id	sid	tid	token	lemma	pos
easat-5823	1	1	edelweiss	edelweiss	PROPN
easat-5823	1	2	applied	apply	VERB
easat-5823	1	3	science	science	NOUN
easat-5823	1	4	and	and	CCONJ
easat-5823	1	5	technology	technology	NOUN
easat-5823	1	6	issn	issn	PROPN
easat-5823	1	7	:	:	PUNCT
easat-5823	1	8	2576	2576	NUM
easat-5823	1	9	-	-	SYM
easat-5823	1	10	8484	8484	NUM
easat-5823	1	11	vol	vol	NOUN
easat-5823	1	12	.	.	PROPN
easat-5823	2	1	9	9	NUM
easat-5823	2	2	,	,	PUNCT
easat-5823	2	3	no	no	INTJ
easat-5823	2	4	.	.	NOUN
easat-5823	2	5	3	3	NUM
easat-5823	2	6	,	,	PUNCT
easat-5823	2	7	2482	2482	NUM
easat-5823	2	8	-	-	SYM
easat-5823	2	9	2494	2494	NUM
easat-5823	2	10	2025	2025	NUM
easat-5823	2	11	publisher	publisher	NOUN
easat-5823	2	12	:	:	PUNCT
easat-5823	2	13	learning	learn	VERB
easat-5823	2	14	gate	gate	NOUN
easat-5823	2	15	doi	doi	PROPN
easat-5823	2	16	:	:	PUNCT
easat-5823	2	17	10.55214/25768484.v9i3.5823	10.55214/25768484.v9i3.5823	NUM
easat-5823	2	18	©	©	PROPN
easat-5823	2	19	2025	2025	NUM
easat-5823	2	20	by	by	ADP
easat-5823	2	21	the	the	DET
easat-5823	2	22	authors	author	NOUN
easat-5823	2	23	;	;	PUNCT
easat-5823	2	24	licensee	licensee	PROPN
easat-5823	2	25	learning	learning	NOUN
easat-5823	2	26	gate	gate	NOUN
easat-5823	3	1	©	©	PROPN
easat-5823	3	2	2025	2025	NUM
easat-5823	3	3	by	by	ADP
easat-5823	3	4	the	the	DET
easat-5823	3	5	authors	author	NOUN
easat-5823	3	6	;	;	PUNCT
easat-5823	3	7	licensee	licensee	PROPN
easat-5823	3	8	learning	learning	NOUN
easat-5823	3	9	gate	gate	NOUN
easat-5823	3	10	history	history	NOUN
easat-5823	3	11	:	:	PUNCT
easat-5823	3	12	received	receive	VERB
easat-5823	3	13	:	:	PUNCT
easat-5823	3	14	16	16	NUM
easat-5823	3	15	january	january	PROPN
easat-5823	3	16	2025	2025	NUM
easat-5823	3	17	;	;	PUNCT
easat-5823	3	18	revised	revise	VERB
easat-5823	3	19	:	:	PUNCT
easat-5823	3	20	5	5	NUM
easat-5823	3	21	march	march	NOUN
easat-5823	3	22	2025	2025	NUM
easat-5823	3	23	;	;	PUNCT
easat-5823	3	24	accepted	accept	VERB
easat-5823	3	25	:	:	PUNCT
easat-5823	3	26	11	11	NUM
easat-5823	3	27	march	march	NOUN
easat-5823	3	28	2025	2025	NUM
easat-5823	3	29	;	;	PUNCT
easat-5823	3	30	published	publish	VERB
easat-5823	3	31	:	:	PUNCT
easat-5823	4	1	27	27	NUM
easat-5823	4	2	march	march	NOUN
easat-5823	4	3	2025	2025	NUM
easat-5823	4	4	*	*	PUNCT
easat-5823	4	5	correspondence	correspondence	NOUN
easat-5823	4	6	:	:	PUNCT
easat-5823	4	7	alexander012@binus.ac.id	alexander012@binus.ac.id	NOUN
easat-5823	4	8	fraud	fraud	NOUN
easat-5823	4	9	credit	credit	NOUN
easat-5823	4	10	card	card	NOUN
easat-5823	4	11	transaction	transaction	NOUN
easat-5823	4	12	detection	detection	NOUN
easat-5823	4	13	using	use	VERB
easat-5823	4	14	hybrid	hybrid	ADJ
easat-5823	4	15	multilayer	multilayer	ADJ
easat-5823	4	16	perceptronrandom	perceptronrandom	PROPN
easat-5823	4	17	forest	forest	NOUN
easat-5823	4	18	method	method	PROPN
easat-5823	4	19	alexander	alexander	PROPN
easat-5823	4	20	subagio1	subagio1	PROPN
easat-5823	4	21	*	*	PROPN
easat-5823	4	22	,	,	PUNCT
easat-5823	4	23	ditdit	ditdit	NOUN
easat-5823	4	24	nugeraha	nugeraha	NOUN
easat-5823	4	25	utama2	utama2	PROPN
easat-5823	5	1	1,2computer	1,2computer	NUM
easat-5823	5	2	science	science	NOUN
easat-5823	5	3	department	department	NOUN
easat-5823	5	4	,	,	PUNCT
easat-5823	5	5	binus	binus	ADJ
easat-5823	5	6	graduate	graduate	NOUN
easat-5823	5	7	program	program	NOUN
easat-5823	5	8	–	–	PUNCT
easat-5823	5	9	master	master	NOUN
easat-5823	5	10	of	of	ADP
easat-5823	5	11	computer	computer	NOUN
easat-5823	5	12	science	science	NOUN
easat-5823	5	13	,	,	PUNCT
easat-5823	5	14	bina	bina	PROPN
easat-5823	5	15	nusantara	nusantara	PROPN
easat-5823	5	16	university	university	PROPN
easat-5823	5	17	,	,	PUNCT
easat-5823	5	18	jakarta	jakarta	PROPN
easat-5823	5	19	,	,	PUNCT
easat-5823	5	20	indonesia	indonesia	PROPN
easat-5823	5	21	;	;	PUNCT
easat-5823	5	22	alexander012@binus.ac.id	alexander012@binus.ac.id	PROPN
easat-5823	5	23	(	(	PUNCT
easat-5823	5	24	a.s	a.s	PROPN
easat-5823	5	25	.	.	PROPN
easat-5823	5	26	)	)	PUNCT
easat-5823	6	1	ditdit.utama@binus.edu	ditdit.utama@binus.edu	PROPN
easat-5823	6	2	(	(	PUNCT
easat-5823	6	3	d.n.u	d.n.u	PROPN
easat-5823	6	4	.	.	PUNCT
easat-5823	6	5	)	)	PUNCT
easat-5823	7	1	abstract	abstract	ADJ
easat-5823	7	2	:	:	PUNCT
easat-5823	7	3	credit	credit	NOUN
easat-5823	7	4	card	card	NOUN
easat-5823	7	5	fraud	fraud	NOUN
easat-5823	7	6	is	be	AUX
easat-5823	7	7	a	a	DET
easat-5823	7	8	leading	lead	VERB
easat-5823	7	9	crime	crime	NOUN
easat-5823	7	10	with	with	ADP
easat-5823	7	11	rapid	rapid	ADJ
easat-5823	7	12	growth	growth	NOUN
easat-5823	7	13	in	in	ADP
easat-5823	7	14	the	the	DET
easat-5823	7	15	world	world	NOUN
easat-5823	7	16	.	.	PUNCT
easat-5823	8	1	this	this	PRON
easat-5823	8	2	is	be	AUX
easat-5823	8	3	due	due	ADJ
easat-5823	8	4	to	to	ADP
easat-5823	8	5	credit	credit	NOUN
easat-5823	8	6	cards	card	NOUN
easat-5823	8	7	being	be	AUX
easat-5823	8	8	one	one	NUM
easat-5823	8	9	of	of	ADP
easat-5823	8	10	the	the	DET
easat-5823	8	11	most	most	ADV
easat-5823	8	12	popular	popular	ADJ
easat-5823	8	13	payment	payment	NOUN
easat-5823	8	14	options	option	NOUN
easat-5823	8	15	worldwide	worldwide	ADV
easat-5823	8	16	.	.	PUNCT
easat-5823	9	1	to	to	PART
easat-5823	9	2	address	address	VERB
easat-5823	9	3	this	this	DET
easat-5823	9	4	problem	problem	NOUN
easat-5823	9	5	,	,	PUNCT
easat-5823	9	6	there	there	PRON
easat-5823	9	7	needs	need	VERB
easat-5823	9	8	to	to	PART
easat-5823	9	9	be	be	AUX
easat-5823	9	10	a	a	DET
easat-5823	9	11	robust	robust	ADJ
easat-5823	9	12	and	and	CCONJ
easat-5823	9	13	efficient	efficient	ADJ
easat-5823	9	14	method	method	NOUN
easat-5823	9	15	to	to	PART
easat-5823	9	16	accurately	accurately	ADV
easat-5823	9	17	identify	identify	VERB
easat-5823	9	18	fraudulent	fraudulent	ADJ
easat-5823	9	19	transactions	transaction	NOUN
easat-5823	9	20	.	.	PUNCT
easat-5823	10	1	this	this	DET
easat-5823	10	2	study	study	NOUN
easat-5823	10	3	aims	aim	VERB
easat-5823	10	4	to	to	PART
easat-5823	10	5	investigate	investigate	VERB
easat-5823	10	6	the	the	DET
easat-5823	10	7	performance	performance	NOUN
easat-5823	10	8	of	of	ADP
easat-5823	10	9	a	a	DET
easat-5823	10	10	hybrid	hybrid	ADJ
easat-5823	10	11	method	method	NOUN
easat-5823	10	12	that	that	PRON
easat-5823	10	13	combines	combine	VERB
easat-5823	10	14	multilayer	multilayer	ADJ
easat-5823	10	15	perceptron	perceptron	PROPN
easat-5823	10	16	(	(	PUNCT
easat-5823	10	17	mlp	mlp	PROPN
easat-5823	10	18	)	)	PUNCT
easat-5823	10	19	as	as	ADP
easat-5823	10	20	a	a	DET
easat-5823	10	21	feature	feature	NOUN
easat-5823	10	22	extractor	extractor	NOUN
easat-5823	10	23	and	and	CCONJ
easat-5823	10	24	a	a	DET
easat-5823	10	25	random	random	ADJ
easat-5823	10	26	forest	forest	NOUN
easat-5823	10	27	(	(	PUNCT
easat-5823	10	28	rf	rf	NOUN
easat-5823	10	29	)	)	PUNCT
easat-5823	10	30	classifier	classifier	NOUN
easat-5823	10	31	for	for	ADP
easat-5823	10	32	detecting	detect	VERB
easat-5823	10	33	fraudulent	fraudulent	ADJ
easat-5823	10	34	credit	credit	NOUN
easat-5823	10	35	card	card	NOUN
easat-5823	10	36	transactions	transaction	NOUN
easat-5823	10	37	.	.	PUNCT
easat-5823	11	1	the	the	DET
easat-5823	11	2	mlp	mlp	NOUN
easat-5823	11	3	is	be	AUX
easat-5823	11	4	used	use	VERB
easat-5823	11	5	to	to	PART
easat-5823	11	6	capture	capture	VERB
easat-5823	11	7	complex	complex	ADJ
easat-5823	11	8	patterns	pattern	NOUN
easat-5823	11	9	in	in	ADP
easat-5823	11	10	the	the	DET
easat-5823	11	11	transaction	transaction	NOUN
easat-5823	11	12	data	datum	NOUN
easat-5823	11	13	,	,	PUNCT
easat-5823	11	14	while	while	SCONJ
easat-5823	11	15	the	the	DET
easat-5823	11	16	rf	rf	NOUN
easat-5823	11	17	classifier	classifier	NOUN
easat-5823	11	18	is	be	AUX
easat-5823	11	19	used	use	VERB
easat-5823	11	20	to	to	PART
easat-5823	11	21	make	make	VERB
easat-5823	11	22	robust	robust	ADJ
easat-5823	11	23	and	and	CCONJ
easat-5823	11	24	accurate	accurate	ADJ
easat-5823	11	25	predictions	prediction	NOUN
easat-5823	11	26	.	.	PUNCT
easat-5823	12	1	the	the	DET
easat-5823	12	2	performance	performance	NOUN
easat-5823	12	3	of	of	ADP
easat-5823	12	4	the	the	DET
easat-5823	12	5	proposed	propose	VERB
easat-5823	12	6	model	model	NOUN
easat-5823	12	7	was	be	AUX
easat-5823	12	8	compared	compare	VERB
easat-5823	12	9	with	with	ADP
easat-5823	12	10	standalone	standalone	ADJ
easat-5823	12	11	mlp	mlp	NOUN
easat-5823	12	12	and	and	CCONJ
easat-5823	12	13	rf	rf	AUX
easat-5823	12	14	using	use	VERB
easat-5823	12	15	several	several	ADJ
easat-5823	12	16	evaluation	evaluation	NOUN
easat-5823	12	17	metrics	metric	NOUN
easat-5823	12	18	.	.	PUNCT
easat-5823	13	1	the	the	DET
easat-5823	13	2	proposed	propose	VERB
easat-5823	13	3	method	method	NOUN
easat-5823	13	4	achieved	achieve	VERB
easat-5823	13	5	the	the	DET
easat-5823	13	6	best	good	ADJ
easat-5823	13	7	performance	performance	NOUN
easat-5823	13	8	among	among	ADP
easat-5823	13	9	other	other	ADJ
easat-5823	13	10	methods	method	NOUN
easat-5823	13	11	,	,	PUNCT
easat-5823	13	12	with	with	ADP
easat-5823	13	13	an	an	DET
easat-5823	13	14	accuracy	accuracy	NOUN
easat-5823	13	15	of	of	ADP
easat-5823	13	16	99.949	99.949	NUM
easat-5823	13	17	%	%	NOUN
easat-5823	13	18	,	,	PUNCT
easat-5823	13	19	precision	precision	NOUN
easat-5823	13	20	of	of	ADP
easat-5823	13	21	87.097	87.097	NUM
easat-5823	13	22	%	%	NOUN
easat-5823	13	23	,	,	PUNCT
easat-5823	13	24	recall	recall	NOUN
easat-5823	13	25	of	of	ADP
easat-5823	13	26	82.653	82.653	NUM
easat-5823	13	27	%	%	NOUN
easat-5823	13	28	,	,	PUNCT
easat-5823	13	29	and	and	CCONJ
easat-5823	13	30	f1score	f1score	NOUN
easat-5823	13	31	of	of	ADP
easat-5823	13	32	84.817	84.817	NUM
easat-5823	13	33	%	%	NOUN
easat-5823	13	34	.	.	PUNCT
easat-5823	14	1	this	this	DET
easat-5823	14	2	result	result	NOUN
easat-5823	14	3	shows	show	VERB
easat-5823	14	4	the	the	DET
easat-5823	14	5	ability	ability	NOUN
easat-5823	14	6	of	of	ADP
easat-5823	14	7	the	the	DET
easat-5823	14	8	proposed	propose	VERB
easat-5823	14	9	method	method	NOUN
easat-5823	14	10	by	by	ADP
easat-5823	14	11	combining	combine	VERB
easat-5823	14	12	the	the	DET
easat-5823	14	13	strengths	strength	NOUN
easat-5823	14	14	of	of	ADP
easat-5823	14	15	mlp	mlp	PROPN
easat-5823	14	16	as	as	ADP
easat-5823	14	17	a	a	DET
easat-5823	14	18	feature	feature	NOUN
easat-5823	14	19	extractor	extractor	NOUN
easat-5823	14	20	and	and	CCONJ
easat-5823	14	21	rf	rf	NOUN
easat-5823	14	22	as	as	ADP
easat-5823	14	23	a	a	DET
easat-5823	14	24	classifier	classifier	NOUN
easat-5823	14	25	,	,	PUNCT
easat-5823	14	26	offering	offer	VERB
easat-5823	14	27	an	an	DET
easat-5823	14	28	effective	effective	ADJ
easat-5823	14	29	and	and	CCONJ
easat-5823	14	30	robust	robust	ADJ
easat-5823	14	31	method	method	NOUN
easat-5823	14	32	for	for	ADP
easat-5823	14	33	fraud	fraud	NOUN
easat-5823	14	34	detection	detection	NOUN
easat-5823	14	35	.	.	PUNCT
easat-5823	15	1	this	this	DET
easat-5823	15	2	research	research	NOUN
easat-5823	15	3	shows	show	VERB
easat-5823	15	4	the	the	DET
easat-5823	15	5	potential	potential	NOUN
easat-5823	15	6	of	of	ADP
easat-5823	15	7	hybrid	hybrid	ADJ
easat-5823	15	8	methods	method	NOUN
easat-5823	15	9	in	in	ADP
easat-5823	15	10	addressing	address	VERB
easat-5823	15	11	financial	financial	ADJ
easat-5823	15	12	challenges	challenge	NOUN
easat-5823	15	13	and	and	CCONJ
easat-5823	15	14	provides	provide	VERB
easat-5823	15	15	further	further	ADJ
easat-5823	15	16	advancement	advancement	NOUN
easat-5823	15	17	in	in	ADP
easat-5823	15	18	fraud	fraud	NOUN
easat-5823	15	19	detection	detection	NOUN
easat-5823	15	20	systems	system	NOUN
easat-5823	15	21	.	.	PUNCT
easat-5823	16	1	keywords	keyword	NOUN
easat-5823	16	2	:	:	PUNCT
easat-5823	16	3	credit	credit	NOUN
easat-5823	16	4	card	card	NOUN
easat-5823	16	5	fraud	fraud	NOUN
easat-5823	16	6	detection	detection	NOUN
easat-5823	16	7	,	,	PUNCT
easat-5823	16	8	machine	machine	NOUN
easat-5823	16	9	learning	learning	NOUN
easat-5823	16	10	,	,	PUNCT
easat-5823	16	11	multilayer	multilayer	PROPN
easat-5823	16	12	perceptron	perceptron	PROPN
easat-5823	16	13	,	,	PUNCT
easat-5823	16	14	random	random	ADJ
easat-5823	16	15	forest	forest	NOUN
easat-5823	16	16	.	.	PUNCT
easat-5823	17	1	1	1	X
easat-5823	17	2	.	.	X
easat-5823	17	3	introduction	introduction	NOUN
easat-5823	17	4	credit	credit	NOUN
easat-5823	17	5	card	card	NOUN
easat-5823	17	6	is	be	AUX
easat-5823	17	7	one	one	NUM
easat-5823	17	8	of	of	ADP
easat-5823	17	9	the	the	DET
easat-5823	17	10	most	most	ADV
easat-5823	17	11	popular	popular	ADJ
easat-5823	17	12	payment	payment	NOUN
easat-5823	17	13	options	option	NOUN
easat-5823	17	14	in	in	ADP
easat-5823	17	15	the	the	DET
easat-5823	17	16	world	world	NOUN
easat-5823	17	17	.	.	PUNCT
easat-5823	18	1	based	base	VERB
easat-5823	18	2	on	on	ADP
easat-5823	18	3	[	[	X
easat-5823	18	4	1	1	X
easat-5823	18	5	]	]	PUNCT
easat-5823	18	6	the	the	DET
easat-5823	18	7	market	market	NOUN
easat-5823	18	8	size	size	NOUN
easat-5823	18	9	of	of	ADP
easat-5823	18	10	credit	credit	NOUN
easat-5823	18	11	card	card	NOUN
easat-5823	18	12	in	in	ADP
easat-5823	18	13	2023	2023	NUM
easat-5823	18	14	was	be	AUX
easat-5823	18	15	usd	usd	NOUN
easat-5823	18	16	572.34	572.34	NUM
easat-5823	18	17	billion	billion	NUM
easat-5823	18	18	.	.	PUNCT
easat-5823	19	1	in	in	ADP
easat-5823	19	2	2024	2024	NUM
easat-5823	19	3	,	,	PUNCT
easat-5823	19	4	the	the	DET
easat-5823	19	5	market	market	NOUN
easat-5823	19	6	size	size	NOUN
easat-5823	19	7	has	have	AUX
easat-5823	19	8	increased	increase	VERB
easat-5823	19	9	to	to	ADP
easat-5823	19	10	usd	usd	NOUN
easat-5823	19	11	622.76	622.76	NUM
easat-5823	19	12	billion	billion	NUM
easat-5823	19	13	.	.	PUNCT
easat-5823	20	1	the	the	DET
easat-5823	20	2	market	market	NOUN
easat-5823	20	3	size	size	NOUN
easat-5823	20	4	of	of	ADP
easat-5823	20	5	credit	credit	NOUN
easat-5823	20	6	card	card	NOUN
easat-5823	20	7	has	have	AUX
easat-5823	20	8	increased	increase	VERB
easat-5823	20	9	exponentially	exponentially	ADV
easat-5823	20	10	and	and	CCONJ
easat-5823	20	11	will	will	AUX
easat-5823	20	12	be	be	AUX
easat-5823	20	13	expected	expect	VERB
easat-5823	20	14	to	to	PART
easat-5823	20	15	reach	reach	VERB
easat-5823	20	16	around	around	ADP
easat-5823	20	17	usd	usd	NOUN
easat-5823	20	18	1,331.50	1,331.50	NUM
easat-5823	20	19	billion	billion	NUM
easat-5823	20	20	by	by	ADP
easat-5823	20	21	the	the	DET
easat-5823	20	22	year	year	NOUN
easat-5823	20	23	2033	2033	NUM
easat-5823	20	24	.	.	PUNCT
easat-5823	21	1	however	however	ADV
easat-5823	21	2	,	,	PUNCT
easat-5823	21	3	with	with	ADP
easat-5823	21	4	such	such	ADJ
easat-5823	21	5	rapid	rapid	ADJ
easat-5823	21	6	growth	growth	NOUN
easat-5823	21	7	,	,	PUNCT
easat-5823	21	8	there	there	PRON
easat-5823	21	9	are	be	VERB
easat-5823	21	10	both	both	ADV
easat-5823	21	11	positive	positive	ADJ
easat-5823	21	12	and	and	CCONJ
easat-5823	21	13	negative	negative	ADJ
easat-5823	21	14	impacts	impact	NOUN
easat-5823	21	15	that	that	PRON
easat-5823	21	16	it	it	PRON
easat-5823	21	17	causes	cause	VERB
easat-5823	21	18	.	.	PUNCT
easat-5823	22	1	the	the	DET
easat-5823	22	2	example	example	NOUN
easat-5823	22	3	of	of	ADP
easat-5823	22	4	this	this	DET
easat-5823	22	5	negative	negative	ADJ
easat-5823	22	6	impact	impact	NOUN
easat-5823	22	7	is	be	AUX
easat-5823	22	8	credit	credit	NOUN
easat-5823	22	9	card	card	NOUN
easat-5823	22	10	fraud	fraud	NOUN
easat-5823	22	11	,	,	PUNCT
easat-5823	22	12	which	which	PRON
easat-5823	22	13	continues	continue	VERB
easat-5823	22	14	to	to	PART
easat-5823	22	15	increase	increase	VERB
easat-5823	22	16	due	due	ADP
easat-5823	22	17	to	to	ADP
easat-5823	22	18	the	the	DET
easat-5823	22	19	advances	advance	NOUN
easat-5823	22	20	in	in	ADP
easat-5823	22	21	cybercrime	cybercrime	NOUN
easat-5823	22	22	methods	method	NOUN
easat-5823	22	23	and	and	CCONJ
easat-5823	22	24	the	the	DET
easat-5823	22	25	adoption	adoption	NOUN
easat-5823	22	26	of	of	ADP
