUM
ejpam-2688	301	12	classification	classification	NOUN
ejpam-2688	301	13	with	with	ADP
ejpam-2688	301	14	kernel	kernel	PROPN
ejpam-2688	301	15	discriminant	discriminant	PROPN
ejpam-2688	301	16	analysis	analysis	NOUN
ejpam-2688	301	17	.	.	PUNCT
ejpam-2688	302	1	however	however	ADV
ejpam-2688	302	2	,	,	PUNCT
ejpam-2688	302	3	cvga	cvga	PROPN
ejpam-2688	302	4	can	can	AUX
ejpam-2688	302	5	be	be	AUX
ejpam-2688	302	6	useful	useful	ADJ
ejpam-2688	302	7	for	for	ADP
ejpam-2688	302	8	any	any	DET
ejpam-2688	302	9	machine	machine	NOUN
ejpam-2688	302	10	learning	learn	VERB
ejpam-2688	302	11	problem	problem	NOUN
ejpam-2688	302	12	that	that	PRON
ejpam-2688	302	13	requires	require	VERB
ejpam-2688	302	14	cross	cross	ADJ
ejpam-2688	302	15	-	-	ADJ
ejpam-2688	302	16	validation	validation	NOUN
ejpam-2688	302	17	and	and	CCONJ
ejpam-2688	302	18	exploration	exploration	NOUN
ejpam-2688	302	19	of	of	ADP
ejpam-2688	302	20	a	a	DET
ejpam-2688	302	21	large	large	ADJ
ejpam-2688	302	22	solution	solution	NOUN
ejpam-2688	302	23	space	space	NOUN
ejpam-2688	302	24	.	.	PUNCT
ejpam-2688	303	1	the	the	DET
ejpam-2688	303	2	only	only	ADJ
ejpam-2688	303	3	requirement	requirement	NOUN
ejpam-2688	303	4	is	be	AUX
ejpam-2688	303	5	the	the	DET
ejpam-2688	303	6	ability	ability	NOUN
ejpam-2688	303	7	to	to	PART
ejpam-2688	303	8	encode	encode	VERB
ejpam-2688	303	9	solutions	solution	NOUN
ejpam-2688	303	10	as	as	ADP
ejpam-2688	303	11	ga	ga	PROPN
ejpam-2688	303	12	chromosomes	chromosome	NOUN
ejpam-2688	303	13	.	.	PUNCT
ejpam-2688	304	1	recall	recall	VERB
ejpam-2688	304	2	that	that	SCONJ
ejpam-2688	304	3	we	we	PRON
ejpam-2688	304	4	set	set	VERB
ejpam-2688	304	5	the	the	DET
ejpam-2688	304	6	kernel	kernel	PROPN
ejpam-2688	304	7	function	function	PROPN
ejpam-2688	304	8	parameters	parameter	NOUN
ejpam-2688	304	9	to	to	ADP
ejpam-2688	304	10	certain	certain	ADJ
ejpam-2688	304	11	values	value	NOUN
ejpam-2688	304	12	a	a	PRON
ejpam-2688	304	13	priori	priori	ADV
ejpam-2688	304	14	,	,	PUNCT
ejpam-2688	304	15	instead	instead	ADV
ejpam-2688	304	16	of	of	ADP
ejpam-2688	304	17	estimating	estimate	VERB
ejpam-2688	304	18	them	they	PRON
ejpam-2688	304	19	from	from	ADP
ejpam-2688	304	20	the	the	DET
ejpam-2688	304	21	data	datum	NOUN
ejpam-2688	304	22	.	.	PUNCT
ejpam-2688	305	1	this	this	DET
ejpam-2688	305	2	research	research	NOUN
ejpam-2688	305	3	could	could	AUX
ejpam-2688	305	4	be	be	AUX
ejpam-2688	305	5	further	far	ADV
ejpam-2688	305	6	extended	extend	VERB
ejpam-2688	305	7	to	to	PART
