id	sid	tid	token	lemma	pos
ejpam-2083	1	1	compiles/023452dd9a48c0c90858183c9f516375	compiles/023452dd9a48c0c90858183c9f516375	VERB
ejpam-2083	1	2	/	/	SYM
ejpam-2083	1	3	output.dvi	output.dvi	PROPN
ejpam-2083	1	4	european	european	PROPN
ejpam-2083	1	5	journal	journal	PROPN
ejpam-2083	1	6	of	of	ADP
ejpam-2083	1	7	pure	pure	ADJ
ejpam-2083	1	8	and	and	CCONJ
ejpam-2083	1	9	applied	apply	VERB
ejpam-2083	1	10	mathematics	mathematic	NOUN
ejpam-2083	1	11	vol	vol	NOUN
ejpam-2083	1	12	.	.	PROPN
ejpam-2083	2	1	6	6	NUM
ejpam-2083	2	2	,	,	PUNCT
ejpam-2083	2	3	no	no	INTJ
ejpam-2083	2	4	.	.	NOUN
ejpam-2083	2	5	4	4	NUM
ejpam-2083	2	6	,	,	PUNCT
ejpam-2083	2	7	2013	2013	NUM
ejpam-2083	2	8	,	,	PUNCT
ejpam-2083	2	9	377	377	NUM
ejpam-2083	2	10	-	-	SYM
ejpam-2083	2	11	386	386	NUM
ejpam-2083	2	12	issn	issn	PROPN
ejpam-2083	2	13	1307	1307	NUM
ejpam-2083	2	14	-	-	SYM
ejpam-2083	2	15	5543	5543	NUM
ejpam-2083	2	16	–	–	PUNCT
ejpam-2083	2	17	www.ejpam.com	www.ejpam.com	X
ejpam-2083	2	18	binary	binary	ADJ
ejpam-2083	2	19	classification	classification	NOUN
ejpam-2083	2	20	for	for	ADP
ejpam-2083	2	21	hydraulic	hydraulic	ADJ
ejpam-2083	2	22	fracturing	fracturing	NOUN
ejpam-2083	2	23	operations	operation	NOUN
ejpam-2083	2	24	in	in	ADP
ejpam-2083	2	25	oil	oil	NOUN
ejpam-2083	2	26	&	&	CCONJ
ejpam-2083	2	27	gas	gas	NOUN
ejpam-2083	2	28	wells	well	NOUN
ejpam-2083	2	29	via	via	ADP
ejpam-2083	2	30	tree	tree	NOUN
ejpam-2083	2	31	based	base	VERB
ejpam-2083	2	32	logistic	logistic	PROPN
ejpam-2083	2	33	rbf	rbf	PROPN
ejpam-2083	2	34	networks	networks	PROPN
ejpam-2083	2	35	oguz	oguz	PROPN
ejpam-2083	2	36	akbilgic	akbilgic	PROPN
ejpam-2083	2	37	department	department	PROPN
ejpam-2083	2	38	of	of	ADP
ejpam-2083	2	39	chemical	chemical	PROPN
ejpam-2083	2	40	and	and	CCONJ
ejpam-2083	2	41	petroleum	petroleum	NOUN
ejpam-2083	2	42	engineering	engineering	NOUN
ejpam-2083	2	43	,	,	PUNCT
ejpam-2083	2	44	schulich	schulich	NOUN
ejpam-2083	2	45	school	school	NOUN
ejpam-2083	2	46	of	of	ADP
ejpam-2083	2	47	engineering	engineering	NOUN
ejpam-2083	2	48	,	,	PUNCT
ejpam-2083	2	49	university	university	PROPN
ejpam-2083	2	50	of	of	ADP
ejpam-2083	2	51	calgary	calgary	PROPN
ejpam-2083	2	52	,	,	PUNCT
ejpam-2083	2	53	ab	ab	PROPN
ejpam-2083	2	54	,	,	PUNCT
ejpam-2083	2	55	canada	canada	PROPN
ejpam-2083	2	56	department	department	PROPN
ejpam-2083	2	57	of	of	ADP
ejpam-2083	2	58	quantitative	quantitative	ADJ
ejpam-2083	2	59	methods	method	NOUN
ejpam-2083	2	60	,	,	PUNCT
ejpam-2083	2	61	istanbul	istanbul	PROPN
ejpam-2083	2	62	university	university	PROPN
ejpam-2083	2	63	school	school	NOUN
ejpam-2083	2	64	of	of	ADP
ejpam-2083	2	65	business	business	NOUN
ejpam-2083	2	66	,	,	PUNCT
ejpam-2083	2	67	istanbul	istanbul	PROPN
ejpam-2083	2	68	,	,	PUNCT
ejpam-2083	2	69	turkey	turkey	PROPN
ejpam-2083	2	70	abstract	abstract	NOUN
ejpam-2083	2	71	.	.	PUNCT
ejpam-2083	3	1	in	in	ADP
ejpam-2083	3	2	this	this	DET
ejpam-2083	3	3	paper	paper	NOUN
ejpam-2083	3	4	we	we	PRON
ejpam-2083	3	5	develop	develop	VERB
ejpam-2083	3	6	a	a	DET
ejpam-2083	3	7	novel	novel	ADJ
ejpam-2083	3	8	tree	tree	NOUN
ejpam-2083	3	9	based	base	VERB
ejpam-2083	3	10	radial	radial	ADJ
ejpam-2083	3	11	basis	basis	NOUN
ejpam-2083	3	12	function	function	NOUN
ejpam-2083	3	13	neural	neural	ADJ
ejpam-2083	3	14	networks	network	NOUN
ejpam-2083	3	15	(	(	PUNCT
ejpam-2083	3	16	rbf	rbf	PROPN
ejpam-2083	3	17	-	-	PUNCT
ejpam-2083	3	18	nns	nns	NOUN
ejpam-2083	3	19	)	)	PUNCT
ejpam-2083	3	20	model	model	NOUN
ejpam-2083	3	21	incorporating	incorporate	VERB
ejpam-2083	3	22	logistic	logistic	ADJ
ejpam-2083	3	23	regression	regression	NOUN
ejpam-2083	3	24	.	.	PUNCT
ejpam-2083	4	1	we	we	PRON
ejpam-2083	4	2	aim	aim	VERB
ejpam-2083	4	3	to	to	PART
ejpam-2083	4	4	improve	improve	VERB
ejpam-2083	4	5	the	the	DET
ejpam-2083	4	6	classification	classification	NOUN
ejpam-2083	4	7	performance	performance	NOUN
ejpam-2083	4	8	of	of	ADP
ejpam-2083	4	9	logistic	logistic	ADJ
ejpam-2083	4	10	regression	regression	NOUN
ejpam-2083	4	11	method	method	NOUN
ejpam-2083	4	12	by	by	ADP
ejpam-2083	4	13	pre	pre	VERB
ejpam-2083	4	14	-	-	ADJ
ejpam-2083	4	15	processing	process	VERB
ejpam-2083	4	16	the	the	DET
ejpam-2083	4	17	input	input	NOUN
ejpam-2083	4	18	data	datum	NOUN
ejpam-2083	4	19	in	in	ADP
ejpam-2083	4	20	rbf	rbf	PROPN
ejpam-2083	4	21	-	-	PUNCT
ejpam-2083	4	22	nn	nn	PROPN
ejpam-2083	4	23	frame	frame	NOUN
ejpam-2083	4	24	.	.	PUNCT
ejpam-2083	5	1	although	although	SCONJ
ejpam-2083	5	2	the	the	DET
ejpam-2083	5	3	scope	scope	NOUN
ejpam-2083	5	4	of	of	ADP
ejpam-2083	5	5	our	our	PRON
ejpam-2083	5	6	proposed	propose	VERB
ejpam-2083	5	7	method	method	NOUN
ejpam-2083	5	8	is	be	AUX
ejpam-2083	5	9	binary	binary	ADJ
ejpam-2083	5	10	classification	classification	NOUN
ejpam-2083	5	11	in	in	ADP
ejpam-2083	5	12	this	this	DET
ejpam-2083	5	13	paper	paper	NOUN
ejpam-2083	5	14	,	,	PUNCT
ejpam-2083	5	15	it	it	PRON
ejpam-2083	5	16	is	be	AUX
ejpam-2083	5	17	easy	easy	ADJ
ejpam-2083	5	18	to	to	PART
ejpam-2083	5	19	generalize	generalize	VERB
ejpam-2083	5	20	it	it	PRON
ejpam-2083	5	21	for	for	ADP
ejpam-2083	5	22	multi	multi	ADJ
ejpam-2083	5	23	-	-	ADJ
ejpam-2083	5	24	class	class	ADJ
ejpam-2083	5	25	classification	classification	NOUN
ejpam-2083	5	26	problems	problem	NOUN
ejpam-2083	5	27	.	.	PUNCT
ejpam-2083	6	1	furthermore	furthermore	ADV
ejpam-2083	6	2	,	,	PUNCT
ejpam-2083	6	3	our	our	PRON
ejpam-2083	6	4	model	model	NOUN
ejpam-2083	6	5	is	be	AUX
ejpam-2083	6	6	very	very	ADV
ejpam-2083	6	7	convenient	convenient	ADJ
ejpam-2083	6	8	to	to	PART
ejpam-2083	6	9	adapt	adapt	VERB
ejpam-2083	6	10	for	for	ADP
ejpam-2083	6	11	n	n	NOUN
ejpam-2083	6	12	<	<	X
ejpam-2083	6	13	p	p	NOUN
ejpam-2083	6	14	classification	classification	NOUN
ejpam-2083	6	15	problem	problem	NOUN
ejpam-2083	6	16	that	that	PRON
ejpam-2083	6	17	is	be	AUX
ejpam-2083	6	18	very	very	ADV
ejpam-2083	6	19	popular	popular	ADJ
ejpam-2083	6	20	yet	yet	ADV
ejpam-2083	6	21	difficult	difficult	ADJ
ejpam-2083	6	22	topic	topic	NOUN
ejpam-2083	6	23	in	in	ADP
ejpam-2083	6	24	statistics	statistic	NOUN
ejpam-2083	6	25	.	.	PUNCT
ejpam-2083	7	1	we	we	PRON
ejpam-2083	7	2	show	show	VERB
ejpam-2083	7	3	the	the	DET
ejpam-2083	7	4	generalization	generalization	NOUN
ejpam-2083	7	5	and	and	CCONJ
ejpam-2083	7	6	classification	classification	NOUN
ejpam-2083	7	7	performance	performance	NOUN
ejpam-2083	7	8	of	of	ADP
ejpam-2083	7	9	our	our	PRON
ejpam-2083	7	10	model	model	NOUN
ejpam-2083	7	11	using	use	VERB
ejpam-2083	7	12	simulated	simulated	ADJ
ejpam-2083	7	13	data	datum	NOUN
ejpam-2083	7	14	.	.	PUNCT
ejpam-2083	8	1	we	we	PRON
ejpam-2083	8	2	have	have	AUX
ejpam-2083	8	3	also	also	ADV
ejpam-2083	8	4	applied	apply	VERB
ejpam-2083	8	5	our	our	PRON
ejpam-2083	8	6	model	model	NOUN
ejpam-2083	8	7	on	on	ADP
ejpam-2083	8	8	a	a	DET
ejpam-2083	8	9	real	real	ADJ
ejpam-2083	8	10	life	life	NOUN
ejpam-2083	8	11	data	datum	NOUN
ejpam-2083	8	12	set	set	VERB
ejpam-2083	8	13	gathered	gather	VERB
ejpam-2083	8	14	from	from	ADP
ejpam-2083	8	15	hydraulic	hydraulic	ADJ
ejpam-2083	8	16	fracturing	fracturing	NOUN
ejpam-2083	8	17	in	in	ADP
ejpam-2083	8	18	oil	oil	NOUN
ejpam-2083	8	19	&	&	CCONJ
ejpam-2083	8	20	gas	gas	NOUN
ejpam-2083	8	21	wells	well	NOUN
ejpam-2083	8	22	.	.	PUNCT
ejpam-2083	9	1	the	the	DET
ejpam-2083	9	2	results	result	NOUN
ejpam-2083	9	3	show	show	VERB
ejpam-2083	9	4	the	the	DET
ejpam-2083	9	5	high	high	ADJ
ejpam-2083	9	6	classification	classification	NOUN
ejpam-2083	9	7	performance	performance	NOUN
ejpam-2083	9	8	of	of	ADP
ejpam-2083	9	9	our	our	PRON
ejpam-2083	9	10	model	model	NOUN
ejpam-2083	9	11	that	that	PRON
ejpam-2083	9	12	is	be	AUX
ejpam-2083	9	13	superior	superior	ADJ
ejpam-2083	9	14	to	to	ADP
ejpam-2083	9	15	logistic	logistic	ADJ
ejpam-2083	9	16	regression	regression	NOUN
ejpam-2083	9	17	.	.	PUNCT
ejpam-2083	10	1	we	we	PRON
ejpam-2083	10	2	have	have	AUX
ejpam-2083	10	3	coded	code	VERB
ejpam-2083	10	4	our	our	PRON
ejpam-2083	10	5	model	model	NOUN
ejpam-2083	10	6	on	on	ADP
ejpam-2083	10	7	r	r	NOUN
ejpam-2083	10	8	software	software	NOUN
ejpam-2083	10	9	.	.	PUNCT
ejpam-2083	11	1	logistic	logistic	ADJ
ejpam-2083	11	2	regression	regression	NOUN
ejpam-2083	11	3	applications	application	NOUN
ejpam-2083	11	4	were	be	AUX
ejpam-2083	11	5	carried	carry	VERB
ejpam-2083	11	6	out	out	ADP
ejpam-2083	11	7	using	use	VERB
ejpam-2083	11	8	ibm	ibm	PROPN
ejpam-2083	11	9	spss	spss	PROPN
ejpam-2083	11	10	version	version	NOUN
ejpam-2083	11	11	20	20	NUM
ejpam-2083	11	12	.	.	PUNCT
ejpam-2083	12	1	2010	2010	NUM
ejpam-2083	12	2	mathematics	mathematic	NOUN
ejpam-2083	12	3	subject	subject	NOUN
ejpam-2083	12	4	classifications	classification	NOUN
ejpam-2083	12	5	:	:	PUNCT
ejpam-2083	12	6	62m45	62m45	NUM
ejpam-2083	12	7	,	,	PUNCT
ejpam-2083	12	8	03c45	03c45	NUM
ejpam-2083	12	9	,	,	PUNCT
ejpam-2083	12	10	62j12	62j12	NUM
ejpam-2083	12	11	key	key	ADJ
ejpam-2083	12	12	words	word	NOUN
ejpam-2083	12	13	and	and	CCONJ
ejpam-2083	12	14	phrases	phrase	NOUN
ejpam-2083	12	15	:	:	PUNCT
ejpam-2083	12	16	hydraulic	hydraulic	ADJ
ejpam-2083	12	17	fracturing	fracturing	NOUN
ejpam-2083	12	18	,	,	PUNCT
ejpam-2083	12	19	radial	radial	ADJ
ejpam-2083	12	20	basis	basis	NOUN
ejpam-2083	12	21	function	function	NOUN
ejpam-2083	12	22	neural	neural	ADJ
ejpam-2083	12	23	networks	network	NOUN
ejpam-2083	12	24	,	,	PUNCT
ejpam-2083	12	25	classification	classification	NOUN
ejpam-2083	12	26	and	and	CCONJ
ejpam-2083	12	27	regression	regression	NOUN
ejpam-2083	12	28	trees	tree	NOUN
ejpam-2083	12	29	,	,	PUNCT
ejpam-2083	12	30	logistic	logistic	ADJ
ejpam-2083	12	31	regression	regression	NOUN
ejpam-2083	12	32	1	1	NUM
ejpam-2083	12	33	.	.	PUNCT
ejpam-2083	13	1	introduction	introduction	NOUN
ejpam-2083	13	2	radial	radial	ADJ
ejpam-2083	13	3	basis	basis	NOUN
ejpam-2083	13	4	function	function	NOUN
ejpam-2083	13	5	(	(	PUNCT
ejpam-2083	13	6	rbf	rbf	PROPN
ejpam-2083	13	7	)	)	PUNCT
ejpam-2083	13	8	neural	neural	ADJ
ejpam-2083	13	9	networks	network	NOUN
ejpam-2083	13	10	(	(	PUNCT
ejpam-2083	13	11	nns	nn	NOUN
ejpam-2083	13	12	)	)	PUNCT
ejpam-2083	14	1	[	[	X
ejpam-2083	14	2	5	5	NUM
ejpam-2083	14	3	]	]	PUNCT
ejpam-2083	14	4	are	be	AUX
ejpam-2083	14	5	one	one	NUM
ejpam-2083	14	6	of	of	ADP
ejpam-2083	14	7	the	the	DET
ejpam-2083	14	8	techniques	technique	NOUN
ejpam-2083	14	9	to	to	PART
ejpam-2083	14	10	handle	handle	VERB
ejpam-2083	14	11	binary	binary	ADJ
ejpam-2083	14	12	classification	classification	NOUN
ejpam-2083	14	13	problems	problem	NOUN
ejpam-2083	14	14	.	.	PUNCT
ejpam-2083	15	1	using	use	VERB
ejpam-2083	15	2	fewer	few	ADJ
ejpam-2083	15	3	assumptions	assumption	NOUN
ejpam-2083	15	4	to	to	PART
ejpam-2083	15	5	compare	compare	VERB
ejpam-2083	15	6	parametric	parametric	ADJ
ejpam-2083	15	7	statistical	statistical	ADJ
ejpam-2083	15	8	techniques	technique	NOUN
ejpam-2083	15	9	is	be	AUX
ejpam-2083	15	10	one	one	NUM
ejpam-2083	15	11	of	of	ADP
ejpam-2083	15	12	the	the	DET
ejpam-2083	15	13	reasons	reason	NOUN
ejpam-2083	15	14	that	that	PRON
ejpam-2083	15	15	rbf	rbf	PROPN
ejpam-2083	15	16	-	-	PUNCT
ejpam-2083	15	17	nns	nns	PROPN
ejpam-2083	15	18	has	have	AUX
ejpam-2083	15	19	become	become	VERB
ejpam-2083	15	20	very	very	ADV
ejpam-2083	15	21	popular	popular	ADJ
ejpam-2083	15	22	for	for	ADP
ejpam-2083	15	23	applications	application	NOUN
ejpam-2083	15	24	for	for	ADP
ejpam-2083	15	25	real	real	ADJ
ejpam-2083	15	26	life	life	NOUN
ejpam-2083	15	27	data	datum	NOUN
ejpam-2083	15	28	[	[	X
ejpam-2083	15	29	6	6	NUM
ejpam-2083	15	30	]	]	PUNCT
ejpam-2083	15	31	.	.	PUNCT
ejpam-2083	16	1	however	however	ADV
ejpam-2083	16	2	,	,	PUNCT
ejpam-2083	16	3	there	there	PRON
ejpam-2083	16	4	are	be	VERB
ejpam-2083	16	5	some	some	DET
ejpam-2083	16	6	problems	problem	NOUN
ejpam-2083	16	7	accompanying	accompany	VERB
ejpam-2083	16	8	rbf	rbf	PROPN
ejpam-2083	16	9	networks	network	NOUN
ejpam-2083	16	10	such	such	ADJ
ejpam-2083	16	11	as	as	ADP
ejpam-2083	16	12	over	over	ADP
ejpam-2083	16	13	fitting	fitting	ADJ
ejpam-2083	16	14	,	,	PUNCT
ejpam-2083	16	15	randomness	randomness	NOUN
ejpam-2083	16	16	in	in	ADP
ejpam-2083	16	17	parameter	parameter	NOUN
ejpam-2083	16	18	detection	detection	NOUN
ejpam-2083	16	19	,	,	PUNCT
ejpam-2083	16	20	and	and	CCONJ
ejpam-2083	16	21	using	use	VERB
ejpam-2083	16	22	a	a	DET
ejpam-2083	16	23	gradient	gradient	ADJ
ejpam-2083	16	24	approach	approach	NOUN
ejpam-2083	16	25	that	that	PRON
ejpam-2083	16	26	might	might	AUX
ejpam-2083	16	27	lead	lead	VERB
ejpam-2083	16	28	networks	network	NOUN
ejpam-2083	16	29	to	to	PART
ejpam-2083	16	30	fixate	fixate	VERB
ejpam-2083	16	31	on	on	ADP
ejpam-2083	16	32	a	a	DET
ejpam-2083	16	33	local	local	ADJ
ejpam-2083	16	34	optimum	optimum	NOUN
ejpam-2083	16	35	.	.	PUNCT
ejpam-2083	17	1	furthermore	furthermore	ADV
ejpam-2083	17	2	,	,	PUNCT
ejpam-2083	17	3	there	there	PRON
ejpam-2083	17	4	is	be	VERB
ejpam-2083	17	5	no	no	DET
ejpam-2083	17	6	theoretical	theoretical	ADJ
ejpam-2083	17	7	justification	justification	NOUN
ejpam-2083	17	8	for	for	ADP
ejpam-2083	17	9	determining	determine	VERB
ejpam-2083	17	10	the	the	DET
ejpam-2083	17	11	number	number	NOUN
ejpam-2083	17	12	of	of	ADP
ejpam-2083	17	13	hidden	hide	VERB
ejpam-2083	17	14	neurons	neuron	NOUN
ejpam-2083	17	15	in	in	ADP
ejpam-2083	17	16	the	the	DET
ejpam-2083	17	17	network	network	NOUN
ejpam-2083	17	18	.	.	PUNCT
ejpam-2083	18	1	in	in	ADP
ejpam-2083	18	2	this	this	DET
ejpam-2083	18	3	paper	paper	NOUN
ejpam-2083	18	4	,	,	PUNCT
ejpam-2083	18	5	we	we	PRON
ejpam-2083	18	6	develop	develop	VERB
ejpam-2083	18	7	a	a	DET
ejpam-2083	18	8	novel	novel	ADJ
ejpam-2083	18	9	tree	tree	NOUN
ejpam-2083	18	10	-	-	PUNCT
ejpam-2083	18	11	based	base	VERB
ejpam-2083	18	12	rbf	rbf	PROPN
ejpam-2083	18	13	-	-	PUNCT
ejpam-2083	18	14	nn	nn	PROPN
ejpam-2083	18	15	model	model	NOUN
ejpam-2083	18	16	incorporating	incorporate	VERB
ejpam-2083	18	17	logistic	logistic	ADJ
ejpam-2083	18	18	regression	regression	NOUN
ejpam-2083	18	19	in	in	ADP
ejpam-2083	18	20	order	order	NOUN
ejpam-2083	18	21	to	to	PART
ejpam-2083	18	22	avoid	avoid	VERB
ejpam-2083	18	23	such	such	ADJ
ejpam-2083	18	24	problems	problem	NOUN
ejpam-2083	18	25	as	as	ADV
ejpam-2083	18	26	well	well	ADV
ejpam-2083	18	27	as	as	ADP
ejpam-2083	18	28	to	to	PART
ejpam-2083	18	29	improve	improve	VERB
ejpam-2083	18	30	the	the	DET
ejpam-2083	18	31	classification	classification	NOUN
ejpam-2083	18	32	performance	performance	NOUN
ejpam-2083	18	33	of	of	ADP
ejpam-2083	18	34	the	the	DET
ejpam-2083	18	35	logistic	logistic	ADJ
ejpam-2083	18	36	regression	regression	NOUN
ejpam-2083	18	37	.	.	PUNCT
ejpam-2083	19	1	email	email	NOUN
ejpam-2083	19	2	address	address	NOUN
ejpam-2083	19	3	:	:	PUNCT
ejpam-2083	19	4	oguzakbilgic@gmail.com	oguzakbilgic@gmail.com	X
ejpam-2083	19	5	http://www.ejpam.com	http://www.ejpam.com	X
ejpam-2083	20	1	377	377	NUM
ejpam-2083	20	2	c	c	NOUN
ejpam-2083	20	3	!	!	PUNCT
ejpam-2083	20	4	2013	2013	NUM
ejpam-2083	20	5	ejpam	ejpam	VERB
ejpam-2083	20	6	all	all	DET
ejpam-2083	20	7	rights	right	NOUN
ejpam-2083	20	8	reserved	reserve	VERB
ejpam-2083	20	9	.	.	PUNCT
ejpam-2083	21	1	o.	o.	PROPN
ejpam-2083	21	2	akbilgic	akbilgic	PROPN
ejpam-2083	21	3	/	/	SYM
ejpam-2083	21	4	eur	eur	PROPN
ejpam-2083	21	5	.	.	PUNCT
ejpam-2083	22	1	j.	j.	PROPN
ejpam-2083	22	2	pure	pure	PROPN
ejpam-2083	22	3	appl	appl	PROPN
ejpam-2083	22	4	.	.	PROPN
ejpam-2083	22	5	math	math	PROPN
ejpam-2083	22	6	,	,	PUNCT
ejpam-2083	22	7	6	6	NUM
ejpam-2083	22	8	(	(	PUNCT
ejpam-2083	22	9	2013	2013	NUM
ejpam-2083	22	10	)	)	PUNCT
ejpam-2083	22	11	,	,	PUNCT
ejpam-2083	22	12	377	377	NUM
ejpam-2083	22	13	-	-	SYM
ejpam-2083	22	14	386	386	NUM
ejpam-2083	22	15	378	378	NUM
ejpam-2083	22	16	there	there	PRON
ejpam-2083	22	17	are	be	VERB
ejpam-2083	22	18	several	several	ADJ
ejpam-2083	22	19	studies	study	NOUN
ejpam-2083	22	20	in	in	ADP
ejpam-2083	22	21	the	the	DET
ejpam-2083	22	22	literature	literature	NOUN
ejpam-2083	22	23	combining	combine	VERB
ejpam-2083	22	24	rbf	rbf	PROPN
ejpam-2083	22	25	networks	network	NOUN
ejpam-2083	22	26	with	with	ADP
ejpam-2083	22	27	other	other	ADJ
ejpam-2083	22	28	statistical	statistical	ADJ
ejpam-2083	22	29	techniques	technique	NOUN
ejpam-2083	22	30	to	to	PART
ejpam-2083	22	31	improve	improve	VERB
ejpam-2083	22	32	its	its	PRON
ejpam-2083	22	33	performance	performance	NOUN
ejpam-2083	22	34	.	.	PUNCT
ejpam-2083	23	1	kubat	kubat	PROPN
ejpam-2083	24	1	[	[	X
ejpam-2083	24	2	11	11	NUM
ejpam-2083	24	3	]	]	PUNCT
ejpam-2083	24	4	introduced	introduce	VERB
ejpam-2083	24	5	the	the	DET
ejpam-2083	24	6	idea	idea	NOUN
ejpam-2083	24	7	of	of	ADP
ejpam-2083	24	8	initializing	initialize	VERB
ejpam-2083	24	9	rbf	rbf	PROPN
ejpam-2083	24	10	networks	network	NOUN
ejpam-2083	24	11	with	with	ADP
ejpam-2083	24	12	decision	decision	NOUN
ejpam-2083	24	13	trees	tree	NOUN
ejpam-2083	24	14	.	.	PUNCT
ejpam-2083	25	1	following	follow	VERB
ejpam-2083	25	2	kubat	kubat	PROPN
ejpam-2083	26	1	[	[	X
ejpam-2083	26	2	11	11	NUM
ejpam-2083	26	3	]	]	PUNCT
ejpam-2083	26	4	,	,	PUNCT
ejpam-2083	26	5	orr	orr	PROPN
ejpam-2083	26	6	[	[	X
ejpam-2083	26	7	12	12	NUM
ejpam-2083	26	8	]	]	PUNCT
ejpam-2083	26	9	used	use	VERB
ejpam-2083	26	10	classification	classification	NOUN
ejpam-2083	26	11	and	and	CCONJ
ejpam-2083	26	12	regression	regression	NOUN
ejpam-2083	26	13	trees	tree	NOUN
ejpam-2083	26	14	to	to	PART
ejpam-2083	26	15	determine	determine	VERB
ejpam-2083	26	16	the	the	DET
ejpam-2083	26	17	center	center	NOUN
ejpam-2083	26	18	and	and	CCONJ
ejpam-2083	26	19	radius	radius	NOUN
ejpam-2083	26	20	parameters	parameter	NOUN
ejpam-2083	26	21	of	of	ADP
ejpam-2083	26	22	rbf	rbf	PROPN