easat-5823	22	27	online	online	ADJ
easat-5823	22	28	payment	payment	NOUN
easat-5823	22	29	systems	system	NOUN
easat-5823	22	30	.	.	PUNCT
easat-5823	23	1	according	accord	VERB
easat-5823	23	2	to	to	ADP
easat-5823	23	3	rej	rej	PROPN
easat-5823	23	4	[	[	X
easat-5823	23	5	2	2	X
easat-5823	23	6	]	]	X
easat-5823	23	7	global	global	ADJ
easat-5823	23	8	losses	loss	NOUN
easat-5823	23	9	due	due	ADP
easat-5823	23	10	to	to	ADP
easat-5823	23	11	credit	credit	NOUN
easat-5823	23	12	card	card	NOUN
easat-5823	23	13	fraud	fraud	NOUN
easat-5823	23	14	reached	reach	VERB
easat-5823	23	15	$	$	SYM
easat-5823	23	16	32.4	32.4	NUM
easat-5823	23	17	billion	billion	NUM
easat-5823	23	18	in	in	ADP
easat-5823	23	19	2021	2021	NUM
easat-5823	23	20	and	and	CCONJ
easat-5823	23	21	are	be	AUX
easat-5823	23	22	expected	expect	VERB
easat-5823	23	23	to	to	PART
easat-5823	23	24	grow	grow	VERB
easat-5823	23	25	to	to	ADP
easat-5823	23	26	$	$	SYM
easat-5823	23	27	43	43	NUM
easat-5823	23	28	billion	billion	NUM
easat-5823	23	29	by	by	ADP
easat-5823	23	30	2026	2026	NUM
easat-5823	23	31	.	.	PUNCT
easat-5823	24	1	a	a	DET
easat-5823	24	2	credit	credit	NOUN
easat-5823	24	3	card	card	NOUN
easat-5823	24	4	fraud	fraud	NOUN
easat-5823	24	5	transaction	transaction	NOUN
easat-5823	24	6	is	be	AUX
easat-5823	24	7	an	an	DET
easat-5823	24	8	illegal	illegal	ADJ
easat-5823	24	9	or	or	CCONJ
easat-5823	24	10	unauthorized	unauthorized	ADJ
easat-5823	24	11	activity	activity	NOUN
easat-5823	24	12	that	that	PRON
easat-5823	24	13	aims	aim	VERB
easat-5823	24	14	to	to	PART
easat-5823	24	15	gain	gain	VERB
easat-5823	24	16	financial	financial	ADJ
easat-5823	24	17	advantage	advantage	NOUN
easat-5823	24	18	by	by	ADP
easat-5823	24	19	using	use	VERB
easat-5823	24	20	the	the	DET
easat-5823	24	21	credit	credit	NOUN
easat-5823	24	22	card	card	NOUN
easat-5823	24	23	without	without	ADP
easat-5823	24	24	the	the	DET
easat-5823	24	25	owner	owner	NOUN
easat-5823	24	26	’s	’s	PART
easat-5823	24	27	permission	permission	NOUN
easat-5823	24	28	.	.	PUNCT
easat-5823	25	1	this	this	DET
easat-5823	25	2	act	act	NOUN
easat-5823	25	3	can	can	AUX
easat-5823	25	4	be	be	AUX
easat-5823	25	5	committed	commit	VERB
easat-5823	25	6	both	both	PRON
easat-5823	25	7	involving	involve	VERB
easat-5823	25	8	the	the	DET
easat-5823	25	9	use	use	NOUN
easat-5823	25	10	of	of	ADP
easat-5823	25	11	physical	physical	ADJ
easat-5823	25	12	credit	credit	NOUN
easat-5823	25	13	card	card	NOUN
easat-5823	25	14	or	or	CCONJ
easat-5823	25	15	other	other	ADJ
easat-5823	25	16	methods	method	NOUN
easat-5823	25	17	that	that	PRON
easat-5823	25	18	do	do	AUX
easat-5823	25	19	not	not	PART
easat-5823	25	20	require	require	VERB
easat-5823	25	21	physical	physical	ADJ
easat-5823	25	22	card	card	NOUN
easat-5823	25	23	ownership	ownership	NOUN
easat-5823	25	24	.	.	PUNCT
easat-5823	26	1	these	these	DET
easat-5823	26	2	methods	method	NOUN
easat-5823	26	3	are	be	AUX
easat-5823	26	4	lost	lose	VERB
easat-5823	26	5	or	or	CCONJ
easat-5823	26	6	stolen	steal	VERB
easat-5823	26	7	card	card	NOUN
easat-5823	26	8	fraud	fraud	NOUN
easat-5823	26	9	,	,	PUNCT
easat-5823	26	10	application	application	NOUN
easat-5823	26	11	fraud	fraud	NOUN
easat-5823	26	12	and	and	CCONJ
easat-5823	26	13	cardholder	cardholder	VERB
easat-5823	26	14	not	not	PART
easat-5823	26	15	present	present	VERB
easat-5823	26	16	fraud	fraud	NOUN
easat-5823	26	17	.	.	PUNCT
easat-5823	27	1	lost	lose	VERB
easat-5823	27	2	or	or	CCONJ
easat-5823	27	3	stolen	steal	VERB
easat-5823	27	4	card	card	NOUN
easat-5823	27	5	fraud	fraud	NOUN
easat-5823	27	6	is	be	AUX
easat-5823	27	7	common	common	ADJ
easat-5823	27	8	crime	crime	NOUN
easat-5823	27	9	that	that	PRON
easat-5823	27	10	uses	use	VERB
easat-5823	27	11	unauthorized	unauthorized	ADJ
easat-5823	27	12	physical	physical	ADJ
easat-5823	27	13	credit	credit	NOUN
easat-5823	27	14	card	card	NOUN
easat-5823	27	15	that	that	PRON
easat-5823	27	16	has	have	AUX
easat-5823	27	17	been	be	AUX
easat-5823	27	18	lost	lose	VERB
easat-5823	27	19	or	or	CCONJ
easat-5823	27	20	stolen	steal	VERB
easat-5823	27	21	to	to	PART
easat-5823	27	22	make	make	VERB
easat-5823	27	23	as	as	ADV
easat-5823	27	24	many	many	ADJ
easat-5823	27	25	and	and	CCONJ
easat-5823	27	26	as	as	ADP
easat-5823	27	27	large	large	ADJ
easat-5823	27	28	transactions	transaction	NOUN
easat-5823	27	29	as	as	ADP
easat-5823	27	30	possible	possible	ADJ
easat-5823	27	31	until	until	SCONJ
easat-5823	27	32	the	the	DET
easat-5823	27	33	card	card	NOUN
easat-5823	27	34	is	be	AUX
easat-5823	27	35	blocked	block	VERB
easat-5823	27	36	.	.	PUNCT
easat-5823	28	1	application	application	NOUN
easat-5823	28	2	fraud	fraud	NOUN
easat-5823	28	3	is	be	AUX
easat-5823	28	4	a	a	DET
easat-5823	28	5	type	type	NOUN
easat-5823	28	6	of	of	ADP
easat-5823	28	7	credit	credit	NOUN
easat-5823	28	8	card	card	NOUN
easat-5823	28	9	fraud	fraud	NOUN
easat-5823	28	10	where	where	SCONJ
easat-5823	28	11	the	the	DET
easat-5823	28	12	fraudster	fraudster	NOUN
easat-5823	28	13	creates	create	VERB
easat-5823	28	14	a	a	DET
easat-5823	28	15	credit	credit	NOUN
easat-5823	28	16	card	card	NOUN
easat-5823	28	17	with	with	ADP
easat-5823	28	18	false	false	ADJ
easat-5823	28	19	personal	personal	ADJ
easat-5823	28	20	information	information	NOUN
easat-5823	28	21	.	.	PUNCT
easat-5823	29	1	application	application	NOUN
easat-5823	29	2	fraud	fraud	NOUN
easat-5823	29	3	is	be	AUX
easat-5823	29	4	hard	hard	ADJ
easat-5823	29	5	to	to	PART
easat-5823	29	6	detect	detect	VERB
easat-5823	29	7	because	because	SCONJ
easat-5823	29	8	the	the	DET
easat-5823	29	9	fraudster	fraudster	NOUN
easat-5823	29	10	usually	usually	ADV
easat-5823	29	11	does	do	AUX
easat-5823	29	12	not	not	PART
easat-5823	29	13	make	make	VERB
easat-5823	29	14	large	large	ADJ
easat-5823	29	15	transactions	transaction	NOUN
easat-5823	29	16	right	right	ADV
easat-5823	29	17	away	away	ADV
easat-5823	29	18	.	.	PUNCT
easat-5823	30	1	cardholder	cardholder	AUX
easat-5823	30	2	not	not	PART
easat-5823	30	3	present	present	VERB
easat-5823	30	4	fraud	fraud	NOUN
easat-5823	30	5	is	be	AUX
easat-5823	30	6	a	a	DET
easat-5823	30	7	type	type	NOUN
easat-5823	30	8	of	of	ADP
easat-5823	30	9	fraud	fraud	NOUN
easat-5823	30	10	that	that	PRON
easat-5823	30	11	does	do	AUX
easat-5823	30	12	not	not	PART
easat-5823	30	13	need	need	VERB
easat-5823	30	14	physical	physical	ADJ
easat-5823	30	15	credit	credit	NOUN
easat-5823	30	16	card	card	NOUN
easat-5823	30	17	and	and	CCONJ
easat-5823	30	18	usually	usually	ADV
easat-5823	30	19	committed	commit	VERB
easat-5823	30	20	through	through	ADP
easat-5823	30	21	online	online	ADJ
easat-5823	30	22	transactions	transaction	NOUN
easat-5823	30	23	or	or	CCONJ
easat-5823	30	24	over	over	ADP
easat-5823	30	25	the	the	DET
easat-5823	30	26	phone	phone	NOUN
easat-5823	30	27	sales	sale	NOUN
easat-5823	30	28	[	[	X
easat-5823	30	29	3	3	NUM
easat-5823	30	30	]	]	PUNCT
easat-5823	30	31	.	.	PUNCT
easat-5823	31	1	traditional	traditional	ADJ
easat-5823	31	2	fraud	fraud	NOUN
easat-5823	31	3	detection	detection	NOUN
easat-5823	31	4	systems	system	NOUN
easat-5823	31	5	generally	generally	ADV
easat-5823	31	6	use	use	VERB
easat-5823	31	7	rule	rule	NOUN
easat-5823	31	8	-	-	PUNCT
easat-5823	31	9	based	base	VERB
easat-5823	31	10	or	or	CCONJ
easat-5823	31	11	statistical	statistical	ADJ
easat-5823	31	12	methods	method	NOUN
easat-5823	31	13	.	.	PUNCT
easat-5823	32	1	these	these	DET
easat-5823	32	2	approaches	approach	NOUN
easat-5823	32	3	often	often	ADV
easat-5823	32	4	have	have	VERB
easat-5823	32	5	2483	2483	NUM
easat-5823	32	6	edelweiss	edelweiss	PROPN
easat-5823	32	7	applied	apply	VERB
easat-5823	32	8	science	science	NOUN
easat-5823	32	9	and	and	CCONJ
easat-5823	32	10	technology	technology	NOUN
easat-5823	32	11	issn	issn	PROPN
easat-5823	32	12	:	:	PUNCT
easat-5823	32	13	2576	2576	NUM
easat-5823	32	14	-	-	SYM
easat-5823	32	15	8484	8484	NUM
easat-5823	32	16	vol	vol	NOUN
easat-5823	32	17	.	.	PROPN
easat-5823	33	1	9	9	NUM
easat-5823	33	2	,	,	PUNCT
easat-5823	33	3	no	no	INTJ
easat-5823	33	4	.	.	NOUN
easat-5823	33	5	3	3	NUM
easat-5823	33	6	:	:	PUNCT
easat-5823	33	7	2482	2482	NUM
easat-5823	33	8	-	-	SYM
easat-5823	33	9	2494	2494	NUM
easat-5823	33	10	,	,	PUNCT
easat-5823	33	11	2025	2025	NUM
easat-5823	33	12	doi	doi	NOUN
easat-5823	33	13	:	:	PUNCT
easat-5823	33	14	10.55214/25768484.v9i3.5823	10.55214/25768484.v9i3.5823	NUM
easat-5823	33	15	©	©	PROPN
easat-5823	33	16	2025	2025	NUM
easat-5823	33	17	by	by	ADP
easat-5823	33	18	the	the	DET
easat-5823	33	19	authors	author	NOUN
easat-5823	33	20	;	;	PUNCT
easat-5823	33	21	licensee	licensee	PROPN
easat-5823	33	22	learning	learn	VERB
easat-5823	33	23	gate	gate	NOUN
easat-5823	33	24	weaknesses	weakness	NOUN
easat-5823	33	25	in	in	ADP
easat-5823	33	26	terms	term	NOUN
easat-5823	33	27	of	of	ADP
easat-5823	33	28	scalability	scalability	NOUN
easat-5823	33	29	and	and	CCONJ
easat-5823	33	30	adaptability	adaptability	NOUN
easat-5823	33	31	which	which	PRON
easat-5823	33	32	makes	make	VERB
easat-5823	33	33	them	they	PRON
easat-5823	33	34	struggle	struggle	VERB
easat-5823	33	35	to	to	PART
easat-5823	33	36	keep	keep	VERB
easat-5823	33	37	up	up	ADP
easat-5823	33	38	with	with	ADP
easat-5823	33	39	the	the	DET
easat-5823	33	40	everevolving	everevolve	VERB
easat-5823	33	41	cybercrime	cybercrime	NOUN
easat-5823	33	42	tactics	tactic	NOUN
easat-5823	33	43	that	that	PRON
easat-5823	33	44	attackers	attacker	NOUN
easat-5823	33	45	use	use	VERB
easat-5823	33	46	and	and	CCONJ
easat-5823	33	47	may	may	AUX
easat-5823	33	48	fail	fail	VERB
easat-5823	33	49	to	to	PART
easat-5823	33	50	capture	capture	VERB
easat-5823	33	51	complex	complex	ADJ
easat-5823	33	52	and	and	CCONJ
easat-5823	33	53	non	non	ADJ
easat-5823	33	54	-	-	ADJ
easat-5823	33	55	linear	linear	ADJ
easat-5823	33	56	patterns	pattern	NOUN
easat-5823	33	57	in	in	ADP
easat-5823	33	58	a	a	DET
easat-5823	33	59	transaction	transaction	NOUN
easat-5823	33	60	data	datum	NOUN
easat-5823	33	61	[	[	X
easat-5823	33	62	4	4	NUM
easat-5823	33	63	]	]	PUNCT
easat-5823	33	64	.	.	PUNCT
easat-5823	34	1	with	with	ADP
easat-5823	34	2	the	the	DET
easat-5823	34	3	growth	growth	NOUN
easat-5823	34	4	of	of	ADP
easat-5823	34	5	technology	technology	NOUN
easat-5823	34	6	,	,	PUNCT
easat-5823	34	7	machine	machine	NOUN
easat-5823	34	8	learning	learning	NOUN
easat-5823	34	9	has	have	AUX
easat-5823	34	10	become	become	VERB
easat-5823	34	11	popular	popular	ADJ
easat-5823	34	12	for	for	ADP
easat-5823	34	13	detecting	detect	VERB
easat-5823	34	14	fraud	fraud	NOUN
easat-5823	34	15	due	due	ADP
easat-5823	34	16	to	to	ADP
easat-5823	34	17	its	its	PRON
easat-5823	34	18	ability	ability	NOUN
easat-5823	34	19	to	to	PART
easat-5823	34	20	analyze	analyze	VERB
easat-5823	34	21	big	big	ADJ
easat-5823	34	22	datasets	dataset	NOUN
easat-5823	34	23	and	and	CCONJ
easat-5823	34	24	its	its	PRON
easat-5823	34	25	capability	capability	NOUN
easat-5823	34	26	to	to	PART
easat-5823	34	27	identify	identify	VERB
easat-5823	34	28	the	the	DET
easat-5823	34	29	complicated	complicated	ADJ
easat-5823	34	30	and	and	CCONJ
easat-5823	34	31	complex	complex	ADJ
easat-5823	34	32	patterns	pattern	NOUN
easat-5823	34	33	in	in	ADP
easat-5823	34	34	real	real	ADJ
easat-5823	34	35	-	-	PUNCT
easat-5823	34	36	time	time	NOUN
easat-5823	34	37	.	.	PUNCT
easat-5823	35	1	fraud	fraud	NOUN
easat-5823	35	2	detection	detection	NOUN
easat-5823	35	3	system	system	NOUN
easat-5823	35	4	that	that	PRON
easat-5823	35	5	is	be	AUX
easat-5823	35	6	based	base	VERB
easat-5823	35	7	on	on	ADP
easat-5823	35	8	machine	machine	NOUN
easat-5823	35	9	learning	learning	NOUN
easat-5823	35	10	can	can	AUX
easat-5823	35	11	adapt	adapt	VERB
easat-5823	35	12	and	and	CCONJ
easat-5823	35	13	evolve	evolve	VERB
easat-5823	35	14	as	as	SCONJ
easat-5823	35	15	time	time	NOUN
easat-5823	35	16	goes	go	VERB
easat-5823	35	17	on	on	ADV
easat-5823	35	18	,	,	PUNCT
easat-5823	35	19	making	make	VERB
easat-5823	35	20	them	they	PRON
easat-5823	35	21	a	a	DET
easat-5823	35	22	suitable	suitable	ADJ
easat-5823	35	23	choice	choice	NOUN
easat-5823	35	24	for	for	ADP
easat-5823	35	25	dealing	deal	VERB
easat-5823	35	26	with	with	ADP
easat-5823	35	27	the	the	DET
easat-5823	35	28	dynamic	dynamic	ADJ
easat-5823	35	29	nature	nature	NOUN
easat-5823	35	30	of	of	ADP
easat-5823	35	31	fraud	fraud	NOUN
easat-5823	35	32	behavior	behavior	NOUN
easat-5823	35	33	.	.	PUNCT
easat-5823	36	1	machine	machine	NOUN
easat-5823	36	2	learning	learning	NOUN
easat-5823	36	3	is	be	AUX
easat-5823	36	4	divided	divide	VERB
easat-5823	36	5	into	into	ADP
easat-5823	36	6	several	several	ADJ
easat-5823	36	7	types	type	NOUN
easat-5823	36	8	based	base	VERB
easat-5823	36	9	on	on	ADP
easat-5823	36	10	their	their	PRON
easat-5823	36	11	training	training	NOUN
easat-5823	36	12	approach	approach	NOUN
easat-5823	36	13	.	.	PUNCT
easat-5823	37	1	one	one	NUM
easat-5823	37	2	of	of	ADP
easat-5823	37	3	the	the	DET
easat-5823	37	4	most	most	ADV
easat-5823	37	5	used	use	VERB
easat-5823	37	6	types	type	NOUN
easat-5823	37	7	of	of	ADP
easat-5823	37	8	machine	machine	NOUN
easat-5823	37	9	learning	learn	VERB
easat-5823	37	10	for	for	ADP
easat-5823	37	11	fraud	fraud	NOUN
easat-5823	37	12	detection	detection	NOUN
easat-5823	37	13	system	system	NOUN
easat-5823	37	14	is	be	AUX
easat-5823	37	15	supervised	supervise	VERB
easat-5823	37	16	learning	learning	NOUN
easat-5823	37	17	.	.	PUNCT
easat-5823	38	1	supervised	supervised	ADJ
easat-5823	38	2	learning	learning	NOUN
easat-5823	38	3	is	be	AUX
easat-5823	38	4	a	a	DET
easat-5823	38	5	machine	machine	NOUN
easat-5823	38	6	learning	learn	VERB
easat-5823	38	7	approach	approach	NOUN
easat-5823	38	8	that	that	PRON
easat-5823	38	9	uses	use	VERB
easat-5823	38	10	labelled	label	VERB
easat-5823	38	11	data	datum	NOUN
easat-5823	38	12	to	to	PART
easat-5823	38	13	train	train	VERB
easat-5823	38	14	its	its	PRON
easat-5823	38	15	model	model	NOUN
easat-5823	38	16	.	.	PUNCT
easat-5823	39	1	with	with	ADP
easat-5823	39	2	this	this	DET
easat-5823	39	3	approach	approach	NOUN
easat-5823	39	4	,	,	PUNCT
easat-5823	39	5	the	the	DET
easat-5823	39	6	model	model	NOUN
easat-5823	39	7	can	can	AUX
easat-5823	39	8	study	study	VERB
easat-5823	39	9	the	the	DET
easat-5823	39	10	given	give	VERB
easat-5823	39	11	historical	historical	ADJ
easat-5823	39	12	transaction	transaction	NOUN
easat-5823	39	13	data	datum	NOUN
easat-5823	39	14	and	and	CCONJ
easat-5823	39	15	identify	identify	VERB
easat-5823	39	16	patterns	pattern	NOUN
easat-5823	39	17	related	relate	VERB
easat-5823	39	18	to	to	ADP
easat-5823	39	19	fraud	fraud	NOUN
easat-5823	39	20	.	.	PUNCT
easat-5823	40	1	there	there	PRON
easat-5823	40	2	are	be	VERB
easat-5823	40	3	several	several	ADJ
easat-5823	40	4	often	often	ADV
easat-5823	40	5	-	-	PUNCT
easat-5823	40	6	used	use	VERB
easat-5823	40	7	supervised	supervised	ADJ
easat-5823	40	8	learning	learning	NOUN
easat-5823	40	9	methods	method	NOUN
easat-5823	40	10	such	such	ADJ
easat-5823	40	11	as	as	ADP
easat-5823	40	12	logistic	logistic	ADJ
easat-5823	40	13	regression	regression	NOUN
easat-5823	40	14	,	,	PUNCT
easat-5823	40	15	decision	decision	NOUN
easat-5823	40	16	trees	tree	NOUN
easat-5823	40	17	,	,	PUNCT
easat-5823	40	18	random	random	ADJ
easat-5823	40	19	forest	forest	NOUN
easat-5823	40	20	,	,	PUNCT
easat-5823	40	21	neural	neural	ADJ
easat-5823	40	22	network	network	NOUN
easat-5823	40	23	,	,	PUNCT
easat-5823	40	24	and	and	CCONJ
easat-5823	40	25	others	other	NOUN
easat-5823	41	1	[	[	X
easat-5823	41	2	5	5	NUM
easat-5823	41	3	]	]	PUNCT
easat-5823	41	4	.	.	PUNCT
easat-5823	42	1	this	this	DET
easat-5823	42	2	research	research	NOUN
easat-5823	42	3	will	will	AUX
easat-5823	42	4	focus	focus	VERB
easat-5823	42	5	on	on	ADP
easat-5823	42	6	exploring	explore	VERB
easat-5823	42	7	a	a	DET
easat-5823	42	8	hybrid	hybrid	ADJ
easat-5823	42	9	model	model	NOUN
easat-5823	42	10	for	for	ADP