ejpam-2688	305	8	allow	allow	VERB
ejpam-2688	305	9	estimation	estimation	NOUN
ejpam-2688	305	10	of	of	ADP
ejpam-2688	305	11	the	the	DET
ejpam-2688	305	12	parameters	parameter	NOUN
ejpam-2688	305	13	.	.	PUNCT
ejpam-2688	306	1	one	one	NUM
ejpam-2688	306	2	approach	approach	NOUN
ejpam-2688	306	3	might	might	AUX
ejpam-2688	306	4	be	be	AUX
ejpam-2688	306	5	to	to	PART
ejpam-2688	306	6	merge	merge	VERB
ejpam-2688	306	7	the	the	DET
ejpam-2688	306	8	cvga	cvga	NOUN
ejpam-2688	306	9	with	with	ADP
ejpam-2688	306	10	the	the	DET
ejpam-2688	306	11	data	data	NOUN
ejpam-2688	306	12	-	-	PUNCT
ejpam-2688	306	13	adaptive	adaptive	NOUN
ejpam-2688	306	14	technique	technique	NOUN
ejpam-2688	306	15	presented	present	VERB
ejpam-2688	306	16	in	in	ADP
ejpam-2688	306	17	[	[	X
ejpam-2688	306	18	12	12	NUM
ejpam-2688	306	19	]	]	PUNCT
ejpam-2688	306	20	.	.	PUNCT
ejpam-2688	307	1	references	reference	NOUN
ejpam-2688	307	2	[	[	X
ejpam-2688	307	3	1	1	NUM
ejpam-2688	307	4	]	]	X
ejpam-2688	307	5	s	s	VERB
ejpam-2688	307	6	aeberhard	aeberhard	NOUN
ejpam-2688	307	7	,	,	PUNCT
ejpam-2688	307	8	d	d	NOUN
ejpam-2688	307	9	coomans	cooman	NOUN
ejpam-2688	307	10	,	,	PUNCT
ejpam-2688	307	11	and	and	CCONJ
ejpam-2688	307	12	o	o	X
ejpam-2688	307	13	de	de	X
ejpam-2688	307	14	vel	vel	PROPN
ejpam-2688	307	15	.	.	PUNCT
ejpam-2688	308	1	comparison	comparison	NOUN
ejpam-2688	308	2	of	of	ADP
ejpam-2688	308	3	classifiers	classifier	NOUN
ejpam-2688	308	4	in	in	ADP
ejpam-2688	308	5	high	high	ADJ
ejpam-2688	308	6	dimensional	dimensional	ADJ
ejpam-2688	308	7	settings	setting	NOUN
ejpam-2688	308	8	.	.	PUNCT
ejpam-2688	309	1	technical	technical	ADJ
ejpam-2688	309	2	report	report	VERB
ejpam-2688	309	3	92	92	NUM
ejpam-2688	309	4	-	-	SYM
ejpam-2688	309	5	02	02	NUM
ejpam-2688	309	6	,	,	PUNCT
ejpam-2688	309	7	dept	dept	NOUN
ejpam-2688	309	8	.	.	PROPN
ejpam-2688	309	9	of	of	ADP
ejpam-2688	309	10	computer	computer	NOUN
ejpam-2688	309	11	science	science	NOUN
ejpam-2688	309	12	and	and	CCONJ
ejpam-2688	309	13	dept	dept	NOUN
ejpam-2688	309	14	.	.	PROPN
ejpam-2688	309	15	of	of	ADP
ejpam-2688	309	16	mathematics	mathematic	NOUN
ejpam-2688	309	17	and	and	CCONJ
ejpam-2688	309	18	statistics	statistic	NOUN
ejpam-2688	309	19	,	,	PUNCT
ejpam-2688	309	20	james	james	PROPN
ejpam-2688	309	21	cook	cook	PROPN
ejpam-2688	309	22	university	university	PROPN
ejpam-2688	309	23	of	of	ADP
ejpam-2688	309	24	north	north	PROPN
ejpam-2688	309	25	queensland	queensland	PROPN
ejpam-2688	309	26	,	,	PUNCT