ejpam-2083	26	23	functions	function	NOUN
ejpam-2083	26	24	.	.	PUNCT
ejpam-2083	27	1	akbilgic	akbilgic	VERB
ejpam-2083	27	2	and	and	CCONJ
ejpam-2083	27	3	bozdogan	bozdogan	NOUN
ejpam-2083	28	1	[	[	X
ejpam-2083	28	2	2	2	NUM
ejpam-2083	28	3	,	,	PUNCT
ejpam-2083	28	4	3	3	NUM
ejpam-2083	28	5	]	]	PUNCT
ejpam-2083	28	6	improved	improve	VERB
ejpam-2083	28	7	orr	orr	PROPN
ejpam-2083	28	8	’s	’s	PART
ejpam-2083	28	9	[	[	X
ejpam-2083	28	10	12	12	NUM
ejpam-2083	28	11	]	]	PUNCT
ejpam-2083	28	12	work	work	NOUN
ejpam-2083	28	13	by	by	ADP
ejpam-2083	28	14	bringing	bring	VERB
ejpam-2083	28	15	ridge	ridge	NOUN
ejpam-2083	28	16	regression	regression	NOUN
ejpam-2083	28	17	and	and	CCONJ
ejpam-2083	28	18	variable	variable	ADJ
ejpam-2083	28	19	selection	selection	NOUN
ejpam-2083	28	20	scheme	scheme	NOUN
ejpam-2083	28	21	into	into	ADP
ejpam-2083	28	22	the	the	DET
ejpam-2083	28	23	rbf	rbf	PROPN
ejpam-2083	28	24	-	-	PUNCT
ejpam-2083	28	25	nn	nn	PROPN
ejpam-2083	28	26	frame	frame	NOUN
ejpam-2083	28	27	.	.	PUNCT
ejpam-2083	29	1	in	in	ADP
ejpam-2083	29	2	our	our	PRON
ejpam-2083	29	3	model	model	NOUN
ejpam-2083	29	4	,	,	PUNCT
ejpam-2083	29	5	we	we	PRON
ejpam-2083	29	6	use	use	VERB
ejpam-2083	29	7	classification	classification	NOUN
ejpam-2083	29	8	and	and	CCONJ
ejpam-2083	29	9	regression	regression	NOUN
ejpam-2083	29	10	trees	tree	NOUN
ejpam-2083	29	11	(	(	PUNCT
ejpam-2083	29	12	cart	cart	NOUN
ejpam-2083	29	13	)	)	PUNCT
ejpam-2083	30	1	[	[	X
ejpam-2083	30	2	4	4	X
ejpam-2083	30	3	]	]	PUNCT
ejpam-2083	30	4	to	to	PART
ejpam-2083	30	5	determine	determine	VERB
ejpam-2083	30	6	the	the	DET
ejpam-2083	30	7	center	center	NOUN
ejpam-2083	30	8	and	and	CCONJ
ejpam-2083	30	9	radius	radius	NOUN
ejpam-2083	30	10	parameters	parameter	NOUN
ejpam-2083	30	11	of	of	ADP
ejpam-2083	30	12	radial	radial	ADJ
ejpam-2083	30	13	basis	basis	NOUN
ejpam-2083	30	14	functions	function	NOUN
ejpam-2083	30	15	taking	take	VERB
ejpam-2083	30	16	place	place	NOUN
ejpam-2083	30	17	in	in	ADP
ejpam-2083	30	18	the	the	DET
ejpam-2083	30	19	hidden	hide	VERB
ejpam-2083	30	20	layer	layer	NOUN
ejpam-2083	30	21	of	of	ADP
ejpam-2083	30	22	rbf	rbf	PROPN
ejpam-2083	30	23	networks	network	NOUN
ejpam-2083	30	24	.	.	PUNCT
ejpam-2083	31	1	each	each	DET
ejpam-2083	31	2	terminal	terminal	ADJ
ejpam-2083	31	3	node	node	NOUN
ejpam-2083	31	4	obtained	obtain	VERB
ejpam-2083	31	5	by	by	ADP
ejpam-2083	31	6	cart	cart	NOUN
ejpam-2083	31	7	corresponds	correspond	NOUN
ejpam-2083	31	8	to	to	ADP
ejpam-2083	31	9	a	a	DET
ejpam-2083	31	10	hidden	hide	VERB
ejpam-2083	31	11	neuron	neuron	NOUN
ejpam-2083	31	12	in	in	ADP
ejpam-2083	31	13	the	the	DET
ejpam-2083	31	14	rbf	rbf	PROPN
ejpam-2083	31	15	network	network	NOUN
ejpam-2083	31	16	[	[	X
ejpam-2083	31	17	11	11	NUM
ejpam-2083	31	18	,	,	PUNCT
ejpam-2083	31	19	12	12	NUM
ejpam-2083	31	20	]	]	PUNCT
ejpam-2083	31	21	.	.	PUNCT
ejpam-2083	32	1	thus	thus	ADV
ejpam-2083	32	2	the	the	DET
ejpam-2083	32	3	number	number	NOUN
ejpam-2083	32	4	of	of	ADP
ejpam-2083	32	5	hidden	hidden	ADJ
ejpam-2083	32	6	neurons	neuron	NOUN
ejpam-2083	32	7	on	on	ADP
ejpam-2083	32	8	a	a	DET
ejpam-2083	32	9	hidden	hide	VERB
ejpam-2083	32	10	layer	layer	NOUN
ejpam-2083	32	11	is	be	AUX
ejpam-2083	32	12	automatically	automatically	ADV
ejpam-2083	32	13	determined	determine	VERB
ejpam-2083	32	14	.	.	PUNCT
ejpam-2083	33	1	at	at	ADP
ejpam-2083	33	2	this	this	DET
ejpam-2083	33	3	point	point	NOUN
ejpam-2083	33	4	,	,	PUNCT
ejpam-2083	33	5	each	each	DET
ejpam-2083	33	6	hidden	hide	VERB
ejpam-2083	33	7	neuron	neuron	NOUN
ejpam-2083	33	8	carries	carry	VERB
ejpam-2083	33	9	out	out	ADP
ejpam-2083	33	10	a	a	DET
ejpam-2083	33	11	nonlinear	nonlinear	ADJ
ejpam-2083	33	12	transformation	transformation	NOUN
ejpam-2083	33	13	of	of	ADP
ejpam-2083	33	14	predictors	predictor	NOUN
ejpam-2083	33	15	via	via	ADP
ejpam-2083	33	16	rbfs	rbfs	NOUN
ejpam-2083	33	17	into	into	ADP
ejpam-2083	33	18	the	the	DET
ejpam-2083	33	19	hidden	hide	VERB
ejpam-2083	33	20	layer	layer	NOUN
ejpam-2083	33	21	.	.	PUNCT
ejpam-2083	34	1	usage	usage	NOUN
ejpam-2083	34	2	of	of	ADP
ejpam-2083	34	3	the	the	DET
ejpam-2083	34	4	new	new	ADJ
ejpam-2083	34	5	data	datum	NOUN
ejpam-2083	34	6	that	that	PRON
ejpam-2083	34	7	is	be	AUX
ejpam-2083	34	8	a	a	DET
ejpam-2083	34	9	nonlinear	nonlinear	ADJ
ejpam-2083	34	10	transformation	transformation	NOUN
ejpam-2083	34	11	of	of	ADP
ejpam-2083	34	12	original	original	ADJ
ejpam-2083	34	13	data	datum	NOUN
ejpam-2083	34	14	by	by	ADP
ejpam-2083	34	15	the	the	DET
ejpam-2083	34	16	hidden	hide	VERB
ejpam-2083	34	17	layer	layer	NOUN
ejpam-2083	34	18	,	,	PUNCT
ejpam-2083	34	19	as	as	SCONJ
ejpam-2083	34	20	predictors	predictor	NOUN
ejpam-2083	34	21	highly	highly	ADV
ejpam-2083	34	22	tends	tend	VERB
ejpam-2083	34	23	to	to	PART
ejpam-2083	34	24	cause	cause	VERB
ejpam-2083	34	25	singularity	singularity	NOUN
ejpam-2083	34	26	problem	problem	NOUN
ejpam-2083	34	27	of	of	ADP
ejpam-2083	34	28	design	design	NOUN
ejpam-2083	34	29	matrix	matrix	NOUN
ejpam-2083	34	30	.	.	PUNCT
ejpam-2083	35	1	to	to	PART
ejpam-2083	35	2	be	be	AUX
ejpam-2083	35	3	able	able	ADJ
ejpam-2083	35	4	to	to	PART
ejpam-2083	35	5	handle	handle	VERB
ejpam-2083	35	6	the	the	DET
ejpam-2083	35	7	possible	possible	ADJ
ejpam-2083	35	8	singularity	singularity	NOUN
ejpam-2083	35	9	problem	problem	NOUN
ejpam-2083	35	10	,	,	PUNCT
ejpam-2083	35	11	we	we	PRON
ejpam-2083	35	12	reduce	reduce	VERB
ejpam-2083	35	13	the	the	DET
ejpam-2083	35	14	dimensionality	dimensionality	NOUN
ejpam-2083	35	15	of	of	ADP
ejpam-2083	35	16	the	the	DET
ejpam-2083	35	17	hidden	hide	VERB
ejpam-2083	35	18	layer	layer	NOUN
ejpam-2083	35	19	by	by	ADP
ejpam-2083	35	20	using	use	VERB
ejpam-2083	35	21	the	the	DET
ejpam-2083	35	22	aic	aic	PROPN
ejpam-2083	35	23	[	[	X
ejpam-2083	35	24	1	1	NUM
ejpam-2083	35	25	]	]	PUNCT
ejpam-2083	35	26	based	base	VERB
ejpam-2083	35	27	stepwise	stepwise	ADJ
ejpam-2083	35	28	technique	technique	NOUN
ejpam-2083	35	29	for	for	ADP
ejpam-2083	35	30	logistic	logistic	ADJ
ejpam-2083	35	31	regression	regression	NOUN
ejpam-2083	35	32	.	.	PUNCT
ejpam-2083	36	1	by	by	ADP
ejpam-2083	36	2	doing	do	VERB
ejpam-2083	36	3	so	so	ADV
ejpam-2083	36	4	,	,	PUNCT
ejpam-2083	36	5	not	not	PART
ejpam-2083	36	6	only	only	ADV
ejpam-2083	36	7	do	do	AUX
ejpam-2083	36	8	we	we	PRON
ejpam-2083	36	9	handle	handle	VERB
ejpam-2083	36	10	the	the	DET
ejpam-2083	36	11	singularity	singularity	NOUN
ejpam-2083	36	12	problem	problem	NOUN
ejpam-2083	36	13	in	in	ADP
ejpam-2083	36	14	logistic	logistic	ADJ
ejpam-2083	36	15	regression	regression	NOUN
ejpam-2083	36	16	,	,	PUNCT
ejpam-2083	36	17	but	but	CCONJ
ejpam-2083	36	18	we	we	PRON
ejpam-2083	36	19	also	also	ADV
ejpam-2083	36	20	reduce	reduce	VERB
ejpam-2083	36	21	the	the	DET
ejpam-2083	36	22	size	size	NOUN
ejpam-2083	36	23	of	of	ADP
ejpam-2083	36	24	the	the	DET
ejpam-2083	36	25	rbf	rbf	PROPN
ejpam-2083	36	26	-	-	PUNCT
ejpam-2083	36	27	nn	nn	PROPN
ejpam-2083	36	28	model	model	NOUN
ejpam-2083	36	29	,	,	PUNCT
ejpam-2083	36	30	which	which	PRON
ejpam-2083	36	31	prevents	prevent	VERB
ejpam-2083	36	32	the	the	DET
ejpam-2083	36	33	model	model	NOUN
ejpam-2083	36	34	from	from	ADP
ejpam-2083	36	35	the	the	DET
ejpam-2083	36	36	over	over	ADP
ejpam-2083	36	37	fitting	fitting	ADJ
ejpam-2083	36	38	problem	problem	NOUN
ejpam-2083	36	39	.	.	PUNCT
ejpam-2083	37	1	furthermore	furthermore	ADV
ejpam-2083	37	2	,	,	PUNCT
ejpam-2083	37	3	the	the	DET
ejpam-2083	37	4	proposed	propose	VERB
ejpam-2083	37	5	model	model	NOUN
ejpam-2083	37	6	leads	lead	VERB
ejpam-2083	37	7	us	we	PRON
ejpam-2083	37	8	to	to	PART
ejpam-2083	37	9	obtain	obtain	VERB
ejpam-2083	37	10	completely	completely	ADV
ejpam-2083	37	11	continuous	continuous	ADJ
ejpam-2083	37	12	predictors	predictor	NOUN
ejpam-2083	37	13	in	in	ADP
ejpam-2083	37	14	hidden	hide	VERB
ejpam-2083	37	15	layer	layer	NOUN
ejpam-2083	37	16	by	by	ADP
ejpam-2083	37	17	processing	process	VERB
ejpam-2083	37	18	original	original	ADJ
ejpam-2083	37	19	categorical	categorical	ADJ
ejpam-2083	37	20	predictors	predictor	NOUN
ejpam-2083	37	21	via	via	ADP
ejpam-2083	37	22	tree	tree	NOUN
ejpam-2083	37	23	-	-	PUNCT
ejpam-2083	37	24	based	base	VERB
ejpam-2083	37	25	rbfs	rbfs	NOUN
ejpam-2083	37	26	.	.	PUNCT
ejpam-2083	38	1	hence	hence	ADV
ejpam-2083	38	2	,	,	PUNCT
ejpam-2083	38	3	the	the	DET
ejpam-2083	38	4	data	datum	NOUN
ejpam-2083	38	5	become	become	VERB
ejpam-2083	38	6	very	very	ADV
ejpam-2083	38	7	suitable	suitable	ADJ
ejpam-2083	38	8	to	to	PART
ejpam-2083	38	9	be	be	AUX
ejpam-2083	38	10	processed	process	VERB
ejpam-2083	38	11	using	use	VERB
ejpam-2083	38	12	logistic	logistic	ADJ
ejpam-2083	38	13	regression	regression	NOUN
ejpam-2083	38	14	in	in	ADP
ejpam-2083	38	15	terms	term	NOUN
ejpam-2083	38	16	of	of	ADP
ejpam-2083	38	17	continuity	continuity	NOUN
ejpam-2083	38	18	assumption	assumption	NOUN
ejpam-2083	38	19	of	of	ADP
ejpam-2083	38	20	predictors	predictor	NOUN
ejpam-2083	38	21	.	.	PUNCT
ejpam-2083	39	1	in	in	ADP
ejpam-2083	39	2	section	section	NOUN
ejpam-2083	39	3	2	2	NUM
ejpam-2083	39	4	,	,	PUNCT
ejpam-2083	39	5	we	we	PRON
ejpam-2083	39	6	described	describe	VERB
ejpam-2083	39	7	our	our	PRON
ejpam-2083	39	8	proposed	propose	VERB
ejpam-2083	39	9	method	method	NOUN
ejpam-2083	39	10	right	right	ADV
ejpam-2083	39	11	after	after	ADP
ejpam-2083	39	12	giving	give	VERB
ejpam-2083	39	13	brief	brief	ADJ
ejpam-2083	39	14	definitions	definition	NOUN
ejpam-2083	39	15	of	of	ADP
ejpam-2083	39	16	rbf	rbf	PROPN
ejpam-2083	39	17	-	-	PUNCT
ejpam-2083	39	18	nns	nn	NOUN
ejpam-2083	39	19	,	,	PUNCT
ejpam-2083	39	20	cart	cart	NOUN
ejpam-2083	39	21	,	,	PUNCT
ejpam-2083	39	22	and	and	CCONJ
ejpam-2083	39	23	the	the	DET
ejpam-2083	39	24	logistic	logistic	ADJ
ejpam-2083	39	25	regression	regression	NOUN
ejpam-2083	39	26	.	.	PUNCT
ejpam-2083	40	1	section	section	NOUN
ejpam-2083	40	2	3	3	NUM
ejpam-2083	40	3	is	be	AUX
ejpam-2083	40	4	to	to	PART
ejpam-2083	40	5	show	show	VERB
ejpam-2083	40	6	our	our	PRON
ejpam-2083	40	7	proposed	propose	VERB
ejpam-2083	40	8	model	model	NOUN
ejpam-2083	40	9	’s	’s	PART
ejpam-2083	40	10	classification	classification	NOUN
ejpam-2083	40	11	and	and	CCONJ
ejpam-2083	40	12	generalization	generalization	NOUN
ejpam-2083	40	13	performance	performance	NOUN
ejpam-2083	40	14	.	.	PUNCT
ejpam-2083	41	1	to	to	PART
ejpam-2083	41	2	do	do	VERB
ejpam-2083	41	3	so	so	ADV
ejpam-2083	41	4	,	,	PUNCT
ejpam-2083	41	5	we	we	PRON
ejpam-2083	41	6	apply	apply	VERB
ejpam-2083	41	7	our	our	PRON
ejpam-2083	41	8	model	model	NOUN
ejpam-2083	41	9	on	on	ADP
ejpam-2083	41	10	simulated	simulated	ADJ
ejpam-2083	41	11	data	datum	NOUN
ejpam-2083	41	12	and	and	CCONJ
ejpam-2083	41	13	a	a	DET
ejpam-2083	41	14	real	real	ADJ
ejpam-2083	41	15	life	life	NOUN
ejpam-2083	41	16	data	datum	NOUN
ejpam-2083	41	17	set	set	VERB
ejpam-2083	41	18	derived	derive	VERB
ejpam-2083	41	19	from	from	ADP
ejpam-2083	41	20	hydraulic	hydraulic	ADJ
ejpam-2083	41	21	fracturing	fracturing	NOUN
ejpam-2083	41	22	operations	operation	NOUN
ejpam-2083	41	23	in	in	ADP
ejpam-2083	41	24	oil	oil	NOUN
ejpam-2083	41	25	&	&	CCONJ
ejpam-2083	41	26	gas	gas	NOUN
ejpam-2083	41	27	wells	well	NOUN
ejpam-2083	41	28	.	.	PUNCT
ejpam-2083	42	1	we	we	PRON
ejpam-2083	42	2	discuss	discuss	VERB
ejpam-2083	42	3	our	our	PRON
ejpam-2083	42	4	model	model	NOUN
ejpam-2083	42	5	and	and	CCONJ
ejpam-2083	42	6	the	the	DET
ejpam-2083	42	7	results	result	NOUN
ejpam-2083	42	8	in	in	ADP
ejpam-2083	42	9	the	the	DET
ejpam-2083	42	10	conclusions	conclusion	NOUN
ejpam-2083	42	11	section	section	NOUN
ejpam-2083	42	12	.	.	PUNCT
ejpam-2083	43	1	2	2	X
ejpam-2083	43	2	.	.	X
ejpam-2083	43	3	tree	tree	NOUN
ejpam-2083	43	4	based	base	VERB
ejpam-2083	43	5	logistic	logistic	PROPN
ejpam-2083	43	6	rbf	rbf	PROPN
ejpam-2083	43	7	network	network	PROPN
ejpam-2083	43	8	model	model	NOUN
ejpam-2083	43	9	with	with	ADP
ejpam-2083	43	10	logistic	logistic	ADJ
ejpam-2083	43	11	regression	regression	NOUN
ejpam-2083	43	12	in	in	ADP
ejpam-2083	43	13	this	this	DET
ejpam-2083	43	14	paper	paper	NOUN
ejpam-2083	43	15	we	we	PRON
ejpam-2083	43	16	developed	develop	VERB
ejpam-2083	43	17	a	a	DET
ejpam-2083	43	18	novel	novel	ADJ
ejpam-2083	43	19	approach	approach	NOUN
ejpam-2083	43	20	for	for	ADP
ejpam-2083	43	21	binary	binary	ADJ
ejpam-2083	43	22	classification	classification	NOUN
ejpam-2083	43	23	problems	problem	NOUN
ejpam-2083	43	24	by	by	ADP
ejpam-2083	43	25	embedding	embed	VERB
ejpam-2083	43	26	the	the	DET
ejpam-2083	43	27	classification	classification	NOUN
ejpam-2083	43	28	,	,	PUNCT
ejpam-2083	43	29	regression	regression	NOUN
ejpam-2083	43	30	trees	tree	NOUN
ejpam-2083	43	31	,	,	PUNCT
ejpam-2083	43	32	and	and	CCONJ
ejpam-2083	43	33	the	the	DET
ejpam-2083	43	34	logistic	logistic	ADJ
ejpam-2083	43	35	regression	regression	NOUN
ejpam-2083	43	36	into	into	ADP
ejpam-2083	43	37	the	the	DET
ejpam-2083	43	38	rbf	rbf	PROPN
ejpam-2083	43	39	-	-	PUNCT
ejpam-2083	43	40	nn	nn	PROPN
ejpam-2083	43	41	frame	frame	NOUN
ejpam-2083	43	42	.	.	PUNCT
ejpam-2083	44	1	brief	brief	ADJ
ejpam-2083	44	2	definitions	definition	NOUN
ejpam-2083	44	3	of	of	ADP
ejpam-2083	44	4	the	the	DET
ejpam-2083	44	5	techniques	technique	NOUN
ejpam-2083	44	6	used	use	VERB
ejpam-2083	44	7	,	,	PUNCT
ejpam-2083	44	8	as	as	ADV
ejpam-2083	44	9	well	well	ADV
ejpam-2083	44	10	as	as	ADP
ejpam-2083	44	11	their	their	PRON
ejpam-2083	44	12	role	role	NOUN
ejpam-2083	44	13	in	in	ADP
ejpam-2083	44	14	rbf	rbf	PROPN
ejpam-2083	44	15	-	-	PUNCT
ejpam-2083	44	16	nn	nn	PROPN
ejpam-2083	44	17	frame	frame	NOUN
ejpam-2083	44	18	,	,	PUNCT
ejpam-2083	44	19	are	be	AUX
ejpam-2083	44	20	described	describe	VERB
ejpam-2083	44	21	in	in	ADP
ejpam-2083	44	22	following	follow	VERB
ejpam-2083	44	23	subsections	subsection	NOUN
ejpam-2083	44	24	.	.	PUNCT
ejpam-2083	45	1	2.1	2.1	NUM
ejpam-2083	45	2	.	.	PUNCT
ejpam-2083	45	3	radial	radial	ADJ
ejpam-2083	45	4	basis	basis	NOUN
ejpam-2083	45	5	function	function	NOUN
ejpam-2083	45	6	neural	neural	ADJ
ejpam-2083	45	7	networks	network	NOUN
ejpam-2083	45	8	radial	radial	ADJ
ejpam-2083	45	9	basis	basis	NOUN
ejpam-2083	45	10	function	function	NOUN
ejpam-2083	45	11	neural	neural	ADJ
ejpam-2083	45	12	networks	network	NOUN
ejpam-2083	45	13	are	be	AUX
ejpam-2083	45	14	special	special	ADJ
ejpam-2083	45	15	types	type	NOUN
ejpam-2083	45	16	of	of	ADP
ejpam-2083	45	17	neural	neural	ADJ
ejpam-2083	45	18	networks	network	NOUN
ejpam-2083	45	19	.	.	PUNCT
ejpam-2083	46	1	rbf	rbf	PROPN
ejpam-2083	46	2	-	-	PUNCT
ejpam-2083	46	3	nns	nn	NOUN
ejpam-2083	46	4	are	be	AUX
ejpam-2083	46	5	distinguished	distinguish	VERB
ejpam-2083	46	6	by	by	ADP
ejpam-2083	46	7	having	have	VERB
ejpam-2083	46	8	only	only	ADV
ejpam-2083	46	9	one	one	NUM
ejpam-2083	46	10	hidden	hide	VERB
ejpam-2083	46	11	layer	layer	NOUN
ejpam-2083	46	12	using	use	VERB
ejpam-2083	46	13	rbfs	rbfs	NOUN
ejpam-2083	46	14	as	as	ADP
ejpam-2083	46	15	an	an	DET
ejpam-2083	46	16	activation	activation	NOUN
ejpam-2083	46	17	function	function	NOUN
ejpam-2083	46	18	of	of	ADP
ejpam-2083	46	19	hidden	hidden	ADJ
ejpam-2083	46	20	neurons	neuron	NOUN
ejpam-2083	46	21	.	.	PUNCT
ejpam-2083	47	1	furthermore	furthermore	ADV
ejpam-2083	47	2	,	,	PUNCT
ejpam-2083	47	3	input	input	NOUN
ejpam-2083	47	4	data	datum	NOUN
ejpam-2083	47	5	is	be	AUX
ejpam-2083	47	6	directly	directly	ADV
ejpam-2083	47	7	sent	send	VERB
ejpam-2083	47	8	to	to	ADP
ejpam-2083	47	9	the	the	DET
ejpam-2083	47	10	hidden	hide	VERB
ejpam-2083	47	11	layer	layer	NOUN
ejpam-2083	47	12	without	without	ADP
ejpam-2083	47	13	being	be	AUX
ejpam-2083	47	14	weighted	weight	VERB
ejpam-2083	47	15	unlike	unlike	ADP
ejpam-2083	47	16	the	the	DET
ejpam-2083	47	17	other	other	ADJ
ejpam-2083	47	18	multi	multi	ADJ
ejpam-2083	47	19	layer	layer	NOUN
ejpam-2083	47	20	feed	feed	VERB
ejpam-2083	47	21	forward	forward	ADV
ejpam-2083	47	22	neural	neural	ADJ
ejpam-2083	47	23	network	network	NOUN
ejpam-2083	47	24	models	model	NOUN
ejpam-2083	47	25	[	[	X
ejpam-2083	47	26	7	7	NUM
ejpam-2083	47	27	]	]	PUNCT
ejpam-2083	47	28	.	.	PUNCT
ejpam-2083	48	1	the	the	DET
ejpam-2083	48	2	simple	simple	ADJ
ejpam-2083	48	3	presentation	presentation	NOUN
ejpam-2083	48	4	of	of	ADP
ejpam-2083	48	5	rbf	rbf	PROPN
ejpam-2083	48	6	-	-	PUNCT
ejpam-2083	48	7	nn	nn	PROPN
ejpam-2083	48	8	is	be	AUX
ejpam-2083	48	9	given	give	VERB
ejpam-2083	48	10	by	by	ADP
ejpam-2083	48	11	(	(	PUNCT
ejpam-2083	48	12	1	1	X
ejpam-2083	48	13	)	)	PUNCT
ejpam-2083	48	14	where	where	SCONJ
ejpam-2083	48	15	the	the	DET
ejpam-2083	48	16	outputs	output	NOUN
ejpam-2083	48	17	are	be	AUX
ejpam-2083	48	18	modeled	model	VERB
ejpam-2083	48	19	as	as	ADP
ejpam-2083	48	20	a	a	DET
ejpam-2083	48	21	sum	sum	NOUN
ejpam-2083	48	22	of	of	ADP
ejpam-2083	48	23	m	m	VERB
ejpam-2083	48	24	weighted	weight	VERB
ejpam-2083	48	25	radial	radial	ADJ
ejpam-2083	48	26	basis	basis	NOUN
ejpam-2083	48	27	o.	o.	NOUN
ejpam-2083	48	28	akbilgic	akbilgic	PROPN
ejpam-2083	48	29	/	/	SYM
ejpam-2083	48	30	eur	eur	PROPN
ejpam-2083	48	31	.	.	PUNCT
ejpam-2083	49	1	j.	j.	PROPN
ejpam-2083	49	2	pure	pure	PROPN
ejpam-2083	49	3	appl	appl	PROPN
ejpam-2083	49	4	.	.	PROPN
ejpam-2083	49	5	math	math	PROPN
ejpam-2083	49	6	,	,	PUNCT
ejpam-2083	49	7	6	6	NUM
ejpam-2083	49	8	(	(	PUNCT
ejpam-2083	49	9	2013	2013	NUM
ejpam-2083	49	10	)	)	PUNCT
ejpam-2083	49	11	,	,	PUNCT
ejpam-2083	49	12	377	377	NUM
ejpam-2083	49	13	-	-	SYM
ejpam-2083	49	14	386	386	NUM
ejpam-2083	49	15	379	379	NUM
ejpam-2083	49	16	figure	figure	NOUN
ejpam-2083	49	17	1	1	NUM
ejpam-2083	49	18	:	:	PUNCT
ejpam-2083	49	19	radial	radial	ADJ
ejpam-2083	49	20	basis	basis	NOUN