easat-5823	42	11	credit	credit	NOUN
easat-5823	42	12	card	card	NOUN
easat-5823	42	13	fraud	fraud	NOUN
easat-5823	42	14	detection	detection	NOUN
easat-5823	42	15	system	system	NOUN
easat-5823	42	16	.	.	PUNCT
easat-5823	43	1	the	the	DET
easat-5823	43	2	proposed	propose	VERB
easat-5823	43	3	hybrid	hybrid	NOUN
easat-5823	43	4	model	model	NOUN
easat-5823	43	5	will	will	AUX
easat-5823	43	6	combine	combine	VERB
easat-5823	43	7	both	both	PRON
easat-5823	43	8	mlp	mlp	PROPN
easat-5823	43	9	neural	neural	ADJ
easat-5823	43	10	network	network	NOUN
easat-5823	43	11	and	and	CCONJ
easat-5823	43	12	random	random	ADJ
easat-5823	43	13	forest	forest	NOUN
easat-5823	43	14	methods	method	NOUN
easat-5823	43	15	.	.	PUNCT
easat-5823	44	1	mlp	mlp	NOUN
easat-5823	44	2	will	will	AUX
easat-5823	44	3	be	be	AUX
easat-5823	44	4	used	use	VERB
easat-5823	44	5	to	to	PART
easat-5823	44	6	perform	perform	VERB
easat-5823	44	7	feature	feature	NOUN
easat-5823	44	8	extraction	extraction	NOUN
easat-5823	44	9	to	to	PART
easat-5823	44	10	identify	identify	VERB
easat-5823	44	11	complex	complex	ADJ
easat-5823	44	12	patterns	pattern	NOUN
easat-5823	44	13	from	from	ADP
easat-5823	44	14	the	the	DET
easat-5823	44	15	dataset	dataset	NOUN
easat-5823	44	16	.	.	PUNCT
easat-5823	45	1	afterwards	afterwards	ADV
easat-5823	45	2	,	,	PUNCT
easat-5823	45	3	the	the	DET
easat-5823	45	4	extracted	extract	VERB
easat-5823	45	5	features	feature	NOUN
easat-5823	45	6	will	will	AUX
easat-5823	45	7	be	be	AUX
easat-5823	45	8	used	use	VERB
easat-5823	45	9	by	by	ADP
easat-5823	45	10	the	the	DET
easat-5823	45	11	random	random	ADJ
easat-5823	45	12	forest	forest	NOUN
easat-5823	45	13	model	model	NOUN
easat-5823	45	14	to	to	PART
easat-5823	45	15	perform	perform	VERB
easat-5823	45	16	classification	classification	NOUN
easat-5823	45	17	and	and	CCONJ
easat-5823	45	18	prediction	prediction	NOUN
easat-5823	45	19	.	.	PUNCT
easat-5823	46	1	research	research	NOUN
easat-5823	46	2	related	relate	VERB
easat-5823	46	3	to	to	PART
easat-5823	46	4	fraud	fraud	VERB
easat-5823	46	5	detection	detection	NOUN
easat-5823	46	6	systems	system	NOUN
easat-5823	46	7	using	use	VERB
easat-5823	46	8	neural	neural	ADJ
easat-5823	46	9	networks	network	NOUN
easat-5823	46	10	has	have	AUX
easat-5823	46	11	been	be	AUX
easat-5823	46	12	done	do	VERB
easat-5823	46	13	by	by	ADP
easat-5823	46	14	researchers	researcher	NOUN
easat-5823	46	15	like	like	ADP
easat-5823	46	16	varmedja	varmedja	PROPN
easat-5823	46	17	,	,	PUNCT
easat-5823	46	18	et	et	PROPN
easat-5823	46	19	al	al	PROPN
easat-5823	46	20	.	.	PUNCT
easat-5823	47	1	[	[	X
easat-5823	47	2	6	6	NUM
easat-5823	47	3	]	]	PUNCT
easat-5823	47	4	;	;	PUNCT
easat-5823	47	5	sadgali	sadgali	PROPN
easat-5823	47	6	,	,	PUNCT
easat-5823	47	7	et	et	PROPN
easat-5823	47	8	al	al	PROPN
easat-5823	47	9	.	.	PUNCT
easat-5823	48	1	[	[	X
easat-5823	48	2	7	7	X
easat-5823	48	3	]	]	PUNCT
easat-5823	48	4	and	and	CCONJ
easat-5823	48	5	andrade	andrade	PROPN
easat-5823	48	6	,	,	PUNCT
easat-5823	48	7	et	et	PROPN
easat-5823	48	8	al	al	PROPN
easat-5823	48	9	.	.	PUNCT
easat-5823	49	1	[	[	X
easat-5823	49	2	8	8	NUM
easat-5823	49	3	]	]	PUNCT
easat-5823	49	4	.	.	PUNCT
easat-5823	50	1	however	however	ADV
easat-5823	50	2	,	,	PUNCT
easat-5823	50	3	in	in	ADP
easat-5823	50	4	those	those	DET
easat-5823	50	5	research	research	NOUN
easat-5823	50	6	,	,	PUNCT
easat-5823	50	7	neural	neural	ADJ
easat-5823	50	8	network	network	NOUN
easat-5823	50	9	has	have	AUX
easat-5823	50	10	not	not	PART
easat-5823	50	11	been	be	AUX
easat-5823	50	12	able	able	ADJ
easat-5823	50	13	to	to	PART
easat-5823	50	14	beat	beat	VERB
easat-5823	50	15	the	the	DET
easat-5823	50	16	performance	performance	NOUN
easat-5823	50	17	of	of	ADP
easat-5823	50	18	other	other	ADJ
easat-5823	50	19	methods	method	NOUN
easat-5823	50	20	.	.	PUNCT
easat-5823	51	1	neural	neural	ADJ
easat-5823	51	2	network	network	NOUN
easat-5823	51	3	,	,	PUNCT
easat-5823	51	4	especially	especially	ADV
easat-5823	51	5	multilayer	multilayer	ADJ
easat-5823	51	6	perceptron	perceptron	PROPN
easat-5823	51	7	(	(	PUNCT
easat-5823	51	8	mlp	mlp	PROPN
easat-5823	51	9	)	)	PUNCT
easat-5823	51	10	,	,	PUNCT
easat-5823	51	11	is	be	AUX
easat-5823	51	12	a	a	DET
easat-5823	51	13	type	type	NOUN
easat-5823	51	14	of	of	ADP
easat-5823	51	15	neural	neural	ADJ
easat-5823	51	16	network	network	NOUN
easat-5823	51	17	that	that	PRON
easat-5823	51	18	consists	consist	VERB
easat-5823	51	19	of	of	ADP
easat-5823	51	20	several	several	ADJ
easat-5823	51	21	layers	layer	NOUN
easat-5823	51	22	of	of	ADP
easat-5823	51	23	neurons	neuron	NOUN
easat-5823	51	24	that	that	PRON
easat-5823	51	25	connect	connect	VERB
easat-5823	51	26	with	with	ADP
easat-5823	51	27	each	each	DET
easat-5823	51	28	other	other	ADJ
easat-5823	51	29	.	.	PUNCT
easat-5823	52	1	mlp	mlp	NOUN
easat-5823	52	2	excels	excel	VERB
easat-5823	52	3	at	at	ADP
easat-5823	52	4	identifying	identify	VERB
easat-5823	52	5	non	non	ADJ
easat-5823	52	6	-	-	ADJ
easat-5823	52	7	linear	linear	ADJ
easat-5823	52	8	relationships	relationship	NOUN
easat-5823	52	9	in	in	ADP
easat-5823	52	10	high	high	ADJ
easat-5823	52	11	-	-	PUNCT
easat-5823	52	12	dimensional	dimensional	ADJ
easat-5823	52	13	data	datum	NOUN
easat-5823	52	14	and	and	CCONJ
easat-5823	52	15	able	able	ADJ
easat-5823	52	16	identify	identify	VERB
easat-5823	52	17	complicated	complicated	ADJ
easat-5823	52	18	patterns	pattern	NOUN
easat-5823	52	19	that	that	PRON
easat-5823	52	20	can	can	AUX
easat-5823	52	21	not	not	PART
easat-5823	52	22	be	be	AUX
easat-5823	52	23	captured	capture	VERB
easat-5823	52	24	by	by	ADP
easat-5823	52	25	simple	simple	ADJ
easat-5823	52	26	statistical	statistical	ADJ
easat-5823	52	27	methods	method	NOUN
easat-5823	52	28	or	or	CCONJ
easat-5823	52	29	linear	linear	ADJ
easat-5823	52	30	methods	method	NOUN
easat-5823	52	31	[	[	X
easat-5823	52	32	9	9	NUM
easat-5823	52	33	]	]	PUNCT
easat-5823	52	34	.	.	PUNCT
easat-5823	53	1	research	research	NOUN
easat-5823	53	2	using	use	VERB
easat-5823	53	3	random	random	ADJ
easat-5823	53	4	forest	forest	NOUN
easat-5823	53	5	related	relate	VERB
easat-5823	53	6	to	to	PART
easat-5823	53	7	fraud	fraud	NOUN
easat-5823	53	8	detection	detection	NOUN
easat-5823	53	9	has	have	AUX
easat-5823	53	10	also	also	ADV
easat-5823	53	11	been	be	AUX
easat-5823	53	12	done	do	VERB
easat-5823	53	13	by	by	ADP
easat-5823	53	14	previous	previous	ADJ
easat-5823	53	15	researchers	researcher	NOUN
easat-5823	53	16	such	such	ADJ
easat-5823	53	17	as	as	ADP
easat-5823	53	18	agarwal	agarwal	PROPN
easat-5823	53	19	and	and	CCONJ
easat-5823	53	20	usha	usha	PROPN
easat-5823	54	1	[	[	X
easat-5823	54	2	10	10	NUM
easat-5823	54	3	]	]	PUNCT
easat-5823	54	4	and	and	CCONJ
easat-5823	54	5	jain	jain	PROPN
easat-5823	54	6	,	,	PUNCT
easat-5823	54	7	et	et	PROPN
easat-5823	54	8	al	al	PROPN
easat-5823	54	9	.	.	PUNCT
easat-5823	55	1	[	[	X
easat-5823	55	2	11	11	NUM
easat-5823	55	3	]	]	PUNCT
easat-5823	55	4	where	where	SCONJ
easat-5823	55	5	it	it	PRON
easat-5823	55	6	produces	produce	VERB
easat-5823	55	7	good	good	ADJ
easat-5823	55	8	results	result	NOUN
easat-5823	55	9	.	.	PUNCT
easat-5823	56	1	random	random	ADJ
easat-5823	56	2	forest	forest	NOUN
easat-5823	56	3	is	be	AUX
easat-5823	56	4	an	an	DET
easat-5823	56	5	ensemble	ensemble	ADJ
easat-5823	56	6	method	method	NOUN
easat-5823	56	7	that	that	PRON
easat-5823	56	8	combines	combine	VERB
easat-5823	56	9	multiple	multiple	ADJ
easat-5823	56	10	decision	decision	NOUN
easat-5823	56	11	tree	tree	NOUN
easat-5823	56	12	models	model	NOUN
easat-5823	56	13	to	to	PART
easat-5823	56	14	improve	improve	VERB
easat-5823	56	15	performance	performance	NOUN
easat-5823	56	16	and	and	CCONJ
easat-5823	56	17	is	be	AUX
easat-5823	56	18	popular	popular	ADJ
easat-5823	56	19	because	because	SCONJ
easat-5823	56	20	of	of	ADP
easat-5823	56	21	its	its	PRON
easat-5823	56	22	effectiveness	effectiveness	NOUN
easat-5823	56	23	in	in	ADP
easat-5823	56	24	performing	perform	VERB
easat-5823	56	25	regression	regression	NOUN
easat-5823	56	26	and	and	CCONJ
easat-5823	56	27	classification	classification	NOUN
easat-5823	56	28	.	.	PUNCT
easat-5823	57	1	2	2	X
easat-5823	57	2	.	.	X
easat-5823	57	3	literature	literature	NOUN
easat-5823	57	4	review	review	PROPN
easat-5823	57	5	research	research	NOUN
easat-5823	57	6	that	that	PRON
easat-5823	57	7	use	use	VERB
easat-5823	57	8	machine	machine	NOUN
easat-5823	57	9	learning	learn	VERB
easat-5823	57	10	to	to	PART
easat-5823	57	11	detect	detect	VERB
easat-5823	57	12	fraud	fraud	NOUN
easat-5823	57	13	transaction	transaction	NOUN
easat-5823	57	14	has	have	AUX
easat-5823	57	15	already	already	ADV
easat-5823	57	16	been	be	AUX
easat-5823	57	17	done	do	VERB
easat-5823	57	18	.	.	PUNCT
easat-5823	58	1	previously	previously	ADV
easat-5823	58	2	varmedja	varmedja	PROPN
easat-5823	58	3	,	,	PUNCT
easat-5823	58	4	et	et	PROPN
easat-5823	58	5	al	al	PROPN
easat-5823	58	6	.	.	PUNCT
easat-5823	59	1	[	[	X
easat-5823	59	2	6	6	NUM
easat-5823	59	3	]	]	PUNCT
easat-5823	59	4	researched	research	VERB
easat-5823	59	5	the	the	DET
easat-5823	59	6	application	application	NOUN
easat-5823	59	7	of	of	ADP
easat-5823	59	8	various	various	ADJ
easat-5823	59	9	machine	machine	NOUN
easat-5823	59	10	learning	learning	NOUN
easat-5823	59	11	models	model	NOUN
easat-5823	59	12	for	for	ADP
easat-5823	59	13	detecting	detect	VERB
easat-5823	59	14	fraudulent	fraudulent	ADJ
easat-5823	59	15	transactions	transaction	NOUN
easat-5823	59	16	in	in	ADP
easat-5823	59	17	credit	credit	NOUN
easat-5823	59	18	card	card	NOUN
easat-5823	59	19	usage	usage	NOUN
easat-5823	59	20	.	.	PUNCT
easat-5823	60	1	this	this	DET
easat-5823	60	2	paper	paper	NOUN
easat-5823	60	3	discussed	discuss	VERB
easat-5823	60	4	the	the	DET
easat-5823	60	5	critical	critical	ADJ
easat-5823	60	6	problem	problem	NOUN
easat-5823	60	7	of	of	ADP
easat-5823	60	8	credit	credit	NOUN
easat-5823	60	9	card	card	NOUN
easat-5823	60	10	fraud	fraud	NOUN
easat-5823	60	11	due	due	ADP
easat-5823	60	12	to	to	ADP
easat-5823	60	13	increasing	increase	VERB
easat-5823	60	14	digital	digital	ADJ
easat-5823	60	15	transactions	transaction	NOUN
easat-5823	60	16	.	.	PUNCT
easat-5823	61	1	the	the	DET
easat-5823	61	2	research	research	NOUN
easat-5823	61	3	underlined	underline	VERB
easat-5823	61	4	the	the	DET
easat-5823	61	5	challenges	challenge	NOUN
easat-5823	61	6	of	of	ADP
easat-5823	61	7	imbalance	imbalance	NOUN
easat-5823	61	8	datasets	dataset	NOUN
easat-5823	61	9	which	which	PRON
easat-5823	61	10	make	make	VERB
easat-5823	61	11	preprocessing	preprocessing	NOUN
easat-5823	61	12	steps	step	NOUN
easat-5823	61	13	like	like	ADP
easat-5823	61	14	smote	smote	NOUN
easat-5823	61	15	and	and	CCONJ
easat-5823	61	16	feature	feature	NOUN
easat-5823	61	17	selection	selection	NOUN
easat-5823	61	18	a	a	DET
easat-5823	61	19	necessity	necessity	NOUN
easat-5823	61	20	.	.	PUNCT
easat-5823	62	1	the	the	DET
easat-5823	62	2	research	research	NOUN
easat-5823	62	3	tested	test	VERB
easat-5823	62	4	multiple	multiple	ADJ
easat-5823	62	5	algorithms	algorithm	NOUN
easat-5823	62	6	such	such	ADJ
easat-5823	62	7	as	as	ADP
easat-5823	62	8	logistic	logistic	ADJ
easat-5823	62	9	regression	regression	NOUN
easat-5823	62	10	(	(	PUNCT
easat-5823	62	11	lr	lr	NOUN
easat-5823	62	12	)	)	PUNCT
easat-5823	62	13	,	,	PUNCT
easat-5823	62	14	naïve	naïve	ADJ
easat-5823	62	15	bayes	bayes	PROPN
easat-5823	62	16	(	(	PUNCT
easat-5823	62	17	nb	nb	PROPN
easat-5823	62	18	)	)	PUNCT
easat-5823	62	19	,	,	PUNCT
easat-5823	62	20	random	random	ADJ
easat-5823	62	21	forest	forest	NOUN
easat-5823	62	22	(	(	PUNCT
easat-5823	62	23	rf	rf	NOUN
easat-5823	62	24	)	)	PUNCT
easat-5823	62	25	,	,	PUNCT
easat-5823	62	26	and	and	CCONJ
easat-5823	62	27	artificial	artificial	ADJ
easat-5823	62	28	neural	neural	ADJ
easat-5823	62	29	networks	network	NOUN
easat-5823	62	30	(	(	PUNCT
easat-5823	62	31	anns	anns	PROPN
easat-5823	62	32	)	)	PUNCT
easat-5823	62	33	.	.	PUNCT
easat-5823	63	1	the	the	DET
easat-5823	63	2	result	result	NOUN
easat-5823	63	3	showed	show	VERB
easat-5823	63	4	that	that	SCONJ
easat-5823	63	5	among	among	ADP
easat-5823	63	6	other	other	ADJ
easat-5823	63	7	models	model	NOUN
easat-5823	63	8	,	,	PUNCT
easat-5823	63	9	rf	rf	NOUN
easat-5823	63	10	and	and	CCONJ
easat-5823	63	11	anns	anns	PROPN
easat-5823	63	12	model	model	NOUN
easat-5823	63	13	performed	perform	VERB
easat-5823	63	14	better	well	ADV
easat-5823	63	15	overall	overall	ADJ
easat-5823	63	16	with	with	ADP
easat-5823	63	17	accuracy	accuracy	NOUN
easat-5823	63	18	of	of	ADP
easat-5823	63	19	99.96	99.96	NUM
easat-5823	63	20	%	%	NOUN
easat-5823	63	21	and	and	CCONJ
easat-5823	63	22	99.93	99.93	NUM
easat-5823	63	23	%	%	NOUN
easat-5823	63	24	,	,	PUNCT
easat-5823	63	25	recall	recall	NOUN
easat-5823	63	26	of	of	ADP
easat-5823	63	27	both	both	DET
easat-5823	63	28	81.63	81.63	NUM
easat-5823	63	29	%	%	NOUN
easat-5823	63	30	,	,	PUNCT
easat-5823	63	31	as	as	ADV
easat-5823	63	32	well	well	ADV
easat-5823	63	33	as	as	ADP
easat-5823	63	34	precision	precision	NOUN
easat-5823	63	35	of	of	ADP
easat-5823	63	36	96.38	96.38	NUM
easat-5823	63	37	%	%	NOUN
easat-5823	63	38	and	and	CCONJ
easat-5823	63	39	79.21	79.21	NUM
easat-5823	63	40	%	%	NOUN
easat-5823	63	41	.	.	PUNCT
easat-5823	64	1	the	the	DET
easat-5823	64	2	study	study	NOUN
easat-5823	64	3	concluded	conclude	VERB
easat-5823	64	4	that	that	SCONJ
easat-5823	64	5	machine	machine	NOUN
easat-5823	64	6	learning	learning	NOUN
easat-5823	64	7	models	model	NOUN
easat-5823	64	8	especially	especially	ADV
easat-5823	64	9	ensemble	ensemble	ADJ
easat-5823	64	10	and	and	CCONJ
easat-5823	64	11	deep	deep	ADJ
easat-5823	64	12	learning	learning	NOUN
easat-5823	64	13	methods	method	NOUN
easat-5823	64	14	can	can	AUX
easat-5823	64	15	significantly	significantly	ADV
easat-5823	64	16	improve	improve	VERB
easat-5823	64	17	fraud	fraud	NOUN
easat-5823	64	18	detection	detection	NOUN
easat-5823	64	19	when	when	SCONJ
easat-5823	64	20	paired	pair	VERB
easat-5823	64	21	with	with	ADP
easat-5823	64	22	effective	effective	ADJ
easat-5823	64	23	preprocessing	preprocessing	NOUN
easat-5823	64	24	techniques	technique	NOUN
easat-5823	64	25	.	.	PUNCT
easat-5823	65	1	other	other	ADJ
easat-5823	65	2	research	research	NOUN
easat-5823	65	3	like	like	ADP
easat-5823	65	4	[	[	X
easat-5823	65	5	12	12	NUM
easat-5823	65	6	]	]	PUNCT
easat-5823	65	7	discussed	discuss	VERB
easat-5823	65	8	utilizing	utilize	VERB
easat-5823	65	9	deep	deep	ADJ
easat-5823	65	10	learning	learning	NOUN
easat-5823	65	11	techniques	technique	NOUN
easat-5823	65	12	to	to	PART
easat-5823	65	13	identify	identify	VERB
easat-5823	65	14	fraudulent	fraudulent	ADJ
easat-5823	65	15	credit	credit	NOUN
easat-5823	65	16	card	card	NOUN
easat-5823	65	17	transactions	transaction	NOUN
easat-5823	65	18	.	.	PUNCT
easat-5823	66	1	the	the	DET
easat-5823	66	2	study	study	NOUN
easat-5823	66	3	used	use	VERB
easat-5823	66	4	convolutional	convolutional	ADJ
easat-5823	66	5	neural	neural	ADJ
easat-5823	66	6	network	network	NOUN
easat-5823	66	7	with	with	ADP
easat-5823	66	8	6	6	NUM
easat-5823	66	9	convolutional	convolutional	ADJ
easat-5823	66	10	layers	layer	NOUN
easat-5823	66	11	.	.	PUNCT
easat-5823	67	1	the	the	DET
easat-5823	67	2	result	result	NOUN
easat-5823	67	3	of	of	ADP
easat-5823	67	4	the	the	DET
easat-5823	67	5	experiment	experiment	NOUN
easat-5823	67	6	showed	show	VERB
easat-5823	67	7	that	that	SCONJ
easat-5823	67	8	cnn	cnn	PROPN
easat-5823	67	9	model	model	NOUN
easat-5823	67	10	got	get	VERB
easat-5823	67	11	an	an	DET
easat-5823	67	12	accuracy	accuracy	NOUN
easat-5823	67	13	of	of	ADP
easat-5823	67	14	99.62	99.62	NUM
easat-5823	67	15	%	%	NOUN
easat-5823	67	16	without	without	ADP
easat-5823	67	17	using	use	VERB
easat-5823	67	18	max	max	PROPN
easat-5823	67	19	pooling	pooling	NOUN
easat-5823	67	20	layer	layer	NOUN
easat-5823	67	21	and	and	CCONJ
easat-5823	67	22	95.93	95.93	NUM