ejpam-2688	309	27	1992	1992	NUM
ejpam-2688	309	28	.	.	PUNCT
ejpam-2688	310	1	[	[	X
ejpam-2688	310	2	2	2	NUM
ejpam-2688	310	3	]	]	PUNCT
ejpam-2688	310	4	n	n	DET
ejpam-2688	310	5	aronszajn	aronszajn	NOUN
ejpam-2688	310	6	.	.	PUNCT
ejpam-2688	311	1	theory	theory	NOUN
ejpam-2688	311	2	of	of	ADP
ejpam-2688	311	3	reproducing	reproduce	VERB
ejpam-2688	311	4	kernels	kernel	NOUN
ejpam-2688	311	5	.	.	PUNCT
ejpam-2688	312	1	in	in	ADP
ejpam-2688	312	2	transactions	transaction	NOUN
ejpam-2688	312	3	of	of	ADP
ejpam-2688	312	4	the	the	DET
ejpam-2688	312	5	american	american	PROPN
ejpam-2688	312	6	mathematical	mathematical	PROPN
ejpam-2688	312	7	society	society	NOUN
ejpam-2688	312	8	,	,	PUNCT
ejpam-2688	312	9	volume	volume	NOUN
ejpam-2688	312	10	68	68	NUM
ejpam-2688	312	11	,	,	PUNCT
ejpam-2688	312	12	pages	page	NOUN
ejpam-2688	312	13	337–404	337–404	NUM
ejpam-2688	312	14	,	,	PUNCT
ejpam-2688	312	15	1950	1950	NUM
ejpam-2688	312	16	.	.	PUNCT
ejpam-2688	313	1	[	[	X
ejpam-2688	313	2	3	3	NUM
ejpam-2688	313	3	]	]	X
ejpam-2688	313	4	h	h	NOUN
ejpam-2688	313	5	bozdogan	bozdogan	NOUN
ejpam-2688	313	6	.	.	PUNCT
ejpam-2688	314	1	icomp	icomp	PROPN
ejpam-2688	314	2	:	:	PUNCT
ejpam-2688	314	3	a	a	DET
ejpam-2688	314	4	new	new	ADJ
ejpam-2688	314	5	model	model	ADJ
ejpam-2688	314	6	-	-	PUNCT
ejpam-2688	314	7	selection	selection	NOUN
ejpam-2688	314	8	criteria	criterion	NOUN
ejpam-2688	314	9	.	.	PUNCT
ejpam-2688	315	1	in	in	ADP
ejpam-2688	315	2	h	h	PROPN
ejpam-2688	315	3	h	h	NOUN
ejpam-2688	315	4	bock	bock	NOUN
ejpam-2688	315	5	,	,	PUNCT
ejpam-2688	315	6	editor	editor	NOUN
ejpam-2688	315	7	,	,	PUNCT
ejpam-2688	315	8	classification	classification	NOUN
ejpam-2688	315	9	and	and	CCONJ
ejpam-2688	315	10	related	related	ADJ
ejpam-2688	315	11	methods	method	NOUN
ejpam-2688	315	12	of	of	ADP
ejpam-2688	315	13	data	datum	NOUN
ejpam-2688	315	14	analysis	analysis	NOUN
ejpam-2688	315	15	,	,	PUNCT
ejpam-2688	315	16	pages	page	NOUN
ejpam-2688	315	17	599–608	599–608	NUM
ejpam-2688	315	18	.	.	PUNCT
ejpam-2688	316	1	elsevier	elsevier	PROPN
ejpam-2688	316	2	science	science	NOUN
ejpam-2688	316	3	publishers	publisher	NOUN
ejpam-2688	316	4	,	,	PUNCT
ejpam-2688	316	5	amsterdam	amsterdam	PROPN
ejpam-2688	316	6	,	,	PUNCT
ejpam-2688	316	7	the	the	DET
ejpam-2688	316	8	netherlands	netherlands	PROPN
ejpam-2688	316	9	,	,	PUNCT
ejpam-2688	316	10	1988	1988	NUM
ejpam-2688	316	11	.	.	PUNCT
ejpam-2688	317	1	[	[	X
ejpam-2688	317	2	4	4	NUM
ejpam-2688	317	3	]	]	X
ejpam-2688	317	4	h	h	NOUN