ejpam-2083	49	21	function	function	NOUN
ejpam-2083	49	22	neural	neural	ADJ
ejpam-2083	49	23	network	network	NOUN
ejpam-2083	49	24	.	.	PUNCT
ejpam-2083	50	1	functions	function	NOUN
ejpam-2083	50	2	h	h	PROPN
ejpam-2083	50	3	(	(	PUNCT
ejpam-2083	50	4	·	·	PUNCT
ejpam-2083	50	5	)	)	PUNCT
ejpam-2083	50	6	with	with	ADP
ejpam-2083	50	7	centers	center	NOUN
ejpam-2083	50	8	c	c	PROPN
ejpam-2083	50	9	j	j	PROPN
ejpam-2083	50	10	,	,	PUNCT
ejpam-2083	50	11	radii	radii	VERB
ejpam-2083	50	12	r	r	PROPN
ejpam-2083	50	13	j	j	PROPN
ejpam-2083	50	14	,	,	PUNCT
ejpam-2083	50	15	and	and	CCONJ
ejpam-2083	50	16	weights	weight	NOUN
ejpam-2083	50	17	wj	wj	PROPN
ejpam-2083	50	18	(	(	PUNCT
ejpam-2083	50	19	j	j	PROPN
ejpam-2083	50	20	=	=	NOUN
ejpam-2083	50	21	1	1	NUM
ejpam-2083	50	22	.	.	PUNCT
ejpam-2083	50	23	.	.	PUNCT
ejpam-2083	50	24	.	.	PUNCT
ejpam-2083	51	1	m	m	PROPN
ejpam-2083	51	2	):	):	PUNCT
ejpam-2083	51	3	ŷi	ŷi	PROPN
ejpam-2083	51	4	=	=	SYM
ejpam-2083	51	5	f	f	PROPN
ejpam-2083	51	6	(	(	PUNCT
ejpam-2083	51	7	x	x	NOUN
ejpam-2083	51	8	;	;	PUNCT
ejpam-2083	51	9	w	w	X
ejpam-2083	51	10	,	,	PUNCT
ejpam-2083	51	11	c	c	NOUN
ejpam-2083	51	12	,	,	PUNCT
ejpam-2083	51	13	r	r	NOUN
ejpam-2083	51	14	)	)	PUNCT
ejpam-2083	51	15	=	=	NOUN
ejpam-2083	51	16	m	m	NOUN
ejpam-2083	51	17	!	!	PUNCT
ejpam-2083	52	1	j=1	j=1	PROPN
ejpam-2083	52	2	wjh	wjh	PROPN
ejpam-2083	52	3	(	(	PUNCT
ejpam-2083	52	4	xi	xi	X
ejpam-2083	52	5	"	"	PUNCT
ejpam-2083	52	6	c	c	PROPN
ejpam-2083	52	7	j	j	PROPN
ejpam-2083	52	8	r	r	PROPN
ejpam-2083	52	9	j	j	PROPN
ejpam-2083	52	10	)	)	PUNCT
ejpam-2083	53	1	i	i	PRON
ejpam-2083	53	2	=	=	NOUN
ejpam-2083	53	3	1	1	NUM
ejpam-2083	53	4	,	,	PUNCT
ejpam-2083	53	5	.	.	PUNCT
ejpam-2083	53	6	.	.	PUNCT
ejpam-2083	54	1	.	.	PUNCT
ejpam-2083	55	1	,	,	PUNCT
ejpam-2083	55	2	n	n	X
ejpam-2083	55	3	(	(	PUNCT
ejpam-2083	55	4	1	1	NUM
ejpam-2083	55	5	)	)	PUNCT
ejpam-2083	55	6	in	in	ADP
ejpam-2083	55	7	(	(	PUNCT
ejpam-2083	55	8	1	1	NUM
ejpam-2083	55	9	)	)	PUNCT
ejpam-2083	55	10	,	,	PUNCT
ejpam-2083	55	11	hj(x	hj(x	NUM
ejpam-2083	55	12	)	)	PUNCT
ejpam-2083	55	13	are	be	AUX
ejpam-2083	55	14	rbfs	rbfs	NOUN
ejpam-2083	55	15	,	,	PUNCT
ejpam-2083	55	16	transferring	transfer	VERB
ejpam-2083	55	17	input	input	NOUN
ejpam-2083	55	18	space	space	NOUN
ejpam-2083	55	19	nonlinearly	nonlinearly	ADV
ejpam-2083	55	20	to	to	ADP
ejpam-2083	55	21	hidden	hidden	ADJ
ejpam-2083	55	22	layer	layer	NOUN
ejpam-2083	55	23	,	,	PUNCT
ejpam-2083	55	24	and	and	CCONJ
ejpam-2083	55	25	w	w	NOUN
ejpam-2083	55	26	are	be	AUX
ejpam-2083	55	27	the	the	DET
ejpam-2083	55	28	parameters	parameter	NOUN
ejpam-2083	55	29	connecting	connect	VERB
ejpam-2083	55	30	hidden	hide	VERB
ejpam-2083	55	31	layer	layer	NOUN
ejpam-2083	55	32	to	to	PART
ejpam-2083	55	33	output	output	VERB
ejpam-2083	55	34	layer	layer	NOUN
ejpam-2083	55	35	.	.	PUNCT
ejpam-2083	56	1	the	the	DET
ejpam-2083	56	2	figure	figure	NOUN
ejpam-2083	56	3	1	1	NUM
ejpam-2083	56	4	simply	simply	ADV
ejpam-2083	56	5	presents	present	VERB
ejpam-2083	56	6	the	the	DET
ejpam-2083	56	7	structure	structure	NOUN
ejpam-2083	56	8	of	of	ADP
ejpam-2083	56	9	rbf	rbf	PROPN
ejpam-2083	56	10	-	-	PUNCT
ejpam-2083	56	11	nn	nn	PROPN
ejpam-2083	56	12	.	.	PROPN
ejpam-2083	56	13	radial	radial	ADJ
ejpam-2083	56	14	basis	basis	NOUN
ejpam-2083	56	15	functions	function	NOUN
ejpam-2083	56	16	produce	produce	AUX
ejpam-2083	56	17	monotonically	monotonically	ADV
ejpam-2083	56	18	increasing	increase	VERB
ejpam-2083	56	19	or	or	CCONJ
ejpam-2083	56	20	decreasing	decrease	VERB
ejpam-2083	56	21	values	value	NOUN
ejpam-2083	56	22	by	by	ADP
ejpam-2083	56	23	moving	move	VERB
ejpam-2083	56	24	away	away	ADV
ejpam-2083	56	25	from	from	ADP
ejpam-2083	56	26	a	a	DET
ejpam-2083	56	27	center	center	NOUN
ejpam-2083	56	28	which	which	PRON
ejpam-2083	56	29	is	be	AUX
ejpam-2083	56	30	a	a	DET
ejpam-2083	56	31	parameter	parameter	NOUN
ejpam-2083	56	32	in	in	ADP
ejpam-2083	56	33	rbf	rbf	PROPN
ejpam-2083	56	34	-	-	PUNCT
ejpam-2083	56	35	nn	nn	PROPN
ejpam-2083	56	36	model	model	NOUN
ejpam-2083	56	37	.	.	PUNCT
ejpam-2083	57	1	by	by	ADP
ejpam-2083	57	2	the	the	DET
ejpam-2083	57	3	strong	strong	ADJ
ejpam-2083	57	4	localization	localization	NOUN
ejpam-2083	57	5	property	property	NOUN
ejpam-2083	57	6	of	of	ADP
ejpam-2083	57	7	rbfs	rbfs	NOUN
ejpam-2083	57	8	,	,	PUNCT
ejpam-2083	57	9	the	the	DET
ejpam-2083	57	10	rbf	rbf	PROPN
ejpam-2083	57	11	-	-	PUNCT
ejpam-2083	57	12	nn	nn	PROPN
ejpam-2083	57	13	model	model	NOUN
ejpam-2083	57	14	possesses	possess	VERB
ejpam-2083	57	15	the	the	DET
ejpam-2083	57	16	properties	property	NOUN
ejpam-2083	57	17	of	of	ADP
ejpam-2083	57	18	best	good	ADJ
ejpam-2083	57	19	approximation	approximation	NOUN
ejpam-2083	57	20	[	[	X
ejpam-2083	57	21	13	13	NUM
ejpam-2083	57	22	]	]	PUNCT
ejpam-2083	57	23	.	.	PUNCT
ejpam-2083	58	1	although	although	SCONJ
ejpam-2083	58	2	there	there	PRON
ejpam-2083	58	3	are	be	VERB
ejpam-2083	58	4	several	several	ADJ
ejpam-2083	58	5	rbfs	rbfs	NOUN
ejpam-2083	58	6	seen	see	VERB
ejpam-2083	58	7	in	in	ADP
ejpam-2083	58	8	the	the	DET
ejpam-2083	58	9	literature	literature	NOUN
ejpam-2083	58	10	,	,	PUNCT
ejpam-2083	58	11	in	in	ADP
ejpam-2083	58	12	this	this	DET
ejpam-2083	58	13	study	study	NOUN
ejpam-2083	58	14	we	we	PRON
ejpam-2083	58	15	use	use	VERB
ejpam-2083	58	16	the	the	DET
ejpam-2083	58	17	most	most	ADV
ejpam-2083	58	18	common	common	ADJ
ejpam-2083	58	19	one	one	NUM
ejpam-2083	58	20	,	,	PUNCT
ejpam-2083	58	21	gaussian	gaussian	PROPN
ejpam-2083	58	22	rbf	rbf	PROPN
ejpam-2083	58	23	in	in	ADP
ejpam-2083	58	24	2	2	NUM
ejpam-2083	58	25	[	[	X
ejpam-2083	58	26	9	9	NUM
ejpam-2083	58	27	]	]	PUNCT
ejpam-2083	58	28	.	.	PUNCT
ejpam-2083	59	1	h(x	h(x	PROPN
ejpam-2083	59	2	;	;	PUNCT
ejpam-2083	59	3	c	c	X
ejpam-2083	59	4	,	,	PUNCT
ejpam-2083	59	5	r	r	NOUN
ejpam-2083	59	6	)	)	PUNCT
ejpam-2083	59	7	=	=	SYM
ejpam-2083	60	1	e	e	X
ejpam-2083	60	2	"	"	PUNCT
ejpam-2083	60	3	"	"	PUNCT
ejpam-2083	60	4	x"c	x"c	PROPN
ejpam-2083	60	5	r	r	NOUN
ejpam-2083	60	6	#	#	SYM
ejpam-2083	60	7	2	2	NUM
ejpam-2083	60	8	(	(	PUNCT
ejpam-2083	60	9	2	2	NUM
ejpam-2083	60	10	)	)	PUNCT
ejpam-2083	60	11	during	during	ADP
ejpam-2083	60	12	the	the	DET
ejpam-2083	60	13	rbf	rbf	PROPN
ejpam-2083	60	14	learning	learning	PROPN
ejpam-2083	60	15	,	,	PUNCT
ejpam-2083	60	16	there	there	PRON
ejpam-2083	60	17	are	be	VERB
ejpam-2083	60	18	basically	basically	ADV
ejpam-2083	60	19	three	three	NUM
ejpam-2083	60	20	parameters	parameter	NOUN
ejpam-2083	60	21	to	to	PART
ejpam-2083	60	22	be	be	AUX
ejpam-2083	60	23	determined	determine	VERB
ejpam-2083	60	24	;	;	PUNCT
ejpam-2083	60	25	w	w	X
ejpam-2083	60	26	,	,	PUNCT
ejpam-2083	60	27	c	c	NOUN
ejpam-2083	60	28	,	,	PUNCT
ejpam-2083	60	29	and	and	CCONJ
ejpam-2083	60	30	r.	r.	PROPN
ejpam-2083	60	31	furthermore	furthermore	ADV
ejpam-2083	60	32	,	,	PUNCT
ejpam-2083	60	33	the	the	DET
ejpam-2083	60	34	number	number	NOUN
ejpam-2083	60	35	of	of	ADP
ejpam-2083	60	36	hidden	hide	VERB
ejpam-2083	60	37	neurons	neuron	NOUN
ejpam-2083	60	38	(	(	PUNCT
ejpam-2083	60	39	m	m	NOUN
ejpam-2083	60	40	)	)	PUNCT
ejpam-2083	60	41	in	in	ADP
ejpam-2083	60	42	the	the	DET
ejpam-2083	60	43	hidden	hide	VERB
ejpam-2083	60	44	layer	layer	NOUN
ejpam-2083	60	45	can	can	AUX
ejpam-2083	60	46	be	be	AUX
ejpam-2083	60	47	considered	consider	VERB
ejpam-2083	60	48	as	as	ADP
ejpam-2083	60	49	another	another	DET
ejpam-2083	60	50	parameter	parameter	NOUN
ejpam-2083	60	51	.	.	PUNCT
ejpam-2083	61	1	as	as	SCONJ
ejpam-2083	61	2	explained	explain	VERB
ejpam-2083	61	3	in	in	ADP
ejpam-2083	61	4	the	the	DET
ejpam-2083	61	5	following	follow	VERB
ejpam-2083	61	6	subsections	subsection	NOUN
ejpam-2083	61	7	,	,	PUNCT
ejpam-2083	61	8	m	m	PROPN
ejpam-2083	61	9	,	,	PUNCT
ejpam-2083	61	10	c	c	NOUN
ejpam-2083	61	11	,	,	PUNCT
ejpam-2083	61	12	and	and	CCONJ
ejpam-2083	61	13	r	r	NOUN
ejpam-2083	61	14	parameters	parameter	NOUN
ejpam-2083	61	15	are	be	AUX
ejpam-2083	61	16	determined	determine	VERB
ejpam-2083	61	17	by	by	ADP
ejpam-2083	61	18	classification	classification	NOUN
ejpam-2083	61	19	and	and	CCONJ
ejpam-2083	61	20	regression	regression	NOUN
ejpam-2083	61	21	trees	tree	NOUN
ejpam-2083	61	22	while	while	SCONJ
ejpam-2083	61	23	the	the	DET
ejpam-2083	61	24	w	w	NOUN
ejpam-2083	61	25	is	be	AUX
ejpam-2083	61	26	determined	determine	VERB
ejpam-2083	61	27	by	by	ADP
ejpam-2083	61	28	using	use	VERB
ejpam-2083	61	29	logistic	logistic	ADJ
ejpam-2083	61	30	regression	regression	NOUN
ejpam-2083	61	31	.	.	PUNCT
ejpam-2083	62	1	2.2	2.2	NUM
ejpam-2083	62	2	.	.	PUNCT
ejpam-2083	63	1	classification	classification	NOUN
ejpam-2083	63	2	and	and	CCONJ
ejpam-2083	63	3	regression	regression	NOUN
ejpam-2083	63	4	trees	tree	NOUN
ejpam-2083	63	5	for	for	ADP
ejpam-2083	63	6	the	the	DET
ejpam-2083	63	7	proposed	propose	VERB
ejpam-2083	63	8	model	model	NOUN
ejpam-2083	63	9	classification	classification	NOUN
ejpam-2083	63	10	and	and	CCONJ
ejpam-2083	63	11	regression	regression	NOUN
ejpam-2083	63	12	trees	tree	NOUN
ejpam-2083	63	13	(	(	PUNCT
ejpam-2083	63	14	cart	cart	NOUN
ejpam-2083	63	15	)	)	PUNCT
ejpam-2083	64	1	[	[	X
ejpam-2083	64	2	4	4	X
ejpam-2083	64	3	]	]	PUNCT
ejpam-2083	64	4	is	be	AUX
ejpam-2083	64	5	one	one	NUM
ejpam-2083	64	6	of	of	ADP
ejpam-2083	64	7	the	the	DET
ejpam-2083	64	8	tree	tree	NOUN
ejpam-2083	64	9	-	-	PUNCT
ejpam-2083	64	10	based	base	VERB
ejpam-2083	64	11	statistical	statistical	ADJ
ejpam-2083	64	12	techniques	technique	NOUN
ejpam-2083	64	13	for	for	ADP
ejpam-2083	64	14	prediction	prediction	NOUN
ejpam-2083	64	15	and	and	CCONJ
ejpam-2083	64	16	classification	classification	NOUN
ejpam-2083	64	17	problems	problem	NOUN
ejpam-2083	64	18	depending	depend	VERB
ejpam-2083	64	19	on	on	ADP
ejpam-2083	64	20	the	the	DET
ejpam-2083	64	21	type	type	NOUN
ejpam-2083	64	22	of	of	ADP
ejpam-2083	64	23	target	target	NOUN
ejpam-2083	64	24	variables	variable	NOUN
ejpam-2083	64	25	,	,	PUNCT
ejpam-2083	64	26	either	either	CCONJ
ejpam-2083	64	27	continuous	continuous	ADJ
ejpam-2083	64	28	or	or	CCONJ
ejpam-2083	64	29	categorical	categorical	ADJ
ejpam-2083	64	30	.	.	PUNCT
ejpam-2083	65	1	the	the	DET
ejpam-2083	65	2	idea	idea	NOUN
ejpam-2083	65	3	of	of	ADP
ejpam-2083	65	4	the	the	DET
ejpam-2083	65	5	cart	cart	NOUN
ejpam-2083	65	6	algorithm	algorithm	NOUN
ejpam-2083	65	7	is	be	AUX
ejpam-2083	65	8	based	base	VERB
ejpam-2083	65	9	on	on	ADP
ejpam-2083	65	10	recursively	recursively	ADV
ejpam-2083	65	11	splitting	split	VERB
ejpam-2083	65	12	input	input	NOUN
ejpam-2083	65	13	space	space	NOUN
ejpam-2083	65	14	into	into	ADP
ejpam-2083	65	15	two	two	NUM
ejpam-2083	65	16	hyper	hyper	ADJ
ejpam-2083	65	17	rectangles	rectangle	NOUN
ejpam-2083	65	18	,	,	PUNCT
ejpam-2083	65	19	minimizing	minimize	VERB
ejpam-2083	65	20	a	a	DET
ejpam-2083	65	21	fitness	fitness	NOUN
ejpam-2083	65	22	value	value	NOUN
ejpam-2083	65	23	such	such	ADJ
ejpam-2083	65	24	as	as	ADP
ejpam-2083	65	25	prediction	prediction	NOUN
ejpam-2083	65	26	or	or	CCONJ
ejpam-2083	65	27	o.	o.	NOUN
ejpam-2083	65	28	akbilgic	akbilgic	PROPN
ejpam-2083	65	29	/	/	SYM
ejpam-2083	65	30	eur	eur	PROPN
ejpam-2083	65	31	.	.	PUNCT
ejpam-2083	66	1	j.	j.	PROPN
ejpam-2083	66	2	pure	pure	PROPN
ejpam-2083	66	3	appl	appl	PROPN
ejpam-2083	66	4	.	.	PROPN
ejpam-2083	66	5	math	math	PROPN
ejpam-2083	66	6	,	,	PUNCT
ejpam-2083	66	7	6	6	NUM
ejpam-2083	66	8	(	(	PUNCT
ejpam-2083	66	9	2013	2013	NUM
ejpam-2083	66	10	)	)	PUNCT
ejpam-2083	66	11	,	,	PUNCT
ejpam-2083	66	12	377	377	NUM
ejpam-2083	66	13	-	-	SYM
ejpam-2083	66	14	386	386	NUM
ejpam-2083	66	15	380	380	NUM
ejpam-2083	66	16	classification	classification	NOUN
ejpam-2083	66	17	error	error	NOUN
ejpam-2083	66	18	,	,	PUNCT
ejpam-2083	66	19	and	and	CCONJ
ejpam-2083	66	20	turning	turn	VERB
ejpam-2083	66	21	input	input	NOUN
ejpam-2083	66	22	space	space	NOUN
ejpam-2083	66	23	to	to	ADP
ejpam-2083	66	24	smaller	small	ADJ
ejpam-2083	66	25	hyper	hyper	NOUN
ejpam-2083	66	26	-	-	NOUN
ejpam-2083	66	27	rectangles	rectangle	NOUN
ejpam-2083	66	28	including	include	VERB
ejpam-2083	66	29	data	datum	NOUN
ejpam-2083	66	30	points	point	NOUN
ejpam-2083	66	31	.	.	PUNCT
ejpam-2083	67	1	the	the	DET
ejpam-2083	67	2	end	end	NOUN
ejpam-2083	67	3	nodes	nod	VERB
ejpam-2083	67	4	,	,	PUNCT
ejpam-2083	67	5	called	call	VERB
ejpam-2083	67	6	terminal	terminal	ADJ
ejpam-2083	67	7	nodes	node	NOUN
ejpam-2083	67	8	,	,	PUNCT
ejpam-2083	67	9	are	be	AUX
ejpam-2083	67	10	the	the	DET
ejpam-2083	67	11	hyper	hyper	NOUN
ejpam-2083	67	12	-	-	NOUN
ejpam-2083	67	13	rectangles	rectangle	NOUN
ejpam-2083	67	14	where	where	SCONJ
ejpam-2083	67	15	there	there	PRON
ejpam-2083	67	16	is	be	VERB
ejpam-2083	67	17	no	no	PRON
ejpam-2083	67	18	more	more	ADV
ejpam-2083	67	19	split	split	ADJ
ejpam-2083	67	20	.	.	PUNCT
ejpam-2083	68	1	following	follow	VERB
ejpam-2083	68	2	kubat	kubat	PROPN
ejpam-2083	68	3	[	[	X
ejpam-2083	68	4	11	11	NUM
ejpam-2083	68	5	]	]	PUNCT
ejpam-2083	68	6	,	,	PUNCT
ejpam-2083	68	7	and	and	CCONJ
ejpam-2083	68	8	orr	orr	PROPN
ejpam-2083	69	1	[	[	X
ejpam-2083	69	2	12	12	NUM
ejpam-2083	69	3	]	]	PUNCT
ejpam-2083	69	4	,	,	PUNCT
ejpam-2083	69	5	we	we	PRON
ejpam-2083	69	6	obtained	obtain	VERB
ejpam-2083	69	7	center	center	NOUN
ejpam-2083	69	8	and	and	CCONJ
ejpam-2083	69	9	radius	radius	NOUN
ejpam-2083	69	10	parameters	parameter	NOUN
ejpam-2083	69	11	of	of	ADP
ejpam-2083	69	12	rbfs	rbfs	NOUN
ejpam-2083	69	13	from	from	ADP
ejpam-2083	69	14	terminal	terminal	ADJ
ejpam-2083	69	15	nodes	node	NOUN
ejpam-2083	69	16	.	.	PUNCT
ejpam-2083	70	1	at	at	ADP
ejpam-2083	70	2	this	this	DET
ejpam-2083	70	3	point	point	NOUN
ejpam-2083	70	4	,	,	PUNCT
ejpam-2083	70	5	each	each	DET
ejpam-2083	70	6	terminal	terminal	ADJ
ejpam-2083	70	7	node	node	NOUN
ejpam-2083	70	8	corresponds	correspond	VERB
ejpam-2083	70	9	to	to	ADP
ejpam-2083	70	10	a	a	DET
ejpam-2083	70	11	hidden	hide	VERB
ejpam-2083	70	12	neuron	neuron	NOUN
ejpam-2083	70	13	in	in	ADP
ejpam-2083	70	14	rbf	rbf	PROPN
ejpam-2083	70	15	-	-	PUNCT
ejpam-2083	70	16	nn	nn	PROPN
ejpam-2083	70	17	structure	structure	NOUN
ejpam-2083	70	18	that	that	PRON
ejpam-2083	70	19	solves	solve	VERB
ejpam-2083	70	20	the	the	DET
ejpam-2083	70	21	problem	problem	NOUN
ejpam-2083	70	22	of	of	ADP
ejpam-2083	70	23	determining	determine	VERB
ejpam-2083	70	24	the	the	DET
ejpam-2083	70	25	number	number	NOUN
ejpam-2083	70	26	of	of	ADP
ejpam-2083	70	27	hidden	hide	VERB
ejpam-2083	70	28	neurons	neuron	NOUN
ejpam-2083	70	29	in	in	ADP
ejpam-2083	70	30	the	the	DET
ejpam-2083	70	31	hidden	hide	VERB
ejpam-2083	70	32	layer	layer	NOUN
ejpam-2083	70	33	of	of	ADP
ejpam-2083	70	34	the	the	DET
ejpam-2083	70	35	network	network	NOUN
ejpam-2083	70	36	.	.	PUNCT
ejpam-2083	71	1	center	center	NOUN
ejpam-2083	71	2	coordinates	coordinate	NOUN
ejpam-2083	71	3	of	of	ADP
ejpam-2083	71	4	the	the	DET
ejpam-2083	71	5	terminal	terminal	ADJ
ejpam-2083	71	6	nodes	node	NOUN
ejpam-2083	71	7	correspond	correspond	VERB
ejpam-2083	71	8	to	to	ADP
ejpam-2083	71	9	the	the	DET
ejpam-2083	71	10	center	center	NOUN
ejpam-2083	71	11	parameters	parameter	NOUN
ejpam-2083	71	12	(	(	PUNCT
ejpam-2083	71	13	c	c	NOUN
ejpam-2083	71	14	)	)	PUNCT
ejpam-2083	71	15	of	of	ADP
ejpam-2083	71	16	rbfs	rbfs	NOUN
ejpam-2083	71	17	while	while	SCONJ
ejpam-2083	71	18	the	the	DET
ejpam-2083	71	19	widths	width	NOUN
ejpam-2083	71	20	(	(	PUNCT
ejpam-2083	71	21	s	s	NOUN
ejpam-2083	71	22	)	)	PUNCT
ejpam-2083	71	23	of	of	ADP
ejpam-2083	71	24	the	the	DET
ejpam-2083	71	25	terminal	terminal	ADJ
ejpam-2083	71	26	nodes	node	NOUN
ejpam-2083	71	27	are	be	AUX
ejpam-2083	71	28	used	use	VERB
ejpam-2083	71	29	to	to	PART
ejpam-2083	71	30	obtain	obtain	VERB
ejpam-2083	71	31	radius	radius	NOUN
ejpam-2083	71	32	parameter	parameter	NOUN
ejpam-2083	71	33	(	(	PUNCT
ejpam-2083	71	34	r	r	NOUN
ejpam-2083	71	35	)	)	PUNCT
ejpam-2083	71	36	of	of	ADP
ejpam-2083	71	37	rbfs	rbfs	NOUN
ejpam-2083	71	38	by	by	ADP
ejpam-2083	71	39	scaling	scale	VERB
ejpam-2083	71	40	with	with	ADP
ejpam-2083	71	41	a	a	DET
ejpam-2083	71	42	!	!	PUNCT
ejpam-2083	71	43	parameter	parameter	NOUN
ejpam-2083	71	44	,	,	PUNCT
ejpam-2083	72	1	r	r	NOUN
ejpam-2083	72	2	=	=	PUNCT
ejpam-2083	72	3	!	!	PUNCT
ejpam-2083	73	1	s.	s.	PROPN
ejpam-2083	73	2	here	here	ADV
ejpam-2083	73	3	,	,	PUNCT
ejpam-2083	73	4	!	!	PUNCT
ejpam-2083	73	5	is	be	AUX
ejpam-2083	73	6	another	another	DET
ejpam-2083	73	7	parameter	parameter	NOUN
ejpam-2083	73	8	of	of	ADP
ejpam-2083	73	9	our	our	PRON
ejpam-2083	73	10	model	model	NOUN
ejpam-2083	73	11	that	that	PRON
ejpam-2083	73	12	needs	need	VERB
ejpam-2083	73	13	to	to	PART
ejpam-2083	73	14	be	be	AUX
ejpam-2083	73	15	optimized	optimize	VERB
ejpam-2083	73	16	.	.	PUNCT
ejpam-2083	74	1	figure	figure	NOUN
ejpam-2083	74	2	2	2	NUM
ejpam-2083	74	3	illustrates	illustrate	VERB
ejpam-2083	74	4	how	how	SCONJ
ejpam-2083	74	5	the	the	DET
ejpam-2083	74	6	two	two	NUM
ejpam-2083	74	7	-	-	PUNCT
ejpam-2083	74	8	dimensional	dimensional	ADJ
ejpam-2083	74	9	input	input	NOUN
ejpam-2083	74	10	space	space	NOUN
ejpam-2083	74	11	is	be	AUX
ejpam-2083	74	12	split	split	VERB
ejpam-2083	74	13	into	into	ADP
ejpam-2083	74	14	hyper	hyper	NOUN
ejpam-2083	74	15	-	-	NOUN
ejpam-2083	74	16	rectangles	rectangle	NOUN
ejpam-2083	74	17	including	include	VERB
ejpam-2083	74	18	data	datum	NOUN
ejpam-2083	74	19	points	point	NOUN
ejpam-2083	74	20	.	.	PUNCT
ejpam-2083	75	1	the	the	DET
ejpam-2083	75	2	beauty	beauty	NOUN
ejpam-2083	75	3	of	of	ADP
ejpam-2083	75	4	classification	classification	NOUN
ejpam-2083	75	5	and	and	CCONJ
ejpam-2083	75	6	regression	regression	NOUN
ejpam-2083	75	7	trees	tree	NOUN
ejpam-2083	75	8	is	be	AUX