easat-5823	67	23	%	%	NOUN
easat-5823	67	24	with	with	ADP
easat-5823	67	25	max	max	PROPN
easat-5823	67	26	pooling	pool	VERB
easat-5823	67	27	layer	layer	NOUN
easat-5823	67	28	.	.	PUNCT
easat-5823	68	1	the	the	DET
easat-5823	68	2	study	study	NOUN
easat-5823	68	3	concluded	conclude	VERB
easat-5823	68	4	that	that	SCONJ
easat-5823	68	5	cnn	cnn	PROPN
easat-5823	68	6	model	model	NOUN
easat-5823	68	7	has	have	VERB
easat-5823	68	8	excellent	excellent	ADJ
easat-5823	68	9	performance	performance	NOUN
easat-5823	68	10	with	with	ADP
easat-5823	68	11	good	good	ADJ
easat-5823	68	12	stability	stability	NOUN
easat-5823	68	13	.	.	PUNCT
easat-5823	69	1	in	in	ADP
easat-5823	69	2	the	the	DET
easat-5823	69	3	area	area	NOUN
easat-5823	69	4	of	of	ADP
easat-5823	69	5	supervised	supervised	ADJ
easat-5823	69	6	learning	learning	NOUN
easat-5823	69	7	technique	technique	NOUN
easat-5823	69	8	,	,	PUNCT
easat-5823	69	9	sadgali	sadgali	PROPN
easat-5823	69	10	,	,	PUNCT
easat-5823	69	11	et	et	PROPN
easat-5823	69	12	al	al	PROPN
easat-5823	69	13	.	.	PUNCT
easat-5823	70	1	[	[	X
easat-5823	70	2	7	7	X
easat-5823	70	3	]	]	PUNCT
easat-5823	70	4	explored	explore	VERB
easat-5823	70	5	the	the	DET
easat-5823	70	6	application	application	NOUN
easat-5823	70	7	of	of	ADP
easat-5823	70	8	neural	neural	ADJ
easat-5823	70	9	network	network	NOUN
easat-5823	70	10	for	for	ADP
easat-5823	70	11	the	the	DET
easat-5823	70	12	topic	topic	NOUN
easat-5823	70	13	of	of	ADP
easat-5823	70	14	fraud	fraud	NOUN
easat-5823	70	15	detection	detection	NOUN
easat-5823	70	16	.	.	PUNCT
easat-5823	71	1	the	the	DET
easat-5823	71	2	study	study	NOUN
easat-5823	71	3	used	use	VERB
easat-5823	71	4	a	a	DET
easat-5823	71	5	generated	generate	VERB
easat-5823	71	6	dataset	dataset	NOUN
easat-5823	71	7	that	that	SCONJ
easat-5823	71	8	mimic	mimic	VERB
easat-5823	71	9	real	real	ADJ
easat-5823	71	10	financial	financial	ADJ
easat-5823	71	11	condition	condition	NOUN
easat-5823	71	12	with	with	ADP
easat-5823	71	13	significant	significant	ADJ
easat-5823	71	14	imbalances	imbalance	NOUN
easat-5823	71	15	which	which	PRON
easat-5823	71	16	includes	include	VERB
easat-5823	71	17	approximately	approximately	ADV
easat-5823	71	18	60.000	60.000	NUM
easat-5823	71	19	transactions	transaction	NOUN
easat-5823	71	20	.	.	PUNCT
easat-5823	72	1	the	the	DET
easat-5823	72	2	study	study	NOUN
easat-5823	72	3	tested	test	VERB
easat-5823	72	4	various	various	ADJ
easat-5823	72	5	machine	machine	NOUN
easat-5823	72	6	learning	learning	NOUN
easat-5823	72	7	models	model	NOUN
easat-5823	72	8	,	,	PUNCT
easat-5823	72	9	including	include	VERB
easat-5823	72	10	decision	decision	NOUN
easat-5823	72	11	tree	tree	NOUN
easat-5823	72	12	,	,	PUNCT
easat-5823	72	13	support	support	NOUN
easat-5823	72	14	vector	vector	NOUN
easat-5823	72	15	machine	machine	NOUN
easat-5823	72	16	(	(	PUNCT
easat-5823	72	17	svm	svm	PROPN
easat-5823	72	18	)	)	PUNCT
easat-5823	72	19	,	,	PUNCT
easat-5823	72	20	random	random	ADJ
easat-5823	72	21	forest	forest	NOUN
easat-5823	72	22	,	,	PUNCT
easat-5823	72	23	and	and	CCONJ
easat-5823	72	24	k	k	X
easat-5823	72	25	-	-	PUNCT
easat-5823	72	26	nearest	near	ADJ
easat-5823	72	27	neighbour	neighbour	NOUN
easat-5823	72	28	.	.	PUNCT
easat-5823	73	1	the	the	DET
easat-5823	73	2	result	result	NOUN
easat-5823	73	3	of	of	ADP
easat-5823	73	4	the	the	DET
easat-5823	73	5	study	study	NOUN
easat-5823	73	6	showed	show	VERB
easat-5823	73	7	that	that	SCONJ
easat-5823	73	8	the	the	DET
easat-5823	73	9	best	well	ADV
easat-5823	73	10	performing	perform	VERB
easat-5823	73	11	2484	2484	NUM
easat-5823	73	12	edelweiss	edelweiss	PROPN
easat-5823	73	13	applied	apply	VERB
easat-5823	73	14	science	science	NOUN
easat-5823	73	15	and	and	CCONJ
easat-5823	73	16	technology	technology	NOUN
easat-5823	73	17	issn	issn	PROPN
easat-5823	73	18	:	:	PUNCT
easat-5823	73	19	2576	2576	NUM
easat-5823	73	20	-	-	SYM
easat-5823	73	21	8484	8484	NUM
easat-5823	73	22	vol	vol	NOUN
easat-5823	73	23	.	.	PROPN
easat-5823	74	1	9	9	NUM
easat-5823	74	2	,	,	PUNCT
easat-5823	74	3	no	no	INTJ
easat-5823	74	4	.	.	NOUN
easat-5823	74	5	3	3	NUM
easat-5823	74	6	:	:	PUNCT
easat-5823	74	7	2482	2482	NUM
easat-5823	74	8	-	-	SYM
easat-5823	74	9	2494	2494	NUM
easat-5823	74	10	,	,	PUNCT
easat-5823	74	11	2025	2025	NUM
easat-5823	74	12	doi	doi	NOUN
easat-5823	74	13	:	:	PUNCT
easat-5823	74	14	10.55214/25768484.v9i3.5823	10.55214/25768484.v9i3.5823	NUM
easat-5823	74	15	©	©	PROPN
easat-5823	74	16	2025	2025	NUM
easat-5823	74	17	by	by	ADP
easat-5823	74	18	the	the	DET
easat-5823	74	19	authors	author	NOUN
easat-5823	74	20	;	;	PUNCT
easat-5823	74	21	licensee	licensee	PROPN
easat-5823	74	22	learning	learning	PROPN
easat-5823	74	23	gate	gate	PROPN
easat-5823	74	24	model	model	NOUN
easat-5823	74	25	was	be	AUX
easat-5823	74	26	support	support	NOUN
easat-5823	74	27	vector	vector	NOUN
easat-5823	74	28	machine	machine	NOUN
easat-5823	74	29	with	with	ADP
easat-5823	74	30	mse	mse	NOUN
easat-5823	74	31	score	score	NOUN
easat-5823	74	32	of	of	ADP
easat-5823	74	33	0.0021	0.0021	NUM
easat-5823	74	34	for	for	ADP
easat-5823	74	35	training	training	NOUN
easat-5823	74	36	dataset	dataset	NOUN
easat-5823	74	37	and	and	CCONJ
easat-5823	74	38	0.0024	0.0024	NUM
easat-5823	74	39	for	for	ADP
easat-5823	74	40	test	test	NOUN
easat-5823	74	41	dataset	dataset	VERB
easat-5823	74	42	as	as	ADV
easat-5823	74	43	well	well	ADV
easat-5823	74	44	as	as	ADP
easat-5823	74	45	an	an	DET
easat-5823	74	46	accuracy	accuracy	NOUN
easat-5823	74	47	99.7	99.7	NUM
easat-5823	74	48	%	%	NOUN
easat-5823	74	49	.	.	PUNCT
easat-5823	75	1	however	however	ADV
easat-5823	75	2	,	,	PUNCT
easat-5823	75	3	svm	svm	PROPN
easat-5823	75	4	is	be	AUX
easat-5823	75	5	proven	prove	VERB
easat-5823	75	6	to	to	PART
easat-5823	75	7	be	be	AUX
easat-5823	75	8	defeated	defeat	VERB
easat-5823	75	9	by	by	ADP
easat-5823	75	10	random	random	ADJ
easat-5823	75	11	forest	forest	NOUN
easat-5823	75	12	in	in	ADP
easat-5823	75	13	other	other	ADJ
easat-5823	75	14	cases	case	NOUN
easat-5823	75	15	like	like	ADP
easat-5823	75	16	in	in	ADP
easat-5823	75	17	the	the	DET
easat-5823	75	18	study	study	NOUN
easat-5823	75	19	by	by	ADP
easat-5823	75	20	swetha	swetha	PROPN
easat-5823	75	21	,	,	PUNCT
easat-5823	75	22	et	et	PROPN
easat-5823	75	23	al	al	PROPN
easat-5823	75	24	.	.	PUNCT
easat-5823	76	1	[	[	X
easat-5823	76	2	13	13	NUM
easat-5823	76	3	]	]	PUNCT
easat-5823	76	4	.	.	PUNCT
easat-5823	77	1	the	the	DET
easat-5823	77	2	study	study	NOUN
easat-5823	77	3	explored	explore	VERB
easat-5823	77	4	the	the	DET
easat-5823	77	5	challenges	challenge	NOUN
easat-5823	77	6	of	of	ADP
easat-5823	77	7	enhancing	enhance	VERB
easat-5823	77	8	credit	credit	NOUN
easat-5823	77	9	card	card	NOUN
easat-5823	77	10	fraud	fraud	NOUN
easat-5823	77	11	detection	detection	NOUN
easat-5823	77	12	by	by	ADP
easat-5823	77	13	applying	apply	VERB
easat-5823	77	14	advanced	advanced	ADJ
easat-5823	77	15	machine	machine	NOUN
easat-5823	77	16	learning	learn	VERB
easat-5823	77	17	algorithms	algorithm	NOUN
easat-5823	77	18	.	.	PUNCT
easat-5823	78	1	a	a	DET
easat-5823	78	2	performance	performance	NOUN
easat-5823	78	3	analysis	analysis	NOUN
easat-5823	78	4	was	be	AUX
easat-5823	78	5	made	make	VERB
easat-5823	78	6	based	base	VERB
easat-5823	78	7	on	on	ADP
easat-5823	78	8	three	three	NUM
easat-5823	78	9	different	different	ADJ
easat-5823	78	10	algorithms	algorithm	NOUN
easat-5823	78	11	,	,	PUNCT
easat-5823	78	12	including	include	VERB
easat-5823	78	13	svm	svm	NOUN
easat-5823	78	14	,	,	PUNCT
easat-5823	78	15	decision	decision	NOUN
easat-5823	78	16	tree	tree	NOUN
easat-5823	78	17	and	and	CCONJ
easat-5823	78	18	random	random	ADJ
easat-5823	78	19	forest	forest	NOUN
easat-5823	78	20	.	.	PUNCT
easat-5823	79	1	the	the	DET
easat-5823	79	2	analysis	analysis	NOUN
easat-5823	79	3	was	be	AUX
easat-5823	79	4	split	split	VERB
easat-5823	79	5	between	between	ADP
easat-5823	79	6	3	3	NUM
easat-5823	79	7	different	different	ADJ
easat-5823	79	8	feature	feature	NOUN
easat-5823	79	9	selection	selection	NOUN
easat-5823	79	10	which	which	PRON
easat-5823	79	11	were	be	AUX
easat-5823	79	12	“	"	PUNCT
easat-5823	79	13	for	for	ADP
easat-5823	79	14	5	5	NUM
easat-5823	79	15	variables	variable	NOUN
easat-5823	79	16	”	"	PUNCT
easat-5823	79	17	,	,	PUNCT
easat-5823	79	18	“	"	PUNCT
easat-5823	79	19	for	for	ADP
easat-5823	79	20	10	10	NUM
easat-5823	79	21	variables	variable	NOUN
easat-5823	79	22	”	"	PUNCT
easat-5823	79	23	and	and	CCONJ
easat-5823	79	24	“	"	PUNCT
easat-5823	79	25	for	for	ADP
easat-5823	79	26	all	all	DET
easat-5823	79	27	variables	variable	NOUN
easat-5823	79	28	”	"	PUNCT
easat-5823	79	29	.	.	PUNCT
easat-5823	80	1	the	the	DET
easat-5823	80	2	result	result	NOUN
easat-5823	80	3	showed	show	VERB
easat-5823	80	4	that	that	SCONJ
easat-5823	80	5	the	the	DET
easat-5823	80	6	accuracy	accuracy	NOUN
easat-5823	80	7	for	for	ADP
easat-5823	80	8	svm	svm	ADJ
easat-5823	80	9	,	,	PUNCT
easat-5823	80	10	decision	decision	NOUN
easat-5823	80	11	tree	tree	NOUN
easat-5823	80	12	and	and	CCONJ
easat-5823	80	13	random	random	ADJ
easat-5823	80	14	forest	forest	NOUN
easat-5823	80	15	model	model	NOUN
easat-5823	80	16	were	be	AUX
easat-5823	80	17	90.0	90.0	NUM
easat-5823	80	18	,	,	PUNCT
easat-5823	80	19	94.3	94.3	NUM
easat-5823	80	20	,	,	PUNCT
easat-5823	80	21	and	and	CCONJ
easat-5823	80	22	95.5	95.5	NUM
easat-5823	80	23	.	.	PUNCT
easat-5823	81	1	this	this	DET
easat-5823	81	2	number	number	NOUN
easat-5823	81	3	indicated	indicate	VERB
easat-5823	81	4	that	that	SCONJ
easat-5823	81	5	the	the	DET
easat-5823	81	6	random	random	ADJ
easat-5823	81	7	forest	forest	NOUN
easat-5823	81	8	classifier	classifier	NOUN
easat-5823	81	9	is	be	AUX
easat-5823	81	10	better	well	ADJ
easat-5823	81	11	than	than	ADP
easat-5823	81	12	the	the	DET
easat-5823	81	13	svm	svm	NOUN
easat-5823	81	14	and	and	CCONJ
easat-5823	81	15	decision	decision	NOUN
easat-5823	81	16	tree	tree	NOUN
easat-5823	81	17	model	model	NOUN
easat-5823	81	18	.	.	PUNCT
easat-5823	82	1	the	the	DET
easat-5823	82	2	study	study	NOUN
easat-5823	82	3	used	use	VERB
easat-5823	82	4	different	different	ADJ
easat-5823	82	5	dataset	dataset	NOUN
easat-5823	82	6	and	and	CCONJ
easat-5823	82	7	feature	feature	NOUN
easat-5823	82	8	selection	selection	NOUN
easat-5823	82	9	,	,	PUNCT
easat-5823	82	10	which	which	PRON
easat-5823	82	11	could	could	AUX
easat-5823	82	12	be	be	AUX
easat-5823	82	13	the	the	DET
easat-5823	82	14	contributing	contribute	VERB
easat-5823	82	15	factor	factor	NOUN
easat-5823	82	16	to	to	ADP
easat-5823	82	17	the	the	DET
easat-5823	82	18	different	different	ADJ
easat-5823	82	19	results	result	NOUN
easat-5823	82	20	.	.	PUNCT
easat-5823	83	1	other	other	ADJ
easat-5823	83	2	research	research	NOUN
easat-5823	83	3	on	on	ADP
easat-5823	83	4	machine	machine	NOUN
easat-5823	83	5	learning	learning	NOUN
easat-5823	83	6	was	be	AUX
easat-5823	83	7	done	do	VERB
easat-5823	83	8	by	by	ADP
easat-5823	83	9	andrade	andrade	PROPN
easat-5823	83	10	,	,	PUNCT
easat-5823	83	11	et	et	PROPN
easat-5823	83	12	al	al	PROPN
easat-5823	83	13	.	.	PUNCT
easat-5823	84	1	[	[	X
easat-5823	84	2	8	8	NUM
easat-5823	84	3	]	]	PUNCT
easat-5823	84	4	where	where	SCONJ
easat-5823	84	5	the	the	DET
easat-5823	84	6	performance	performance	NOUN
easat-5823	84	7	of	of	ADP
easat-5823	84	8	four	four	NUM
easat-5823	84	9	machine	machine	NOUN
easat-5823	84	10	learning	learning	NOUN
easat-5823	84	11	models	model	NOUN
easat-5823	84	12	,	,	PUNCT
easat-5823	84	13	including	include	VERB
easat-5823	84	14	k	k	NOUN
easat-5823	84	15	-	-	PUNCT
easat-5823	84	16	nearest	near	ADJ
easat-5823	84	17	neighbors	neighbor	NOUN
easat-5823	84	18	(	(	PUNCT
easat-5823	84	19	knn	knn	PROPN
easat-5823	84	20	)	)	PUNCT
easat-5823	84	21	,	,	PUNCT
easat-5823	84	22	random	random	ADJ
easat-5823	84	23	forest	forest	NOUN
easat-5823	84	24	(	(	PUNCT
easat-5823	84	25	rf	rf	NOUN
easat-5823	84	26	)	)	PUNCT
easat-5823	84	27	,	,	PUNCT
easat-5823	84	28	support	support	VERB
easat-5823	84	29	vector	vector	NOUN
easat-5823	84	30	machines	machine	NOUN
easat-5823	84	31	(	(	PUNCT
easat-5823	84	32	svm	svm	PROPN
easat-5823	84	33	)	)	PUNCT
easat-5823	84	34	and	and	CCONJ
easat-5823	84	35	neural	neural	ADJ
easat-5823	84	36	network	network	NOUN
easat-5823	84	37	(	(	PUNCT
easat-5823	84	38	nn	nn	NOUN
easat-5823	84	39	)	)	PUNCT
easat-5823	84	40	was	be	AUX
easat-5823	84	41	evaluated	evaluate	VERB
easat-5823	84	42	.	.	PUNCT
easat-5823	85	1	the	the	DET
easat-5823	85	2	result	result	NOUN
easat-5823	85	3	showed	show	VERB
easat-5823	85	4	that	that	SCONJ
easat-5823	85	5	random	random	ADJ
easat-5823	85	6	forest	forest	NOUN
easat-5823	85	7	has	have	VERB
easat-5823	85	8	the	the	DET
easat-5823	85	9	highest	high	ADJ
easat-5823	85	10	score	score	NOUN
easat-5823	85	11	in	in	ADP
easat-5823	85	12	all	all	DET
easat-5823	85	13	metrics	metric	NOUN
easat-5823	85	14	indicating	indicate	VERB
easat-5823	85	15	that	that	SCONJ
easat-5823	85	16	random	random	ADJ
easat-5823	85	17	forest	forest	NOUN
easat-5823	85	18	has	have	VERB
easat-5823	85	19	the	the	DET
easat-5823	85	20	best	good	ADJ
easat-5823	85	21	performance	performance	NOUN
easat-5823	85	22	.	.	PUNCT
easat-5823	86	1	random	random	ADJ
easat-5823	86	2	forest	forest	NOUN
easat-5823	86	3	achieved	achieve	VERB
easat-5823	86	4	a	a	DET
easat-5823	86	5	precision	precision	NOUN
easat-5823	86	6	of	of	ADP
easat-5823	86	7	94.24	94.24	NUM
easat-5823	86	8	%	%	NOUN
easat-5823	86	9	,	,	PUNCT
easat-5823	86	10	recall	recall	NOUN
easat-5823	86	11	of	of	ADP
easat-5823	86	12	92.04	92.04	NUM
easat-5823	86	13	%	%	NOUN
easat-5823	86	14	and	and	CCONJ
easat-5823	86	15	f1	f1	NOUN
easat-5823	86	16	-	-	PUNCT
easat-5823	86	17	score	score	NOUN
easat-5823	86	18	of	of	ADP
easat-5823	86	19	92.98	92.98	NUM
easat-5823	86	20	%	%	NOUN
easat-5823	86	21	.	.	PUNCT
easat-5823	87	1	the	the	DET
easat-5823	87	2	potential	potential	NOUN
easat-5823	87	3	of	of	ADP
easat-5823	87	4	random	random	ADJ
easat-5823	87	5	forest	forest	NOUN
easat-5823	87	6	has	have	AUX
easat-5823	87	7	also	also	ADV
easat-5823	87	8	been	be	AUX
easat-5823	87	9	proven	prove	VERB
easat-5823	87	10	by	by	ADP
easat-5823	87	11	several	several	ADJ
easat-5823	87	12	research	research	NOUN
easat-5823	87	13	like	like	ADP
easat-5823	87	14	the	the	DET
easat-5823	87	15	study	study	NOUN
easat-5823	87	16	by	by	ADP
easat-5823	87	17	bhattacharyya	bhattacharyya	ADJ
easat-5823	87	18	,	,	PUNCT
easat-5823	87	19	et	et	PROPN
easat-5823	87	20	al	al	PROPN
easat-5823	87	21	.	.	PUNCT
easat-5823	88	1	[	[	X
easat-5823	88	2	14	14	NUM
easat-5823	88	3	]	]	PUNCT
easat-5823	88	4	where	where	SCONJ
easat-5823	88	5	the	the	DET
easat-5823	88	6	authors	author	NOUN
easat-5823	88	7	utilized	utilize	VERB
easat-5823	88	8	various	various	ADJ
easat-5823	88	9	data	datum	NOUN
easat-5823	88	10	mining	mining	NOUN
easat-5823	88	11	techniques	technique	NOUN
easat-5823	88	12	including	include	VERB
easat-5823	88	13	logistic	logistic	ADJ
easat-5823	88	14	regression	regression	NOUN
easat-5823	88	15	,	,	PUNCT
easat-5823	88	16	support	support	VERB
easat-5823	88	17	vector	vector	NOUN
easat-5823	88	18	machines	machine	NOUN
easat-5823	88	19	(	(	PUNCT
easat-5823	88	20	svm	svm	PROPN
easat-5823	88	21	)	)	PUNCT
easat-5823	88	22	and	and	CCONJ
easat-5823	88	23	random	random	ADJ
easat-5823	88	24	forests	forest	NOUN
easat-5823	88	25	to	to	PART
easat-5823	88	26	analyzed	analyze	VERB
easat-5823	88	27	the	the	DET
easat-5823	88	28	performance	performance	NOUN
easat-5823	88	29	of	of	ADP
easat-5823	88	30	each	each	DET
easat-5823	88	31	technique	technique	NOUN
easat-5823	88	32	.	.	PUNCT
easat-5823	89	1	the	the	DET
easat-5823	89	2	authors	author	NOUN
easat-5823	89	3	used	use	VERB
easat-5823	89	4	several	several	ADJ
easat-5823	89	5	measures	measure	NOUN
easat-5823	89	6	of	of	ADP
easat-5823	89	7	classification	classification	NOUN
easat-5823	89	8	performance	performance	NOUN
easat-5823	89	9	such	such	ADJ