ejpam-2688	317	5	bozdogan	bozdogan	NOUN
ejpam-2688	317	6	.	.	PUNCT
ejpam-2688	318	1	on	on	ADP
ejpam-2688	318	2	the	the	DET
ejpam-2688	318	3	information	information	NOUN
ejpam-2688	318	4	-	-	PUNCT
ejpam-2688	318	5	based	base	VERB
ejpam-2688	318	6	measure	measure	NOUN
ejpam-2688	318	7	of	of	ADP
ejpam-2688	318	8	covariance	covariance	NOUN
ejpam-2688	318	9	complexity	complexity	NOUN
ejpam-2688	318	10	and	and	CCONJ
ejpam-2688	318	11	its	its	PRON
ejpam-2688	318	12	application	application	NOUN
ejpam-2688	318	13	to	to	ADP
ejpam-2688	318	14	the	the	DET
ejpam-2688	318	15	evaluation	evaluation	NOUN
ejpam-2688	318	16	of	of	ADP
ejpam-2688	318	17	multivariate	multivariate	NOUN
ejpam-2688	318	18	linear	linear	NOUN
ejpam-2688	318	19	models	model	NOUN
ejpam-2688	318	20	.	.	PUNCT
ejpam-2688	319	1	communication	communication	NOUN
ejpam-2688	319	2	in	in	ADP
ejpam-2688	319	3	statistics	statistic	NOUN
ejpam-2688	319	4	,	,	PUNCT
ejpam-2688	319	5	theory	theory	NOUN
ejpam-2688	319	6	and	and	CCONJ
ejpam-2688	319	7	methods	method	NOUN
ejpam-2688	319	8	,	,	PUNCT
ejpam-2688	319	9	19:221–278	19:221–278	NUM
ejpam-2688	319	10	,	,	PUNCT
ejpam-2688	319	11	1990	1990	NUM
ejpam-2688	319	12	.	.	PUNCT
ejpam-2688	320	1	[	[	X
ejpam-2688	320	2	5	5	NUM
ejpam-2688	320	3	]	]	PUNCT
ejpam-2688	320	4	h	h	NOUN
ejpam-2688	320	5	bozdogan	bozdogan	NOUN
ejpam-2688	320	6	.	.	PUNCT
ejpam-2688	321	1	akaike	akaike	ADP
ejpam-2688	321	2	’s	’s	PART
ejpam-2688	321	3	information	information	NOUN
ejpam-2688	321	4	criterion	criterion	NOUN
ejpam-2688	321	5	and	and	CCONJ
ejpam-2688	321	6	recent	recent	ADJ
ejpam-2688	321	7	developments	development	NOUN
ejpam-2688	321	8	in	in	ADP
ejpam-2688	321	9	information	information	NOUN
ejpam-2688	321	10	complexity	complexity	NOUN
ejpam-2688	321	11	.	.	PUNCT
ejpam-2688	322	1	journal	journal	PROPN
ejpam-2688	322	2	of	of	ADP
ejpam-2688	322	3	mathematical	mathematical	ADJ
ejpam-2688	322	4	psychology	psychology	NOUN
ejpam-2688	322	5	,	,	PUNCT
ejpam-2688	322	6	44:62–91	44:62–91	NUM
ejpam-2688	322	7	,	,	PUNCT
ejpam-2688	322	8	march	march	PROPN
ejpam-2688	322	9	2000	2000	NUM
ejpam-2688	322	10	.	.	PUNCT
ejpam-2688	323	1	[	[	X
ejpam-2688	323	2	6	6	NUM
ejpam-2688	323	3	]	]	X
ejpam-2688	323	4	m	m	VERB
ejpam-2688	323	5	chen	chen	PROPN
ejpam-2688	323	6	.	.	PUNCT
ejpam-2688	324	1	estimation	estimation	NOUN
ejpam-2688	324	2	of	of	ADP
ejpam-2688	324	3	covariance	covariance	NOUN
ejpam-2688	324	4	matrices	matrix	NOUN
ejpam-2688	324	5	under	under	ADP