ejpam-2083	75	9	to	to	PART
ejpam-2083	75	10	be	be	AUX
ejpam-2083	75	11	able	able	ADJ
ejpam-2083	75	12	to	to	PART
ejpam-2083	75	13	handle	handle	VERB
ejpam-2083	75	14	the	the	DET
ejpam-2083	75	15	different	different	ADJ
ejpam-2083	75	16	input	input	NOUN
ejpam-2083	75	17	-	-	PUNCT
ejpam-2083	75	18	output	output	NOUN
ejpam-2083	75	19	relationships	relationship	NOUN
ejpam-2083	75	20	in	in	ADP
ejpam-2083	75	21	different	different	ADJ
ejpam-2083	75	22	sub	sub	NOUN
ejpam-2083	75	23	spaces	space	NOUN
ejpam-2083	75	24	of	of	ADP
ejpam-2083	75	25	overall	overall	ADJ
ejpam-2083	75	26	input	input	NOUN
ejpam-2083	75	27	space	space	NOUN
ejpam-2083	75	28	as	as	SCONJ
ejpam-2083	75	29	can	can	AUX
ejpam-2083	75	30	be	be	AUX
ejpam-2083	75	31	seen	see	VERB
ejpam-2083	75	32	in	in	ADP
ejpam-2083	75	33	figure	figure	NOUN
ejpam-2083	75	34	2	2	NUM
ejpam-2083	75	35	.	.	PUNCT
ejpam-2083	75	36	figure	figure	NOUN
ejpam-2083	75	37	2	2	NUM
ejpam-2083	75	38	:	:	PUNCT
ejpam-2083	75	39	splitting	split	VERB
ejpam-2083	75	40	the	the	DET
ejpam-2083	75	41	data	data	NOUN
ejpam-2083	75	42	space	space	NOUN
ejpam-2083	75	43	into	into	ADP
ejpam-2083	75	44	sub	sub	NOUN
ejpam-2083	75	45	-	-	NOUN
ejpam-2083	75	46	spaces	space	NOUN
ejpam-2083	75	47	using	use	VERB
ejpam-2083	75	48	cart	cart	NOUN
ejpam-2083	75	49	2.3	2.3	NUM
ejpam-2083	75	50	.	.	PUNCT
ejpam-2083	76	1	logistic	logistic	ADJ
ejpam-2083	76	2	regression	regression	NOUN
ejpam-2083	76	3	for	for	ADP
ejpam-2083	76	4	the	the	DET
ejpam-2083	76	5	proposed	propose	VERB
ejpam-2083	76	6	model	model	NOUN
ejpam-2083	76	7	logistic	logistic	ADJ
ejpam-2083	76	8	regression	regression	NOUN
ejpam-2083	76	9	is	be	AUX
ejpam-2083	76	10	one	one	NUM
ejpam-2083	76	11	of	of	ADP
ejpam-2083	76	12	the	the	DET
ejpam-2083	76	13	most	most	ADV
ejpam-2083	76	14	commonly	commonly	ADV
ejpam-2083	76	15	used	use	VERB
ejpam-2083	76	16	classification	classification	NOUN
ejpam-2083	76	17	methods	method	NOUN
ejpam-2083	76	18	in	in	ADP
ejpam-2083	76	19	the	the	DET
ejpam-2083	76	20	literature	literature	NOUN
ejpam-2083	76	21	.	.	PUNCT
ejpam-2083	77	1	for	for	ADP
ejpam-2083	77	2	a	a	DET
ejpam-2083	77	3	given	give	VERB
ejpam-2083	77	4	input	input	NOUN
ejpam-2083	77	5	variables	variable	NOUN
ejpam-2083	77	6	x	x	SYM
ejpam-2083	77	7	,	,	PUNCT
ejpam-2083	77	8	the	the	DET
ejpam-2083	77	9	logistic	logistic	ADJ
ejpam-2083	77	10	regression	regression	NOUN
ejpam-2083	77	11	function	function	NOUN
ejpam-2083	77	12	is	be	AUX
ejpam-2083	77	13	given	give	VERB
ejpam-2083	77	14	by	by	ADP
ejpam-2083	77	15	(	(	PUNCT
ejpam-2083	77	16	3	3	X
ejpam-2083	77	17	)	)	PUNCT
ejpam-2083	77	18	[	[	X
ejpam-2083	77	19	14	14	NUM
ejpam-2083	77	20	]	]	PUNCT
ejpam-2083	77	21	,	,	PUNCT
ejpam-2083	77	22	where	where	SCONJ
ejpam-2083	77	23	the	the	DET
ejpam-2083	77	24	regression	regression	NOUN
ejpam-2083	77	25	parameters	parameter	NOUN
ejpam-2083	77	26	"	"	PUNCT
ejpam-2083	77	27	are	be	AUX
ejpam-2083	77	28	determined	determine	VERB
ejpam-2083	77	29	by	by	ADP
ejpam-2083	77	30	numerical	numerical	ADJ
ejpam-2083	77	31	optimization	optimization	NOUN
ejpam-2083	77	32	,	,	PUNCT
ejpam-2083	77	33	such	such	ADJ
ejpam-2083	77	34	as	as	ADP
ejpam-2083	77	35	in	in	ADP
ejpam-2083	77	36	newton	newton	PROPN
ejpam-2083	77	37	’s	’s	PART
ejpam-2083	77	38	method	method	NOUN
ejpam-2083	77	39	.	.	PUNCT
ejpam-2083	78	1	y	y	NOUN
ejpam-2083	78	2	=	=	SYM
ejpam-2083	79	1	1	1	NUM
ejpam-2083	79	2	1	1	NUM
ejpam-2083	79	3	+	+	NUM
ejpam-2083	79	4	e	e	NOUN
ejpam-2083	79	5	"	"	PUNCT
ejpam-2083	79	6	$	$	SYM
ejpam-2083	79	7	x	x	NOUN
ejpam-2083	79	8	"	"	PUNCT
ejpam-2083	79	9	(	(	PUNCT
ejpam-2083	79	10	3	3	X
ejpam-2083	79	11	)	)	PUNCT
ejpam-2083	79	12	we	we	PRON
ejpam-2083	79	13	use	use	VERB
ejpam-2083	79	14	logistic	logistic	ADJ
ejpam-2083	79	15	regression	regression	NOUN
ejpam-2083	79	16	to	to	PART
ejpam-2083	79	17	estimate	estimate	VERB
ejpam-2083	79	18	the	the	DET
ejpam-2083	79	19	hidden	hide	VERB
ejpam-2083	79	20	layer	layer	NOUN
ejpam-2083	79	21	weights	weight	VERB
ejpam-2083	79	22	wj	wj	PROPN
ejpam-2083	79	23	,	,	PUNCT
ejpam-2083	79	24	and	and	CCONJ
ejpam-2083	79	25	for	for	ADP
ejpam-2083	79	26	classification	classification	NOUN
ejpam-2083	79	27	o.	o.	NOUN
ejpam-2083	79	28	akbilgic	akbilgic	PROPN
ejpam-2083	79	29	/	/	SYM
ejpam-2083	79	30	eur	eur	PROPN
ejpam-2083	79	31	.	.	PUNCT
ejpam-2083	80	1	j.	j.	PROPN
ejpam-2083	80	2	pure	pure	PROPN
ejpam-2083	80	3	appl	appl	PROPN
ejpam-2083	80	4	.	.	PROPN
ejpam-2083	80	5	math	math	PROPN
ejpam-2083	80	6	,	,	PUNCT
ejpam-2083	80	7	6	6	NUM
ejpam-2083	80	8	(	(	PUNCT
ejpam-2083	80	9	2013	2013	NUM
ejpam-2083	80	10	)	)	PUNCT
ejpam-2083	80	11	,	,	PUNCT
ejpam-2083	80	12	377	377	NUM
ejpam-2083	80	13	-	-	SYM
ejpam-2083	80	14	386	386	NUM
ejpam-2083	80	15	381	381	NUM
ejpam-2083	80	16	in	in	ADP
ejpam-2083	80	17	the	the	DET
ejpam-2083	80	18	output	output	NOUN
ejpam-2083	80	19	layer	layer	NOUN
ejpam-2083	80	20	of	of	ADP
ejpam-2083	80	21	the	the	DET
ejpam-2083	80	22	rbf	rbf	PROPN
ejpam-2083	80	23	-	-	PUNCT
ejpam-2083	80	24	nn	nn	PROPN
ejpam-2083	80	25	frame	frame	NOUN
ejpam-2083	80	26	.	.	PUNCT
ejpam-2083	81	1	in	in	ADP
ejpam-2083	81	2	our	our	PRON
ejpam-2083	81	3	model	model	NOUN
ejpam-2083	81	4	,	,	PUNCT
ejpam-2083	81	5	the	the	DET
ejpam-2083	81	6	h	h	NOUN
ejpam-2083	81	7	matrix	matrix	NOUN
ejpam-2083	81	8	,	,	PUNCT
ejpam-2083	81	9	which	which	PRON
ejpam-2083	81	10	is	be	AUX
ejpam-2083	81	11	the	the	DET
ejpam-2083	81	12	nonlinear	nonlinear	ADJ
ejpam-2083	81	13	transformation	transformation	NOUN
ejpam-2083	81	14	of	of	ADP
ejpam-2083	81	15	predictors	predictor	NOUN
ejpam-2083	81	16	under	under	ADP
ejpam-2083	81	17	the	the	DET
ejpam-2083	81	18	rbf	rbf	PROPN
ejpam-2083	81	19	-	-	PUNCT
ejpam-2083	81	20	nn	nn	PROPN
ejpam-2083	81	21	frame	frame	NOUN
ejpam-2083	81	22	,	,	PUNCT
ejpam-2083	81	23	replaces	replace	VERB
ejpam-2083	81	24	x	x	PUNCT
ejpam-2083	81	25	in	in	ADP
ejpam-2083	81	26	(	(	PUNCT
ejpam-2083	81	27	3	3	NUM
ejpam-2083	81	28	)	)	PUNCT
ejpam-2083	81	29	.	.	PUNCT
ejpam-2083	82	1	hn#(m+1	hn#(m+1	VERB
ejpam-2083	82	2	)	)	PUNCT
ejpam-2083	83	1	=	=	SYM
ejpam-2083	83	2	%	%	NOUN
ejpam-2083	83	3	&	&	CCONJ
ejpam-2083	83	4	&	&	CCONJ
ejpam-2083	83	5	&	&	CCONJ
ejpam-2083	83	6	&	&	CCONJ
ejpam-2083	83	7	&	&	CCONJ
ejpam-2083	83	8	'	'	PART
ejpam-2083	83	9	1	1	NUM
ejpam-2083	83	10	w1h	w1h	NOUN
ejpam-2083	83	11	(	(	PUNCT
ejpam-2083	83	12	xi1"c1	xi1"c1	PROPN
ejpam-2083	83	13	r1	r1	PROPN
ejpam-2083	83	14	)	)	PUNCT
ejpam-2083	83	15	.	.	PUNCT
ejpam-2083	83	16	.	.	PUNCT
ejpam-2083	84	1	.	.	PUNCT
ejpam-2083	85	1	wmh	wmh	NOUN
ejpam-2083	85	2	(	(	PUNCT
ejpam-2083	85	3	xim"cm	xim"cm	PROPN
ejpam-2083	85	4	rm	rm	PROPN
ejpam-2083	85	5	)	)	PUNCT
ejpam-2083	85	6	1	1	NUM
ejpam-2083	85	7	w1h	w1h	NOUN
ejpam-2083	85	8	(	(	PUNCT
ejpam-2083	85	9	x21"c1	x21"c1	PROPN
ejpam-2083	85	10	r1	r1	PROPN
ejpam-2083	85	11	)	)	PUNCT
ejpam-2083	85	12	.	.	PUNCT
ejpam-2083	85	13	.	.	PUNCT
ejpam-2083	85	14	.	.	PUNCT
ejpam-2083	86	1	wmh	wmh	NOUN
ejpam-2083	86	2	(	(	PUNCT
ejpam-2083	86	3	x2m"cm	x2m"cm	PROPN
ejpam-2083	86	4	rm	rm	PROPN
ejpam-2083	86	5	)	)	PUNCT
ejpam-2083	86	6	...	...	PUNCT
ejpam-2083	87	1	1	1	NUM
ejpam-2083	87	2	w1h	w1h	NOUN
ejpam-2083	87	3	(	(	PUNCT
ejpam-2083	87	4	xn1"c1	xn1"c1	PROPN
ejpam-2083	87	5	r1	r1	PROPN
ejpam-2083	87	6	)	)	PUNCT
ejpam-2083	87	7	.	.	PUNCT
ejpam-2083	87	8	.	.	PUNCT
ejpam-2083	87	9	.	.	PUNCT
ejpam-2083	88	1	wmh	wmh	NOUN
ejpam-2083	88	2	(	(	PUNCT
ejpam-2083	88	3	xnm"cm	xnm"cm	PROPN
ejpam-2083	88	4	rm	rm	PROPN
ejpam-2083	88	5	)	)	PUNCT
ejpam-2083	88	6	(	(	PUNCT
ejpam-2083	88	7	)	)	PUNCT
ejpam-2083	88	8	)	)	PUNCT
ejpam-2083	88	9	)	)	PUNCT
ejpam-2083	88	10	)	)	PUNCT
ejpam-2083	88	11	)	)	PUNCT
ejpam-2083	89	1	*	*	PUNCT
ejpam-2083	89	2	(	(	PUNCT
ejpam-2083	89	3	4	4	NUM
ejpam-2083	89	4	)	)	PUNCT
ejpam-2083	89	5	2.4	2.4	NUM
ejpam-2083	89	6	.	.	PUNCT
ejpam-2083	90	1	proposed	propose	VERB
ejpam-2083	90	2	model	model	NOUN
ejpam-2083	90	3	:	:	PUNCT
ejpam-2083	90	4	data	data	NOUN
ejpam-2083	90	5	flow	flow	NOUN
ejpam-2083	90	6	algorithm	algorithm	NOUN
ejpam-2083	90	7	our	our	PRON
ejpam-2083	90	8	proposed	propose	VERB
ejpam-2083	90	9	method	method	NOUN
ejpam-2083	90	10	is	be	AUX
ejpam-2083	90	11	based	base	VERB
ejpam-2083	90	12	on	on	ADP
ejpam-2083	90	13	pre	pre	ADJ
ejpam-2083	90	14	-	-	ADJ
ejpam-2083	90	15	processing	processing	ADJ
ejpam-2083	90	16	data	datum	NOUN
ejpam-2083	90	17	by	by	ADP
ejpam-2083	90	18	using	use	VERB
ejpam-2083	90	19	classification	classification	NOUN
ejpam-2083	90	20	and	and	CCONJ
ejpam-2083	90	21	regression	regression	VERB
ejpam-2083	90	22	trees	tree	NOUN
ejpam-2083	90	23	before	before	ADP
ejpam-2083	90	24	applying	apply	VERB
ejpam-2083	90	25	logistic	logistic	ADJ
ejpam-2083	90	26	regression	regression	NOUN
ejpam-2083	90	27	in	in	ADP
ejpam-2083	90	28	the	the	DET
ejpam-2083	90	29	rbf	rbf	PROPN
ejpam-2083	90	30	-	-	PUNCT
ejpam-2083	90	31	nn	nn	PROPN
ejpam-2083	90	32	frame	frame	NOUN
ejpam-2083	90	33	.	.	PUNCT
ejpam-2083	91	1	the	the	DET
ejpam-2083	91	2	data	data	NOUN
ejpam-2083	91	3	flow	flow	NOUN
ejpam-2083	91	4	of	of	ADP
ejpam-2083	91	5	proposed	propose	VERB
ejpam-2083	91	6	method	method	NOUN
ejpam-2083	91	7	is	be	AUX
ejpam-2083	91	8	explained	explain	VERB
ejpam-2083	91	9	step	step	NOUN
ejpam-2083	91	10	by	by	ADP
ejpam-2083	91	11	step	step	NOUN
ejpam-2083	91	12	.	.	PUNCT
ejpam-2083	92	1	note	note	VERB
ejpam-2083	92	2	that	that	SCONJ
ejpam-2083	92	3	there	there	PRON
ejpam-2083	92	4	are	be	VERB
ejpam-2083	92	5	two	two	NUM
ejpam-2083	92	6	conditional	conditional	ADJ
ejpam-2083	92	7	steps	step	NOUN
ejpam-2083	92	8	depending	depend	VERB
ejpam-2083	92	9	on	on	ADP
ejpam-2083	92	10	the	the	DET
ejpam-2083	92	11	problem	problem	NOUN
ejpam-2083	92	12	specifications	specification	NOUN
ejpam-2083	92	13	.	.	PUNCT
ejpam-2083	93	1	step	step	NOUN
ejpam-2083	93	2	1	1	NUM
ejpam-2083	93	3	use	use	VERB
ejpam-2083	93	4	cart	cart	NOUN
ejpam-2083	93	5	to	to	PART
ejpam-2083	93	6	split	split	VERB
ejpam-2083	93	7	the	the	DET
ejpam-2083	93	8	original	original	ADJ
ejpam-2083	93	9	p	p	ADJ
ejpam-2083	93	10	-	-	PUNCT
ejpam-2083	93	11	dimensional	dimensional	ADJ
ejpam-2083	93	12	input	input	NOUN
ejpam-2083	93	13	space	space	NOUN
ejpam-2083	93	14	into	into	ADP
ejpam-2083	93	15	m	m	PROPN
ejpam-2083	93	16	hyper	hyper	NOUN
ejpam-2083	93	17	-	-	NOUN
ejpam-2083	93	18	rectangles	rectangle	NOUN
ejpam-2083	93	19	.	.	PUNCT
ejpam-2083	94	1	step	step	NOUN
ejpam-2083	94	2	2	2	NUM
ejpam-2083	94	3	(	(	PUNCT
ejpam-2083	94	4	conditional	conditional	ADJ
ejpam-2083	94	5	)	)	PUNCT
ejpam-2083	94	6	if	if	SCONJ
ejpam-2083	94	7	n	n	PRON
ejpam-2083	94	8	<	<	X
ejpam-2083	94	9	p	p	X
ejpam-2083	94	10	and/or	and/or	CCONJ
ejpam-2083	94	11	n	n	CCONJ
ejpam-2083	94	12	<	<	X
ejpam-2083	94	13	m	m	PROPN
ejpam-2083	94	14	,	,	PUNCT
ejpam-2083	94	15	prune	prune	VERB
ejpam-2083	94	16	the	the	DET
ejpam-2083	94	17	tree	tree	NOUN
ejpam-2083	94	18	until	until	SCONJ
ejpam-2083	94	19	m	m	PROPN
ejpam-2083	94	20	is	be	AUX
ejpam-2083	94	21	small	small	ADJ
ejpam-2083	94	22	enough	enough	ADV
ejpam-2083	94	23	to	to	PART
ejpam-2083	94	24	avoid	avoid	VERB
ejpam-2083	94	25	a	a	DET
ejpam-2083	94	26	design	design	NOUN
ejpam-2083	94	27	matrix	matrix	NOUN
ejpam-2083	94	28	that	that	PRON
ejpam-2083	94	29	is	be	AUX
ejpam-2083	94	30	rank	rank	NOUN
ejpam-2083	94	31	deficient	deficient	ADJ
ejpam-2083	94	32	.	.	PUNCT
ejpam-2083	95	1	step	step	NOUN
ejpam-2083	95	2	3	3	NUM
ejpam-2083	95	3	from	from	ADP
ejpam-2083	95	4	each	each	DET
ejpam-2083	95	5	terminal	terminal	ADJ
ejpam-2083	95	6	node	node	NOUN
ejpam-2083	95	7	,	,	PUNCT
ejpam-2083	95	8	compute	compute	PROPN
ejpam-2083	95	9	c	c	PROPN
ejpam-2083	95	10	j	j	PROPN
ejpam-2083	95	11	and	and	CCONJ
ejpam-2083	95	12	r	r	PROPN
ejpam-2083	95	13	j	j	PROPN
ejpam-2083	96	1	=	=	PUNCT
ejpam-2083	96	2	!	!	PUNCT
ejpam-2083	96	3	s	s	PROPN
ejpam-2083	96	4	j	j	PROPN
ejpam-2083	96	5	,	,	PUNCT
ejpam-2083	96	6	and	and	CCONJ
ejpam-2083	96	7	place	place	VERB
ejpam-2083	96	8	them	they	PRON
ejpam-2083	96	9	in	in	ADP
ejpam-2083	96	10	the	the	DET
ejpam-2083	96	11	m	m	PROPN
ejpam-2083	96	12	neurons	neuron	NOUN
ejpam-2083	96	13	of	of	ADP
ejpam-2083	96	14	the	the	DET
ejpam-2083	96	15	rbf	rbf	PROPN
ejpam-2083	96	16	hidden	hide	VERB
ejpam-2083	96	17	layer	layer	NOUN
ejpam-2083	96	18	.	.	PUNCT
ejpam-2083	97	1	step	step	NOUN
ejpam-2083	97	2	4	4	NUM
ejpam-2083	97	3	with	with	ADP
ejpam-2083	97	4	the	the	DET
ejpam-2083	97	5	weights	weight	NOUN
ejpam-2083	97	6	initialized	initialize	VERB
ejpam-2083	97	7	to	to	ADP
ejpam-2083	97	8	1	1	NUM
ejpam-2083	97	9	,	,	PUNCT
ejpam-2083	97	10	transform	transform	VERB
ejpam-2083	97	11	the	the	DET
ejpam-2083	97	12	original	original	ADJ
ejpam-2083	97	13	n	n	CCONJ
ejpam-2083	97	14	#	#	NOUN
ejpam-2083	97	15	p	p	NOUN
ejpam-2083	97	16	matrix	matrix	NOUN
ejpam-2083	97	17	x	x	PUNCT
ejpam-2083	97	18	to	to	ADP
ejpam-2083	97	19	the	the	DET
ejpam-2083	97	20	n#m	n#m	ADJ
ejpam-2083	97	21	matrix	matrix	NOUN
ejpam-2083	97	22	h	h	NOUN
ejpam-2083	97	23	using	use	VERB
ejpam-2083	97	24	the	the	DET
ejpam-2083	97	25	parameterized	parameterized	ADJ
ejpam-2083	97	26	radial	radial	ADJ
ejpam-2083	97	27	basis	basis	NOUN
ejpam-2083	97	28	functions	function	NOUN
ejpam-2083	97	29	.	.	PUNCT
ejpam-2083	98	1	step	step	NOUN
ejpam-2083	98	2	5	5	NUM
ejpam-2083	98	3	using	use	VERB
ejpam-2083	98	4	the	the	DET
ejpam-2083	98	5	initial	initial	ADJ
ejpam-2083	98	6	h	h	NOUN
ejpam-2083	98	7	matrix	matrix	NOUN
ejpam-2083	98	8	and	and	CCONJ
ejpam-2083	98	9	the	the	DET
ejpam-2083	98	10	original	original	ADJ
ejpam-2083	98	11	n	n	NOUN
ejpam-2083	98	12	#	#	NOUN
ejpam-2083	98	13	1	1	NUM
ejpam-2083	98	14	matrix	matrix	NOUN
ejpam-2083	98	15	of	of	ADP
ejpam-2083	98	16	binary	binary	ADJ
ejpam-2083	98	17	class	class	NOUN
ejpam-2083	98	18	labels	label	NOUN
ejpam-2083	98	19	,	,	PUNCT
ejpam-2083	98	20	y	y	PROPN
ejpam-2083	98	21	,	,	PUNCT
ejpam-2083	98	22	perform	perform	VERB
ejpam-2083	98	23	logistic	logistic	ADJ
ejpam-2083	98	24	regression	regression	NOUN
ejpam-2083	98	25	to	to	PART
ejpam-2083	98	26	estimate	estimate	VERB
ejpam-2083	98	27	the	the	DET
ejpam-2083	98	28	optimal	optimal	ADJ
ejpam-2083	98	29	weight	weight	NOUN
ejpam-2083	98	30	parameters	parameter	NOUN
ejpam-2083	98	31	,	,	PUNCT
ejpam-2083	98	32	wj	wj	X
ejpam-2083	98	33	.	.	PUNCT
ejpam-2083	99	1	step	step	NOUN
ejpam-2083	99	2	6	6	NUM
ejpam-2083	99	3	(	(	PUNCT
ejpam-2083	99	4	conditional	conditional	ADJ
ejpam-2083	99	5	)	)	PUNCT
ejpam-2083	99	6	use	use	NOUN
ejpam-2083	99	7	stepwise	stepwise	ADJ
ejpam-2083	99	8	logistic	logistic	ADJ
ejpam-2083	99	9	regression	regression	NOUN
ejpam-2083	99	10	to	to	PART
ejpam-2083	99	11	avoid	avoid	VERB
ejpam-2083	99	12	singularity	singularity	NOUN
ejpam-2083	99	13	of	of	ADP
ejpam-2083	99	14	the	the	DET
ejpam-2083	99	15	design	design	NOUN
ejpam-2083	99	16	matrix	matrix	NOUN
ejpam-2083	99	17	and	and	CCONJ
ejpam-2083	99	18	to	to	PART
ejpam-2083	99	19	avoid	avoid	VERB
ejpam-2083	99	20	over	over	ADP
ejpam-2083	99	21	fitting	fitting	ADJ
ejpam-2083	99	22	.	.	PUNCT
ejpam-2083	100	1	step	step	NOUN
ejpam-2083	100	2	7	7	NUM
ejpam-2083	100	3	obtain	obtain	VERB
ejpam-2083	100	4	the	the	DET
ejpam-2083	100	5	final	final	ADJ
ejpam-2083	100	6	classifier	classifier	NOUN
ejpam-2083	100	7	ŷ	ŷ	NUM
ejpam-2083	100	8	by	by	ADP
ejpam-2083	100	9	combining	combine	VERB
ejpam-2083	100	10	(	(	PUNCT
ejpam-2083	100	11	3	3	NUM
ejpam-2083	100	12	)	)	PUNCT
ejpam-2083	100	13	and	and	CCONJ
ejpam-2083	100	14	(	(	PUNCT
ejpam-2083	100	15	4	4	NUM
ejpam-2083	100	16	)	)	PUNCT
ejpam-2083	100	17	,	,	PUNCT
ejpam-2083	100	18	with	with	ADP
ejpam-2083	100	19	the	the	DET
ejpam-2083	100	20	weights	weight	NOUN
ejpam-2083	100	21	from	from	ADP
ejpam-2083	100	22	step	step	NOUN
ejpam-2083	100	23	5	5	NUM
ejpam-2083	100	24	.	.	PUNCT
ejpam-2083	101	1	following	follow	VERB
ejpam-2083	101	2	the	the	DET
ejpam-2083	101	3	given	give	VERB
ejpam-2083	101	4	steps	step	NOUN
ejpam-2083	101	5	of	of	ADP
ejpam-2083	101	6	the	the	DET
ejpam-2083	101	7	proposed	propose	VERB
ejpam-2083	101	8	model	model	NOUN
ejpam-2083	101	9	,	,	PUNCT
ejpam-2083	101	10	the	the	DET
ejpam-2083	101	11	final	final	ADJ
ejpam-2083	101	12	output	output	NOUN
ejpam-2083	101	13	of	of	ADP
ejpam-2083	101	14	the	the	DET
ejpam-2083	101	15	model	model	NOUN
ejpam-2083	101	16	is	be	AUX
ejpam-2083	101	17	given	give	VERB
ejpam-2083	101	18	by	by	ADP
ejpam-2083	101	19	(	(	PUNCT
ejpam-2083	101	20	5	5	NUM
ejpam-2083	101	21	)	)	PUNCT
ejpam-2083	101	22	.	.	PUNCT
ejpam-2083	102	1	y	y	NOUN
ejpam-2083	102	2	=	=	SYM
ejpam-2083	103	1	1	1	NUM
ejpam-2083	103	2	1	1	NUM
ejpam-2083	103	3	+	+	NUM
ejpam-2083	103	4	e	e	NOUN
ejpam-2083	103	5	"	"	PUNCT
ejpam-2083	103	6	m	m	VERB
ejpam-2083	103	7	$	$	SYM
ejpam-2083	103	8	j=0	j=0	PROPN
ejpam-2083	103	9	h(x;c	h(x;c	NOUN
ejpam-2083	103	10	,	,	PUNCT
ejpam-2083	103	11	r)w	r)w	NOUN
ejpam-2083	103	12	(	(	PUNCT
ejpam-2083	103	13	5	5	NUM
ejpam-2083	103	14	)	)	PUNCT
ejpam-2083	103	15	as	as	SCONJ
ejpam-2083	103	16	can	can	AUX
ejpam-2083	103	17	be	be	AUX
ejpam-2083	103	18	seen	see	VERB
ejpam-2083	103	19	from	from	ADP
ejpam-2083	103	20	the	the	DET
ejpam-2083	103	21	steps	step	NOUN
ejpam-2083	103	22	of	of	ADP
ejpam-2083	103	23	the	the	DET
ejpam-2083	103	24	proposed	propose	VERB
ejpam-2083	103	25	method	method	NOUN
ejpam-2083	103	26	,	,	PUNCT
ejpam-2083	103	27	our	our	PRON
ejpam-2083	103	28	model	model	NOUN
ejpam-2083	103	29	gives	give	VERB
ejpam-2083	103	30	us	we	PRON
ejpam-2083	103	31	options	option	NOUN
ejpam-2083	103	32	to	to	PART
ejpam-2083	103	33	solve	solve	VERB
ejpam-2083	103	34	n	n	CCONJ
ejpam-2083	103	35	<	<	X