easat-5823	89	10	as	as	ADP
easat-5823	89	11	accuracy	accuracy	NOUN
easat-5823	89	12	,	,	PUNCT
easat-5823	89	13	sensitivity	sensitivity	NOUN
easat-5823	89	14	,	,	PUNCT
easat-5823	89	15	specificity	specificity	NOUN
easat-5823	89	16	,	,	PUNCT
easat-5823	89	17	precision	precision	NOUN
easat-5823	89	18	,	,	PUNCT
easat-5823	89	19	f	f	X
easat-5823	89	20	-	-	PUNCT
easat-5823	89	21	measure	measure	NOUN
easat-5823	89	22	,	,	PUNCT
easat-5823	89	23	g	g	NOUN
easat-5823	89	24	-	-	PUNCT
easat-5823	89	25	mean	mean	NOUN
easat-5823	89	26	and	and	CCONJ
easat-5823	89	27	wtdacc	wtdacc	ADJ
easat-5823	89	28	.	.	PUNCT
easat-5823	90	1	the	the	DET
easat-5823	90	2	results	result	NOUN
easat-5823	90	3	showed	show	VERB
easat-5823	90	4	that	that	SCONJ
easat-5823	90	5	random	random	ADJ
easat-5823	90	6	forest	forest	NOUN
easat-5823	90	7	has	have	VERB
easat-5823	90	8	the	the	DET
easat-5823	90	9	best	good	ADJ
easat-5823	90	10	performance	performance	NOUN
easat-5823	90	11	compared	compare	VERB
easat-5823	90	12	to	to	ADP
easat-5823	90	13	the	the	DET
easat-5823	90	14	other	other	ADJ
easat-5823	90	15	two	two	NUM
easat-5823	90	16	methods	method	NOUN
easat-5823	90	17	.	.	PUNCT
easat-5823	91	1	another	another	DET
easat-5823	91	2	research	research	NOUN
easat-5823	91	3	that	that	PRON
easat-5823	91	4	proved	prove	VERB
easat-5823	91	5	the	the	DET
easat-5823	91	6	excellent	excellent	ADJ
easat-5823	91	7	performance	performance	NOUN
easat-5823	91	8	of	of	ADP
easat-5823	91	9	random	random	ADJ
easat-5823	91	10	forest	forest	NOUN
easat-5823	91	11	is	be	AUX
easat-5823	91	12	the	the	DET
easat-5823	91	13	research	research	NOUN
easat-5823	91	14	by	by	ADP
easat-5823	91	15	aftab	aftab	PROPN
easat-5823	91	16	,	,	PUNCT
easat-5823	91	17	et	et	PROPN
easat-5823	91	18	al	al	PROPN
easat-5823	91	19	.	.	PUNCT
easat-5823	92	1	[	[	X
easat-5823	92	2	15	15	NUM
easat-5823	92	3	]	]	PUNCT
easat-5823	92	4	.	.	PUNCT
easat-5823	93	1	the	the	DET
easat-5823	93	2	research	research	NOUN
easat-5823	93	3	aimed	aim	VERB
easat-5823	93	4	to	to	PART
easat-5823	93	5	identify	identify	VERB
easat-5823	93	6	the	the	DET
easat-5823	93	7	best	well	ADV
easat-5823	93	8	supervised	supervised	ADJ
easat-5823	93	9	machine	machine	NOUN
easat-5823	93	10	learning	learning	NOUN
easat-5823	93	11	method	method	NOUN
easat-5823	93	12	for	for	ADP
easat-5823	93	13	credit	credit	NOUN
easat-5823	93	14	card	card	NOUN
easat-5823	93	15	fraud	fraud	NOUN
easat-5823	93	16	detection	detection	NOUN
easat-5823	93	17	.	.	PUNCT
easat-5823	94	1	the	the	DET
easat-5823	94	2	methods	method	NOUN
easat-5823	94	3	that	that	PRON
easat-5823	94	4	were	be	AUX
easat-5823	94	5	compared	compare	VERB
easat-5823	94	6	include	include	VERB
easat-5823	94	7	logistic	logistic	ADJ
easat-5823	94	8	regression	regression	NOUN
easat-5823	94	9	,	,	PUNCT
easat-5823	94	10	random	random	ADJ
easat-5823	94	11	forest	forest	NOUN
easat-5823	94	12	,	,	PUNCT
easat-5823	94	13	support	support	NOUN
easat-5823	94	14	vector	vector	NOUN
easat-5823	94	15	machine	machine	NOUN
easat-5823	94	16	,	,	PUNCT
easat-5823	94	17	and	and	CCONJ
easat-5823	94	18	decision	decision	NOUN
easat-5823	94	19	trees	tree	NOUN
easat-5823	94	20	.	.	PUNCT
easat-5823	95	1	furthermore	furthermore	ADV
easat-5823	95	2	,	,	PUNCT
easat-5823	95	3	the	the	DET
easat-5823	95	4	research	research	NOUN
easat-5823	95	5	also	also	ADV
easat-5823	95	6	used	use	VERB
easat-5823	95	7	smote	smote	NOUN
easat-5823	95	8	to	to	PART
easat-5823	95	9	address	address	VERB
easat-5823	95	10	the	the	DET
easat-5823	95	11	imbalance	imbalance	NOUN
easat-5823	95	12	in	in	ADP
easat-5823	95	13	dataset	dataset	NOUN
easat-5823	95	14	.	.	PUNCT
easat-5823	96	1	the	the	DET
easat-5823	96	2	result	result	NOUN
easat-5823	96	3	of	of	ADP
easat-5823	96	4	the	the	DET
easat-5823	96	5	research	research	NOUN
easat-5823	96	6	showed	show	VERB
easat-5823	96	7	that	that	SCONJ
easat-5823	96	8	random	random	ADJ
easat-5823	96	9	forest	forest	NOUN
easat-5823	96	10	have	have	VERB
easat-5823	96	11	the	the	DET
easat-5823	96	12	best	good	ADJ
easat-5823	96	13	performance	performance	NOUN
easat-5823	96	14	compared	compare	VERB
easat-5823	96	15	to	to	ADP
easat-5823	96	16	other	other	ADJ
easat-5823	96	17	methods	method	NOUN
easat-5823	96	18	.	.	PUNCT
easat-5823	97	1	other	other	ADJ
easat-5823	97	2	than	than	ADP
easat-5823	97	3	that	that	PRON
easat-5823	97	4	,	,	PUNCT
easat-5823	97	5	agarwal	agarwal	PROPN
easat-5823	97	6	and	and	CCONJ
easat-5823	97	7	usha	usha	PROPN
easat-5823	98	1	[	[	X
easat-5823	98	2	10	10	NUM
easat-5823	98	3	]	]	PUNCT
easat-5823	98	4	also	also	ADV
easat-5823	98	5	conducted	conduct	VERB
easat-5823	98	6	a	a	DET
easat-5823	98	7	research	research	NOUN
easat-5823	98	8	that	that	PRON
easat-5823	98	9	investigate	investigate	VERB
easat-5823	98	10	the	the	DET
easat-5823	98	11	usage	usage	NOUN
easat-5823	98	12	of	of	ADP
easat-5823	98	13	machine	machine	NOUN
easat-5823	98	14	learning	learning	NOUN
easat-5823	98	15	technique	technique	NOUN
easat-5823	98	16	for	for	ADP
easat-5823	98	17	detecting	detect	VERB
easat-5823	98	18	fraud	fraud	NOUN
easat-5823	98	19	credit	credit	NOUN
easat-5823	98	20	card	card	NOUN
easat-5823	98	21	transactions	transaction	NOUN
easat-5823	98	22	.	.	PUNCT
easat-5823	99	1	the	the	DET
easat-5823	99	2	research	research	NOUN
easat-5823	99	3	utilized	utilize	VERB
easat-5823	99	4	a	a	DET
easat-5823	99	5	large	large	ADJ
easat-5823	99	6	dataset	dataset	NOUN
easat-5823	99	7	that	that	PRON
easat-5823	99	8	consisted	consist	VERB
easat-5823	99	9	of	of	ADP
easat-5823	99	10	credit	credit	NOUN
easat-5823	99	11	card	card	NOUN
easat-5823	99	12	transactions	transaction	NOUN
easat-5823	99	13	and	and	CCONJ
easat-5823	99	14	identified	identify	VERB
easat-5823	99	15	the	the	DET
easat-5823	99	16	suspicious	suspicious	ADJ
easat-5823	99	17	patterns	pattern	NOUN
easat-5823	99	18	in	in	ADP
easat-5823	99	19	the	the	DET
easat-5823	99	20	data	datum	NOUN
easat-5823	99	21	that	that	PRON
easat-5823	99	22	may	may	AUX
easat-5823	99	23	resulted	result	VERB
easat-5823	99	24	to	to	ADP
easat-5823	99	25	fraudulent	fraudulent	ADJ
easat-5823	99	26	activity	activity	NOUN
easat-5823	99	27	.	.	PUNCT
easat-5823	100	1	the	the	DET
easat-5823	100	2	authors	author	NOUN
easat-5823	100	3	used	use	VERB
easat-5823	100	4	random	random	ADJ
easat-5823	100	5	forest	forest	NOUN
easat-5823	100	6	as	as	ADP
easat-5823	100	7	the	the	DET
easat-5823	100	8	algorithm	algorithm	NOUN
easat-5823	100	9	which	which	PRON
easat-5823	100	10	performed	perform	VERB
easat-5823	100	11	extremely	extremely	ADV
easat-5823	100	12	well	well	ADV
easat-5823	100	13	.	.	PUNCT
easat-5823	101	1	the	the	DET
easat-5823	101	2	result	result	NOUN
easat-5823	101	3	showed	show	VERB
easat-5823	101	4	that	that	SCONJ
easat-5823	101	5	the	the	DET
easat-5823	101	6	algorithm	algorithm	NOUN
easat-5823	101	7	performed	perform	VERB
easat-5823	101	8	extremely	extremely	ADV
easat-5823	101	9	well	well	ADV
easat-5823	101	10	with	with	ADP
easat-5823	101	11	a	a	DET
easat-5823	101	12	high	high	ADJ
easat-5823	101	13	accuracy	accuracy	NOUN
easat-5823	101	14	,	,	PUNCT
easat-5823	101	15	precision	precision	NOUN
easat-5823	101	16	and	and	CCONJ
easat-5823	101	17	recall	recall	NOUN
easat-5823	101	18	of	of	ADP
easat-5823	101	19	0.999	0.999	NUM
easat-5823	101	20	,	,	PUNCT
easat-5823	101	21	0.999	0.999	NUM
easat-5823	101	22	,	,	PUNCT
easat-5823	101	23	and	and	CCONJ
easat-5823	101	24	1.0	1.0	NUM
easat-5823	101	25	.	.	PUNCT
easat-5823	102	1	the	the	DET
easat-5823	102	2	result	result	NOUN
easat-5823	102	3	indicated	indicate	VERB
easat-5823	102	4	that	that	SCONJ
easat-5823	102	5	to	to	PART
easat-5823	102	6	significantly	significantly	ADV
easat-5823	102	7	reduce	reduce	VERB
easat-5823	102	8	the	the	DET
easat-5823	102	9	amount	amount	NOUN
easat-5823	102	10	of	of	ADP
easat-5823	102	11	fraud	fraud	NOUN
easat-5823	102	12	credit	credit	NOUN
easat-5823	102	13	card	card	NOUN
easat-5823	102	14	transactions	transaction	NOUN
easat-5823	102	15	,	,	PUNCT
easat-5823	102	16	random	random	ADJ
easat-5823	102	17	forest	forest	NOUN
easat-5823	102	18	is	be	AUX
easat-5823	102	19	a	a	DET
easat-5823	102	20	great	great	ADJ
easat-5823	102	21	option	option	NOUN
easat-5823	102	22	.	.	PUNCT
easat-5823	103	1	other	other	ADJ
easat-5823	103	2	than	than	ADP
easat-5823	103	3	random	random	ADJ
easat-5823	103	4	forest	forest	NOUN
easat-5823	103	5	,	,	PUNCT
easat-5823	103	6	there	there	PRON
easat-5823	103	7	is	be	VERB
easat-5823	103	8	another	another	DET
easat-5823	103	9	algorithm	algorithm	NOUN
easat-5823	103	10	that	that	PRON
easat-5823	103	11	has	have	VERB
easat-5823	103	12	excellent	excellent	ADJ
easat-5823	103	13	performance	performance	NOUN
easat-5823	103	14	which	which	PRON
easat-5823	103	15	is	be	AUX
easat-5823	103	16	xgboost	xgboost	X
easat-5823	103	17	algorithm	algorithm	NOUN
easat-5823	103	18	.	.	PUNCT
easat-5823	104	1	in	in	ADP
easat-5823	104	2	the	the	DET
easat-5823	104	3	study	study	NOUN
easat-5823	104	4	by	by	ADP
easat-5823	104	5	singh	singh	PROPN
easat-5823	104	6	and	and	CCONJ
easat-5823	104	7	mahrishi	mahrishi	VERB
easat-5823	104	8	[	[	X
easat-5823	104	9	16	16	NUM
easat-5823	104	10	]	]	PUNCT
easat-5823	104	11	the	the	DET
easat-5823	104	12	authors	author	NOUN
easat-5823	104	13	explored	explore	VERB
easat-5823	104	14	and	and	CCONJ
easat-5823	104	15	compared	compare	VERB
easat-5823	104	16	the	the	DET
easat-5823	104	17	various	various	ADJ
easat-5823	104	18	methods	method	NOUN
easat-5823	104	19	for	for	ADP
easat-5823	104	20	credit	credit	NOUN
easat-5823	104	21	card	card	NOUN
easat-5823	104	22	fraud	fraud	NOUN
easat-5823	104	23	detection	detection	NOUN
easat-5823	104	24	.	.	PUNCT
easat-5823	105	1	the	the	DET
easat-5823	105	2	study	study	NOUN
easat-5823	105	3	used	use	VERB
easat-5823	105	4	k	k	PROPN
easat-5823	105	5	-	-	PUNCT
easat-5823	105	6	means	means	NOUN
easat-5823	105	7	clustering	clustering	NOUN
easat-5823	105	8	,	,	PUNCT
easat-5823	105	9	logistic	logistic	ADJ
easat-5823	105	10	regression	regression	NOUN
easat-5823	105	11	,	,	PUNCT
easat-5823	105	12	random	random	ADJ
easat-5823	105	13	forest	forest	NOUN
easat-5823	105	14	and	and	CCONJ
easat-5823	105	15	xgboost	xgboost	NOUN
easat-5823	105	16	models	model	NOUN
easat-5823	105	17	.	.	PUNCT
easat-5823	106	1	the	the	DET
easat-5823	106	2	study	study	NOUN
easat-5823	106	3	used	use	VERB
easat-5823	106	4	dataset	dataset	VERB
easat-5823	106	5	with	with	ADP
easat-5823	106	6	284,807	284,807	NUM
easat-5823	106	7	transactions	transaction	NOUN
easat-5823	106	8	which	which	PRON
easat-5823	106	9	were	be	AUX
easat-5823	106	10	obtained	obtain	VERB
easat-5823	106	11	from	from	ADP
easat-5823	106	12	kaggle	kaggle	PROPN
easat-5823	106	13	.	.	PUNCT
easat-5823	107	1	the	the	DET
easat-5823	107	2	models	model	NOUN
easat-5823	107	3	were	be	AUX
easat-5823	107	4	tested	test	VERB
easat-5823	107	5	and	and	CCONJ
easat-5823	107	6	compared	compare	VERB
easat-5823	107	7	using	use	VERB
easat-5823	107	8	precision	precision	NOUN
easat-5823	107	9	as	as	SCONJ
easat-5823	107	10	the	the	DET
easat-5823	107	11	comparison	comparison	NOUN
easat-5823	107	12	metric	metric	ADJ
easat-5823	107	13	.	.	PUNCT
easat-5823	108	1	the	the	DET
easat-5823	108	2	result	result	NOUN
easat-5823	108	3	showed	show	VERB
easat-5823	108	4	that	that	SCONJ
easat-5823	108	5	xgboost	xgboost	PROPN
easat-5823	108	6	were	be	AUX
easat-5823	108	7	more	more	ADV
easat-5823	108	8	accurate	accurate	ADJ
easat-5823	108	9	than	than	ADP
easat-5823	108	10	other	other	ADJ
easat-5823	108	11	models	model	NOUN
easat-5823	108	12	thus	thus	ADV
easat-5823	108	13	making	make	VERB
easat-5823	108	14	it	it	PRON
easat-5823	108	15	preferable	preferable	ADJ
easat-5823	108	16	over	over	ADP
easat-5823	108	17	the	the	DET
easat-5823	108	18	other	other	ADJ
easat-5823	108	19	models	model	NOUN
easat-5823	108	20	.	.	PUNCT
easat-5823	109	1	unlike	unlike	ADP
easat-5823	109	2	the	the	DET
easat-5823	109	3	previous	previous	ADJ
easat-5823	109	4	papers	paper	NOUN
easat-5823	109	5	,	,	PUNCT
easat-5823	109	6	the	the	DET
easat-5823	109	7	study	study	NOUN
easat-5823	109	8	shows	show	VERB
easat-5823	109	9	that	that	SCONJ
easat-5823	109	10	xgboost	xgboost	PROPN
easat-5823	109	11	performs	perform	VERB
easat-5823	109	12	better	well	ADJ
easat-5823	109	13	than	than	ADP
easat-5823	109	14	random	random	ADJ
easat-5823	109	15	forest	forest	NOUN
easat-5823	109	16	.	.	PUNCT
easat-5823	110	1	to	to	PART
easat-5823	110	2	determine	determine	VERB
easat-5823	110	3	the	the	DET
easat-5823	110	4	superiority	superiority	NOUN
easat-5823	110	5	of	of	ADP
easat-5823	110	6	xgboost	xgboost	ADV
easat-5823	110	7	over	over	ADP
easat-5823	110	8	random	random	ADJ
easat-5823	110	9	forest	forest	NOUN
easat-5823	110	10	,	,	PUNCT
easat-5823	110	11	there	there	PRON
easat-5823	110	12	are	be	VERB
easat-5823	110	13	other	other	ADJ
easat-5823	110	14	research	research	NOUN
easat-5823	110	15	that	that	PRON
easat-5823	110	16	also	also	ADV
easat-5823	110	17	showed	show	VERB
easat-5823	110	18	that	that	SCONJ
easat-5823	110	19	xgboost	xgboost	PROPN
easat-5823	110	20	has	have	VERB
easat-5823	110	21	the	the	DET
easat-5823	110	22	better	well	ADJ
easat-5823	110	23	performances	performance	NOUN
easat-5823	110	24	.	.	PUNCT
easat-5823	111	1	in	in	ADP
easat-5823	111	2	the	the	DET
easat-5823	111	3	study	study	NOUN
easat-5823	111	4	by	by	ADP
easat-5823	111	5	jain	jain	PROPN
easat-5823	111	6	,	,	PUNCT
easat-5823	111	7	et	et	PROPN
easat-5823	111	8	al	al	PROPN
easat-5823	111	9	.	.	PUNCT
easat-5823	112	1	[	[	X
easat-5823	112	2	11	11	NUM
easat-5823	112	3	]	]	PUNCT
easat-5823	112	4	the	the	DET
easat-5823	112	5	authors	author	NOUN
easat-5823	112	6	analyzed	analyze	VERB
easat-5823	112	7	the	the	DET
easat-5823	112	8	role	role	NOUN
easat-5823	112	9	of	of	ADP
easat-5823	112	10	machine	machine	NOUN
easat-5823	112	11	learning	learn	VERB
easat-5823	112	12	to	to	PART
easat-5823	112	13	detect	detect	VERB
easat-5823	112	14	fraudulent	fraudulent	ADJ
easat-5823	112	15	patterns	pattern	NOUN
easat-5823	112	16	effectively	effectively	ADV
easat-5823	112	17	.	.	PUNCT
easat-5823	113	1	the	the	DET
easat-5823	113	2	study	study	NOUN
easat-5823	113	3	used	use	VERB
easat-5823	113	4	a	a	DET
easat-5823	113	5	credit	credit	NOUN
easat-5823	113	6	card	card	NOUN
easat-5823	113	7	transaction	transaction	NOUN
easat-5823	113	8	dataset	dataset	NOUN
easat-5823	113	9	that	that	PRON
easat-5823	113	10	are	be	AUX
easat-5823	113	11	preprocessed	preprocesse	VERB
easat-5823	113	12	first	first	ADV
easat-5823	113	13	to	to	PART
easat-5823	113	14	address	address	VERB
easat-5823	113	15	the	the	DET
easat-5823	113	16	class	class	NOUN
easat-5823	113	17	imbalance	imbalance	NOUN
easat-5823	113	18	.	.	PUNCT
easat-5823	114	1	the	the	DET
easat-5823	114	2	study	study	NOUN
easat-5823	114	3	compared	compare	VERB
easat-5823	114	4	the	the	DET
easat-5823	114	5	performance	performance	NOUN
easat-5823	114	6	of	of	ADP
easat-5823	114	7	3	3	NUM
easat-5823	114	8	machine	machine	NOUN
easat-5823	114	9	learning	learn	VERB
easat-5823	114	10	algorithms	algorithm	NOUN
easat-5823	114	11	,	,	PUNCT
easat-5823	114	12	such	such	ADJ
easat-5823	114	13	as	as	ADP
easat-5823	114	14	decision	decision	NOUN
easat-5823	114	15	tree	tree	NOUN
easat-5823	114	16	,	,	PUNCT
easat-5823	114	17	random	random	ADJ
easat-5823	114	18	forest	forest	NOUN
easat-5823	114	19	and	and	CCONJ
easat-5823	114	20	xgboost	xgboost	X
easat-5823	114	21	.	.	PUNCT
easat-5823	115	1	the	the	DET
easat-5823	115	2	prediction	prediction	NOUN
easat-5823	115	3	accuracy	accuracy	NOUN
easat-5823	115	4	of	of	ADP
easat-5823	115	5	each	each	DET
easat-5823	115	6	algorithm	algorithm	NOUN
easat-5823	115	7	was	be	AUX
easat-5823	115	8	99.923	99.923	NUM
easat-5823	115	9	%	%	NOUN
easat-5823	115	10	for	for	ADP
easat-5823	115	11	decision	decision	NOUN
easat-5823	115	12	tree	tree	NOUN
easat-5823	115	13	,	,	PUNCT