ejpam-2688	324	6	a	a	DET
ejpam-2688	324	7	quadratic	quadratic	ADJ
ejpam-2688	324	8	loss	loss	NOUN
ejpam-2688	324	9	function	function	NOUN
ejpam-2688	324	10	.	.	PUNCT
ejpam-2688	325	1	research	research	NOUN
ejpam-2688	325	2	report	report	PROPN
ejpam-2688	325	3	s-46	s-46	PROPN
ejpam-2688	325	4	,	,	PUNCT
ejpam-2688	325	5	department	department	NOUN
ejpam-2688	325	6	of	of	ADP
ejpam-2688	325	7	mathematics	mathematics	PROPN
ejpam-2688	325	8	,	,	PUNCT
ejpam-2688	325	9	suny	suny	PROPN
ejpam-2688	325	10	at	at	ADP
ejpam-2688	325	11	albany	albany	PROPN
ejpam-2688	325	12	,	,	PUNCT
ejpam-2688	325	13	1976	1976	NUM
ejpam-2688	325	14	.	.	PUNCT
ejpam-2688	326	1	[	[	X
ejpam-2688	326	2	7	7	X
ejpam-2688	326	3	]	]	X
ejpam-2688	326	4	d	d	PROPN
ejpam-2688	326	5	goldberg	goldberg	PROPN
ejpam-2688	326	6	.	.	PUNCT
ejpam-2688	327	1	genetic	genetic	ADJ
ejpam-2688	327	2	algorithms	algorithm	NOUN
ejpam-2688	327	3	in	in	ADP
ejpam-2688	327	4	search	search	NOUN
ejpam-2688	327	5	,	,	PUNCT
ejpam-2688	327	6	optimization	optimization	NOUN
ejpam-2688	327	7	and	and	CCONJ
ejpam-2688	327	8	machine	machine	NOUN
ejpam-2688	327	9	learning	learning	NOUN
ejpam-2688	327	10	.	.	PUNCT
ejpam-2688	328	1	addisonwesley	addisonwesley	ADJ
ejpam-2688	328	2	longman	longman	PROPN
ejpam-2688	328	3	publishing	publishing	PROPN
ejpam-2688	328	4	col	col	PROPN
ejpam-2688	328	5	,	,	PUNCT
ejpam-2688	328	6	inc	inc	PROPN
ejpam-2688	328	7	.	.	PROPN
ejpam-2688	328	8	„	„	PROPN
ejpam-2688	328	9	boston	boston	PROPN
ejpam-2688	328	10	,	,	PUNCT
ejpam-2688	328	11	usa	usa	PROPN
ejpam-2688	328	12	,	,	PUNCT
ejpam-2688	328	13	1989	1989	NUM
ejpam-2688	328	14	.	.	PUNCT
ejpam-2688	329	1	[	[	X
ejpam-2688	329	2	8	8	NUM
ejpam-2688	329	3	]	]	X
ejpam-2688	329	4	r	r	NOUN
ejpam-2688	329	5	haupt	haupt	PROPN
ejpam-2688	329	6	and	and	CCONJ
ejpam-2688	329	7	s	s	PROPN
ejpam-2688	329	8	haupt	haupt	PROPN
ejpam-2688	329	9	.	.	PROPN
ejpam-2688	329	10	practical	practical	ADJ
ejpam-2688	329	11	genetic	genetic	ADJ
ejpam-2688	329	12	algorithms	algorithm	NOUN
ejpam-2688	329	13	.	.	PUNCT
ejpam-2688	330	1	john	john	PROPN
ejpam-2688	330	2	wiley	wiley	PROPN
ejpam-2688	330	3	,	,	PUNCT
ejpam-2688	330	4	hoboken	hoboken	PROPN
ejpam-2688	330	5	,	,	PUNCT
ejpam-2688	330	6	usa	usa	PROPN
ejpam-2688	330	7	,	,	PUNCT
ejpam-2688	330	8	2004	2004	NUM
ejpam-2688	330	9	.	.	PUNCT
ejpam-2688	331	1	[	[	X
ejpam-2688	331	2	9	9	NUM
ejpam-2688	331	3	]	]	SYM
ejpam-2688	331	4	j	j	PROPN
ejpam-2688	331	5	h	h	PROPN
ejpam-2688	331	6	holland	holland	PROPN