ejpam-2083	103	36	p	p	ADJ
ejpam-2083	103	37	classification	classification	NOUN
ejpam-2083	103	38	problems	problem	NOUN
ejpam-2083	103	39	that	that	PRON
ejpam-2083	103	40	is	be	AUX
ejpam-2083	103	41	one	one	NUM
ejpam-2083	103	42	of	of	ADP
ejpam-2083	103	43	the	the	DET
ejpam-2083	103	44	popular	popular	ADJ
ejpam-2083	103	45	and	and	CCONJ
ejpam-2083	103	46	most	most	ADV
ejpam-2083	103	47	difficult	difficult	ADJ
ejpam-2083	103	48	problems	problem	NOUN
ejpam-2083	103	49	in	in	ADP
ejpam-2083	103	50	statistics	statistic	NOUN
ejpam-2083	103	51	and	and	CCONJ
ejpam-2083	103	52	machine	machine	NOUN
ejpam-2083	103	53	learning	learning	NOUN
ejpam-2083	103	54	.	.	PUNCT
ejpam-2083	104	1	applications	application	NOUN
ejpam-2083	104	2	of	of	ADP
ejpam-2083	104	3	our	our	PRON
ejpam-2083	104	4	models	model	NOUN
ejpam-2083	104	5	on	on	ADP
ejpam-2083	104	6	simulated	simulate	VERB
ejpam-2083	104	7	and	and	CCONJ
ejpam-2083	104	8	real	real	ADJ
ejpam-2083	104	9	data	datum	NOUN
ejpam-2083	104	10	are	be	AUX
ejpam-2083	104	11	documented	document	VERB
ejpam-2083	104	12	in	in	ADP
ejpam-2083	104	13	the	the	DET
ejpam-2083	104	14	following	follow	VERB
ejpam-2083	104	15	section	section	NOUN
ejpam-2083	104	16	.	.	PUNCT
ejpam-2083	105	1	o.	o.	PROPN
ejpam-2083	105	2	akbilgic	akbilgic	PROPN
ejpam-2083	105	3	/	/	SYM
ejpam-2083	105	4	eur	eur	PROPN
ejpam-2083	105	5	.	.	PUNCT
ejpam-2083	106	1	j.	j.	PROPN
ejpam-2083	106	2	pure	pure	PROPN
ejpam-2083	106	3	appl	appl	PROPN
ejpam-2083	106	4	.	.	PROPN
ejpam-2083	106	5	math	math	PROPN
ejpam-2083	106	6	,	,	PUNCT
ejpam-2083	106	7	6	6	NUM
ejpam-2083	106	8	(	(	PUNCT
ejpam-2083	106	9	2013	2013	NUM
ejpam-2083	106	10	)	)	PUNCT
ejpam-2083	106	11	,	,	PUNCT
ejpam-2083	106	12	377	377	NUM
ejpam-2083	106	13	-	-	SYM
ejpam-2083	106	14	386	386	NUM
ejpam-2083	106	15	382	382	NUM
ejpam-2083	106	16	3	3	NUM
ejpam-2083	106	17	.	.	PUNCT
ejpam-2083	107	1	applications	application	NOUN
ejpam-2083	107	2	in	in	ADP
ejpam-2083	107	3	this	this	DET
ejpam-2083	107	4	section	section	NOUN
ejpam-2083	107	5	we	we	PRON
ejpam-2083	107	6	first	first	ADV
ejpam-2083	107	7	apply	apply	VERB
ejpam-2083	107	8	our	our	PRON
ejpam-2083	107	9	method	method	NOUN
ejpam-2083	107	10	on	on	ADP
ejpam-2083	107	11	simulated	simulated	ADJ
ejpam-2083	107	12	data	datum	NOUN
ejpam-2083	107	13	in	in	ADP
ejpam-2083	107	14	order	order	NOUN
ejpam-2083	107	15	to	to	PART
ejpam-2083	107	16	show	show	VERB
ejpam-2083	107	17	the	the	DET
ejpam-2083	107	18	generalization	generalization	NOUN
ejpam-2083	107	19	performance	performance	NOUN
ejpam-2083	107	20	of	of	ADP
ejpam-2083	107	21	the	the	DET
ejpam-2083	107	22	proposed	propose	VERB
ejpam-2083	107	23	method	method	NOUN
ejpam-2083	107	24	.	.	PUNCT
ejpam-2083	108	1	we	we	PRON
ejpam-2083	108	2	compare	compare	VERB
ejpam-2083	108	3	our	our	PRON
ejpam-2083	108	4	results	result	NOUN
ejpam-2083	108	5	with	with	ADP
ejpam-2083	108	6	classical	classical	ADJ
ejpam-2083	108	7	logistic	logistic	ADJ
ejpam-2083	108	8	regression	regression	NOUN
ejpam-2083	108	9	.	.	PUNCT
ejpam-2083	109	1	after	after	ADP
ejpam-2083	109	2	showing	show	VERB
ejpam-2083	109	3	the	the	DET
ejpam-2083	109	4	generalization	generalization	NOUN
ejpam-2083	109	5	performance	performance	NOUN
ejpam-2083	109	6	of	of	ADP
ejpam-2083	109	7	our	our	PRON
ejpam-2083	109	8	method	method	NOUN
ejpam-2083	109	9	,	,	PUNCT
ejpam-2083	109	10	we	we	PRON
ejpam-2083	109	11	applied	apply	VERB
ejpam-2083	109	12	it	it	PRON
ejpam-2083	109	13	using	use	VERB
ejpam-2083	109	14	real	real	ADJ
ejpam-2083	109	15	data	datum	NOUN
ejpam-2083	109	16	.	.	PUNCT
ejpam-2083	110	1	all	all	DET
ejpam-2083	110	2	calculations	calculation	NOUN
ejpam-2083	110	3	for	for	ADP
ejpam-2083	110	4	the	the	DET
ejpam-2083	110	5	proposed	propose	VERB
ejpam-2083	110	6	model	model	NOUN
ejpam-2083	110	7	are	be	AUX
ejpam-2083	110	8	carried	carry	VERB
ejpam-2083	110	9	out	out	ADP
ejpam-2083	110	10	using	use	VERB
ejpam-2083	110	11	r	r	NOUN
ejpam-2083	110	12	[	[	NOUN
ejpam-2083	110	13	8	8	NUM
ejpam-2083	110	14	]	]	PUNCT
ejpam-2083	110	15	while	while	SCONJ
ejpam-2083	110	16	for	for	ADP
ejpam-2083	110	17	the	the	DET
ejpam-2083	110	18	logistic	logistic	ADJ
ejpam-2083	110	19	regression	regression	NOUN
ejpam-2083	110	20	,	,	PUNCT
ejpam-2083	110	21	spss	spss	PROPN
ejpam-2083	110	22	20	20	NUM
ejpam-2083	110	23	is	be	AUX
ejpam-2083	110	24	used	use	VERB
ejpam-2083	110	25	.	.	PUNCT
ejpam-2083	111	1	3.1	3.1	NUM
ejpam-2083	111	2	.	.	PUNCT
ejpam-2083	111	3	application	application	NOUN
ejpam-2083	111	4	of	of	ADP
ejpam-2083	111	5	proposed	propose	VERB
ejpam-2083	111	6	method	method	NOUN
ejpam-2083	111	7	on	on	ADP
ejpam-2083	111	8	simulated	simulated	ADJ
ejpam-2083	111	9	data	datum	NOUN
ejpam-2083	111	10	we	we	PRON
ejpam-2083	111	11	aimed	aim	VERB
ejpam-2083	111	12	to	to	PART
ejpam-2083	111	13	explore	explore	VERB
ejpam-2083	111	14	the	the	DET
ejpam-2083	111	15	generalization	generalization	NOUN
ejpam-2083	111	16	performance	performance	NOUN
ejpam-2083	111	17	of	of	ADP
ejpam-2083	111	18	our	our	PRON
ejpam-2083	111	19	proposed	propose	VERB
ejpam-2083	111	20	method	method	NOUN
ejpam-2083	111	21	on	on	ADP
ejpam-2083	111	22	simulated	simulated	ADJ
ejpam-2083	111	23	data	datum	NOUN
ejpam-2083	111	24	.	.	PUNCT
ejpam-2083	112	1	simulation	simulation	NOUN
ejpam-2083	112	2	data	data	PROPN
ejpam-2083	112	3	included	include	VERB
ejpam-2083	112	4	a	a	DET
ejpam-2083	112	5	mixture	mixture	NOUN
ejpam-2083	112	6	of	of	ADP
ejpam-2083	112	7	two	two	NUM
ejpam-2083	112	8	bivariate	bivariate	ADJ
ejpam-2083	112	9	normal	normal	ADJ
ejpam-2083	112	10	distribution	distribution	NOUN
ejpam-2083	112	11	,	,	PUNCT
ejpam-2083	112	12	n(µ	n(µ	VERB
ejpam-2083	112	13	,	,	PUNCT
ejpam-2083	112	14	!	!	PUNCT
ejpam-2083	112	15	)	)	PUNCT
ejpam-2083	112	16	,	,	PUNCT
ejpam-2083	112	17	which	which	PRON
ejpam-2083	112	18	are	be	AUX
ejpam-2083	112	19	highly	highly	ADV
ejpam-2083	112	20	overlapped	overlapped	ADJ
ejpam-2083	112	21	as	as	SCONJ
ejpam-2083	112	22	it	it	PRON
ejpam-2083	112	23	is	be	AUX
ejpam-2083	112	24	seen	see	VERB
ejpam-2083	112	25	in	in	ADP
ejpam-2083	112	26	figure	figure	NOUN
ejpam-2083	112	27	3	3	NUM
ejpam-2083	112	28	.	.	PUNCT
ejpam-2083	113	1	the	the	DET
ejpam-2083	113	2	number	number	NOUN
ejpam-2083	113	3	of	of	ADP
ejpam-2083	113	4	observations	observation	NOUN
ejpam-2083	113	5	of	of	ADP
ejpam-2083	113	6	each	each	DET
ejpam-2083	113	7	group	group	NOUN
ejpam-2083	113	8	are	be	AUX
ejpam-2083	113	9	specified	specify	VERB
ejpam-2083	113	10	as	as	ADP
ejpam-2083	113	11	250	250	NUM
ejpam-2083	113	12	each	each	PRON
ejpam-2083	113	13	,	,	PUNCT
ejpam-2083	113	14	and	and	CCONJ
ejpam-2083	113	15	parameters	parameter	NOUN
ejpam-2083	113	16	of	of	ADP
ejpam-2083	113	17	the	the	DET
ejpam-2083	113	18	distributions	distribution	NOUN
ejpam-2083	113	19	for	for	ADP
ejpam-2083	113	20	each	each	DET
ejpam-2083	113	21	group	group	NOUN
ejpam-2083	113	22	are	be	AUX
ejpam-2083	113	23	defined	define	VERB
ejpam-2083	113	24	below	below	ADV
ejpam-2083	113	25	.	.	PUNCT
ejpam-2083	114	1	we	we	PRON
ejpam-2083	114	2	ran	run	VERB
ejpam-2083	114	3	our	our	PRON
ejpam-2083	114	4	model	model	NOUN
ejpam-2083	114	5	for	for	ADP
ejpam-2083	114	6	generated	generate	VERB
ejpam-2083	114	7	data	datum	NOUN
ejpam-2083	114	8	by	by	ADP
ejpam-2083	114	9	chancing	chance	VERB
ejpam-2083	114	10	the	the	DET
ejpam-2083	114	11	!	!	PUNCT
ejpam-2083	114	12	parameter	parameter	NOUN
ejpam-2083	114	13	from	from	ADP
ejpam-2083	114	14	the	the	DET
ejpam-2083	114	15	set	set	NOUN
ejpam-2083	114	16	{	{	PUNCT
ejpam-2083	114	17	.15	.15	NUM
ejpam-2083	114	18	,	,	PUNCT
ejpam-2083	114	19	.20	.20	NUM
ejpam-2083	114	20	,	,	PUNCT
ejpam-2083	114	21	.25	.25	NUM
ejpam-2083	114	22	,	,	PUNCT
ejpam-2083	114	23	.	.	PUNCT
ejpam-2083	114	24	.	.	PUNCT
ejpam-2083	115	1	.	.	PUNCT
ejpam-2083	116	1	,	,	PUNCT
ejpam-2083	116	2	2.5	2.5	NUM
ejpam-2083	116	3	}	}	PUNCT
ejpam-2083	116	4	.	.	PUNCT
ejpam-2083	117	1	we	we	PRON
ejpam-2083	117	2	find	find	VERB
ejpam-2083	117	3	best	good	ADJ
ejpam-2083	117	4	!	!	PUNCT
ejpam-2083	118	1	parameter	parameter	NOUN
ejpam-2083	118	2	as	as	ADP
ejpam-2083	118	3	alpha	alpha	NOUN
ejpam-2083	118	4	=	=	NOUN
ejpam-2083	118	5	0.9	0.9	NUM
ejpam-2083	118	6	giving	give	VERB
ejpam-2083	118	7	the	the	DET
ejpam-2083	118	8	highest	high	ADJ
ejpam-2083	118	9	classification	classification	NOUN
ejpam-2083	118	10	accuracy	accuracy	NOUN
ejpam-2083	118	11	.	.	PUNCT
ejpam-2083	119	1	the	the	DET
ejpam-2083	119	2	confusion	confusion	NOUN
ejpam-2083	119	3	matrix	matrix	NOUN
ejpam-2083	119	4	obtained	obtain	VERB
ejpam-2083	119	5	for	for	ADP
ejpam-2083	119	6	alpha	alpha	NOUN
ejpam-2083	119	7	=	=	SYM
ejpam-2083	119	8	0.9	0.9	NUM
ejpam-2083	119	9	is	be	AUX
ejpam-2083	119	10	shown	show	VERB
ejpam-2083	119	11	in	in	ADP
ejpam-2083	119	12	table	table	NOUN
ejpam-2083	120	1	1	1	NUM
ejpam-2083	120	2	.	.	PUNCT
ejpam-2083	120	3	µ1	µ1	PROPN
ejpam-2083	120	4	=	=	SYM
ejpam-2083	120	5	+	+	CCONJ
ejpam-2083	120	6	2.0	2.0	NUM
ejpam-2083	120	7	1.0	1.0	NUM
ejpam-2083	120	8	,	,	PUNCT
ejpam-2083	120	9	!	!	PUNCT
ejpam-2083	120	10	1	1	X
ejpam-2083	121	1	=	=	SYM
ejpam-2083	121	2	+	+	NUM
ejpam-2083	121	3	1.2	1.2	NUM
ejpam-2083	121	4	0.1	0.1	NUM
ejpam-2083	121	5	0.1	0.1	NUM
ejpam-2083	121	6	0.25	0.25	NUM
ejpam-2083	121	7	,	,	PUNCT
ejpam-2083	121	8	,	,	PUNCT
ejpam-2083	121	9	µ2	µ2	PROPN
ejpam-2083	121	10	=	=	PUNCT
ejpam-2083	121	11	+	+	CCONJ
ejpam-2083	121	12	3.0	3.0	NUM
ejpam-2083	121	13	2.0	2.0	NUM
ejpam-2083	121	14	,	,	PUNCT
ejpam-2083	121	15	!	!	PUNCT
ejpam-2083	122	1	2	2	X
ejpam-2083	123	1	=	=	SYM
ejpam-2083	123	2	+	+	CCONJ
ejpam-2083	123	3	0.5	0.5	NUM
ejpam-2083	123	4	"	"	PUNCT
ejpam-2083	123	5	0.1	0.1	NUM
ejpam-2083	123	6	"	"	PUNCT
ejpam-2083	123	7	0.1	0.1	NUM
ejpam-2083	123	8	0.3	0.3	NUM
ejpam-2083	123	9	,	,	PUNCT
ejpam-2083	123	10	figure	figure	VERB
ejpam-2083	123	11	3	3	NUM
ejpam-2083	123	12	:	:	PUNCT
ejpam-2083	123	13	highly	highly	ADV
ejpam-2083	123	14	overlapped	overlapped	ADJ
ejpam-2083	123	15	structure	structure	NOUN
ejpam-2083	123	16	of	of	ADP
ejpam-2083	123	17	simulated	simulated	ADJ
ejpam-2083	123	18	data	datum	NOUN
ejpam-2083	123	19	.	.	PUNCT
ejpam-2083	124	1	o.	o.	PROPN
ejpam-2083	124	2	akbilgic	akbilgic	PROPN
ejpam-2083	124	3	/	/	SYM
ejpam-2083	124	4	eur	eur	PROPN
ejpam-2083	124	5	.	.	PUNCT
ejpam-2083	125	1	j.	j.	PROPN
ejpam-2083	125	2	pure	pure	PROPN
ejpam-2083	125	3	appl	appl	PROPN
ejpam-2083	125	4	.	.	PROPN
ejpam-2083	125	5	math	math	PROPN
ejpam-2083	125	6	,	,	PUNCT
ejpam-2083	125	7	6	6	NUM
ejpam-2083	125	8	(	(	PUNCT
ejpam-2083	125	9	2013	2013	NUM
ejpam-2083	125	10	)	)	PUNCT
ejpam-2083	125	11	,	,	PUNCT
ejpam-2083	125	12	377	377	NUM
ejpam-2083	125	13	-	-	SYM
ejpam-2083	125	14	386	386	NUM
ejpam-2083	125	15	383	383	NUM
ejpam-2083	125	16	table	table	NOUN
ejpam-2083	125	17	1	1	NUM
ejpam-2083	125	18	:	:	PUNCT
ejpam-2083	125	19	confusion	confusion	NOUN
ejpam-2083	125	20	matrix	matrix	NOUN
ejpam-2083	125	21	for	for	ADP
ejpam-2083	125	22	log	log	NOUN
ejpam-2083	125	23	-	-	PUNCT
ejpam-2083	125	24	rbf	rbf	PROPN
ejpam-2083	125	25	-	-	PUNCT
ejpam-2083	125	26	nn	nn	PROPN
ejpam-2083	125	27	model	model	NOUN
ejpam-2083	125	28	group	group	NOUN
ejpam-2083	125	29	label	label	NOUN
ejpam-2083	125	30	0	0	NUM
ejpam-2083	125	31	1	1	NUM
ejpam-2083	125	32	total	total	NOUN
ejpam-2083	125	33	accuracy	accuracy	NOUN
ejpam-2083	125	34	0	0	NUM
ejpam-2083	125	35	219	219	NUM
ejpam-2083	125	36	31	31	NUM
ejpam-2083	125	37	250	250	NUM
ejpam-2083	125	38	87.60	87.60	NUM
ejpam-2083	125	39	%	%	NOUN
ejpam-2083	125	40	1	1	NUM
ejpam-2083	125	41	18	18	NUM
ejpam-2083	125	42	232	232	NUM
ejpam-2083	125	43	250	250	NUM
ejpam-2083	125	44	92.80	92.80	NUM
ejpam-2083	125	45	%	%	NOUN
ejpam-2083	125	46	total	total	ADJ
ejpam-2083	125	47	500	500	NUM
ejpam-2083	125	48	90.20	90.20	NUM
ejpam-2083	125	49	%	%	NOUN
ejpam-2083	125	50	table	table	NOUN
ejpam-2083	125	51	2	2	NUM
ejpam-2083	125	52	:	:	PUNCT
ejpam-2083	125	53	confusion	confusion	NOUN
ejpam-2083	125	54	matrix	matrix	NOUN
ejpam-2083	125	55	for	for	ADP
ejpam-2083	125	56	logistic	logistic	ADJ
ejpam-2083	125	57	regression	regression	NOUN
ejpam-2083	125	58	group	group	NOUN
ejpam-2083	125	59	label	label	NOUN
ejpam-2083	125	60	0	0	NUM
ejpam-2083	125	61	1	1	NUM
ejpam-2083	125	62	total	total	NOUN
ejpam-2083	125	63	accuracy	accuracy	NOUN
ejpam-2083	125	64	0	0	NUM
ejpam-2083	125	65	215	215	NUM
ejpam-2083	125	66	35	35	NUM
ejpam-2083	125	67	250	250	NUM
ejpam-2083	125	68	86.00	86.00	NUM
ejpam-2083	125	69	%	%	NOUN
ejpam-2083	125	70	1	1	NUM
ejpam-2083	125	71	26	26	NUM
ejpam-2083	125	72	224	224	NUM
ejpam-2083	125	73	250	250	NUM
ejpam-2083	125	74	89.60	89.60	NUM
ejpam-2083	125	75	%	%	NOUN
ejpam-2083	125	76	total	total	NOUN
ejpam-2083	125	77	500	500	NUM
ejpam-2083	125	78	87.80	87.80	NUM
ejpam-2083	125	79	%	%	NOUN
ejpam-2083	125	80	table	table	NOUN
ejpam-2083	125	81	3	3	NUM
ejpam-2083	125	82	:	:	PUNCT
ejpam-2083	125	83	confusion	confusion	NOUN
ejpam-2083	125	84	matrix	matrix	NOUN
ejpam-2083	125	85	for	for	ADP
ejpam-2083	125	86	train	train	NOUN
ejpam-2083	125	87	data	datum	NOUN
ejpam-2083	125	88	group	group	NOUN
ejpam-2083	125	89	label	label	NOUN
ejpam-2083	125	90	0	0	NUM
ejpam-2083	125	91	1	1	NUM
ejpam-2083	125	92	total	total	NOUN
ejpam-2083	125	93	accuracy	accuracy	NOUN
ejpam-2083	125	94	0	0	NUM
ejpam-2083	125	95	174.33	174.33	NUM
ejpam-2083	125	96	25.61	25.61	NUM
ejpam-2083	125	97	199.94	199.94	NUM
ejpam-2083	125	98	87.19	87.19	NUM
ejpam-2083	125	99	%	%	NOUN
ejpam-2083	125	100	1	1	NUM
ejpam-2083	125	101	15.85	15.85	NUM
ejpam-2083	125	102	184.21	184.21	NUM
ejpam-2083	125	103	200.06	200.06	NUM
ejpam-2083	125	104	92.07	92.07	NUM
ejpam-2083	125	105	%	%	NOUN
ejpam-2083	125	106	total	total	NOUN
ejpam-2083	125	107	400.00	400.00	NUM
ejpam-2083	125	108	89.64	89.64	NUM
ejpam-2083	125	109	%	%	NOUN
ejpam-2083	125	110	table	table	NOUN
ejpam-2083	125	111	4	4	NUM
ejpam-2083	125	112	:	:	PUNCT
ejpam-2083	125	113	confusion	confusion	NOUN
ejpam-2083	125	114	matrix	matrix	NOUN
ejpam-2083	125	115	for	for	ADP
ejpam-2083	125	116	test	test	NOUN
ejpam-2083	125	117	data	datum	NOUN
ejpam-2083	125	118	group	group	NOUN
ejpam-2083	125	119	label	label	NOUN
ejpam-2083	125	120	0	0	NUM
ejpam-2083	125	121	1	1	NUM
ejpam-2083	125	122	total	total	NOUN
ejpam-2083	125	123	accuracy	accuracy	NOUN
ejpam-2083	125	124	0	0	NUM
ejpam-2083	125	125	42.99	42.99	NUM
ejpam-2083	125	126	7.07	7.07	NUM
ejpam-2083	125	127	50.06	50.06	NUM
ejpam-2083	125	128	85.85	85.85	NUM
ejpam-2083	125	129	%	%	NOUN
ejpam-2083	125	130	1	1	NUM
ejpam-2083	125	131	4.71	4.71	NUM
ejpam-2083	125	132	45.23	45.23	NUM
ejpam-2083	125	133	49.94	49.94	NUM
ejpam-2083	125	134	90.47	90.47	NUM
ejpam-2083	125	135	%	%	NOUN
ejpam-2083	125	136	total	total	NOUN
ejpam-2083	125	137	100.00	100.00	NUM
ejpam-2083	125	138	88.22	88.22	NUM
ejpam-2083	125	139	%	%	NOUN
ejpam-2083	125	140	as	as	SCONJ
ejpam-2083	125	141	is	be	AUX
ejpam-2083	125	142	seen	see	VERB
ejpam-2083	125	143	from	from	ADP
ejpam-2083	125	144	table	table	NOUN
ejpam-2083	125	145	1	1	NUM
ejpam-2083	125	146	,	,	PUNCT
ejpam-2083	125	147	the	the	DET
ejpam-2083	125	148	proposed	propose	VERB
ejpam-2083	125	149	model	model	NOUN
ejpam-2083	125	150	shows	show	VERB
ejpam-2083	125	151	high	high	ADJ
ejpam-2083	125	152	classification	classification	NOUN
ejpam-2083	125	153	accuracy	accuracy	NOUN
ejpam-2083	125	154	,	,	PUNCT
ejpam-2083	125	155	although	although	SCONJ
ejpam-2083	125	156	the	the	DET
ejpam-2083	125	157	groups	group	NOUN
ejpam-2083	125	158	are	be	AUX
ejpam-2083	125	159	highly	highly	ADV
ejpam-2083	125	160	overlapped	overlapped	ADJ
ejpam-2083	125	161	.	.	PUNCT
ejpam-2083	126	1	we	we	PRON
ejpam-2083	126	2	ran	run	VERB
ejpam-2083	126	3	logistic	logistic	ADJ
ejpam-2083	126	4	regression	regression	NOUN
ejpam-2083	126	5	for	for	ADP
ejpam-2083	126	6	the	the	DET
ejpam-2083	126	7	same	same	ADJ
ejpam-2083	126	8	data	datum	NOUN
ejpam-2083	126	9	set	set	VERB
ejpam-2083	126	10	and	and	CCONJ
ejpam-2083	126	11	show	show	VERB
ejpam-2083	126	12	the	the	DET
ejpam-2083	126	13	confusion	confusion	NOUN
ejpam-2083	126	14	matrix	matrix	NOUN
ejpam-2083	126	15	in	in	ADP
ejpam-2083	126	16	table	table	NOUN
ejpam-2083	126	17	2	2	NUM
ejpam-2083	126	18	comparing	compare	VERB
ejpam-2083	126	19	our	our	PRON
ejpam-2083	126	20	results	result	NOUN
ejpam-2083	126	21	.	.	PUNCT
ejpam-2083	127	1	comparing	compare	VERB
ejpam-2083	127	2	table	table	NOUN
ejpam-2083	127	3	1	1	NUM
ejpam-2083	127	4	and	and	CCONJ
ejpam-2083	127	5	table	table	NOUN
ejpam-2083	127	6	2	2	NUM
ejpam-2083	127	7	,	,	PUNCT
ejpam-2083	127	8	we	we	PRON
ejpam-2083	127	9	can	can	AUX
ejpam-2083	127	10	see	see	VERB
ejpam-2083	127	11	that	that	SCONJ
ejpam-2083	127	12	the	the	DET
ejpam-2083	127	13	proposed	propose	VERB
ejpam-2083	127	14	method	method	NOUN
ejpam-2083	127	15	is	be	AUX
ejpam-2083	127	16	superior	superior	ADJ
ejpam-2083	127	17	to	to	ADP
ejpam-2083	127	18	the	the	DET
ejpam-2083	127	19	logistic	logistic	ADJ
ejpam-2083	127	20	regression	regression	NOUN
ejpam-2083	127	21	in	in	ADP
ejpam-2083	127	22	terms	term	NOUN
ejpam-2083	127	23	of	of	ADP
ejpam-2083	127	24	classification	classification	NOUN
ejpam-2083	127	25	accuracy	accuracy	NOUN
ejpam-2083	127	26	.	.	PUNCT
ejpam-2083	128	1	although	although	SCONJ
ejpam-2083	128	2	our	our	PRON
ejpam-2083	128	3	model	model	NOUN
ejpam-2083	128	4	uses	use	VERB
ejpam-2083	128	5	the	the	DET
ejpam-2083	128	6	rbf	rbf	PROPN
ejpam-2083	128	7	-	-	PUNCT
ejpam-2083	128	8	nn	nn	PROPN
ejpam-2083	128	9	frame	frame	NOUN
ejpam-2083	128	10	,	,	PUNCT
ejpam-2083	128	11	there	there	PRON