easat-5823	115	14	99.957	99.957	NUM
easat-5823	115	15	%	%	NOUN
easat-5823	115	16	for	for	ADP
easat-5823	115	17	random	random	ADJ
easat-5823	115	18	forest	forest	NOUN
easat-5823	115	19	and	and	CCONJ
easat-5823	115	20	99.962	99.962	NUM
easat-5823	115	21	%	%	NOUN
easat-5823	115	22	for	for	ADP
easat-5823	115	23	xgboost	xgboost	PROPN
easat-5823	115	24	.	.	PUNCT
easat-5823	116	1	same	same	ADJ
easat-5823	116	2	with	with	ADP
easat-5823	116	3	the	the	DET
easat-5823	116	4	previous	previous	ADJ
easat-5823	116	5	paper	paper	NOUN
easat-5823	116	6	,	,	PUNCT
easat-5823	116	7	the	the	DET
easat-5823	116	8	result	result	NOUN
easat-5823	116	9	showed	show	VERB
easat-5823	116	10	that	that	SCONJ
easat-5823	116	11	xgboost	xgboost	ADV
easat-5823	116	12	is	be	AUX
easat-5823	116	13	the	the	DET
easat-5823	116	14	best	good	ADJ
easat-5823	116	15	out	out	ADP
easat-5823	116	16	of	of	ADP
easat-5823	116	17	all	all	DET
easat-5823	116	18	three	three	NUM
easat-5823	116	19	with	with	ADP
easat-5823	116	20	a	a	DET
easat-5823	116	21	slight	slight	ADJ
easat-5823	116	22	difference	difference	NOUN
easat-5823	116	23	with	with	ADP
easat-5823	116	24	random	random	ADJ
easat-5823	116	25	forest	forest	NOUN
easat-5823	116	26	model	model	NOUN
easat-5823	116	27	.	.	PUNCT
easat-5823	117	1	2485	2485	NUM
easat-5823	117	2	edelweiss	edelweiss	PROPN
easat-5823	117	3	applied	apply	VERB
easat-5823	117	4	science	science	NOUN
easat-5823	117	5	and	and	CCONJ
easat-5823	117	6	technology	technology	NOUN
easat-5823	117	7	issn	issn	PROPN
easat-5823	117	8	:	:	PUNCT
easat-5823	117	9	2576	2576	NUM
easat-5823	117	10	-	-	SYM
easat-5823	117	11	8484	8484	NUM
easat-5823	117	12	vol	vol	NOUN
easat-5823	117	13	.	.	PROPN
easat-5823	118	1	9	9	NUM
easat-5823	118	2	,	,	PUNCT
easat-5823	118	3	no	no	INTJ
easat-5823	118	4	.	.	NOUN
easat-5823	118	5	3	3	NUM
easat-5823	118	6	:	:	PUNCT
easat-5823	118	7	2482	2482	NUM
easat-5823	118	8	-	-	SYM
easat-5823	118	9	2494	2494	NUM
easat-5823	118	10	,	,	PUNCT
easat-5823	118	11	2025	2025	NUM
easat-5823	118	12	doi	doi	NOUN
easat-5823	118	13	:	:	PUNCT
easat-5823	118	14	10.55214/25768484.v9i3.5823	10.55214/25768484.v9i3.5823	NUM
easat-5823	118	15	©	©	PROPN
easat-5823	118	16	2025	2025	NUM
easat-5823	118	17	by	by	ADP
easat-5823	118	18	the	the	DET
easat-5823	118	19	authors	author	NOUN
easat-5823	118	20	;	;	PUNCT
easat-5823	118	21	licensee	licensee	PROPN
easat-5823	118	22	learning	learning	NOUN
easat-5823	118	23	gate	gate	NOUN
easat-5823	118	24	3	3	NUM
easat-5823	118	25	.	.	PUNCT
easat-5823	118	26	methods	method	NOUN
easat-5823	118	27	in	in	ADP
easat-5823	118	28	this	this	DET
easat-5823	118	29	research	research	NOUN
easat-5823	118	30	,	,	PUNCT
easat-5823	118	31	the	the	DET
easat-5823	118	32	workflow	workflow	NOUN
easat-5823	118	33	of	of	ADP
easat-5823	118	34	the	the	DET
easat-5823	118	35	proposed	propose	VERB
easat-5823	118	36	methodology	methodology	NOUN
easat-5823	118	37	can	can	AUX
easat-5823	118	38	be	be	AUX
easat-5823	118	39	seen	see	VERB
easat-5823	118	40	in	in	ADP
easat-5823	118	41	figure	figure	NOUN
easat-5823	118	42	1	1	NUM
easat-5823	118	43	,	,	PUNCT
easat-5823	118	44	which	which	PRON
easat-5823	118	45	starts	start	VERB
easat-5823	118	46	with	with	ADP
easat-5823	118	47	preprocessing	preprocesse	VERB
easat-5823	118	48	the	the	DET
easat-5823	118	49	dataset	dataset	NOUN
easat-5823	118	50	.	.	PUNCT
easat-5823	119	1	preprocessing	preprocesse	VERB
easat-5823	119	2	dataset	dataset	NOUN
easat-5823	119	3	includes	include	VERB
easat-5823	119	4	cleaning	clean	VERB
easat-5823	119	5	the	the	DET
easat-5823	119	6	dataset	dataset	NOUN
easat-5823	119	7	and	and	CCONJ
easat-5823	119	8	splitting	split	VERB
easat-5823	119	9	the	the	DET
easat-5823	119	10	dataset	dataset	NOUN
easat-5823	119	11	into	into	ADP
easat-5823	119	12	train	train	NOUN
easat-5823	119	13	and	and	CCONJ
easat-5823	119	14	test	test	NOUN
easat-5823	119	15	sets	set	NOUN
easat-5823	119	16	.	.	PUNCT
easat-5823	120	1	then	then	ADV
easat-5823	120	2	,	,	PUNCT
easat-5823	120	3	because	because	SCONJ
easat-5823	120	4	of	of	ADP
easat-5823	120	5	the	the	DET
easat-5823	120	6	imbalance	imbalance	NOUN
easat-5823	120	7	in	in	ADP
easat-5823	120	8	the	the	DET
easat-5823	120	9	dataset	dataset	NOUN
easat-5823	120	10	,	,	PUNCT
easat-5823	120	11	smote	smote	NOUN
easat-5823	120	12	will	will	AUX
easat-5823	120	13	be	be	AUX
easat-5823	120	14	used	use	VERB
easat-5823	120	15	to	to	PART
easat-5823	120	16	address	address	VERB
easat-5823	120	17	the	the	DET
easat-5823	120	18	problem	problem	NOUN
easat-5823	120	19	.	.	PUNCT
easat-5823	121	1	standardscaler	standardscaler	NOUN
easat-5823	121	2	will	will	AUX
easat-5823	121	3	also	also	ADV
easat-5823	121	4	be	be	AUX
easat-5823	121	5	applied	apply	VERB
easat-5823	121	6	for	for	ADP
easat-5823	121	7	standardization	standardization	NOUN
easat-5823	121	8	.	.	PUNCT
easat-5823	122	1	the	the	DET
easat-5823	122	2	train	train	NOUN
easat-5823	122	3	data	datum	NOUN
easat-5823	122	4	set	set	VERB
easat-5823	122	5	will	will	AUX
easat-5823	122	6	then	then	ADV
easat-5823	122	7	be	be	AUX
easat-5823	122	8	used	use	VERB
easat-5823	122	9	to	to	PART
easat-5823	122	10	train	train	VERB
easat-5823	122	11	the	the	DET
easat-5823	122	12	multilayer	multilayer	ADJ
easat-5823	122	13	perceptron	perceptron	PROPN
easat-5823	122	14	standalone	standalone	PROPN
easat-5823	122	15	model	model	NOUN
easat-5823	122	16	,	,	PUNCT
easat-5823	122	17	random	random	ADJ
easat-5823	122	18	forest	forest	NOUN
easat-5823	122	19	standalone	standalone	NOUN
easat-5823	122	20	model	model	NOUN
easat-5823	122	21	and	and	CCONJ
easat-5823	122	22	the	the	DET
easat-5823	122	23	proposed	propose	VERB
easat-5823	122	24	multilayer	multilayer	NOUN
easat-5823	122	25	perceptron	perceptron	PROPN
easat-5823	122	26	–	–	PUNCT
easat-5823	122	27	random	random	ADJ
easat-5823	122	28	forest	forest	NOUN
easat-5823	122	29	model	model	NOUN
easat-5823	122	30	.	.	PUNCT
easat-5823	123	1	each	each	DET
easat-5823	123	2	model	model	NOUN
easat-5823	123	3	will	will	AUX
easat-5823	123	4	then	then	ADV
easat-5823	123	5	be	be	AUX
easat-5823	123	6	used	use	VERB
easat-5823	123	7	to	to	PART
easat-5823	123	8	predict	predict	VERB
easat-5823	123	9	the	the	DET
easat-5823	123	10	fraudulent	fraudulent	ADJ
easat-5823	123	11	transaction	transaction	NOUN
easat-5823	123	12	using	use	VERB
easat-5823	123	13	the	the	DET
easat-5823	123	14	test	test	NOUN
easat-5823	123	15	data	datum	NOUN
easat-5823	123	16	set	set	VERB
easat-5823	123	17	that	that	PRON
easat-5823	123	18	has	have	AUX
easat-5823	123	19	been	be	AUX
easat-5823	123	20	split	split	VERB
easat-5823	123	21	at	at	ADP
easat-5823	123	22	the	the	DET
easat-5823	123	23	beginning	beginning	NOUN
easat-5823	123	24	.	.	PUNCT
easat-5823	124	1	lastly	lastly	ADV
easat-5823	124	2	the	the	DET
easat-5823	124	3	performance	performance	NOUN
easat-5823	124	4	of	of	ADP
easat-5823	124	5	each	each	DET
easat-5823	124	6	prediction	prediction	NOUN
easat-5823	124	7	model	model	NOUN
easat-5823	124	8	will	will	AUX
easat-5823	124	9	then	then	ADV
easat-5823	124	10	be	be	AUX
easat-5823	124	11	evaluated	evaluate	VERB
easat-5823	124	12	using	use	VERB
easat-5823	124	13	several	several	ADJ
easat-5823	124	14	evaluation	evaluation	NOUN
easat-5823	124	15	metrics	metric	NOUN
easat-5823	124	16	to	to	PART
easat-5823	124	17	make	make	VERB
easat-5823	124	18	an	an	DET
easat-5823	124	19	analysis	analysis	NOUN
easat-5823	124	20	.	.	PUNCT
easat-5823	125	1	figure	figure	NOUN
easat-5823	125	2	1	1	NUM
easat-5823	125	3	.	.	PUNCT
easat-5823	125	4	system	system	NOUN
easat-5823	125	5	architecture	architecture	NOUN
easat-5823	125	6	of	of	ADP
easat-5823	125	7	the	the	DET
easat-5823	125	8	proposed	propose	VERB
easat-5823	125	9	methodology	methodology	NOUN
easat-5823	125	10	.	.	PUNCT
easat-5823	126	1	3.1	3.1	NUM
easat-5823	126	2	.	.	PUNCT
easat-5823	126	3	dataset	dataset	NOUN
easat-5823	126	4	and	and	CCONJ
easat-5823	126	5	preprocessing	preprocesse	VERB
easat-5823	126	6	the	the	DET
easat-5823	126	7	dataset	dataset	NOUN
easat-5823	126	8	used	use	VERB
easat-5823	126	9	in	in	ADP
easat-5823	126	10	this	this	DET
easat-5823	126	11	study	study	NOUN
easat-5823	126	12	was	be	AUX
easat-5823	126	13	from	from	ADP
easat-5823	126	14	kaggle	kaggle	PROPN
easat-5823	126	15	which	which	PRON
easat-5823	126	16	contains	contain	VERB
easat-5823	126	17	the	the	DET
easat-5823	126	18	data	datum	NOUN
easat-5823	126	19	of	of	ADP
easat-5823	126	20	credit	credit	NOUN
easat-5823	126	21	card	card	NOUN
easat-5823	126	22	transactions	transaction	NOUN
easat-5823	126	23	made	make	VERB
easat-5823	126	24	in	in	ADP
easat-5823	126	25	two	two	NUM
easat-5823	126	26	days	day	NOUN
easat-5823	126	27	by	by	ADP
easat-5823	126	28	european	european	ADJ
easat-5823	126	29	cardholder	cardholder	NOUN
easat-5823	126	30	in	in	ADP
easat-5823	126	31	september	september	PROPN
easat-5823	126	32	2013	2013	NUM
easat-5823	126	33	.	.	PUNCT
easat-5823	127	1	the	the	DET
easat-5823	127	2	dataset	dataset	NOUN
easat-5823	127	3	contains	contain	VERB
easat-5823	127	4	a	a	DET
easat-5823	127	5	total	total	NOUN
easat-5823	127	6	of	of	ADP
easat-5823	127	7	284,807	284,807	NUM
easat-5823	127	8	transactions	transaction	NOUN
easat-5823	127	9	with	with	ADP
easat-5823	127	10	492	492	NUM
easat-5823	127	11	of	of	ADP
easat-5823	127	12	them	they	PRON
easat-5823	127	13	were	be	AUX
easat-5823	127	14	labelled	label	VERB
easat-5823	127	15	as	as	ADP
easat-5823	127	16	fraud	fraud	NOUN
easat-5823	127	17	.	.	PUNCT
easat-5823	128	1	the	the	DET
easat-5823	128	2	dataset	dataset	NOUN
easat-5823	128	3	consists	consist	VERB
easat-5823	128	4	of	of	ADP
easat-5823	128	5	31	31	NUM
easat-5823	128	6	attributes	attribute	NOUN
easat-5823	128	7	in	in	ADP
easat-5823	128	8	which	which	PRON
easat-5823	128	9	28	28	NUM
easat-5823	128	10	of	of	ADP
easat-5823	128	11	them	they	PRON
easat-5823	128	12	were	be	AUX
easat-5823	128	13	the	the	DET
easat-5823	128	14	result	result	NOUN
easat-5823	128	15	of	of	ADP
easat-5823	128	16	a	a	DET
easat-5823	128	17	dimensionality	dimensionality	NOUN
easat-5823	128	18	reduction	reduction	NOUN
easat-5823	128	19	technique	technique	NOUN
easat-5823	128	20	called	call	VERB
easat-5823	128	21	pca	pca	PROPN
easat-5823	128	22	transformation	transformation	NOUN
easat-5823	128	23	named	name	VERB
easat-5823	128	24	v1	v1	PROPN
easat-5823	128	25	,	,	PUNCT
easat-5823	128	26	v2	v2	PROPN
easat-5823	128	27	,	,	PUNCT
easat-5823	128	28	…	…	PUNCT
easat-5823	128	29	v28	v28	VERB
easat-5823	128	30	.	.	PUNCT
easat-5823	129	1	due	due	ADP
easat-5823	129	2	to	to	ADP
easat-5823	129	3	privacy	privacy	NOUN
easat-5823	129	4	issues	issue	NOUN
easat-5823	129	5	,	,	PUNCT
easat-5823	129	6	the	the	DET
easat-5823	129	7	original	original	ADJ
easat-5823	129	8	features	feature	NOUN
easat-5823	129	9	can	can	AUX
easat-5823	129	10	not	not	PART
easat-5823	129	11	be	be	AUX
easat-5823	129	12	provided	provide	VERB
easat-5823	129	13	thus	thus	ADV
easat-5823	129	14	the	the	DET
easat-5823	129	15	anonymized	anonymize	VERB
easat-5823	129	16	features	feature	NOUN
easat-5823	129	17	were	be	AUX
easat-5823	129	18	given	give	VERB
easat-5823	129	19	.	.	PUNCT
easat-5823	130	1	the	the	DET
easat-5823	130	2	“	"	PUNCT
easat-5823	130	3	time	time	NOUN
easat-5823	130	4	”	"	PUNCT
easat-5823	130	5	feature	feature	NOUN
easat-5823	130	6	represents	represent	VERB
easat-5823	130	7	the	the	DET
easat-5823	130	8	time	time	NOUN
easat-5823	130	9	that	that	PRON
easat-5823	130	10	has	have	AUX
easat-5823	130	11	passed	pass	VERB
easat-5823	130	12	between	between	ADP
easat-5823	130	13	each	each	DET
easat-5823	130	14	transaction	transaction	NOUN
easat-5823	130	15	and	and	CCONJ
easat-5823	130	16	the	the	DET
easat-5823	130	17	initial	initial	ADJ
easat-5823	130	18	transaction	transaction	NOUN
easat-5823	130	19	.	.	PUNCT
easat-5823	131	1	the	the	DET
easat-5823	131	2	“	"	PUNCT
easat-5823	131	3	amount	amount	NOUN
easat-5823	131	4	”	"	PUNCT
easat-5823	131	5	feature	feature	NOUN
easat-5823	131	6	is	be	AUX
easat-5823	131	7	the	the	DET
easat-5823	131	8	amount	amount	NOUN
easat-5823	131	9	made	make	VERB
easat-5823	131	10	in	in	ADP
easat-5823	131	11	each	each	DET
easat-5823	131	12	transaction	transaction	NOUN
easat-5823	131	13	.	.	PUNCT
easat-5823	132	1	lastly	lastly	ADV
easat-5823	132	2	,	,	PUNCT
easat-5823	132	3	the	the	DET
easat-5823	132	4	“	"	PUNCT
easat-5823	132	5	class	class	NOUN
easat-5823	132	6	”	"	PUNCT
easat-5823	132	7	feature	feature	NOUN
easat-5823	132	8	shows	show	VERB
easat-5823	132	9	whether	whether	SCONJ
easat-5823	132	10	the	the	DET
easat-5823	132	11	transaction	transaction	NOUN
easat-5823	132	12	is	be	AUX
easat-5823	132	13	fraudulent	fraudulent	ADJ
easat-5823	132	14	or	or	CCONJ
easat-5823	132	15	not	not	PART
easat-5823	132	16	by	by	ADP
easat-5823	132	17	labelling	label	VERB
easat-5823	132	18	it	it	PRON
easat-5823	132	19	with	with	ADP
easat-5823	132	20	1	1	NUM
easat-5823	132	21	for	for	ADP
easat-5823	132	22	fraud	fraud	NOUN
easat-5823	132	23	transaction	transaction	NOUN
easat-5823	132	24	and	and	CCONJ
easat-5823	132	25	0	0	NUM
easat-5823	132	26	for	for	ADP
easat-5823	132	27	genuine	genuine	ADJ
easat-5823	132	28	transaction	transaction	NOUN
easat-5823	132	29	.	.	PUNCT
easat-5823	133	1	in	in	ADP
easat-5823	133	2	this	this	DET
easat-5823	133	3	study	study	NOUN
easat-5823	133	4	,	,	PUNCT
easat-5823	133	5	the	the	DET
easat-5823	133	6	dataset	dataset	NOUN
easat-5823	133	7	was	be	AUX
easat-5823	133	8	split	split	VERB
easat-5823	133	9	into	into	ADP
easat-5823	133	10	80	80	NUM
easat-5823	133	11	%	%	NOUN
easat-5823	133	12	of	of	ADP
easat-5823	133	13	train	train	NOUN
easat-5823	133	14	set	set	NOUN
easat-5823	133	15	and	and	CCONJ
easat-5823	133	16	20	20	NUM
easat-5823	133	17	%	%	NOUN
easat-5823	133	18	of	of	ADP
easat-5823	133	19	test	test	NOUN
easat-5823	133	20	set	set	VERB
easat-5823	133	21	.	.	PUNCT
easat-5823	134	1	the	the	DET
easat-5823	134	2	train	train	NOUN
easat-5823	134	3	set	set	NOUN
easat-5823	134	4	was	be	AUX
easat-5823	134	5	used	use	VERB
easat-5823	134	6	for	for	ADP
easat-5823	134	7	training	train	VERB
easat-5823	134	8	the	the	DET
easat-5823	134	9	models	model	NOUN
easat-5823	134	10	and	and	CCONJ
easat-5823	134	11	the	the	DET
easat-5823	134	12	test	test	NOUN
easat-5823	134	13	set	set	NOUN
easat-5823	134	14	was	be	AUX
easat-5823	134	15	later	later	ADV
easat-5823	134	16	used	use	VERB
easat-5823	134	17	for	for	ADP
easat-5823	134	18	evaluating	evaluate	VERB
easat-5823	134	19	the	the	DET
easat-5823	134	20	2486	2486	NUM
easat-5823	134	21	edelweiss	edelweiss	PROPN
easat-5823	134	22	applied	apply	VERB
easat-5823	134	23	science	science	NOUN
easat-5823	134	24	and	and	CCONJ
easat-5823	134	25	technology	technology	NOUN
easat-5823	134	26	issn	issn	PROPN
easat-5823	134	27	:	:	PUNCT
easat-5823	134	28	2576	2576	NUM
easat-5823	134	29	-	-	SYM
easat-5823	134	30	8484	8484	NUM
easat-5823	134	31	vol	vol	NOUN
easat-5823	134	32	.	.	PROPN
easat-5823	135	1	9	9	NUM
easat-5823	135	2	,	,	PUNCT
easat-5823	135	3	no	no	INTJ
easat-5823	135	4	.	.	NOUN
easat-5823	135	5	3	3	NUM
easat-5823	135	6	:	:	PUNCT
easat-5823	135	7	2482	2482	NUM
easat-5823	135	8	-	-	SYM
easat-5823	135	9	2494	2494	NUM
easat-5823	135	10	,	,	PUNCT
easat-5823	135	11	2025	2025	NUM
easat-5823	135	12	doi	doi	NOUN
easat-5823	135	13	:	:	PUNCT
easat-5823	135	14	10.55214/25768484.v9i3.5823	10.55214/25768484.v9i3.5823	NUM
easat-5823	135	15	©	©	PROPN
easat-5823	135	16	2025	2025	NUM
easat-5823	135	17	by	by	ADP
easat-5823	135	18	the	the	DET
easat-5823	135	19	authors	author	NOUN
easat-5823	135	20	;	;	PUNCT
easat-5823	135	21	licensee	licensee	PROPN
easat-5823	135	22	learning	learning	NOUN
easat-5823	135	23	gate	gate	NOUN
easat-5823	135	24	performance	performance	NOUN
easat-5823	135	25	of	of	ADP
easat-5823	135	26	each	each	DET
easat-5823	135	27	model	model	NOUN
easat-5823	135	28	.	.	PUNCT
easat-5823	136	1	with	with	ADP
easat-5823	136	2	only	only	ADV