ejpam-2688	331	7	.	.	PUNCT
ejpam-2688	332	1	adaptation	adaptation	NOUN
ejpam-2688	332	2	in	in	ADP
ejpam-2688	332	3	natural	natural	ADJ
ejpam-2688	332	4	and	and	CCONJ
ejpam-2688	332	5	artificial	artificial	ADJ
ejpam-2688	332	6	systems	system	NOUN
ejpam-2688	332	7	:	:	PUNCT
ejpam-2688	332	8	an	an	DET
ejpam-2688	332	9	introductory	introductory	ADJ
ejpam-2688	332	10	analysis	analysis	NOUN
ejpam-2688	332	11	with	with	ADP
ejpam-2688	332	12	applications	application	NOUN
ejpam-2688	332	13	to	to	ADP
ejpam-2688	332	14	biology	biology	NOUN
ejpam-2688	332	15	,	,	PUNCT
ejpam-2688	332	16	control	control	NOUN
ejpam-2688	332	17	,	,	PUNCT
ejpam-2688	332	18	and	and	CCONJ
ejpam-2688	332	19	artificial	artificial	ADJ
ejpam-2688	332	20	intelligence	intelligence	NOUN
ejpam-2688	332	21	.	.	PUNCT
ejpam-2688	333	1	the	the	DET
ejpam-2688	333	2	university	university	PROPN
ejpam-2688	333	3	of	of	ADP
ejpam-2688	333	4	michigan	michigan	PROPN
ejpam-2688	333	5	press	press	PROPN
ejpam-2688	333	6	,	,	PUNCT
ejpam-2688	333	7	ann	ann	PROPN
ejpam-2688	333	8	arbor	arbor	PROPN
ejpam-2688	333	9	,	,	PUNCT
ejpam-2688	333	10	usa	usa	PROPN
ejpam-2688	333	11	,	,	PUNCT
ejpam-2688	333	12	1975	1975	NUM
ejpam-2688	333	13	.	.	PUNCT
ejpam-2688	334	1	[	[	X
ejpam-2688	334	2	10	10	NUM
ejpam-2688	334	3	]	]	X
ejpam-2688	334	4	j	j	PROPN
ejpam-2688	334	5	h	h	PROPN
ejpam-2688	334	6	holland	holland	PROPN
ejpam-2688	334	7	.	.	PUNCT
ejpam-2688	335	1	genetic	genetic	ADJ
ejpam-2688	335	2	algorithms	algorithm	NOUN
ejpam-2688	335	3	.	.	PUNCT
ejpam-2688	336	1	scientific	scientific	ADJ
ejpam-2688	336	2	american	american	PROPN
ejpam-2688	336	3	,	,	PUNCT
ejpam-2688	336	4	267:66–72	267:66–72	PROPN
ejpam-2688	336	5	,	,	PUNCT
ejpam-2688	336	6	1992	1992	NUM
ejpam-2688	336	7	.	.	PUNCT
ejpam-2688	337	1	[	[	X
ejpam-2688	337	2	11	11	NUM
ejpam-2688	337	3	]	]	X
ejpam-2688	337	4	c	c	PROPN
ejpam-2688	337	5	hsu	hsu	PROPN
ejpam-2688	337	6	and	and	CCONJ
ejpam-2688	337	7	c	c	PROPN
ejpam-2688	337	8	lin	lin	PROPN
ejpam-2688	337	9	.	.	PUNCT
ejpam-2688	338	1	a	a	DET
ejpam-2688	338	2	comparison	comparison	NOUN
ejpam-2688	338	3	of	of	ADP
ejpam-2688	338	4	methods	method	NOUN
ejpam-2688	338	5	for	for	ADP
ejpam-2688	338	6	multiclass	multiclass	ADJ
ejpam-2688	338	7	support	support	NOUN
ejpam-2688	338	8	vector	vector	NOUN
ejpam-2688	338	9	machines	machine	NOUN
ejpam-2688	338	10	.	.	PUNCT
ejpam-2688	339	1	in	in	ADP
ejpam-2688	339	2	ieee	ieee	NOUN
ejpam-2688	339	3	transactions	transaction	NOUN