ejpam-2083	128	12	is	be	VERB
ejpam-2083	128	13	no	no	DET
ejpam-2083	128	14	random	random	ADJ
ejpam-2083	128	15	process	process	NOUN
ejpam-2083	128	16	to	to	PART
ejpam-2083	128	17	determine	determine	VERB
ejpam-2083	128	18	the	the	DET
ejpam-2083	128	19	network	network	NOUN
ejpam-2083	128	20	parameters	parameter	NOUN
ejpam-2083	128	21	.	.	PUNCT
ejpam-2083	129	1	at	at	ADP
ejpam-2083	129	2	this	this	DET
ejpam-2083	129	3	point	point	NOUN
ejpam-2083	129	4	,	,	PUNCT
ejpam-2083	129	5	it	it	PRON
ejpam-2083	129	6	is	be	AUX
ejpam-2083	129	7	a	a	DET
ejpam-2083	129	8	question	question	NOUN
ejpam-2083	129	9	of	of	ADP
ejpam-2083	129	10	whether	whether	SCONJ
ejpam-2083	129	11	the	the	DET
ejpam-2083	129	12	proposed	propose	VERB
ejpam-2083	129	13	model	model	NOUN
ejpam-2083	129	14	requires	require	VERB
ejpam-2083	129	15	cross	cross	VERB
ejpam-2083	129	16	validation	validation	NOUN
ejpam-2083	129	17	as	as	ADP
ejpam-2083	129	18	the	the	DET
ejpam-2083	129	19	classical	classical	ADJ
ejpam-2083	129	20	neural	neural	ADJ
ejpam-2083	129	21	network	network	NOUN
ejpam-2083	129	22	methods	method	NOUN
ejpam-2083	129	23	or	or	CCONJ
ejpam-2083	129	24	not	not	PART
ejpam-2083	129	25	.	.	PUNCT
ejpam-2083	130	1	to	to	PART
ejpam-2083	130	2	make	make	VERB
ejpam-2083	130	3	sure	sure	ADJ
ejpam-2083	130	4	about	about	ADP
ejpam-2083	130	5	the	the	DET
ejpam-2083	130	6	generalization	generalization	NOUN
ejpam-2083	130	7	performance	performance	NOUN
ejpam-2083	130	8	of	of	ADP
ejpam-2083	130	9	our	our	PRON
ejpam-2083	130	10	model	model	NOUN
ejpam-2083	130	11	,	,	PUNCT
ejpam-2083	130	12	we	we	PRON
ejpam-2083	130	13	randomly	randomly	VERB
ejpam-2083	130	14	split	split	VERB
ejpam-2083	130	15	data	datum	NOUN
ejpam-2083	130	16	into	into	ADP
ejpam-2083	130	17	train	train	NOUN
ejpam-2083	130	18	(	(	PUNCT
ejpam-2083	130	19	80	80	NUM
ejpam-2083	130	20	%	%	NOUN
ejpam-2083	130	21	)	)	PUNCT
ejpam-2083	130	22	and	and	CCONJ
ejpam-2083	130	23	test	test	NOUN
ejpam-2083	130	24	(	(	PUNCT
ejpam-2083	130	25	20	20	NUM
ejpam-2083	130	26	%	%	NOUN
ejpam-2083	130	27	)	)	PUNCT
ejpam-2083	130	28	.	.	PUNCT
ejpam-2083	131	1	we	we	PRON
ejpam-2083	131	2	repeated	repeat	VERB
ejpam-2083	131	3	this	this	DET
ejpam-2083	131	4	splitting	splitting	NOUN
ejpam-2083	131	5	process	process	NOUN
ejpam-2083	131	6	100	100	NUM
ejpam-2083	131	7	times	time	NOUN
ejpam-2083	131	8	and	and	CCONJ
ejpam-2083	131	9	document	document	VERB
ejpam-2083	131	10	the	the	DET
ejpam-2083	131	11	average	average	ADJ
ejpam-2083	131	12	results	result	NOUN
ejpam-2083	131	13	in	in	ADP
ejpam-2083	131	14	table	table	NOUN
ejpam-2083	131	15	3	3	NUM
ejpam-2083	131	16	and	and	CCONJ
ejpam-2083	131	17	table	table	NOUN
ejpam-2083	131	18	4	4	NUM
ejpam-2083	131	19	.	.	PUNCT
ejpam-2083	132	1	during	during	ADP
ejpam-2083	132	2	the	the	DET
ejpam-2083	132	3	cross	cross	NOUN
ejpam-2083	132	4	validation	validation	NOUN
ejpam-2083	132	5	process	process	NOUN
ejpam-2083	132	6	,	,	PUNCT
ejpam-2083	132	7	we	we	PRON
ejpam-2083	132	8	determined	determine	VERB
ejpam-2083	132	9	network	network	NOUN
ejpam-2083	132	10	parameters	parameter	NOUN
ejpam-2083	132	11	using	use	VERB
ejpam-2083	132	12	train	train	NOUN
ejpam-2083	132	13	data	datum	NOUN
ejpam-2083	132	14	and	and	CCONJ
ejpam-2083	132	15	carried	carry	VERB
ejpam-2083	132	16	out	out	ADP
ejpam-2083	132	17	classification	classification	NOUN
ejpam-2083	132	18	for	for	ADP
ejpam-2083	132	19	test	test	NOUN
ejpam-2083	132	20	data	datum	NOUN
ejpam-2083	132	21	with	with	ADP
ejpam-2083	132	22	pre	pre	ADJ
ejpam-2083	132	23	-	-	ADJ
ejpam-2083	132	24	determined	determined	ADJ
ejpam-2083	132	25	parameters	parameter	NOUN
ejpam-2083	132	26	.	.	PUNCT
ejpam-2083	133	1	at	at	ADP
ejpam-2083	133	2	this	this	DET
ejpam-2083	133	3	point	point	NOUN
ejpam-2083	133	4	,	,	PUNCT
ejpam-2083	133	5	o.	o.	PROPN
ejpam-2083	133	6	akbilgic	akbilgic	PROPN
ejpam-2083	133	7	/	/	SYM
ejpam-2083	133	8	eur	eur	PROPN
ejpam-2083	133	9	.	.	PUNCT
ejpam-2083	134	1	j.	j.	PROPN
ejpam-2083	134	2	pure	pure	PROPN
ejpam-2083	134	3	appl	appl	PROPN
ejpam-2083	134	4	.	.	PROPN
ejpam-2083	134	5	math	math	PROPN
ejpam-2083	134	6	,	,	PUNCT
ejpam-2083	134	7	6	6	NUM
ejpam-2083	134	8	(	(	PUNCT
ejpam-2083	134	9	2013	2013	NUM
ejpam-2083	134	10	)	)	PUNCT
ejpam-2083	134	11	,	,	PUNCT
ejpam-2083	134	12	377	377	NUM
ejpam-2083	134	13	-	-	SYM
ejpam-2083	134	14	386	386	NUM
ejpam-2083	134	15	384	384	NUM
ejpam-2083	134	16	classification	classification	NOUN
ejpam-2083	134	17	accuracy	accuracy	NOUN
ejpam-2083	134	18	should	should	AUX
ejpam-2083	134	19	not	not	PART
ejpam-2083	134	20	be	be	AUX
ejpam-2083	134	21	decreased	decrease	VERB
ejpam-2083	134	22	for	for	SCONJ
ejpam-2083	134	23	test	test	NOUN
ejpam-2083	134	24	data	datum	NOUN
ejpam-2083	134	25	to	to	PART
ejpam-2083	134	26	be	be	AUX
ejpam-2083	134	27	able	able	ADJ
ejpam-2083	134	28	to	to	PART
ejpam-2083	134	29	claim	claim	VERB
ejpam-2083	134	30	that	that	SCONJ
ejpam-2083	134	31	the	the	DET
ejpam-2083	134	32	proposed	propose	VERB
ejpam-2083	134	33	method	method	NOUN
ejpam-2083	134	34	offers	offer	VERB
ejpam-2083	134	35	good	good	ADJ
ejpam-2083	134	36	generalization	generalization	NOUN
ejpam-2083	134	37	performance	performance	NOUN
ejpam-2083	134	38	.	.	PUNCT
ejpam-2083	135	1	table	table	NOUN
ejpam-2083	135	2	3	3	NUM
ejpam-2083	135	3	and	and	CCONJ
ejpam-2083	135	4	table	table	NOUN
ejpam-2083	135	5	4	4	NUM
ejpam-2083	135	6	show	show	VERB
ejpam-2083	135	7	the	the	DET
ejpam-2083	135	8	high	high	ADJ
ejpam-2083	135	9	generalization	generalization	NOUN
ejpam-2083	135	10	performance	performance	NOUN
ejpam-2083	135	11	of	of	ADP
ejpam-2083	135	12	our	our	PRON
ejpam-2083	135	13	model	model	NOUN
ejpam-2083	135	14	in	in	ADP
ejpam-2083	135	15	terms	term	NOUN
ejpam-2083	135	16	of	of	ADP
ejpam-2083	135	17	classification	classification	NOUN
ejpam-2083	135	18	accuracy	accuracy	NOUN
ejpam-2083	135	19	where	where	SCONJ
ejpam-2083	135	20	there	there	PRON
ejpam-2083	135	21	is	be	VERB
ejpam-2083	135	22	no	no	DET
ejpam-2083	135	23	significant	significant	ADJ
ejpam-2083	135	24	drop	drop	NOUN
ejpam-2083	135	25	off	off	ADP
ejpam-2083	135	26	in	in	ADP
ejpam-2083	135	27	test	test	NOUN
ejpam-2083	135	28	data	datum	NOUN
ejpam-2083	135	29	.	.	PUNCT
ejpam-2083	136	1	moreover	moreover	ADV
ejpam-2083	136	2	,	,	PUNCT
ejpam-2083	136	3	the	the	DET
ejpam-2083	136	4	classification	classification	NOUN
ejpam-2083	136	5	accuracy	accuracy	NOUN
ejpam-2083	136	6	for	for	ADP
ejpam-2083	136	7	train	train	NOUN
ejpam-2083	136	8	and	and	CCONJ
ejpam-2083	136	9	test	test	NOUN
ejpam-2083	136	10	data	datum	NOUN
ejpam-2083	136	11	is	be	AUX
ejpam-2083	136	12	very	very	ADV
ejpam-2083	136	13	close	close	ADJ
ejpam-2083	136	14	to	to	ADP
ejpam-2083	136	15	that	that	PRON
ejpam-2083	136	16	obtained	obtain	VERB
ejpam-2083	136	17	without	without	ADP
ejpam-2083	136	18	splitting	split	VERB
ejpam-2083	136	19	data	datum	NOUN
ejpam-2083	136	20	.	.	PUNCT
ejpam-2083	137	1	the	the	DET
ejpam-2083	137	2	small	small	ADJ
ejpam-2083	137	3	difference	difference	NOUN
ejpam-2083	137	4	between	between	ADP
ejpam-2083	137	5	classification	classification	NOUN
ejpam-2083	137	6	accuracy	accuracy	NOUN
ejpam-2083	137	7	between	between	ADP
ejpam-2083	137	8	“	"	PUNCT
ejpam-2083	137	9	with	with	ADP
ejpam-2083	137	10	and	and	CCONJ
ejpam-2083	137	11	without	without	ADP
ejpam-2083	137	12	”	"	PUNCT
ejpam-2083	137	13	splitting	splitting	NOUN
ejpam-2083	137	14	can	can	AUX
ejpam-2083	137	15	be	be	AUX
ejpam-2083	137	16	explained	explain	VERB
ejpam-2083	137	17	with	with	ADP
ejpam-2083	137	18	the	the	DET
ejpam-2083	137	19	number	number	NOUN
ejpam-2083	137	20	of	of	ADP
ejpam-2083	137	21	observations	observation	NOUN
ejpam-2083	137	22	which	which	PRON
ejpam-2083	137	23	are	be	AUX
ejpam-2083	137	24	obviously	obviously	ADV
ejpam-2083	137	25	more	more	ADJ
ejpam-2083	137	26	for	for	ADP
ejpam-2083	137	27	non	non	ADJ
ejpam-2083	137	28	-	-	ADJ
ejpam-2083	137	29	split	split	ADJ
ejpam-2083	137	30	data	datum	NOUN
ejpam-2083	137	31	.	.	PUNCT
ejpam-2083	138	1	3.2	3.2	NUM
ejpam-2083	138	2	.	.	PUNCT
ejpam-2083	139	1	pre	pre	VERB
ejpam-2083	139	2	-	-	NOUN
ejpam-2083	139	3	determination	determination	NOUN
ejpam-2083	139	4	of	of	ADP
ejpam-2083	139	5	hydraulic	hydraulic	ADJ
ejpam-2083	139	6	fracturing	fracturing	NOUN
ejpam-2083	139	7	failure	failure	NOUN
ejpam-2083	139	8	for	for	ADP
ejpam-2083	139	9	oil	oil	NOUN
ejpam-2083	139	10	&	&	CCONJ
ejpam-2083	139	11	gas	gas	NOUN
ejpam-2083	139	12	wells	wells	PROPN
ejpam-2083	139	13	hydraulic	hydraulic	PROPN
ejpam-2083	139	14	fracturing	fracturing	NOUN
ejpam-2083	139	15	(	(	PUNCT
ejpam-2083	139	16	fracking	fracking	NOUN
ejpam-2083	139	17	)	)	PUNCT
ejpam-2083	139	18	is	be	AUX
ejpam-2083	139	19	an	an	DET
ejpam-2083	139	20	unconventional	unconventional	ADJ
ejpam-2083	139	21	oil	oil	NOUN
ejpam-2083	139	22	&	&	CCONJ
ejpam-2083	139	23	gas	gas	NOUN
ejpam-2083	139	24	extraction	extraction	NOUN
ejpam-2083	139	25	technique	technique	NOUN
ejpam-2083	139	26	[	[	X
ejpam-2083	139	27	10	10	NUM
ejpam-2083	139	28	,	,	PUNCT
ejpam-2083	139	29	15	15	NUM
ejpam-2083	139	30	]	]	PUNCT
ejpam-2083	139	31	.	.	PUNCT
ejpam-2083	140	1	fracking	fracke	VERB
ejpam-2083	140	2	operation	operation	NOUN
ejpam-2083	140	3	is	be	AUX
ejpam-2083	140	4	basically	basically	ADV
ejpam-2083	140	5	injecting	inject	VERB
ejpam-2083	140	6	a	a	DET
ejpam-2083	140	7	high	high	ADV
ejpam-2083	140	8	-	-	PUNCT
ejpam-2083	140	9	pressured	pressure	VERB
ejpam-2083	140	10	solution	solution	NOUN
ejpam-2083	140	11	of	of	ADP
ejpam-2083	140	12	chemicals	chemical	NOUN
ejpam-2083	140	13	into	into	ADP
ejpam-2083	140	14	the	the	DET
ejpam-2083	140	15	ground	ground	NOUN
ejpam-2083	140	16	around	around	ADP
ejpam-2083	140	17	the	the	DET
ejpam-2083	140	18	walls	wall	NOUN
ejpam-2083	140	19	of	of	ADP
ejpam-2083	140	20	oil	oil	NOUN
ejpam-2083	140	21	or	or	CCONJ
ejpam-2083	140	22	gas	gas	NOUN
ejpam-2083	140	23	wells	well	NOUN
ejpam-2083	140	24	[	[	X
ejpam-2083	140	25	5	5	NUM
ejpam-2083	140	26	,	,	PUNCT
ejpam-2083	140	27	6	6	NUM
ejpam-2083	140	28	]	]	PUNCT
ejpam-2083	140	29	.	.	PUNCT
ejpam-2083	141	1	fracking	fracke	VERB
ejpam-2083	141	2	operations	operation	NOUN
ejpam-2083	141	3	are	be	AUX
ejpam-2083	141	4	not	not	PART
ejpam-2083	141	5	allowed	allow	VERB
ejpam-2083	141	6	in	in	ADP
ejpam-2083	141	7	some	some	DET
ejpam-2083	141	8	countries	country	NOUN
ejpam-2083	141	9	because	because	SCONJ
ejpam-2083	141	10	of	of	ADP
ejpam-2083	141	11	the	the	DET
ejpam-2083	141	12	chemicals	chemical	NOUN
ejpam-2083	141	13	injected	inject	VERB
ejpam-2083	141	14	into	into	ADP
ejpam-2083	141	15	ground	ground	NOUN
ejpam-2083	141	16	,	,	PUNCT
ejpam-2083	141	17	which	which	PRON
ejpam-2083	141	18	contain	contain	VERB
ejpam-2083	141	19	very	very	ADV
ejpam-2083	141	20	hazardous	hazardous	ADJ
ejpam-2083	141	21	elements	element	NOUN
ejpam-2083	141	22	.	.	PUNCT
ejpam-2083	142	1	furthermore	furthermore	ADV
ejpam-2083	142	2	,	,	PUNCT
ejpam-2083	142	3	fracking	fracking	NOUN
ejpam-2083	142	4	is	be	AUX
ejpam-2083	142	5	a	a	DET
ejpam-2083	142	6	very	very	ADV
ejpam-2083	142	7	costly	costly	ADJ
ejpam-2083	142	8	operation	operation	NOUN
ejpam-2083	142	9	costing	cost	VERB
ejpam-2083	142	10	approximately	approximately	ADV
ejpam-2083	142	11	$	$	SYM
ejpam-2083	142	12	500,000	500,000	NUM
ejpam-2083	142	13	or	or	CCONJ
ejpam-2083	142	14	more	more	ADJ
ejpam-2083	142	15	for	for	ADP
ejpam-2083	142	16	each	each	DET
ejpam-2083	142	17	operation	operation	NOUN
ejpam-2083	142	18	.	.	PUNCT
ejpam-2083	143	1	due	due	ADP
ejpam-2083	143	2	to	to	ADP
ejpam-2083	143	3	these	these	DET
ejpam-2083	143	4	two	two	NUM
ejpam-2083	143	5	reasons	reason	NOUN
ejpam-2083	143	6	,	,	PUNCT
ejpam-2083	143	7	it	it	PRON
ejpam-2083	143	8	is	be	AUX
ejpam-2083	143	9	crucial	crucial	ADJ
ejpam-2083	143	10	to	to	PART
ejpam-2083	143	11	make	make	VERB
ejpam-2083	143	12	an	an	DET
ejpam-2083	143	13	educated	educate	VERB
ejpam-2083	143	14	decision	decision	NOUN
ejpam-2083	143	15	regarding	regard	VERB
ejpam-2083	143	16	applying	apply	VERB
ejpam-2083	143	17	a	a	DET
ejpam-2083	143	18	fracking	fracke	VERB
ejpam-2083	143	19	operation	operation	NOUN
ejpam-2083	143	20	within	within	ADP
ejpam-2083	143	21	a	a	DET
ejpam-2083	143	22	specific	specific	ADJ
ejpam-2083	143	23	zone	zone	NOUN
ejpam-2083	143	24	.	.	PUNCT
ejpam-2083	144	1	in	in	ADP
ejpam-2083	144	2	this	this	DET
ejpam-2083	144	3	study	study	NOUN
ejpam-2083	144	4	,	,	PUNCT
ejpam-2083	144	5	we	we	PRON
ejpam-2083	144	6	applied	apply	VERB
ejpam-2083	144	7	our	our	PRON
ejpam-2083	144	8	proposed	propose	VERB
ejpam-2083	144	9	method	method	NOUN
ejpam-2083	144	10	on	on	ADP
ejpam-2083	144	11	historical	historical	ADJ
ejpam-2083	144	12	data	datum	NOUN
ejpam-2083	144	13	obtained	obtain	VERB
ejpam-2083	144	14	from	from	ADP
ejpam-2083	144	15	an	an	DET
ejpam-2083	144	16	international	international	ADJ
ejpam-2083	144	17	oil	oil	NOUN
ejpam-2083	144	18	company	company	NOUN
ejpam-2083	144	19	operating	operate	VERB
ejpam-2083	144	20	in	in	ADP
ejpam-2083	144	21	turkey	turkey	NOUN
ejpam-2083	144	22	under	under	ADP
ejpam-2083	144	23	a	a	DET
ejpam-2083	144	24	non	non	ADJ
ejpam-2083	144	25	-	-	ADJ
ejpam-2083	144	26	disclosure	disclosure	ADJ
ejpam-2083	144	27	agreement	agreement	NOUN
ejpam-2083	144	28	.	.	PUNCT
ejpam-2083	145	1	our	our	PRON
ejpam-2083	145	2	data	datum	NOUN
ejpam-2083	145	3	includes	include	VERB
ejpam-2083	145	4	50	50	NUM
ejpam-2083	145	5	hydraulic	hydraulic	ADJ
ejpam-2083	145	6	fracturing	fracturing	NOUN
ejpam-2083	145	7	operations	operation	NOUN
ejpam-2083	145	8	from	from	ADP
ejpam-2083	145	9	38	38	NUM
ejpam-2083	145	10	different	different	ADJ
ejpam-2083	145	11	natural	natural	ADJ
ejpam-2083	145	12	gas	gas	NOUN
ejpam-2083	145	13	wells	well	NOUN
ejpam-2083	145	14	.	.	PUNCT
ejpam-2083	146	1	for	for	ADP
ejpam-2083	146	2	each	each	DET
ejpam-2083	146	3	fracking	fracke	VERB
ejpam-2083	146	4	operation	operation	NOUN
ejpam-2083	146	5	,	,	PUNCT
ejpam-2083	146	6	our	our	PRON
ejpam-2083	146	7	input	input	NOUN
ejpam-2083	146	8	data	data	NOUN
ejpam-2083	146	9	contains	contain	VERB
ejpam-2083	146	10	18	18	NUM
ejpam-2083	146	11	different	different	ADJ
ejpam-2083	146	12	well	well	ADJ
ejpam-2083	146	13	-	-	PUNCT
ejpam-2083	146	14	log	log	NOUN
ejpam-2083	146	15	measurements	measurement	NOUN
ejpam-2083	146	16	,	,	PUNCT
ejpam-2083	146	17	such	such	ADJ
ejpam-2083	146	18	as	as	ADP
ejpam-2083	146	19	gamma	gamma	PROPN
ejpam-2083	146	20	ray	ray	PROPN
ejpam-2083	146	21	,	,	PUNCT
ejpam-2083	146	22	resistivity	resistivity	NOUN
ejpam-2083	146	23	logs	log	NOUN
ejpam-2083	146	24	,	,	PUNCT
ejpam-2083	146	25	porosity	porosity	NOUN
ejpam-2083	146	26	logs	log	NOUN
ejpam-2083	146	27	,	,	PUNCT
ejpam-2083	146	28	etc	etc	X
ejpam-2083	146	29	.	.	X
ejpam-2083	147	1	we	we	PRON
ejpam-2083	147	2	also	also	ADV
ejpam-2083	147	3	have	have	VERB
ejpam-2083	147	4	the	the	DET
ejpam-2083	147	5	results	result	NOUN
ejpam-2083	147	6	from	from	ADP
ejpam-2083	147	7	fracking	fracke	VERB
ejpam-2083	147	8	operations	operation	NOUN
ejpam-2083	147	9	as	as	ADP
ejpam-2083	147	10	to	to	ADP
ejpam-2083	147	11	whether	whether	SCONJ
ejpam-2083	147	12	gas	gas	NOUN
ejpam-2083	147	13	was	be	AUX
ejpam-2083	147	14	produced	produce	VERB
ejpam-2083	147	15	or	or	CCONJ
ejpam-2083	147	16	not	not	PART
ejpam-2083	147	17	.	.	PUNCT
ejpam-2083	148	1	the	the	DET
ejpam-2083	148	2	goal	goal	NOUN
ejpam-2083	148	3	is	be	AUX
ejpam-2083	148	4	to	to	PART
ejpam-2083	148	5	find	find	VERB
ejpam-2083	148	6	a	a	DET
ejpam-2083	148	7	classification	classification	NOUN
ejpam-2083	148	8	model	model	NOUN
ejpam-2083	148	9	to	to	PART
ejpam-2083	148	10	determine	determine	VERB
ejpam-2083	148	11	,	,	PUNCT
ejpam-2083	148	12	before	before	ADP
ejpam-2083	148	13	the	the	DET
ejpam-2083	148	14	operation	operation	NOUN
ejpam-2083	148	15	,	,	PUNCT
ejpam-2083	148	16	which	which	DET
ejpam-2083	148	17	zones	zone	NOUN
ejpam-2083	148	18	are	be	AUX
ejpam-2083	148	19	going	go	VERB
ejpam-2083	148	20	to	to	PART
ejpam-2083	148	21	produce	produce	VERB
ejpam-2083	148	22	gas	gas	NOUN
ejpam-2083	148	23	by	by	ADP
ejpam-2083	148	24	fracking	fracke	VERB
ejpam-2083	148	25	.	.	PUNCT
ejpam-2083	149	1	thus	thus	ADV
ejpam-2083	149	2	,	,	PUNCT
ejpam-2083	149	3	the	the	DET
ejpam-2083	149	4	companies	company	NOUN
ejpam-2083	149	5	can	can	AUX
ejpam-2083	149	6	avoid	avoid	VERB
ejpam-2083	149	7	the	the	DET
ejpam-2083	149	8	unnecessary	unnecessary	ADJ
ejpam-2083	149	9	cost	cost	NOUN
ejpam-2083	149	10	of	of	ADP
ejpam-2083	149	11	the	the	DET
ejpam-2083	149	12	operation	operation	NOUN
ejpam-2083	149	13	as	as	ADV
ejpam-2083	149	14	well	well	ADV
ejpam-2083	149	15	as	as	ADP
ejpam-2083	149	16	ensuring	ensure	VERB
ejpam-2083	149	17	that	that	SCONJ
ejpam-2083	149	18	hazardous	hazardous	ADJ
ejpam-2083	149	19	chemicals	chemical	NOUN
ejpam-2083	149	20	would	would	AUX
ejpam-2083	149	21	not	not	PART
ejpam-2083	149	22	unnecessarily	unnecessarily	ADV
ejpam-2083	149	23	affect	affect	VERB
ejpam-2083	149	24	the	the	DET
ejpam-2083	149	25	environment	environment	NOUN
ejpam-2083	149	26	.	.	PUNCT
ejpam-2083	150	1	we	we	PRON
ejpam-2083	150	2	performed	perform	VERB
ejpam-2083	150	3	our	our	PRON
ejpam-2083	150	4	tree	tree	NOUN
ejpam-2083	150	5	based	base	VERB
ejpam-2083	150	6	log	log	PROPN
ejpam-2083	150	7	-	-	PUNCT
ejpam-2083	150	8	rbf	rbf	PROPN
ejpam-2083	150	9	-	-	PUNCT
ejpam-2083	150	10	nn	nn	PROPN
ejpam-2083	150	11	model	model	NOUN
ejpam-2083	150	12	to	to	PART
ejpam-2083	150	13	carry	carry	VERB
ejpam-2083	150	14	out	out	ADP
ejpam-2083	150	15	classification	classification	NOUN