easat-5823	136	3	0.1729	0.1729	NUM
easat-5823	136	4	%	%	NOUN
easat-5823	136	5	of	of	ADP
easat-5823	136	6	the	the	DET
easat-5823	136	7	total	total	ADJ
easat-5823	136	8	transactions	transaction	NOUN
easat-5823	136	9	being	be	AUX
easat-5823	136	10	fraud	fraud	NOUN
easat-5823	136	11	,	,	PUNCT
easat-5823	136	12	this	this	PRON
easat-5823	136	13	clearly	clearly	ADV
easat-5823	136	14	shows	show	VERB
easat-5823	136	15	that	that	SCONJ
easat-5823	136	16	the	the	DET
easat-5823	136	17	dataset	dataset	NOUN
easat-5823	136	18	is	be	AUX
easat-5823	136	19	extremely	extremely	ADV
easat-5823	136	20	imbalanced	imbalanced	ADJ
easat-5823	136	21	as	as	SCONJ
easat-5823	136	22	depicted	depict	VERB
easat-5823	136	23	in	in	ADP
easat-5823	136	24	figure	figure	NOUN
easat-5823	136	25	2	2	NUM
easat-5823	136	26	.	.	PUNCT
easat-5823	136	27	figure	figure	NOUN
easat-5823	136	28	2	2	NUM
easat-5823	136	29	.	.	PUNCT
easat-5823	136	30	pie	pie	NOUN
easat-5823	136	31	chart	chart	NOUN
easat-5823	136	32	of	of	ADP
easat-5823	136	33	class	class	NOUN
easat-5823	136	34	distribution	distribution	NOUN
easat-5823	136	35	before	before	ADP
easat-5823	136	36	applying	apply	VERB
easat-5823	136	37	smote	smote	ADJ
easat-5823	136	38	.	.	PUNCT
easat-5823	137	1	figure	figure	VERB
easat-5823	137	2	3	3	NUM
easat-5823	137	3	.	.	PUNCT
easat-5823	137	4	pie	pie	NOUN
easat-5823	137	5	chart	chart	NOUN
easat-5823	137	6	of	of	ADP
easat-5823	137	7	class	class	NOUN
easat-5823	137	8	distribution	distribution	NOUN
easat-5823	137	9	after	after	ADP
easat-5823	137	10	applying	apply	VERB
easat-5823	137	11	smote	smote	VERB
easat-5823	137	12	the	the	DET
easat-5823	137	13	imbalanced	imbalanced	ADJ
easat-5823	137	14	in	in	ADP
easat-5823	137	15	data	datum	NOUN
easat-5823	137	16	can	can	AUX
easat-5823	137	17	prove	prove	VERB
easat-5823	137	18	to	to	PART
easat-5823	137	19	be	be	AUX
easat-5823	137	20	a	a	DET
easat-5823	137	21	problem	problem	NOUN
easat-5823	137	22	for	for	ADP
easat-5823	137	23	training	train	VERB
easat-5823	137	24	the	the	DET
easat-5823	137	25	machine	machine	NOUN
easat-5823	137	26	learning	learn	VERB
easat-5823	137	27	algorithms	algorithm	NOUN
easat-5823	137	28	[	[	X
easat-5823	137	29	6	6	NUM
easat-5823	137	30	]	]	PUNCT
easat-5823	137	31	.	.	PUNCT
easat-5823	138	1	therefore	therefore	ADV
easat-5823	138	2	,	,	PUNCT
easat-5823	138	3	synthetic	synthetic	ADJ
easat-5823	138	4	minority	minority	NOUN
easat-5823	138	5	oversampling	oversample	VERB
easat-5823	138	6	technique	technique	NOUN
easat-5823	138	7	(	(	PUNCT
easat-5823	138	8	smote	smote	NOUN
easat-5823	138	9	)	)	PUNCT
easat-5823	138	10	was	be	AUX
easat-5823	138	11	utilized	utilize	VERB
easat-5823	138	12	to	to	ADP
easat-5823	138	13	addresses	address	NOUN
easat-5823	138	14	this	this	DET
easat-5823	138	15	problem	problem	NOUN
easat-5823	138	16	.	.	PUNCT
easat-5823	139	1	smote	smote	ADJ
easat-5823	139	2	is	be	AUX
easat-5823	139	3	a	a	DET
easat-5823	139	4	preprocessing	preprocessing	NOUN
easat-5823	139	5	algorithm	algorithm	NOUN
easat-5823	139	6	that	that	PRON
easat-5823	139	7	is	be	AUX
easat-5823	139	8	widely	widely	ADV
easat-5823	139	9	used	use	VERB
easat-5823	139	10	due	due	ADP
easat-5823	139	11	to	to	ADP
easat-5823	139	12	its	its	PRON
easat-5823	139	13	simplicity	simplicity	NOUN
easat-5823	139	14	and	and	CCONJ
easat-5823	139	15	robustness	robustness	NOUN
easat-5823	139	16	for	for	ADP
easat-5823	139	17	handling	handle	VERB
easat-5823	139	18	imbalanced	imbalanced	ADJ
easat-5823	139	19	data	datum	NOUN
easat-5823	139	20	[	[	X
easat-5823	139	21	17	17	NUM
easat-5823	139	22	]	]	PUNCT
easat-5823	139	23	.	.	PUNCT
easat-5823	140	1	in	in	ADP
easat-5823	140	2	this	this	DET
easat-5823	140	3	study	study	NOUN
easat-5823	140	4	,	,	PUNCT
easat-5823	140	5	smote	smote	ADJ
easat-5823	140	6	algorithm	algorithm	PROPN
easat-5823	140	7	was	be	AUX
easat-5823	140	8	used	use	VERB
easat-5823	140	9	for	for	SCONJ
easat-5823	140	10	the	the	DET
easat-5823	140	11	train	train	NOUN
easat-5823	140	12	set	set	NOUN
easat-5823	140	13	only	only	ADV
easat-5823	140	14	to	to	PART
easat-5823	140	15	balance	balance	VERB
easat-5823	140	16	the	the	DET
easat-5823	140	17	class	class	NOUN
easat-5823	140	18	distribution	distribution	NOUN
easat-5823	140	19	of	of	ADP
easat-5823	140	20	the	the	DET
easat-5823	140	21	data	datum	NOUN
easat-5823	140	22	.	.	PUNCT
easat-5823	141	1	as	as	SCONJ
easat-5823	141	2	depicted	depict	VERB
easat-5823	141	3	in	in	ADP
easat-5823	141	4	figure	figure	NOUN
easat-5823	141	5	3	3	NUM
easat-5823	141	6	,	,	PUNCT
easat-5823	141	7	the	the	DET
easat-5823	141	8	class	class	NOUN
easat-5823	141	9	distribution	distribution	NOUN
easat-5823	141	10	has	have	AUX
easat-5823	141	11	been	be	AUX
easat-5823	141	12	successfully	successfully	ADV
easat-5823	141	13	balanced	balance	VERB
easat-5823	141	14	with	with	ADP
easat-5823	141	15	227,451	227,451	NUM
easat-5823	141	16	transactions	transaction	NOUN
easat-5823	141	17	labelled	label	VERB
easat-5823	141	18	as	as	ADP
easat-5823	141	19	non	non	ADJ
easat-5823	141	20	-	-	NOUN
easat-5823	141	21	fraud	fraud	NOUN
easat-5823	141	22	and	and	CCONJ
easat-5823	141	23	227,451	227,451	NUM
easat-5823	141	24	transactions	transaction	NOUN
easat-5823	141	25	also	also	ADV
easat-5823	141	26	labelled	label	VERB
easat-5823	141	27	as	as	ADP
easat-5823	141	28	fraud	fraud	NOUN
easat-5823	141	29	.	.	PUNCT
easat-5823	142	1	after	after	ADP
easat-5823	142	2	balancing	balance	VERB
easat-5823	142	3	the	the	DET
easat-5823	142	4	class	class	NOUN
easat-5823	142	5	distribution	distribution	NOUN
easat-5823	142	6	,	,	PUNCT
easat-5823	142	7	standardscaler	standardscaler	NOUN
easat-5823	142	8	was	be	AUX
easat-5823	142	9	also	also	ADV
easat-5823	142	10	used	use	VERB
easat-5823	142	11	to	to	PART
easat-5823	142	12	standardized	standardized	VERB
easat-5823	142	13	2487	2487	NUM
easat-5823	142	14	edelweiss	edelweiss	PROPN
easat-5823	142	15	applied	apply	VERB
easat-5823	142	16	science	science	NOUN
easat-5823	142	17	and	and	CCONJ
easat-5823	142	18	technology	technology	NOUN
easat-5823	142	19	issn	issn	PROPN
easat-5823	142	20	:	:	PUNCT
easat-5823	142	21	2576	2576	NUM
easat-5823	142	22	-	-	SYM
easat-5823	142	23	8484	8484	NUM
easat-5823	142	24	vol	vol	NOUN
easat-5823	142	25	.	.	PROPN
easat-5823	143	1	9	9	NUM
easat-5823	143	2	,	,	PUNCT
easat-5823	143	3	no	no	INTJ
easat-5823	143	4	.	.	NOUN
easat-5823	143	5	3	3	NUM
easat-5823	143	6	:	:	PUNCT
easat-5823	143	7	2482	2482	NUM
easat-5823	143	8	-	-	SYM
easat-5823	143	9	2494	2494	NUM
easat-5823	143	10	,	,	PUNCT
easat-5823	143	11	2025	2025	NUM
easat-5823	143	12	doi	doi	NOUN
easat-5823	143	13	:	:	PUNCT
easat-5823	143	14	10.55214/25768484.v9i3.5823	10.55214/25768484.v9i3.5823	NUM
easat-5823	143	15	©	©	PROPN
easat-5823	143	16	2025	2025	NUM
easat-5823	143	17	by	by	ADP
easat-5823	143	18	the	the	DET
easat-5823	143	19	authors	author	NOUN
easat-5823	143	20	;	;	PUNCT
easat-5823	143	21	licensee	licensee	PROPN
easat-5823	143	22	learning	learning	NOUN
easat-5823	143	23	gate	gate	VERB
easat-5823	143	24	the	the	DET
easat-5823	143	25	data	datum	NOUN
easat-5823	143	26	.	.	PUNCT
easat-5823	144	1	standardscaler	standardscaler	NOUN
easat-5823	144	2	is	be	AUX
easat-5823	144	3	a	a	DET
easat-5823	144	4	standardization	standardization	NOUN
easat-5823	144	5	method	method	NOUN
easat-5823	144	6	that	that	PRON
easat-5823	144	7	scale	scale	VERB
easat-5823	144	8	the	the	DET
easat-5823	144	9	features	feature	NOUN
easat-5823	144	10	by	by	ADP
easat-5823	144	11	removing	remove	VERB
easat-5823	144	12	the	the	DET
easat-5823	144	13	mean	mean	NOUN
easat-5823	144	14	and	and	CCONJ
easat-5823	144	15	scaling	scale	VERB
easat-5823	144	16	the	the	DET
easat-5823	144	17	features	feature	NOUN
easat-5823	144	18	to	to	ADP
easat-5823	144	19	unit	unit	NOUN
easat-5823	144	20	variance	variance	NOUN
easat-5823	144	21	(	(	PUNCT
easat-5823	144	22	standard	standard	ADJ
easat-5823	144	23	deviation	deviation	NOUN
easat-5823	144	24	of	of	ADP
easat-5823	144	25	1	1	NUM
easat-5823	144	26	)	)	PUNCT
easat-5823	145	1	[	[	X
easat-5823	145	2	18	18	NUM
easat-5823	145	3	]	]	SYM
easat-5823	145	4	.	.	PUNCT
easat-5823	146	1	3.2	3.2	NUM
easat-5823	146	2	.	.	PUNCT
easat-5823	146	3	model	model	NOUN
easat-5823	146	4	training	training	NOUN
easat-5823	146	5	in	in	ADP
easat-5823	146	6	this	this	DET
easat-5823	146	7	study	study	NOUN
easat-5823	146	8	,	,	PUNCT
easat-5823	146	9	the	the	DET
easat-5823	146	10	proposed	propose	VERB
easat-5823	146	11	method	method	NOUN
easat-5823	146	12	will	will	AUX
easat-5823	146	13	use	use	VERB
easat-5823	146	14	mlp	mlp	NOUN
easat-5823	146	15	for	for	ADP
easat-5823	146	16	feature	feature	NOUN
easat-5823	146	17	extraction	extraction	NOUN
easat-5823	146	18	and	and	CCONJ
easat-5823	146	19	then	then	ADV
easat-5823	146	20	random	random	ADJ
easat-5823	146	21	forest	forest	NOUN
easat-5823	146	22	will	will	AUX
easat-5823	146	23	be	be	AUX
easat-5823	146	24	used	use	VERB
easat-5823	146	25	for	for	ADP
easat-5823	146	26	prediction	prediction	NOUN
easat-5823	146	27	.	.	PUNCT
easat-5823	147	1	the	the	DET
easat-5823	147	2	proposed	propose	VERB
easat-5823	147	3	method	method	NOUN
easat-5823	147	4	will	will	AUX
easat-5823	147	5	then	then	ADV
easat-5823	147	6	be	be	AUX
easat-5823	147	7	compared	compare	VERB
easat-5823	147	8	to	to	ADP
easat-5823	147	9	the	the	DET
easat-5823	147	10	standalone	standalone	ADJ
easat-5823	147	11	mlp	mlp	NOUN
easat-5823	147	12	and	and	CCONJ
easat-5823	147	13	random	random	ADJ
easat-5823	147	14	forest	forest	NOUN
easat-5823	147	15	.	.	PUNCT
easat-5823	148	1	the	the	DET
easat-5823	148	2	comparison	comparison	NOUN
easat-5823	148	3	will	will	AUX
easat-5823	148	4	be	be	AUX
easat-5823	148	5	used	use	VERB
easat-5823	148	6	to	to	PART
easat-5823	148	7	evaluate	evaluate	VERB
easat-5823	148	8	each	each	DET
easat-5823	148	9	performance	performance	NOUN
easat-5823	148	10	of	of	ADP
easat-5823	148	11	the	the	DET
easat-5823	148	12	method	method	NOUN
easat-5823	148	13	.	.	PUNCT
easat-5823	149	1	mlp	mlp	NOUN
easat-5823	149	2	is	be	AUX
easat-5823	149	3	a	a	DET
easat-5823	149	4	feed	feed	NOUN
easat-5823	149	5	-	-	PUNCT
easat-5823	149	6	forward	forward	ADV
easat-5823	149	7	artificial	artificial	ADJ
easat-5823	149	8	neural	neural	ADJ
easat-5823	149	9	network	network	NOUN
easat-5823	149	10	(	(	PUNCT
easat-5823	149	11	ann	ann	PROPN
easat-5823	149	12	)	)	PUNCT
easat-5823	149	13	where	where	SCONJ
easat-5823	149	14	the	the	DET
easat-5823	149	15	network	network	NOUN
easat-5823	149	16	is	be	AUX
easat-5823	149	17	made	make	VERB
easat-5823	149	18	of	of	ADP
easat-5823	149	19	multiple	multiple	ADJ
easat-5823	149	20	layers	layer	NOUN
easat-5823	149	21	of	of	ADP
easat-5823	149	22	neurons	neuron	NOUN
easat-5823	149	23	that	that	PRON
easat-5823	149	24	are	be	AUX
easat-5823	149	25	linked	link	VERB
easat-5823	149	26	together	together	ADV
easat-5823	149	27	by	by	ADP
easat-5823	149	28	connecting	connect	VERB
easat-5823	149	29	weights	weight	NOUN
easat-5823	149	30	[	[	X
easat-5823	149	31	19	19	NUM
easat-5823	149	32	]	]	PUNCT
easat-5823	149	33	.	.	PUNCT
easat-5823	150	1	mlp	mlp	NOUN
easat-5823	150	2	transforms	transform	VERB
easat-5823	150	3	a	a	DET
easat-5823	150	4	set	set	NOUN
easat-5823	150	5	of	of	ADP
easat-5823	150	6	given	give	VERB
easat-5823	150	7	inputs	input	NOUN
easat-5823	150	8	into	into	ADP
easat-5823	150	9	the	the	DET
easat-5823	150	10	desired	desire	VERB
easat-5823	150	11	output	output	NOUN
easat-5823	150	12	.	.	PUNCT
easat-5823	151	1	mlp	mlp	NOUN
easat-5823	151	2	consists	consist	VERB
easat-5823	151	3	of	of	ADP
easat-5823	151	4	three	three	NUM
easat-5823	151	5	layers	layer	NOUN
easat-5823	151	6	such	such	ADJ
easat-5823	151	7	as	as	ADP
easat-5823	151	8	input	input	NOUN
easat-5823	151	9	layer	layer	NOUN
easat-5823	151	10	to	to	PART
easat-5823	151	11	receive	receive	VERB
easat-5823	151	12	data	data	NOUN
easat-5823	151	13	inputs	input	NOUN
easat-5823	151	14	,	,	PUNCT
easat-5823	151	15	hidden	hide	VERB
easat-5823	151	16	layer	layer	NOUN
easat-5823	151	17	to	to	PART
easat-5823	151	18	process	process	VERB
easat-5823	151	19	the	the	DET
easat-5823	151	20	data	datum	NOUN
easat-5823	151	21	and	and	CCONJ
easat-5823	151	22	output	output	NOUN
easat-5823	151	23	layer	layer	NOUN
easat-5823	151	24	which	which	PRON
easat-5823	151	25	will	will	AUX
easat-5823	151	26	output	output	VERB
easat-5823	151	27	the	the	DET
easat-5823	151	28	final	final	ADJ
easat-5823	151	29	prediction	prediction	NOUN
easat-5823	151	30	.	.	PUNCT
easat-5823	152	1	each	each	DET
easat-5823	152	2	layer	layer	NOUN
easat-5823	152	3	consists	consist	VERB
easat-5823	152	4	of	of	ADP
easat-5823	152	5	a	a	DET
easat-5823	152	6	number	number	NOUN
easat-5823	152	7	of	of	ADP
easat-5823	152	8	neurons	neuron	NOUN
easat-5823	152	9	where	where	SCONJ
easat-5823	152	10	the	the	DET
easat-5823	152	11	weight	weight	NOUN
easat-5823	152	12	and	and	CCONJ
easat-5823	152	13	bias	bias	NOUN
easat-5823	152	14	are	be	AUX
easat-5823	152	15	used	use	VERB
easat-5823	152	16	to	to	PART
easat-5823	152	17	connect	connect	VERB
easat-5823	152	18	the	the	DET
easat-5823	152	19	neurons	neuron	NOUN
easat-5823	152	20	between	between	ADP
easat-5823	152	21	each	each	DET
easat-5823	152	22	layer	layer	NOUN
easat-5823	152	23	.	.	PUNCT
easat-5823	153	1	in	in	ADP
easat-5823	153	2	this	this	DET
easat-5823	153	3	study	study	NOUN
easat-5823	153	4	,	,	PUNCT
easat-5823	153	5	the	the	DET
easat-5823	153	6	standalone	standalone	ADJ
easat-5823	153	7	mlp	mlp	NOUN
easat-5823	153	8	method	method	NOUN
easat-5823	153	9	used	use	VERB
easat-5823	153	10	the	the	DET
easat-5823	153	11	default	default	NOUN
easat-5823	153	12	parameter	parameter	NOUN
easat-5823	153	13	which	which	PRON
easat-5823	153	14	had	have	VERB
easat-5823	153	15	1	1	NUM
easat-5823	153	16	hidden	hidden	ADJ
easat-5823	153	17	layer	layer	NOUN
easat-5823	153	18	with	with	ADP
easat-5823	153	19	100	100	NUM
easat-5823	153	20	neurons	neuron	NOUN
easat-5823	153	21	.	.	PUNCT
easat-5823	154	1	random	random	ADJ
easat-5823	154	2	forest	forest	NOUN
easat-5823	154	3	is	be	AUX
easat-5823	154	4	an	an	DET
easat-5823	154	5	ensemble	ensemble	ADJ
easat-5823	154	6	-	-	PUNCT
easat-5823	154	7	based	base	VERB
easat-5823	154	8	machine	machine	NOUN
easat-5823	154	9	learning	learning	NOUN
easat-5823	154	10	algorithm	algorithm	NOUN
easat-5823	154	11	introduced	introduce	VERB
easat-5823	154	12	by	by	ADP
easat-5823	154	13	breiman	breiman	NOUN
easat-5823	154	14	[	[	X
easat-5823	154	15	20	20	NUM
easat-5823	154	16	]	]	PUNCT
easat-5823	154	17	.	.	PUNCT
easat-5823	155	1	this	this	DET
easat-5823	155	2	technique	technique	NOUN
easat-5823	155	3	is	be	AUX
easat-5823	155	4	a	a	DET
easat-5823	155	5	development	development	NOUN
easat-5823	155	6	of	of	ADP
easat-5823	155	7	the	the	DET
easat-5823	155	8	bagging	bagging	NOUN
easat-5823	155	9	method	method	NOUN
easat-5823	155	10	by	by	ADP
easat-5823	155	11	introducing	introduce	VERB
easat-5823	155	12	the	the	DET
easat-5823	155	13	concept	concept	NOUN
easat-5823	155	14	of	of	ADP
easat-5823	155	15	random	random	ADJ
easat-5823	155	16	feature	feature	NOUN
easat-5823	155	17	selection	selection	NOUN
easat-5823	155	18	at	at	ADP
easat-5823	155	19	each	each	DET
easat-5823	155	20	split	split	ADJ
easat-5823	155	21	node	node	NOUN
easat-5823	155	22	in	in	ADP
easat-5823	155	23	the	the	DET
easat-5823	155	24	decision	decision	NOUN
easat-5823	155	25	tree	tree	NOUN
easat-5823	155	26	.	.	PUNCT
easat-5823	156	1	random	random	ADJ
easat-5823	156	2	forest	forest	NOUN
easat-5823	156	3	builds	build	VERB
easat-5823	156	4	many	many	ADJ
easat-5823	156	5	decision	decision	NOUN
easat-5823	156	6	trees	tree	NOUN
easat-5823	156	7	during	during	ADP
easat-5823	156	8	training	training	NOUN
easat-5823	156	9	and	and	CCONJ
easat-5823	156	10	combines	combine	VERB
easat-5823	156	11	the	the	DET
easat-5823	156	12	results	result	NOUN
easat-5823	156	13	of	of	ADP
easat-5823	156	14	each	each	DET