ejpam-2688	339	4	on	on	ADP
ejpam-2688	339	5	neural	neural	ADJ
ejpam-2688	339	6	networks	network	NOUN
ejpam-2688	339	7	,	,	PUNCT
ejpam-2688	339	8	volume	volume	NOUN
ejpam-2688	339	9	13	13	NUM
ejpam-2688	339	10	,	,	PUNCT
ejpam-2688	339	11	pages	page	NOUN
ejpam-2688	339	12	415–425	415–425	NUM
ejpam-2688	339	13	,	,	PUNCT
ejpam-2688	339	14	2002	2002	NUM
ejpam-2688	339	15	.	.	PUNCT
ejpam-2688	340	1	[	[	X
ejpam-2688	340	2	12	12	NUM
ejpam-2688	340	3	]	]	X
ejpam-2688	340	4	c	c	X
ejpam-2688	340	5	liberati	liberati	PROPN
ejpam-2688	340	6	,	,	PUNCT
ejpam-2688	340	7	j	j	PROPN
ejpam-2688	340	8	a	a	DET
ejpam-2688	340	9	howe	howe	NOUN
ejpam-2688	340	10	,	,	PUNCT
ejpam-2688	340	11	and	and	CCONJ
ejpam-2688	340	12	h	h	NOUN
ejpam-2688	340	13	bozdogan	bozdogan	NOUN
ejpam-2688	340	14	.	.	PUNCT
ejpam-2688	341	1	data	datum	NOUN
ejpam-2688	341	2	adaptive	adaptive	ADJ
ejpam-2688	341	3	simultaneous	simultaneous	ADJ
ejpam-2688	341	4	parameter	parameter	NOUN
ejpam-2688	341	5	and	and	CCONJ
ejpam-2688	341	6	kernel	kernel	PROPN
ejpam-2688	341	7	selection	selection	NOUN
ejpam-2688	341	8	in	in	ADP
ejpam-2688	341	9	kernel	kernel	PROPN
ejpam-2688	341	10	discriminant	discriminant	ADJ
ejpam-2688	341	11	analysis	analysis	NOUN
ejpam-2688	341	12	using	use	VERB
ejpam-2688	341	13	information	information	NOUN
ejpam-2688	341	14	complexity	complexity	NOUN
ejpam-2688	341	15	.	.	PUNCT
ejpam-2688	342	1	journal	journal	NOUN
ejpam-2688	342	2	of	of	ADP
ejpam-2688	342	3	pattern	pattern	NOUN
ejpam-2688	342	4	recognition	recognition	NOUN
ejpam-2688	342	5	research	research	NOUN
ejpam-2688	342	6	,	,	PUNCT
ejpam-2688	342	7	4(1):119–132	4(1):119–132	NUM
ejpam-2688	342	8	,	,	PUNCT
ejpam-2688	342	9	2009	2009	NUM
ejpam-2688	342	10	.	.	PUNCT
ejpam-2688	343	1	references	reference	NOUN
ejpam-2688	343	2	230	230	NUM
ejpam-2688	343	3	[	[	SYM
ejpam-2688	343	4	13	13	NUM
ejpam-2688	343	5	]	]	SYM
ejpam-2688	343	6	j	j	PROPN
ejpam-2688	343	7	pearlman	pearlman	PROPN
ejpam-2688	343	8	.	.	PUNCT
ejpam-2688	344	1	nuclear	nuclear	ADJ
ejpam-2688	344	2	magnetic	magnetic	ADJ
ejpam-2688	344	3	resonance	resonance	NOUN
ejpam-2688	344	4	spectral	spectral	ADJ
ejpam-2688	344	5	signatures	signature	NOUN
ejpam-2688	344	6	of	of	ADP
ejpam-2688	344	7	liquid	liquid	ADJ
ejpam-2688	344	8	crystals	crystal	NOUN
ejpam-2688	344	9	in	in	ADP
ejpam-2688	344	10	human	human	ADJ
ejpam-2688	344	11	atheroma	atheroma	NOUN
ejpam-2688	344	12	as	as	ADP
ejpam-2688	344	13	basis	basis	NOUN
ejpam-2688	344	14	for	for	ADP