ejpam-2083	150	16	on	on	ADP
ejpam-2083	150	17	hydraulic	hydraulic	ADJ
ejpam-2083	150	18	fracturing	fracturing	NOUN
ejpam-2083	150	19	data	datum	NOUN
ejpam-2083	150	20	.	.	PUNCT
ejpam-2083	151	1	again	again	ADV
ejpam-2083	151	2	,	,	PUNCT
ejpam-2083	151	3	we	we	PRON
ejpam-2083	151	4	ran	run	VERB
ejpam-2083	151	5	the	the	DET
ejpam-2083	151	6	proposed	propose	VERB
ejpam-2083	151	7	model	model	NOUN
ejpam-2083	151	8	for	for	ADP
ejpam-2083	151	9	different	different	ADJ
ejpam-2083	151	10	!	!	PUNCT
ejpam-2083	152	1	parameters	parameter	NOUN
ejpam-2083	152	2	from	from	ADP
ejpam-2083	152	3	the	the	DET
ejpam-2083	152	4	set	set	NOUN
ejpam-2083	152	5	{	{	PUNCT
ejpam-2083	152	6	.15	.15	NUM
ejpam-2083	152	7	,	,	PUNCT
ejpam-2083	152	8	.20	.20	NUM
ejpam-2083	152	9	,	,	PUNCT
ejpam-2083	152	10	.25	.25	NUM
ejpam-2083	152	11	,	,	PUNCT
ejpam-2083	152	12	.	.	PUNCT
ejpam-2083	152	13	.	.	PUNCT
ejpam-2083	152	14	.	.	PUNCT
ejpam-2083	153	1	,	,	PUNCT
ejpam-2083	153	2	2.5	2.5	NUM
ejpam-2083	153	3	}	}	PUNCT
ejpam-2083	153	4	.	.	PUNCT
ejpam-2083	154	1	we	we	PRON
ejpam-2083	154	2	found	find	VERB
ejpam-2083	154	3	the	the	DET
ejpam-2083	154	4	best	good	ADJ
ejpam-2083	154	5	performing	performing	NOUN
ejpam-2083	154	6	!	!	PUNCT
ejpam-2083	154	7	value	value	NOUN
ejpam-2083	154	8	as	as	ADP
ejpam-2083	154	9	!	!	PUNCT
ejpam-2083	155	1	=	=	SYM
ejpam-2083	155	2	0.85	0.85	NUM
ejpam-2083	155	3	which	which	PRON
ejpam-2083	155	4	is	be	AUX
ejpam-2083	155	5	very	very	ADV
ejpam-2083	155	6	close	close	ADJ
ejpam-2083	155	7	for	for	ADP
ejpam-2083	155	8	the	the	DET
ejpam-2083	155	9	best	good	ADJ
ejpam-2083	155	10	operating	operating	NOUN
ejpam-2083	155	11	!	!	PUNCT
ejpam-2083	156	1	parameter	parameter	NOUN
ejpam-2083	156	2	for	for	ADP
ejpam-2083	156	3	simulated	simulated	ADJ
ejpam-2083	156	4	data	datum	NOUN
ejpam-2083	156	5	.	.	PUNCT
ejpam-2083	157	1	note	note	VERB
ejpam-2083	157	2	that	that	SCONJ
ejpam-2083	157	3	,	,	PUNCT
ejpam-2083	157	4	the	the	DET
ejpam-2083	157	5	classification	classification	NOUN
ejpam-2083	157	6	accuracy	accuracy	NOUN
ejpam-2083	157	7	of	of	ADP
ejpam-2083	157	8	the	the	DET
ejpam-2083	157	9	model	model	NOUN
ejpam-2083	157	10	was	be	AUX
ejpam-2083	157	11	increasing	increase	VERB
ejpam-2083	157	12	until	until	ADP
ejpam-2083	157	13	the	the	DET
ejpam-2083	157	14	best	good	ADJ
ejpam-2083	157	15	performing	performing	NOUN
ejpam-2083	157	16	!	!	PUNCT
ejpam-2083	158	1	values	value	NOUN
ejpam-2083	158	2	while	while	SCONJ
ejpam-2083	158	3	it	it	PRON
ejpam-2083	158	4	was	be	AUX
ejpam-2083	158	5	decreasing	decrease	VERB
ejpam-2083	158	6	with	with	ADP
ejpam-2083	158	7	the	the	DET
ejpam-2083	158	8	larger	large	ADJ
ejpam-2083	158	9	values	value	NOUN
ejpam-2083	158	10	for	for	ADP
ejpam-2083	158	11	both	both	CCONJ
ejpam-2083	158	12	simulated	simulated	ADJ
ejpam-2083	158	13	and	and	CCONJ
ejpam-2083	158	14	real	real	ADJ
ejpam-2083	158	15	data	datum	NOUN
ejpam-2083	158	16	.	.	PUNCT
ejpam-2083	159	1	table	table	NOUN
ejpam-2083	159	2	5	5	NUM
ejpam-2083	159	3	shows	show	VERB
ejpam-2083	159	4	the	the	DET
ejpam-2083	159	5	results	result	NOUN
ejpam-2083	159	6	of	of	ADP
ejpam-2083	159	7	the	the	DET
ejpam-2083	159	8	confusion	confusion	NOUN
ejpam-2083	159	9	matrix	matrix	NOUN
ejpam-2083	159	10	for	for	ADP
ejpam-2083	159	11	the	the	DET
ejpam-2083	159	12	classification	classification	NOUN
ejpam-2083	159	13	of	of	ADP
ejpam-2083	159	14	hydraulic	hydraulic	ADJ
ejpam-2083	159	15	fracturing	fracturing	NOUN
ejpam-2083	159	16	data	datum	NOUN
ejpam-2083	159	17	.	.	PUNCT
ejpam-2083	160	1	since	since	SCONJ
ejpam-2083	160	2	our	our	PRON
ejpam-2083	160	3	sample	sample	NOUN
ejpam-2083	160	4	size	size	NOUN
ejpam-2083	160	5	is	be	AUX
ejpam-2083	160	6	very	very	ADV
ejpam-2083	160	7	small	small	ADJ
ejpam-2083	160	8	,	,	PUNCT
ejpam-2083	160	9	we	we	PRON
ejpam-2083	160	10	did	do	AUX
ejpam-2083	160	11	not	not	PART
ejpam-2083	160	12	divide	divide	VERB
ejpam-2083	160	13	our	our	PRON
ejpam-2083	160	14	data	datum	NOUN
ejpam-2083	160	15	into	into	ADP
ejpam-2083	160	16	train	train	NOUN
ejpam-2083	160	17	and	and	CCONJ
ejpam-2083	160	18	test	test	NOUN
ejpam-2083	160	19	.	.	PUNCT
ejpam-2083	161	1	instead	instead	ADV
ejpam-2083	161	2	,	,	PUNCT
ejpam-2083	161	3	we	we	PRON
ejpam-2083	161	4	pruned	prune	VERB
ejpam-2083	161	5	the	the	DET
ejpam-2083	161	6	classification	classification	NOUN
ejpam-2083	161	7	and	and	CCONJ
ejpam-2083	161	8	regression	regression	NOUN
ejpam-2083	161	9	tree	tree	NOUN
ejpam-2083	161	10	so	so	SCONJ
ejpam-2083	161	11	that	that	SCONJ
ejpam-2083	161	12	it	it	PRON
ejpam-2083	161	13	produced	produce	VERB
ejpam-2083	161	14	only	only	ADV
ejpam-2083	161	15	five	five	NUM
ejpam-2083	161	16	terminal	terminal	ADJ
ejpam-2083	161	17	nodes	node	NOUN
ejpam-2083	161	18	returning	return	VERB
ejpam-2083	161	19	five	five	NUM
ejpam-2083	161	20	hidden	hidden	ADJ
ejpam-2083	161	21	neurons	neuron	NOUN
ejpam-2083	161	22	in	in	ADP
ejpam-2083	161	23	the	the	DET
ejpam-2083	161	24	hidden	hidden	ADJ
ejpam-2083	161	25	layer	layer	NOUN
ejpam-2083	161	26	considering	consider	VERB
ejpam-2083	161	27	the	the	DET
ejpam-2083	161	28	number	number	NOUN
ejpam-2083	161	29	of	of	ADP
ejpam-2083	161	30	observations	observation	NOUN
ejpam-2083	161	31	,	,	PUNCT
ejpam-2083	161	32	n	n	NOUN
ejpam-2083	161	33	=	=	SYM
ejpam-2083	161	34	50	50	NUM
ejpam-2083	161	35	.	.	PUNCT
ejpam-2083	162	1	note	note	VERB
ejpam-2083	162	2	that	that	SCONJ
ejpam-2083	162	3	the	the	DET
ejpam-2083	162	4	pruning	prune	VERB
ejpam-2083	162	5	operation	operation	NOUN
ejpam-2083	162	6	is	be	AUX
ejpam-2083	162	7	basically	basically	ADV
ejpam-2083	162	8	selecting	select	VERB
ejpam-2083	162	9	the	the	DET
ejpam-2083	162	10	best	well	ADV
ejpam-2083	162	11	performing	perform	VERB
ejpam-2083	162	12	hidden	hidden	ADJ
ejpam-2083	162	13	neurons	neuron	NOUN
ejpam-2083	162	14	in	in	ADP
ejpam-2083	162	15	the	the	DET
ejpam-2083	162	16	hidden	hide	VERB
ejpam-2083	162	17	layer	layer	NOUN
ejpam-2083	162	18	using	use	VERB
ejpam-2083	162	19	the	the	DET
ejpam-2083	162	20	aic	aic	PROPN
ejpam-2083	162	21	-	-	PUNCT
ejpam-2083	162	22	based	base	VERB
ejpam-2083	162	23	variable	variable	ADJ
ejpam-2083	162	24	selection	selection	NOUN
ejpam-2083	162	25	scheme	scheme	NOUN
ejpam-2083	162	26	for	for	ADP
ejpam-2083	162	27	logistic	logistic	ADJ
ejpam-2083	162	28	regression	regression	NOUN
ejpam-2083	162	29	.	.	PUNCT
ejpam-2083	163	1	table	table	NOUN
ejpam-2083	163	2	5	5	NUM
ejpam-2083	163	3	shows	show	VERB
ejpam-2083	163	4	the	the	DET
ejpam-2083	163	5	high	high	ADJ
ejpam-2083	163	6	classification	classification	NOUN
ejpam-2083	163	7	accuracy	accuracy	NOUN
ejpam-2083	163	8	of	of	ADP
ejpam-2083	163	9	our	our	PRON
ejpam-2083	163	10	proposed	propose	VERB
ejpam-2083	163	11	method	method	NOUN
ejpam-2083	163	12	on	on	ADP
ejpam-2083	163	13	fracking	fracke	VERB
ejpam-2083	163	14	data	datum	NOUN
ejpam-2083	163	15	.	.	PUNCT
ejpam-2083	164	1	using	use	VERB
ejpam-2083	164	2	this	this	DET
ejpam-2083	164	3	model	model	NOUN
ejpam-2083	164	4	as	as	ADP
ejpam-2083	164	5	a	a	DET
ejpam-2083	164	6	decision	decision	NOUN
ejpam-2083	164	7	support	support	NOUN
ejpam-2083	164	8	system	system	NOUN
ejpam-2083	164	9	in	in	ADP
ejpam-2083	164	10	the	the	DET
ejpam-2083	164	11	oil	oil	NOUN
ejpam-2083	164	12	&	&	CCONJ
ejpam-2083	164	13	gas	gas	NOUN
ejpam-2083	164	14	industry	industry	NOUN
ejpam-2083	164	15	might	might	AUX
ejpam-2083	164	16	result	result	VERB
ejpam-2083	164	17	in	in	ADP
ejpam-2083	164	18	saving	save	VERB
ejpam-2083	164	19	time	time	NOUN
ejpam-2083	164	20	and	and	CCONJ
ejpam-2083	164	21	potentially	potentially	ADV
ejpam-2083	164	22	millions	million	NOUN
ejpam-2083	164	23	of	of	ADP
ejpam-2083	164	24	dollars	dollar	NOUN
ejpam-2083	164	25	.	.	PUNCT
ejpam-2083	165	1	furthermore	furthermore	ADV
ejpam-2083	165	2	,	,	PUNCT
ejpam-2083	165	3	the	the	DET
ejpam-2083	165	4	environment	environment	NOUN
ejpam-2083	165	5	would	would	AUX
ejpam-2083	165	6	be	be	AUX
ejpam-2083	165	7	protected	protect	VERB
ejpam-2083	165	8	from	from	ADP
ejpam-2083	165	9	the	the	DET
ejpam-2083	165	10	hazardous	hazardous	ADJ
ejpam-2083	165	11	effects	effect	NOUN
ejpam-2083	165	12	of	of	ADP
ejpam-2083	165	13	chemicals	chemical	NOUN
ejpam-2083	165	14	used	use	VERB
ejpam-2083	165	15	in	in	ADP
ejpam-2083	165	16	fracking	fracke	VERB
ejpam-2083	165	17	operations	operation	NOUN
ejpam-2083	165	18	.	.	PUNCT
ejpam-2083	166	1	note	note	VERB
ejpam-2083	166	2	that	that	SCONJ
ejpam-2083	166	3	classification	classification	NOUN
ejpam-2083	166	4	references	reference	NOUN
ejpam-2083	166	5	385	385	NUM
ejpam-2083	166	6	accuracy	accuracy	NOUN
ejpam-2083	166	7	obtained	obtain	VERB
ejpam-2083	166	8	by	by	ADP
ejpam-2083	166	9	logistic	logistic	ADJ
ejpam-2083	166	10	regression	regression	NOUN
ejpam-2083	166	11	for	for	ADP
ejpam-2083	166	12	same	same	ADJ
ejpam-2083	166	13	data	datum	NOUN
ejpam-2083	166	14	is	be	AUX
ejpam-2083	166	15	78.00	78.00	NUM
ejpam-2083	166	16	%	%	NOUN
ejpam-2083	166	17	,	,	PUNCT
ejpam-2083	166	18	which	which	PRON
ejpam-2083	166	19	is	be	AUX
ejpam-2083	166	20	very	very	ADV
ejpam-2083	166	21	low	low	ADJ
ejpam-2083	166	22	compared	compare	VERB
ejpam-2083	166	23	to	to	ADP
ejpam-2083	166	24	our	our	PRON
ejpam-2083	166	25	method	method	NOUN
ejpam-2083	166	26	’s	’s	PART
ejpam-2083	166	27	accuracy	accuracy	NOUN
ejpam-2083	166	28	of	of	ADP
ejpam-2083	166	29	94.00	94.00	NUM
ejpam-2083	166	30	%	%	NOUN
ejpam-2083	166	31	.	.	PUNCT
ejpam-2083	167	1	on	on	ADP
ejpam-2083	167	2	the	the	DET
ejpam-2083	167	3	other	other	ADJ
ejpam-2083	167	4	hand	hand	NOUN
ejpam-2083	167	5	,	,	PUNCT
ejpam-2083	167	6	the	the	DET
ejpam-2083	167	7	accuracy	accuracy	NOUN
ejpam-2083	167	8	of	of	ADP
ejpam-2083	167	9	the	the	DET
ejpam-2083	167	10	engineers	engineer	NOUN
ejpam-2083	167	11	who	who	PRON
ejpam-2083	167	12	are	be	AUX
ejpam-2083	167	13	decision	decision	NOUN
ejpam-2083	167	14	makers	maker	NOUN
ejpam-2083	167	15	making	make	VERB
ejpam-2083	167	16	decisions	decision	NOUN
ejpam-2083	167	17	on	on	ADP
ejpam-2083	167	18	hydraulic	hydraulic	ADJ
ejpam-2083	167	19	fracturing	fracturing	NOUN
ejpam-2083	167	20	operations	operation	NOUN
ejpam-2083	167	21	is	be	AUX
ejpam-2083	167	22	66	66	NUM
ejpam-2083	167	23	%	%	NOUN
ejpam-2083	167	24	.	.	PUNCT
ejpam-2083	168	1	table	table	NOUN
ejpam-2083	168	2	5	5	NUM
ejpam-2083	168	3	:	:	PUNCT
ejpam-2083	168	4	confusion	confusion	NOUN
ejpam-2083	168	5	matrix	matrix	NOUN
ejpam-2083	168	6	for	for	ADP
ejpam-2083	168	7	hydraulic	hydraulic	ADJ
ejpam-2083	168	8	fracturing	fracturing	NOUN
ejpam-2083	168	9	data	datum	NOUN
ejpam-2083	168	10	set	set	VERB
ejpam-2083	168	11	group	group	NOUN
ejpam-2083	168	12	label	label	NOUN
ejpam-2083	168	13	0	0	NUM
ejpam-2083	168	14	1	1	NUM
ejpam-2083	168	15	total	total	NOUN
ejpam-2083	168	16	accuracy	accuracy	NOUN
ejpam-2083	168	17	0	0	NUM
ejpam-2083	168	18	15	15	NUM
ejpam-2083	168	19	2	2	NUM
ejpam-2083	168	20	17	17	NUM
ejpam-2083	168	21	88.24	88.24	NUM
ejpam-2083	168	22	%	%	NOUN
ejpam-2083	168	23	1	1	NUM
ejpam-2083	168	24	1	1	NUM
ejpam-2083	168	25	32	32	NUM
ejpam-2083	168	26	33	33	NUM
ejpam-2083	168	27	96.97	96.97	NUM
ejpam-2083	168	28	%	%	NOUN
ejpam-2083	168	29	total	total	NOUN
ejpam-2083	168	30	50	50	NUM
ejpam-2083	168	31	94.00	94.00	NUM
ejpam-2083	168	32	%	%	NOUN
ejpam-2083	168	33	4	4	NUM
ejpam-2083	168	34	.	.	PUNCT
ejpam-2083	169	1	conclusions	conclusion	NOUN
ejpam-2083	169	2	in	in	ADP
ejpam-2083	169	3	this	this	DET
ejpam-2083	169	4	paper	paper	NOUN
ejpam-2083	169	5	we	we	PRON
ejpam-2083	169	6	developed	develop	VERB
ejpam-2083	169	7	a	a	DET
ejpam-2083	169	8	novel	novel	ADJ
ejpam-2083	169	9	tree	tree	NOUN
ejpam-2083	169	10	-	-	PUNCT
ejpam-2083	169	11	based	base	VERB
ejpam-2083	169	12	logistic	logistic	ADJ
ejpam-2083	169	13	rbf	rbf	PROPN
ejpam-2083	169	14	-	-	PUNCT
ejpam-2083	169	15	nn	nn	PROPN
ejpam-2083	169	16	model	model	NOUN
ejpam-2083	169	17	for	for	ADP
ejpam-2083	169	18	binary	binary	ADJ
ejpam-2083	169	19	classification	classification	NOUN
ejpam-2083	169	20	problems	problem	NOUN
ejpam-2083	169	21	.	.	PUNCT
ejpam-2083	170	1	we	we	PRON
ejpam-2083	170	2	avoided	avoid	VERB
ejpam-2083	170	3	using	use	VERB
ejpam-2083	170	4	any	any	DET
ejpam-2083	170	5	techniques	technique	NOUN
ejpam-2083	170	6	using	use	VERB
ejpam-2083	170	7	random	random	ADJ
ejpam-2083	170	8	process	process	NOUN
ejpam-2083	170	9	during	during	ADP
ejpam-2083	170	10	the	the	DET
ejpam-2083	170	11	determination	determination	NOUN
ejpam-2083	170	12	of	of	ADP
ejpam-2083	170	13	network	network	NOUN
ejpam-2083	170	14	parameters	parameter	NOUN
ejpam-2083	170	15	.	.	PUNCT
ejpam-2083	171	1	as	as	ADP
ejpam-2083	171	2	a	a	DET
ejpam-2083	171	3	result	result	NOUN
ejpam-2083	171	4	,	,	PUNCT
ejpam-2083	171	5	our	our	PRON
ejpam-2083	171	6	model	model	NOUN
ejpam-2083	171	7	reflects	reflect	VERB
ejpam-2083	171	8	very	very	ADV
ejpam-2083	171	9	good	good	ADJ
ejpam-2083	171	10	generalization	generalization	NOUN
ejpam-2083	171	11	properties	property	NOUN
ejpam-2083	171	12	,	,	PUNCT
ejpam-2083	171	13	which	which	PRON
ejpam-2083	171	14	are	be	AUX
ejpam-2083	171	15	supported	support	VERB
ejpam-2083	171	16	by	by	ADP
ejpam-2083	171	17	an	an	DET
ejpam-2083	171	18	example	example	NOUN
ejpam-2083	171	19	using	use	VERB
ejpam-2083	171	20	highly	highly	ADV
ejpam-2083	171	21	overlapping	overlapping	ADJ
ejpam-2083	171	22	simulation	simulation	NOUN
ejpam-2083	171	23	data	datum	NOUN
ejpam-2083	171	24	.	.	PUNCT
ejpam-2083	172	1	furthermore	furthermore	ADV
ejpam-2083	172	2	,	,	PUNCT
ejpam-2083	172	3	our	our	PRON
ejpam-2083	172	4	model	model	NOUN
ejpam-2083	172	5	gives	give	VERB
ejpam-2083	172	6	high	high	ADJ
ejpam-2083	172	7	classification	classification	NOUN
ejpam-2083	172	8	accuracy	accuracy	NOUN
ejpam-2083	172	9	using	use	VERB
ejpam-2083	172	10	real	real	ADJ
ejpam-2083	172	11	life	life	NOUN
ejpam-2083	172	12	data	datum	NOUN
ejpam-2083	172	13	as	as	ADV
ejpam-2083	172	14	well	well	ADV
ejpam-2083	172	15	.	.	PUNCT
ejpam-2083	173	1	since	since	SCONJ
ejpam-2083	173	2	our	our	PRON
ejpam-2083	173	3	model	model	NOUN
ejpam-2083	173	4	is	be	AUX
ejpam-2083	173	5	a	a	DET
ejpam-2083	173	6	novel	novel	ADJ
ejpam-2083	173	7	approach	approach	NOUN
ejpam-2083	173	8	it	it	PRON
ejpam-2083	173	9	is	be	AUX
ejpam-2083	173	10	open	open	ADJ
ejpam-2083	173	11	for	for	ADP
ejpam-2083	173	12	improvement	improvement	NOUN
ejpam-2083	173	13	in	in	ADP
ejpam-2083	173	14	different	different	ADJ
ejpam-2083	173	15	ways	way	NOUN
ejpam-2083	173	16	.	.	PUNCT
ejpam-2083	174	1	although	although	SCONJ
ejpam-2083	174	2	there	there	PRON
ejpam-2083	174	3	are	be	VERB
ejpam-2083	174	4	no	no	DET
ejpam-2083	174	5	examples	example	NOUN
ejpam-2083	174	6	taking	take	VERB
ejpam-2083	174	7	place	place	NOUN
ejpam-2083	174	8	in	in	ADP
ejpam-2083	174	9	the	the	DET
ejpam-2083	174	10	paper	paper	NOUN
ejpam-2083	174	11	,	,	PUNCT
ejpam-2083	174	12	we	we	PRON
ejpam-2083	174	13	have	have	AUX
ejpam-2083	174	14	applied	apply	VERB
ejpam-2083	174	15	our	our	PRON
ejpam-2083	174	16	model	model	NOUN
ejpam-2083	174	17	on	on	ADP
ejpam-2083	174	18	n	n	CCONJ
ejpam-2083	174	19	<	<	X
ejpam-2083	174	20	p	p	NOUN
ejpam-2083	174	21	classification	classification	NOUN
ejpam-2083	174	22	problems	problem	NOUN
ejpam-2083	174	23	and	and	CCONJ
ejpam-2083	174	24	obtained	obtain	VERB
ejpam-2083	174	25	promising	promising	ADJ
ejpam-2083	174	26	results	result	NOUN
ejpam-2083	174	27	.	.	PUNCT
ejpam-2083	175	1	we	we	PRON
ejpam-2083	175	2	have	have	AUX
ejpam-2083	175	3	also	also	ADV
ejpam-2083	175	4	tested	test	VERB
ejpam-2083	175	5	our	our	PRON
ejpam-2083	175	6	model	model	NOUN
ejpam-2083	175	7	on	on	ADP
ejpam-2083	175	8	classification	classification	NOUN
ejpam-2083	175	9	problems	problem	NOUN
ejpam-2083	175	10	with	with	ADP
ejpam-2083	175	11	more	more	ADJ
ejpam-2083	175	12	than	than	ADP
ejpam-2083	175	13	two	two	NUM
ejpam-2083	175	14	classes	class	NOUN
ejpam-2083	175	15	and	and	CCONJ
ejpam-2083	175	16	again	again	ADV
ejpam-2083	175	17	our	our	PRON
ejpam-2083	175	18	results	result	NOUN
ejpam-2083	175	19	were	be	AUX
ejpam-2083	175	20	encouraging	encouraging	ADJ
ejpam-2083	175	21	in	in	ADP
ejpam-2083	175	22	terms	term	NOUN
ejpam-2083	175	23	of	of	ADP
ejpam-2083	175	24	classification	classification	NOUN
ejpam-2083	175	25	accuracy	accuracy	NOUN
ejpam-2083	175	26	.	.	PUNCT
ejpam-2083	176	1	an	an	DET
ejpam-2083	176	2	additional	additional	ADJ
ejpam-2083	176	3	benefit	benefit	NOUN
ejpam-2083	176	4	to	to	ADP
ejpam-2083	176	5	using	use	VERB
ejpam-2083	176	6	our	our	PRON
ejpam-2083	176	7	model	model	NOUN
ejpam-2083	176	8	is	be	AUX
ejpam-2083	176	9	that	that	SCONJ
ejpam-2083	176	10	it	it	PRON
ejpam-2083	176	11	is	be	AUX
ejpam-2083	176	12	possible	possible	ADJ
ejpam-2083	176	13	to	to	PART
ejpam-2083	176	14	reduce	reduce	VERB
ejpam-2083	176	15	dimension	dimension	NOUN
ejpam-2083	176	16	by	by	ADP
ejpam-2083	176	17	excluding	exclude	VERB
ejpam-2083	176	18	the	the	DET
ejpam-2083	176	19	predictors	predictor	NOUN
ejpam-2083	176	20	that	that	PRON
ejpam-2083	176	21	are	be	AUX
ejpam-2083	176	22	not	not	PART
ejpam-2083	176	23	used	use	VERB
ejpam-2083	176	24	in	in	ADP
ejpam-2083	176	25	splitting	split	VERB
ejpam-2083	176	26	data	datum	NOUN
ejpam-2083	176	27	by	by	ADP
ejpam-2083	176	28	classification	classification	NOUN
ejpam-2083	176	29	and	and	CCONJ
ejpam-2083	176	30	regression	regression	NOUN
ejpam-2083	176	31	trees	tree	NOUN
ejpam-2083	176	32	algorithms	algorithm	NOUN
ejpam-2083	176	33	.	.	PUNCT
ejpam-2083	177	1	while	while	SCONJ
ejpam-2083	177	2	the	the	DET
ejpam-2083	177	3	real	real	ADJ
ejpam-2083	177	4	data	datum	NOUN
ejpam-2083	177	5	used	use	VERB
ejpam-2083	177	6	in	in	ADP
ejpam-2083	177	7	this	this	DET
ejpam-2083	177	8	study	study	NOUN
ejpam-2083	177	9	is	be	AUX
ejpam-2083	177	10	related	relate	VERB
ejpam-2083	177	11	to	to	ADP
ejpam-2083	177	12	obtaining	obtain	VERB
ejpam-2083	177	13	natural	natural	ADJ
ejpam-2083	177	14	gas	gas	NOUN
ejpam-2083	177	15	by	by	ADP
ejpam-2083	177	16	hydraulic	hydraulic	ADJ
ejpam-2083	177	17	fracturing	fracturing	NOUN
ejpam-2083	177	18	,	,	PUNCT
ejpam-2083	177	19	this	this	DET
ejpam-2083	177	20	data	data	NOUN
ejpam-2083	177	21	does	do	AUX
ejpam-2083	177	22	not	not	PART
ejpam-2083	177	23	clearly	clearly	ADV
ejpam-2083	177	24	indicate	indicate	VERB
ejpam-2083	177	25	the	the	DET
ejpam-2083	177	26	true	true	ADJ
ejpam-2083	177	27	economic	economic	ADJ
ejpam-2083	177	28	value	value	NOUN
ejpam-2083	177	29	.	.	PUNCT
ejpam-2083	178	1	while	while	SCONJ
ejpam-2083	178	2	the	the	DET
ejpam-2083	178	3	fracking	fracking	NOUN
ejpam-2083	178	4	may	may	AUX
ejpam-2083	178	5	be	be	AUX
ejpam-2083	178	6	deemed	deem	VERB
ejpam-2083	178	7	successful	successful	ADJ
ejpam-2083	178	8	,	,	PUNCT
ejpam-2083	178	9	it	it	PRON
ejpam-2083	178	10	may	may	AUX
ejpam-2083	178	11	cost	cost	VERB
ejpam-2083	178	12	more	more	ADJ
ejpam-2083	178	13	to	to	PART
ejpam-2083	178	14	extract	extract	VERB
ejpam-2083	178	15	than	than	ADP
ejpam-2083	178	16	the	the	DET
ejpam-2083	178	17	value	value	NOUN
ejpam-2083	178	18	of	of	ADP
ejpam-2083	178	19	the	the	DET
ejpam-2083	178	20	gas	gas	NOUN
ejpam-2083	178	21	obtained	obtain	VERB
ejpam-2083	178	22	or	or	CCONJ
ejpam-2083	178	23	produced	produce	VERB
ejpam-2083	178	24	.	.	PUNCT
ejpam-2083	179	1	if	if	SCONJ
ejpam-2083	179	2	we	we	PRON
ejpam-2083	179	3	were	be	AUX
ejpam-2083	179	4	to	to	PART
ejpam-2083	179	5	define	define	VERB
ejpam-2083	179	6	successful	successful	ADJ
ejpam-2083	179	7	fracking	fracking	NOUN
ejpam-2083	179	8	as	as	ADP
ejpam-2083	179	9	obtaining	obtain	VERB
ejpam-2083	179	10	economical	economical	ADJ
ejpam-2083	179	11	natural	natural	ADJ
ejpam-2083	179	12	gas	gas	NOUN
ejpam-2083	179	13	,	,	PUNCT
ejpam-2083	179	14	the	the	DET
ejpam-2083	179	15	success	success	NOUN
ejpam-2083	179	16	of	of	ADP
ejpam-2083	179	17	the	the	DET
ejpam-2083	179	18	company	company	NOUN
ejpam-2083	179	19	decreases	decrease	VERB
ejpam-2083	179	20	from	from	ADP
ejpam-2083	179	21	66	66	NUM
ejpam-2083	179	22	%	%	NOUN
ejpam-2083	179	23	to	to	ADP
ejpam-2083	179	24	slightly	slightly	ADV
ejpam-2083	179	25	less	less	ADJ
ejpam-2083	179	26	than	than	ADP
ejpam-2083	179	27	40	40	NUM
ejpam-2083	179	28	%	%	NOUN
ejpam-2083	179	29	.	.	PUNCT
ejpam-2083	180	1	this	this	PRON
ejpam-2083	180	2	opens	open	VERB
ejpam-2083	180	3	up	up	ADP
ejpam-2083	180	4	new	new	ADJ
ejpam-2083	180	5	areas	area	NOUN
ejpam-2083	180	6	to	to	PART
ejpam-2083	180	7	examine	examine	VERB
ejpam-2083	180	8	,	,	PUNCT
ejpam-2083	180	9	which	which	PRON
ejpam-2083	180	10	we	we	PRON
ejpam-2083	180	11	will	will	AUX
ejpam-2083	180	12	be	be	AUX
ejpam-2083	180	13	focusing	focus	VERB
ejpam-2083	180	14	on	on	ADP
ejpam-2083	180	15	in	in	ADP
ejpam-2083	180	16	our	our	PRON
ejpam-2083	180	17	future	future	ADJ
ejpam-2083	180	18	studies	study	NOUN
ejpam-2083	180	19	.	.	PUNCT
ejpam-2083	181	1	acknowledgements	acknowledgement	VERB
ejpam-2083	181	2	the	the	DET
ejpam-2083	181	3	author	author	NOUN
ejpam-2083	181	4	would	would	AUX
ejpam-2083	181	5	like	like	VERB
ejpam-2083	181	6	to	to	PART
ejpam-2083	181	7	thank	thank	VERB
ejpam-2083	181	8	dr	dr	PROPN
ejpam-2083	181	9	.	.	PROPN
ejpam-2083	181	10	j.andrew	j.andrew	PROPN
ejpam-2083	181	11	howe	howe	NOUN
ejpam-2083	181	12	and	and	CCONJ
ejpam-2083	181	13	clarissa	clarissa	PROPN
ejpam-2083	181	14	stevens	stevens	PROPN
ejpam-2083	181	15	-	-	PUNCT
ejpam-2083	181	16	guille	guille	NOUN
ejpam-2083	181	17	for	for	ADP
ejpam-2083	181	18	reviewing	review	VERB
ejpam-2083	181	19	the	the	DET
ejpam-2083	181	20	paper	paper	NOUN
ejpam-2083	181	21	and	and	CCONJ
ejpam-2083	181	22	for	for	ADP
ejpam-2083	181	23	the	the	DET
ejpam-2083	181	24	grammatical	grammatical	ADJ
ejpam-2083	181	25	corrections	correction	NOUN
ejpam-2083	181	26	.	.	PUNCT
ejpam-2083	182	1	references	reference	NOUN
ejpam-2083	182	2	[	[	X
ejpam-2083	182	3	1	1	NUM
ejpam-2083	182	4	]	]	X
ejpam-2083	182	5	h.	h.	NOUN
ejpam-2083	182	6	akaike	akaike	PROPN
ejpam-2083	182	7	.	.	PUNCT
ejpam-2083	183	1	information	information	NOUN
ejpam-2083	183	2	theory	theory	NOUN
ejpam-2083	183	3	and	and	CCONJ
ejpam-2083	183	4	an	an	DET
ejpam-2083	183	5	extension	extension	NOUN
ejpam-2083	183	6	of	of	ADP
ejpam-2083	183	7	the	the	DET
ejpam-2083	183	8	maximum	maximum	ADJ
ejpam-2083	183	9	likelihood	likelihood	NOUN
ejpam-2083	183	10	principle	principle	NOUN
ejpam-2083	183	11	.	.	PUNCT
ejpam-2083	184	1	in	in	ADP
ejpam-2083	184	2	b.n	b.n	PROPN
ejpam-2083	184	3	.	.	PROPN
ejpam-2083	184	4	petrox	petrox	PROPN
ejpam-2083	184	5	and	and	CCONJ
ejpam-2083	184	6	f.	f.	PROPN
ejpam-2083	184	7	csaki	csaki	PROPN
ejpam-2083	184	8	,	,	PUNCT
ejpam-2083	184	9	editors	editor	NOUN
ejpam-2083	184	10	,	,	PUNCT
ejpam-2083	184	11	second	second	ADJ
ejpam-2083	184	12	international	international	ADJ
ejpam-2083	184	13	symposium	symposium	NOUN
ejpam-2083	184	14	on	on	ADP
ejpam-2083	184	15	information	information	NOUN
ejpam-2083	184	16	theory	theory	NOUN
ejpam-2083	184	17	.	.	PUNCT
ejpam-2083	185	1	,	,	PUNCT
ejpam-2083	185	2	pages	page	NOUN
ejpam-2083	185	3	267–281	267–281	NUM
ejpam-2083	185	4	,	,	PUNCT
ejpam-2083	185	5	budapest	budapest	NOUN
ejpam-2083	185	6	,	,	PUNCT
ejpam-2083	185	7	1973	1973	NUM
ejpam-2083	185	8	.	.	PUNCT
ejpam-2083	186	1	academiai	academiai	PROPN
ejpam-2083	186	2	kiado	kiado	PROPN
ejpam-2083	186	3	.	.	PUNCT
ejpam-2083	187	1	[	[	X
ejpam-2083	187	2	2	2	X
ejpam-2083	187	3	]	]	PUNCT
ejpam-2083	187	4	o.	o.	NOUN
ejpam-2083	187	5	akbilgic	akbilgic	PROPN
ejpam-2083	187	6	and	and	CCONJ
ejpam-2083	187	7	h.	h.	PROPN
ejpam-2083	187	8	bozdogan	bozdogan	PROPN
ejpam-2083	187	9	.	.	PUNCT
ejpam-2083	188	1	predictive	predictive	ADJ
ejpam-2083	188	2	subset	subset	NOUN
ejpam-2083	188	3	selection	selection	NOUN
ejpam-2083	188	4	using	use	VERB
ejpam-2083	188	5	regression	regression	NOUN
ejpam-2083	188	6	trees	tree	NOUN
ejpam-2083	188	7	and	and	CCONJ
ejpam-2083	188	8	references	reference	NOUN
ejpam-2083	188	9	386	386	NUM
ejpam-2083	188	10	rbf	rbf	PROPN
ejpam-2083	188	11	neural	neural	ADJ
ejpam-2083	188	12	networks	network	NOUN
ejpam-2083	188	13	hybridized	hybridize	VERB
ejpam-2083	188	14	with	with	ADP
ejpam-2083	188	15	the	the	DET
ejpam-2083	188	16	genetic	genetic	ADJ
ejpam-2083	188	17	algorithm	algorithm	NOUN
ejpam-2083	188	18	.	.	PUNCT
ejpam-2083	189	1	european	european	ADJ
ejpam-2083	189	2	journal	journal	PROPN
ejpam-2083	189	3	of	of	ADP
ejpam-2083	189	4	pure	pure	ADJ
ejpam-2083	189	5	and	and	CCONJ
ejpam-2083	189	6	applied	applied	ADJ
ejpam-2083	189	7	mathematics	mathematic	NOUN
ejpam-2083	189	8	,	,	PUNCT
ejpam-2083	189	9	4:467–485	4:467–485	NOUN
ejpam-2083	189	10	,	,	PUNCT
ejpam-2083	189	11	2011	2011	NUM
ejpam-2083	189	12	.	.	PUNCT
ejpam-2083	190	1	[	[	X
ejpam-2083	190	2	3	3	NUM
ejpam-2083	190	3	]	]	X
ejpam-2083	190	4	o.	o.	PROPN
ejpam-2083	190	5	akbilgic	akbilgic	PROPN
ejpam-2083	190	6	,	,	PUNCT
ejpam-2083	190	7	h.	h.	PROPN
ejpam-2083	190	8	bozdogan	bozdogan	PROPN
ejpam-2083	190	9	,	,	PUNCT
ejpam-2083	190	10	and	and	CCONJ
ejpam-2083	190	11	m.e	m.e	PROPN
ejpam-2083	190	12	.	.	PROPN
ejpam-2083	190	13	balaban	balaban	PROPN
ejpam-2083	190	14	.	.	PUNCT
ejpam-2083	191	1	a	a	DET
ejpam-2083	191	2	novel	novel	ADJ
ejpam-2083	191	3	hybrid	hybrid	ADJ
ejpam-2083	191	4	rbf	rbf	PROPN
ejpam-2083	191	5	neural	neural	PROPN
ejpam-2083	191	6	networks	network	NOUN
ejpam-2083	191	7	model	model	NOUN
ejpam-2083	191	8	as	as	ADP
ejpam-2083	191	9	a	a	DET
ejpam-2083	191	10	forecaster	forecaster	NOUN
ejpam-2083	191	11	.	.	PUNCT
ejpam-2083	192	1	statistics	statistic	NOUN
ejpam-2083	192	2	and	and	CCONJ
ejpam-2083	192	3	computing	computing	NOUN
ejpam-2083	192	4	,	,	PUNCT
ejpam-2083	192	5	2013	2013	NUM
ejpam-2083	192	6	.	.	PUNCT
ejpam-2083	193	1	[	[	X
ejpam-2083	193	2	4	4	NUM
ejpam-2083	193	3	]	]	X
ejpam-2083	193	4	l.	l.	PROPN
ejpam-2083	193	5	breiman	breiman	PROPN
ejpam-2083	193	6	,	,	PUNCT
ejpam-2083	193	7	j.	j.	PROPN
ejpam-2083	193	8	freidman	freidman	PROPN
ejpam-2083	193	9	,	,	PUNCT
ejpam-2083	193	10	j.	j.	PROPN
ejpam-2083	193	11	c.	c.	PROPN
ejpam-2083	193	12	stone	stone	PROPN
ejpam-2083	193	13	,	,	PUNCT
ejpam-2083	193	14	and	and	CCONJ
ejpam-2083	193	15	r.	r.	PROPN
ejpam-2083	193	16	a.	a.	PROPN
ejpam-2083	193	17	olsen	olsen	PROPN
ejpam-2083	193	18	.	.	PUNCT
ejpam-2083	194	1	classification	classification	NOUN
ejpam-2083	194	2	and	and	CCONJ
ejpam-2083	194	3	regression	regression	NOUN
ejpam-2083	194	4	trees	tree	NOUN
ejpam-2083	194	5	.	.	PUNCT
ejpam-2083	195	1	chapman	chapman	PROPN
ejpam-2083	195	2	&	&	CCONJ
ejpam-2083	195	3	hall	hall	PROPN
ejpam-2083	195	4	,	,	PUNCT
ejpam-2083	195	5	1984	1984	NUM
ejpam-2083	195	6	.	.	PUNCT
ejpam-2083	196	1	[	[	X
ejpam-2083	196	2	5	5	X
ejpam-2083	196	3	]	]	PUNCT
ejpam-2083	196	4	j.	j.	PROPN
ejpam-2083	196	5	caers	caers	PROPN
ejpam-2083	196	6	.	.	PUNCT
ejpam-2083	197	1	petroleum	petroleum	NOUN
ejpam-2083	197	2	geostatistics	geostatistic	NOUN
ejpam-2083	197	3	.	.	PUNCT
ejpam-2083	198	1	society	society	NOUN
ejpam-2083	198	2	of	of	ADP
ejpam-2083	198	3	petroleum	petroleum	NOUN
ejpam-2083	198	4	engineers	engineer	NOUN
ejpam-2083	198	5	,	,	PUNCT
ejpam-2083	198	6	2005	2005	NUM
ejpam-2083	198	7	.	.	PUNCT
ejpam-2083	199	1	[	[	X
ejpam-2083	199	2	6	6	NUM
ejpam-2083	199	3	]	]	X
ejpam-2083	199	4	d.m	d.m	PROPN
ejpam-2083	199	5	.	.	PROPN
ejpam-2083	199	6	carson	carson	PROPN
ejpam-2083	199	7	.	.	PUNCT
ejpam-2083	200	1	our	our	PRON
ejpam-2083	200	2	petroleum	petroleum	NOUN
ejpam-2083	200	3	challenge	challenge	NOUN
ejpam-2083	200	4	:	:	PUNCT
ejpam-2083	200	5	sustainability	sustainability	NOUN
ejpam-2083	200	6	into	into	ADP
ejpam-2083	200	7	21st	21st	ADJ
ejpam-2083	200	8	century	century	NOUN
ejpam-2083	200	9	.	.	PUNCT
ejpam-2083	201	1	canadian	canadian	ADJ
ejpam-2083	201	2	centre	centre	NOUN
ejpam-2083	201	3	for	for	ADP
ejpam-2083	201	4	energy	energy	NOUN
ejpam-2083	201	5	information	information	NOUN
ejpam-2083	201	6	,	,	PUNCT
ejpam-2083	201	7	7th	7th	ADJ
ejpam-2083	201	8	edition	edition	NOUN
ejpam-2083	201	9	,	,	PUNCT
ejpam-2083	201	10	2009	2009	NUM
ejpam-2083	201	11	.	.	PUNCT
ejpam-2083	202	1	[	[	X
ejpam-2083	202	2	7	7	NUM
ejpam-2083	202	3	]	]	SYM
ejpam-2083	202	4	s	s	PART
ejpam-2083	202	5	haykin	haykin	NOUN
ejpam-2083	202	6	.	.	PUNCT
ejpam-2083	203	1	neural	neural	ADJ
ejpam-2083	203	2	networks	network	NOUN
ejpam-2083	203	3	:	:	PUNCT
ejpam-2083	203	4	a	a	DET
ejpam-2083	203	5	comprehensive	comprehensive	ADJ
ejpam-2083	203	6	foundation	foundation	NOUN
ejpam-2083	203	7	.	.	PUNCT
ejpam-2083	204	1	prentice	prentice	PROPN
ejpam-2083	204	2	hall	hall	PROPN
ejpam-2083	204	3	„	„	PUNCT
ejpam-2083	204	4	new	new	PROPN
ejpam-2083	204	5	jersey	jersey	PROPN
ejpam-2083	204	6	,	,	PUNCT
ejpam-2083	204	7	1999	1999	NUM
ejpam-2083	204	8	.	.	PUNCT
ejpam-2083	205	1	[	[	X
ejpam-2083	205	2	8	8	NUM
ejpam-2083	205	3	]	]	X
ejpam-2083	205	4	kurt	kurt	PROPN
ejpam-2083	205	5	hornik	hornik	PROPN
ejpam-2083	205	6	.	.	PUNCT
ejpam-2083	206	1	the	the	DET
ejpam-2083	206	2	r	r	PROPN
ejpam-2083	206	3	faq	faq	NOUN
ejpam-2083	206	4	,	,	PUNCT
ejpam-2083	206	5	2013	2013	NUM
ejpam-2083	206	6	.	.	PUNCT
ejpam-2083	207	1	[	[	X
ejpam-2083	207	2	9	9	NUM
ejpam-2083	207	3	]	]	X
ejpam-2083	207	4	r.j	r.j	PROPN
ejpam-2083	207	5	.	.	PROPN
ejpam-2083	207	6	howlett	howlett	PROPN
ejpam-2083	207	7	and	and	CCONJ
ejpam-2083	207	8	l.c	l.c	PROPN
ejpam-2083	207	9	.	.	PROPN
ejpam-2083	207	10	jain	jain	PROPN
ejpam-2083	207	11	.	.	PUNCT
ejpam-2083	208	1	radial	radial	ADJ
ejpam-2083	208	2	basis	basis	NOUN
ejpam-2083	208	3	function	function	NOUN
ejpam-2083	208	4	networks	network	NOUN
ejpam-2083	208	5	1	1	NUM
ejpam-2083	208	6	:	:	PUNCT
ejpam-2083	208	7	recent	recent	ADJ
ejpam-2083	208	8	developments	development	NOUN
ejpam-2083	208	9	in	in	ADP
ejpam-2083	208	10	theory	theory	NOUN
ejpam-2083	208	11	and	and	CCONJ
ejpam-2083	208	12	applications	application	NOUN
ejpam-2083	208	13	.	.	PUNCT
ejpam-2083	209	1	physica	physica	PROPN
ejpam-2083	209	2	verlag	verlag	PROPN
ejpam-2083	209	3	,	,	PUNCT
ejpam-2083	209	4	new	new	PROPN
ejpam-2083	209	5	york	york	PROPN
ejpam-2083	209	6	,	,	PUNCT
ejpam-2083	209	7	2001	2001	NUM
ejpam-2083	209	8	.	.	PUNCT
ejpam-2083	210	1	[	[	X
ejpam-2083	210	2	10	10	NUM
ejpam-2083	210	3	]	]	X
ejpam-2083	210	4	j.r	j.r	PROPN
ejpam-2083	210	5	.	.	PROPN
ejpam-2083	210	6	jones	jones	PROPN
ejpam-2083	210	7	and	and	CCONJ
ejpam-2083	210	8	l.k	l.k	PROPN
ejpam-2083	210	9	.	.	PROPN
ejpam-2083	210	10	britt	britt	PROPN
ejpam-2083	210	11	.	.	PUNCT
ejpam-2083	211	1	design	design	NOUN
ejpam-2083	211	2	and	and	CCONJ
ejpam-2083	211	3	appraisal	appraisal	NOUN
ejpam-2083	211	4	of	of	ADP
ejpam-2083	211	5	hydraulic	hydraulic	ADJ
ejpam-2083	211	6	fractures	fracture	NOUN
ejpam-2083	211	7	.	.	PUNCT
ejpam-2083	212	1	society	society	NOUN
ejpam-2083	212	2	of	of	ADP
ejpam-2083	212	3	petroleum	petroleum	NOUN
ejpam-2083	212	4	engineers	engineer	NOUN
ejpam-2083	212	5	,	,	PUNCT
ejpam-2083	212	6	2009	2009	NUM
ejpam-2083	212	7	.	.	PUNCT
ejpam-2083	213	1	[	[	X
ejpam-2083	213	2	11	11	NUM
ejpam-2083	213	3	]	]	PUNCT
ejpam-2083	213	4	m.	m.	NOUN
ejpam-2083	213	5	kubat	kubat	PROPN
ejpam-2083	213	6	.	.	PUNCT
ejpam-2083	214	1	decision	decision	NOUN
ejpam-2083	214	2	trees	tree	NOUN
ejpam-2083	214	3	can	can	AUX
ejpam-2083	214	4	initialize	initialize	VERB
ejpam-2083	214	5	radial	radial	ADJ
ejpam-2083	214	6	basis	basis	NOUN
ejpam-2083	214	7	function	function	NOUN
ejpam-2083	214	8	networks	network	NOUN
ejpam-2083	214	9	.	.	PUNCT
ejpam-2083	215	1	transactions	transaction	NOUN
ejpam-2083	215	2	on	on	ADP
ejpam-2083	215	3	neural	neural	ADJ
ejpam-2083	215	4	networks	network	NOUN
ejpam-2083	215	5	,	,	PUNCT
ejpam-2083	215	6	9:813–821	9:813–821	NUM
ejpam-2083	215	7	,	,	PUNCT
ejpam-2083	215	8	1998	1998	NUM
ejpam-2083	215	9	.	.	PUNCT
ejpam-2083	216	1	[	[	X
ejpam-2083	216	2	12	12	NUM
ejpam-2083	216	3	]	]	PUNCT
ejpam-2083	216	4	m.	m.	PROPN
ejpam-2083	216	5	orr	orr	PROPN
ejpam-2083	216	6	.	.	PUNCT
ejpam-2083	217	1	combining	combine	VERB
ejpam-2083	217	2	regression	regression	NOUN
ejpam-2083	217	3	trees	tree	NOUN
ejpam-2083	217	4	and	and	CCONJ
ejpam-2083	217	5	rbfs	rbfs	NOUN
ejpam-2083	217	6	.	.	PUNCT
ejpam-2083	218	1	international	international	ADJ
ejpam-2083	218	2	journal	journal	PROPN
ejpam-2083	218	3	of	of	ADP
ejpam-2083	218	4	neural	neural	ADJ
ejpam-2083	218	5	systems	system	NOUN
ejpam-2083	218	6	,	,	PUNCT
ejpam-2083	218	7	10:453–465	10:453–465	NUM
ejpam-2083	218	8	,	,	PUNCT
ejpam-2083	218	9	2000	2000	NUM
ejpam-2083	218	10	.	.	PUNCT
ejpam-2083	219	1	[	[	X
ejpam-2083	219	2	13	13	NUM
ejpam-2083	219	3	]	]	PUNCT
ejpam-2083	219	4	t.	t.	PROPN
ejpam-2083	219	5	poggio	poggio	PROPN
ejpam-2083	219	6	and	and	CCONJ
ejpam-2083	219	7	f.	f.	PROPN
ejpam-2083	219	8	girosi	girosi	PROPN
ejpam-2083	219	9	.	.	PUNCT
ejpam-2083	220	1	regularization	regularization	NOUN
ejpam-2083	220	2	algorithms	algorithm	NOUN
ejpam-2083	220	3	for	for	ADP
ejpam-2083	220	4	learning	learn	VERB
ejpam-2083	220	5	that	that	PRON
ejpam-2083	220	6	are	be	AUX
ejpam-2083	220	7	equivalent	equivalent	ADJ
ejpam-2083	220	8	to	to	ADP
ejpam-2083	220	9	multilayer	multilayer	ADJ
ejpam-2083	220	10	networks	network	NOUN
ejpam-2083	220	11	.	.	PUNCT
ejpam-2083	221	1	science	science	NOUN
ejpam-2083	221	2	,	,	PUNCT
ejpam-2083	221	3	new	new	ADJ
ejpam-2083	221	4	-	-	PUNCT
ejpam-2083	221	5	series	series	NOUN
ejpam-2083	221	6	,	,	PUNCT
ejpam-2083	221	7	247:978–982	247:978–982	NUM
ejpam-2083	221	8	,	,	PUNCT
ejpam-2083	221	9	1990	1990	NUM
ejpam-2083	221	10	.	.	PUNCT
ejpam-2083	222	1	[	[	X
ejpam-2083	222	2	14	14	NUM
ejpam-2083	222	3	]	]	X
ejpam-2083	222	4	i.h	i.h	PROPN
ejpam-2083	222	5	.	.	PROPN
ejpam-2083	222	6	witten	witten	PROPN
ejpam-2083	222	7	,	,	PUNCT
ejpam-2083	222	8	e.	e.	PROPN
ejpam-2083	222	9	frank	frank	PROPN
ejpam-2083	222	10	,	,	PUNCT
ejpam-2083	222	11	and	and	CCONJ
ejpam-2083	222	12	m.a	m.a	PROPN
ejpam-2083	222	13	.	.	PROPN
ejpam-2083	222	14	hall	hall	PROPN
ejpam-2083	222	15	.	.	PUNCT
ejpam-2083	223	1	data	datum	NOUN
ejpam-2083	223	2	mining	mining	NOUN
ejpam-2083	223	3	:	:	PUNCT
ejpam-2083	223	4	practical	practical	ADJ
ejpam-2083	223	5	machine	machine	NOUN
ejpam-2083	223	6	learning	learning	NOUN
ejpam-2083	223	7	tools	tool	NOUN
ejpam-2083	223	8	and	and	CCONJ
ejpam-2083	223	9	techniques	technique	NOUN
ejpam-2083	223	10	.	.	PUNCT
ejpam-2083	224	1	morgan	morgan	PROPN
ejpam-2083	224	2	kaufman	kaufman	PROPN
ejpam-2083	224	3	,	,	PUNCT
ejpam-2083	224	4	3rd	3rd	PROPN
ejpam-2083	224	5	edition	edition	NOUN
ejpam-2083	224	6	,	,	PUNCT
ejpam-2083	224	7	2011	2011	NUM
ejpam-2083	224	8	.	.	PUNCT
ejpam-2083	225	1	[	[	X
ejpam-2083	225	2	15	15	NUM
ejpam-2083	225	3	]	]	X
ejpam-2083	225	4	c.h	c.h	PROPN
ejpam-2083	225	5	.	.	PROPN
ejpam-2083	225	6	yew	yew	PROPN
ejpam-2083	225	7	.	.	PUNCT
ejpam-2083	226	1	mechanics	mechanic	NOUN
ejpam-2083	226	2	of	of	ADP
ejpam-2083	226	3	hydraulic	hydraulic	ADJ
ejpam-2083	226	4	fracturing	fracturing	NOUN
ejpam-2083	226	5	.	.	PUNCT
ejpam-2083	227	1	gulf	gulf	PROPN
ejpam-2083	227	2	professional	professional	ADJ
ejpam-2083	227	3	publishing	publishing	NOUN
ejpam-2083	227	4	,	,	PUNCT
ejpam-2083	227	5	1st	1st	PROPN
ejpam-2083	227	6	edition	edition	NOUN
ejpam-2083	227	7	,	,	PUNCT
ejpam-2083	227	8	1997	1997	NUM
ejpam-2083	227	9	.	.	PUNCT