ejpam-2688	344	15	multi	multi	ADJ
ejpam-2688	344	16	-	-	ADJ
ejpam-2688	344	17	dimensional	dimensional	ADJ
ejpam-2688	344	18	digital	digital	ADJ
ejpam-2688	344	19	imaging	imaging	NOUN
ejpam-2688	344	20	of	of	ADP
ejpam-2688	344	21	atherosclerosis	atherosclerosis	NOUN
ejpam-2688	344	22	.	.	PUNCT
ejpam-2688	345	1	phd	phd	NOUN
ejpam-2688	345	2	thesis	thesis	PROPN
ejpam-2688	345	3	,	,	PUNCT
ejpam-2688	345	4	university	university	PROPN
ejpam-2688	345	5	of	of	ADP
ejpam-2688	345	6	virginia	virginia	PROPN
ejpam-2688	345	7	,	,	PUNCT
ejpam-2688	345	8	1986	1986	NUM
ejpam-2688	345	9	.	.	PUNCT
ejpam-2688	346	1	[	[	X
ejpam-2688	346	2	14	14	NUM
ejpam-2688	346	3	]	]	PUNCT
ejpam-2688	346	4	s	s	PART
ejpam-2688	346	5	press	press	NOUN
ejpam-2688	346	6	.	.	PUNCT
ejpam-2688	347	1	estimation	estimation	NOUN
ejpam-2688	347	2	of	of	ADP
ejpam-2688	347	3	a	a	DET
ejpam-2688	347	4	normal	normal	ADJ
ejpam-2688	347	5	covariance	covariance	NOUN
ejpam-2688	347	6	matrix	matrix	NOUN
ejpam-2688	347	7	.	.	PUNCT
ejpam-2688	348	1	technical	technical	ADJ
ejpam-2688	348	2	report	report	PROPN
ejpam-2688	348	3	,	,	PUNCT
ejpam-2688	348	4	university	university	NOUN
ejpam-2688	348	5	of	of	ADP
ejpam-2688	348	6	british	british	PROPN
ejpam-2688	348	7	columbia	columbia	PROPN
ejpam-2688	348	8	,	,	PUNCT
ejpam-2688	348	9	1975	1975	NUM
ejpam-2688	348	10	.	.	PUNCT
ejpam-2688	349	1	[	[	X
ejpam-2688	349	2	15	15	NUM
ejpam-2688	349	3	]	]	X
ejpam-2688	349	4	c	c	PROPN
ejpam-2688	349	5	thomaz	thomaz	PROPN
ejpam-2688	349	6	.	.	PUNCT
ejpam-2688	350	1	maximum	maximum	PROPN
ejpam-2688	350	2	entropy	entropy	PROPN
ejpam-2688	350	3	covariance	covariance	NOUN
ejpam-2688	350	4	estimate	estimate	NOUN
ejpam-2688	350	5	for	for	ADP
ejpam-2688	350	6	statistical	statistical	ADJ
ejpam-2688	350	7	pattern	pattern	NOUN
ejpam-2688	350	8	recognition	recognition	NOUN
ejpam-2688	350	9	.	.	PUNCT
ejpam-2688	351	1	phd	phd	NOUN
ejpam-2688	351	2	thesis	thesis	PROPN
ejpam-2688	351	3	,	,	PUNCT
ejpam-2688	351	4	university	university	NOUN
ejpam-2688	351	5	of	of	ADP
ejpam-2688	351	6	london	london	PROPN
ejpam-2688	351	7	and	and	CCONJ
ejpam-2688	351	8	diploma	diploma	NOUN
ejpam-2688	351	9	of	of	ADP
ejpam-2688	351	10	the	the	DET
ejpam-2688	351	11	imperial	imperial	ADJ
ejpam-2688	351	12	college	college	PROPN
ejpam-2688	351	13	(	(	PUNCT
ejpam-2688	351	14	d.i.c	d.i.c	PROPN
ejpam-2688	351	15	.	.	PUNCT
ejpam-2688	351	16	)	)	PUNCT
ejpam-2688	351	17	,	,	PUNCT
ejpam-2688	351	18	2004	2004	NUM
ejpam-2688	351	19	.	.	PUNCT