easat-5823	156	15	tree	tree	NOUN
easat-5823	156	16	to	to	PART
easat-5823	156	17	produce	produce	VERB
easat-5823	156	18	more	more	ADV
easat-5823	156	19	accurate	accurate	ADJ
easat-5823	156	20	and	and	CCONJ
easat-5823	156	21	stable	stable	ADJ
easat-5823	156	22	predictions	prediction	NOUN
easat-5823	156	23	.	.	PUNCT
easat-5823	157	1	random	random	ADJ
easat-5823	157	2	forest	forest	NOUN
easat-5823	157	3	has	have	VERB
easat-5823	157	4	two	two	NUM
easat-5823	157	5	main	main	ADJ
easat-5823	157	6	concepts	concept	NOUN
easat-5823	157	7	which	which	PRON
easat-5823	157	8	are	be	AUX
easat-5823	157	9	bootstrap	bootstrap	NOUN
easat-5823	157	10	sampling	sampling	NOUN
easat-5823	157	11	and	and	CCONJ
easat-5823	157	12	random	random	ADJ
easat-5823	157	13	feature	feature	NOUN
easat-5823	157	14	selection	selection	NOUN
easat-5823	157	15	.	.	PUNCT
easat-5823	158	1	bootstrap	bootstrap	NOUN
easat-5823	158	2	sampling	sampling	NOUN
easat-5823	158	3	is	be	AUX
easat-5823	158	4	used	use	VERB
easat-5823	158	5	to	to	PART
easat-5823	158	6	ensure	ensure	VERB
easat-5823	158	7	that	that	SCONJ
easat-5823	158	8	each	each	DET
easat-5823	158	9	tree	tree	NOUN
easat-5823	158	10	is	be	AUX
easat-5823	158	11	trained	train	VERB
easat-5823	158	12	with	with	ADP
easat-5823	158	13	different	different	ADJ
easat-5823	158	14	subsets	subset	NOUN
easat-5823	158	15	of	of	ADP
easat-5823	158	16	data	datum	NOUN
easat-5823	158	17	thus	thus	ADV
easat-5823	158	18	reducing	reduce	VERB
easat-5823	158	19	overfitting	overfitting	NOUN
easat-5823	158	20	.	.	PUNCT
easat-5823	159	1	random	random	ADJ
easat-5823	159	2	feature	feature	NOUN
easat-5823	159	3	selection	selection	NOUN
easat-5823	159	4	selects	select	NOUN
easat-5823	159	5	a	a	DET
easat-5823	159	6	random	random	ADJ
easat-5823	159	7	subset	subset	NOUN
easat-5823	159	8	for	for	ADP
easat-5823	159	9	consideration	consideration	NOUN
easat-5823	159	10	to	to	PART
easat-5823	159	11	determine	determine	VERB
easat-5823	159	12	the	the	DET
easat-5823	159	13	best	good	ADJ
easat-5823	159	14	splits	split	NOUN
easat-5823	159	15	thus	thus	ADV
easat-5823	159	16	ensuring	ensure	VERB
easat-5823	159	17	that	that	SCONJ
easat-5823	159	18	the	the	DET
easat-5823	159	19	model	model	NOUN
easat-5823	159	20	is	be	AUX
easat-5823	159	21	diverse	diverse	ADJ
easat-5823	159	22	.	.	PUNCT
easat-5823	160	1	in	in	ADP
easat-5823	160	2	this	this	DET
easat-5823	160	3	study	study	NOUN
easat-5823	160	4	,	,	PUNCT
easat-5823	160	5	the	the	DET
easat-5823	160	6	standalone	standalone	ADJ
easat-5823	160	7	random	random	ADJ
easat-5823	160	8	forest	forest	NOUN
easat-5823	160	9	that	that	PRON
easat-5823	160	10	was	be	AUX
easat-5823	160	11	used	use	VERB
easat-5823	160	12	for	for	ADP
easat-5823	160	13	comparison	comparison	NOUN
easat-5823	160	14	used	use	VERB
easat-5823	160	15	the	the	DET
easat-5823	160	16	default	default	NOUN
easat-5823	160	17	parameter	parameter	NOUN
easat-5823	160	18	.	.	PUNCT
easat-5823	161	1	these	these	DET
easat-5823	161	2	parameters	parameter	NOUN
easat-5823	161	3	consisted	consist	VERB
easat-5823	161	4	of	of	ADP
easat-5823	161	5	several	several	ADJ
easat-5823	161	6	parameters	parameter	NOUN
easat-5823	161	7	including	include	VERB
easat-5823	161	8	number	number	NOUN
easat-5823	161	9	of	of	ADP
easat-5823	161	10	trees	tree	NOUN
easat-5823	161	11	of	of	ADP
easat-5823	161	12	100	100	NUM
easat-5823	161	13	,	,	PUNCT
easat-5823	161	14	minimum	minimum	ADJ
easat-5823	161	15	number	number	NOUN
easat-5823	161	16	of	of	ADP
easat-5823	161	17	samples	sample	NOUN
easat-5823	161	18	to	to	PART
easat-5823	161	19	split	split	VERB
easat-5823	161	20	of	of	ADP
easat-5823	161	21	2	2	NUM
easat-5823	161	22	and	and	CCONJ
easat-5823	161	23	minimum	minimum	NOUN
easat-5823	161	24	samples	sample	NOUN
easat-5823	161	25	at	at	ADP
easat-5823	161	26	a	a	DET
easat-5823	161	27	leaf	leaf	NOUN
easat-5823	161	28	node	node	NOUN
easat-5823	161	29	of	of	ADP
easat-5823	161	30	1	1	NUM
easat-5823	161	31	.	.	PUNCT
easat-5823	161	32	figure	figure	VERB
easat-5823	161	33	4	4	NUM
easat-5823	161	34	.	.	PUNCT
easat-5823	161	35	system	system	NOUN
easat-5823	161	36	architecture	architecture	NOUN
easat-5823	161	37	of	of	ADP
easat-5823	161	38	the	the	DET
easat-5823	161	39	proposed	propose	VERB
easat-5823	161	40	methodology	methodology	NOUN
easat-5823	161	41	.	.	PUNCT
easat-5823	162	1	for	for	ADP
easat-5823	162	2	the	the	DET
easat-5823	162	3	proposed	propose	VERB
easat-5823	162	4	method	method	NOUN
easat-5823	162	5	,	,	PUNCT
easat-5823	162	6	figure	figure	NOUN
easat-5823	162	7	4	4	NUM
easat-5823	162	8	is	be	AUX
easat-5823	162	9	used	use	VERB
easat-5823	162	10	to	to	PART
easat-5823	162	11	visualize	visualize	VERB
easat-5823	162	12	the	the	DET
easat-5823	162	13	flow	flow	NOUN
easat-5823	162	14	of	of	ADP
easat-5823	162	15	the	the	DET
easat-5823	162	16	proposed	propose	VERB
easat-5823	162	17	architecture	architecture	NOUN
easat-5823	162	18	.	.	PUNCT
easat-5823	163	1	first	first	ADV
easat-5823	163	2	,	,	PUNCT
easat-5823	163	3	the	the	DET
easat-5823	163	4	input	input	NOUN
easat-5823	163	5	data	datum	NOUN
easat-5823	163	6	was	be	AUX
easat-5823	163	7	used	use	VERB
easat-5823	163	8	to	to	PART
easat-5823	163	9	train	train	VERB
easat-5823	163	10	the	the	DET
easat-5823	163	11	mlp	mlp	NOUN
easat-5823	163	12	model	model	NOUN
easat-5823	163	13	as	as	ADP
easat-5823	163	14	a	a	DET
easat-5823	163	15	feature	feature	NOUN
easat-5823	163	16	extractor	extractor	NOUN
easat-5823	163	17	.	.	PUNCT
easat-5823	164	1	the	the	DET
easat-5823	164	2	parameters	parameter	NOUN
easat-5823	164	3	used	use	VERB
easat-5823	164	4	for	for	ADP
easat-5823	164	5	the	the	DET
easat-5823	164	6	mlp	mlp	NOUN
easat-5823	164	7	feature	feature	NOUN
easat-5823	164	8	extractor	extractor	NOUN
easat-5823	164	9	were	be	AUX
easat-5823	164	10	obtained	obtain	VERB
easat-5823	164	11	through	through	ADP
easat-5823	164	12	exhaustive	exhaustive	ADJ
easat-5823	164	13	search	search	NOUN
easat-5823	164	14	starting	start	VERB
easat-5823	164	15	from	from	ADP
easat-5823	164	16	small	small	ADJ
easat-5823	164	17	number	number	NOUN
easat-5823	164	18	of	of	ADP
easat-5823	164	19	neurons	neuron	NOUN
easat-5823	164	20	to	to	ADP
easat-5823	164	21	higher	high	ADJ
easat-5823	164	22	numbers	number	NOUN
easat-5823	164	23	.	.	PUNCT
easat-5823	165	1	at	at	ADP
easat-5823	165	2	the	the	DET
easat-5823	165	3	end	end	NOUN
easat-5823	165	4	,	,	PUNCT
easat-5823	165	5	the	the	DET
easat-5823	165	6	parameters	parameter	NOUN
easat-5823	165	7	that	that	PRON
easat-5823	165	8	produced	produce	VERB
easat-5823	165	9	the	the	DET
easat-5823	165	10	best	good	ADJ
easat-5823	165	11	result	result	NOUN
easat-5823	165	12	were	be	AUX
easat-5823	165	13	1	1	NUM
easat-5823	165	14	hidden	hidden	ADJ
easat-5823	165	15	layer	layer	NOUN
easat-5823	165	16	with	with	ADP
easat-5823	165	17	256	256	NUM
easat-5823	165	18	neurons	neuron	NOUN
easat-5823	165	19	,	,	PUNCT
easat-5823	165	20	activation	activation	NOUN
easat-5823	165	21	function	function	NOUN
easat-5823	165	22	of	of	ADP
easat-5823	165	23	tanh	tanh	PROPN
easat-5823	165	24	and	and	CCONJ
easat-5823	165	25	adam	adam	PROPN
easat-5823	165	26	optimizer	optimizer	NOUN
easat-5823	165	27	.	.	PUNCT
easat-5823	166	1	random	random	ADJ
easat-5823	166	2	state	state	NOUN
easat-5823	166	3	of	of	ADP
easat-5823	166	4	42	42	NUM
easat-5823	166	5	was	be	AUX
easat-5823	166	6	also	also	ADV
easat-5823	166	7	used	use	VERB
easat-5823	166	8	to	to	PART
easat-5823	166	9	ensure	ensure	VERB
easat-5823	166	10	consistency	consistency	NOUN
easat-5823	166	11	in	in	ADP
easat-5823	166	12	training	train	VERB
easat-5823	166	13	the	the	DET
easat-5823	166	14	model	model	NOUN
easat-5823	166	15	.	.	PUNCT
easat-5823	167	1	after	after	ADP
easat-5823	167	2	training	train	VERB
easat-5823	167	3	the	the	DET
easat-5823	167	4	mlp	mlp	NOUN
easat-5823	167	5	feature	feature	NOUN
easat-5823	167	6	extractor	extractor	NOUN
easat-5823	167	7	,	,	PUNCT
easat-5823	167	8	the	the	DET
easat-5823	167	9	extracted	extract	VERB
easat-5823	167	10	features	feature	NOUN
easat-5823	167	11	were	be	AUX
easat-5823	167	12	then	then	ADV
easat-5823	167	13	obtained	obtain	VERB
easat-5823	167	14	and	and	CCONJ
easat-5823	167	15	used	use	VERB
easat-5823	167	16	to	to	PART
easat-5823	167	17	train	train	VERB
easat-5823	167	18	the	the	DET
easat-5823	167	19	random	random	ADJ
easat-5823	167	20	forest	forest	NOUN
easat-5823	167	21	.	.	PUNCT
easat-5823	168	1	the	the	DET
easat-5823	168	2	parameters	parameter	NOUN
easat-5823	168	3	that	that	PRON
easat-5823	168	4	were	be	AUX
easat-5823	168	5	used	use	VERB
easat-5823	168	6	to	to	PART
easat-5823	168	7	train	train	VERB
easat-5823	168	8	the	the	DET
easat-5823	168	9	random	random	ADJ
easat-5823	168	10	forest	forest	NOUN
easat-5823	168	11	were	be	AUX
easat-5823	168	12	obtained	obtain	VERB
easat-5823	168	13	through	through	ADP
easat-5823	168	14	grid	grid	NOUN
easat-5823	168	15	search	search	NOUN
easat-5823	168	16	with	with	ADP
easat-5823	168	17	3	3	NUM
easat-5823	168	18	cross	cross	NOUN
easat-5823	168	19	validation	validation	NOUN
easat-5823	168	20	over	over	ADP
easat-5823	168	21	a	a	DET
easat-5823	168	22	range	range	NOUN
easat-5823	168	23	of	of	ADP
easat-5823	168	24	hyperparameter	hyperparameter	NOUN
easat-5823	168	25	combinations	combination	NOUN
easat-5823	168	26	using	use	VERB
easat-5823	168	27	the	the	DET
easat-5823	168	28	following	follow	VERB
easat-5823	168	29	parameters	parameter	NOUN
easat-5823	168	30	based	base	VERB
easat-5823	168	31	on	on	ADP
easat-5823	168	32	f1	f1	NOUN
easat-5823	168	33	-	-	PUNCT
easat-5823	168	34	score	score	NOUN
easat-5823	168	35	.	.	PUNCT
easat-5823	169	1	the	the	DET
easat-5823	169	2	number	number	NOUN
easat-5823	169	3	of	of	ADP
easat-5823	169	4	estimators	estimator	NOUN
easat-5823	169	5	/	/	SYM
easat-5823	169	6	trees	tree	NOUN
easat-5823	169	7	in	in	ADP
easat-5823	169	8	the	the	DET
easat-5823	169	9	forest	forest	NOUN
easat-5823	169	10	were	be	AUX
easat-5823	169	11	evaluated	evaluate	VERB
easat-5823	169	12	using	use	VERB
easat-5823	169	13	values	value	NOUN
easat-5823	169	14	of	of	ADP
easat-5823	169	15	100	100	NUM
easat-5823	169	16	,	,	PUNCT
easat-5823	169	17	200	200	NUM
easat-5823	169	18	,	,	PUNCT
easat-5823	169	19	and	and	CCONJ
easat-5823	169	20	300	300	NUM
easat-5823	169	21	.	.	PUNCT
easat-5823	170	1	the	the	DET
easat-5823	170	2	tree	tree	NOUN
easat-5823	170	3	’s	’s	PART
easat-5823	170	4	maximum	maximum	ADJ
easat-5823	170	5	depth	depth	NOUN
easat-5823	170	6	was	be	AUX
easat-5823	170	7	tested	test	VERB
easat-5823	170	8	at	at	ADP
easat-5823	170	9	10	10	NUM
easat-5823	170	10	,	,	PUNCT
easat-5823	170	11	20	20	NUM
easat-5823	170	12	,	,	PUNCT
easat-5823	170	13	and	and	CCONJ
easat-5823	170	14	30	30	NUM
easat-5823	170	15	.	.	PUNCT
easat-5823	171	1	for	for	ADP
easat-5823	171	2	the	the	DET
easat-5823	171	3	minimum	minimum	ADJ
easat-5823	171	4	samples	sample	NOUN
easat-5823	171	5	required	require	VERB
easat-5823	171	6	to	to	PART
easat-5823	171	7	split	split	VERB
easat-5823	171	8	a	a	DET
easat-5823	171	9	node	node	NOUN
easat-5823	171	10	,	,	PUNCT
easat-5823	171	11	values	value	NOUN
easat-5823	171	12	of	of	ADP
easat-5823	171	13	2	2	NUM
easat-5823	171	14	,	,	PUNCT
easat-5823	171	15	5	5	NUM
easat-5823	171	16	,	,	PUNCT
easat-5823	171	17	and	and	CCONJ
easat-5823	171	18	10	10	NUM
easat-5823	171	19	were	be	AUX
easat-5823	171	20	considered	consider	VERB
easat-5823	171	21	,	,	PUNCT
easat-5823	171	22	while	while	SCONJ
easat-5823	171	23	the	the	DET
easat-5823	171	24	minimum	minimum	NOUN
easat-5823	171	25	samples	sample	NOUN
easat-5823	171	26	required	require	VERB
easat-5823	171	27	per	per	ADP
easat-5823	171	28	leaf	leaf	NOUN
easat-5823	171	29	node	node	NOUN
easat-5823	171	30	were	be	AUX
easat-5823	171	31	tested	test	VERB
easat-5823	171	32	with	with	ADP
easat-5823	171	33	values	value	NOUN
easat-5823	171	34	of	of	ADP
easat-5823	171	35	1	1	NUM
easat-5823	171	36	,	,	PUNCT
easat-5823	171	37	2	2	NUM
easat-5823	171	38	,	,	PUNCT
easat-5823	171	39	and	and	CCONJ
easat-5823	171	40	4	4	X
easat-5823	171	41	.	.	PUNCT
easat-5823	172	1	lastly	lastly	ADV
easat-5823	172	2	,	,	PUNCT
easat-5823	172	3	there	there	PRON
easat-5823	172	4	are	be	VERB
easat-5823	172	5	two	two	NUM
easat-5823	172	6	options	option	NOUN
easat-5823	172	7	tested	test	VERB
easat-5823	172	8	for	for	ADP
easat-5823	172	9	the	the	DET
easat-5823	172	10	maximum	maximum	ADJ
easat-5823	172	11	number	number	NOUN
easat-5823	172	12	of	of	ADP
easat-5823	172	13	features	feature	NOUN
easat-5823	172	14	considered	consider	VERB
easat-5823	172	15	for	for	ADP
easat-5823	172	16	a	a	DET
easat-5823	172	17	split	split	NOUN
easat-5823	172	18	which	which	PRON
easat-5823	172	19	are	be	AUX
easat-5823	172	20	sqrt	sqrt	NOUN
easat-5823	172	21	and	and	CCONJ
easat-5823	172	22	log2	log2	PROPN
easat-5823	172	23	.	.	PUNCT
easat-5823	173	1	the	the	DET
easat-5823	173	2	combination	combination	NOUN
easat-5823	173	3	of	of	ADP
easat-5823	173	4	parameters	parameter	NOUN
easat-5823	173	5	that	that	PRON
easat-5823	173	6	produce	produce	VERB
easat-5823	173	7	the	the	DET
easat-5823	173	8	best	good	ADJ
easat-5823	173	9	result	result	NOUN
easat-5823	173	10	for	for	ADP
easat-5823	173	11	random	random	ADJ
easat-5823	173	12	forest	forest	NOUN
easat-5823	173	13	model	model	NOUN
easat-5823	173	14	were	be	AUX
easat-5823	173	15	100	100	NUM
easat-5823	173	16	estimators	estimator	NOUN
easat-5823	173	17	,	,	PUNCT
easat-5823	173	18	maximum	maximum	ADJ
easat-5823	173	19	depth	depth	NOUN
easat-5823	173	20	of	of	ADP
easat-5823	173	21	10	10	NUM
easat-5823	173	22	,	,	PUNCT
easat-5823	173	23	minimum	minimum	NOUN
easat-5823	173	24	samples	sample	NOUN
easat-5823	173	25	to	to	PART
easat-5823	173	26	split	split	VERB
easat-5823	173	27	of	of	ADP
easat-5823	173	28	2	2	NUM
easat-5823	173	29	,	,	PUNCT
easat-5823	173	30	4	4	NUM
easat-5823	173	31	minimum	minimum	NOUN
easat-5823	173	32	samples	sample	NOUN
easat-5823	173	33	required	require	VERB
easat-5823	173	34	in	in	ADP
easat-5823	173	35	a	a	DET
easat-5823	173	36	leaf	leaf	NOUN
easat-5823	173	37	and	and	CCONJ
easat-5823	173	38	maximum	maximum	ADJ
easat-5823	173	39	features	feature	NOUN
easat-5823	173	40	using	use	VERB
easat-5823	173	41	sqrt	sqrt	NOUN
easat-5823	173	42	.	.	PUNCT
easat-5823	174	1	additionally	additionally	ADV
easat-5823	174	2	,	,	PUNCT
easat-5823	174	3	a	a	DET
easat-5823	174	4	random	random	ADJ
easat-5823	174	5	state	state	NOUN
easat-5823	174	6	of	of	ADP
easat-5823	174	7	42	42	NUM
easat-5823	174	8	is	be	AUX
easat-5823	174	9	also	also	ADV
easat-5823	174	10	used	use	VERB
easat-5823	174	11	to	to	PART
easat-5823	174	12	ensure	ensure	VERB
easat-5823	174	13	consistency	consistency	NOUN
easat-5823	174	14	during	during	ADP
easat-5823	174	15	training	training	NOUN
easat-5823	174	16	.	.	PUNCT
easat-5823	175	1	2488	2488	NUM
easat-5823	175	2	edelweiss	edelweiss	PROPN
easat-5823	175	3	applied	apply	VERB
easat-5823	175	4	science	science	NOUN
easat-5823	175	5	and	and	CCONJ
easat-5823	175	6	technology	technology	NOUN
easat-5823	175	7	issn	issn	PROPN
easat-5823	175	8	:	:	PUNCT
easat-5823	175	9	2576	2576	NUM
easat-5823	175	10	-	-	SYM
easat-5823	175	11	8484	8484	NUM
easat-5823	175	12	vol	vol	NOUN
easat-5823	175	13	.	.	PROPN
easat-5823	176	1	9	9	NUM
easat-5823	176	2	,	,	PUNCT
easat-5823	176	3	no	no	INTJ
easat-5823	176	4	.	.	NOUN
easat-5823	176	5	3	3	NUM
easat-5823	176	6	:	:	PUNCT
easat-5823	176	7	2482	2482	NUM
easat-5823	176	8	-	-	SYM
easat-5823	176	9	2494	2494	NUM
easat-5823	176	10	,	,	PUNCT
easat-5823	176	11	2025	2025	NUM
easat-5823	176	12	doi	doi	NOUN
easat-5823	176	13	:	:	PUNCT
easat-5823	176	14	10.55214/25768484.v9i3.5823	10.55214/25768484.v9i3.5823	NUM
easat-5823	176	15	©	©	PROPN
easat-5823	176	16	2025	2025	NUM
easat-5823	176	17	by	by	ADP
easat-5823	176	18	the	the	DET
easat-5823	176	19	authors	author	NOUN
easat-5823	176	20	;	;	PUNCT
easat-5823	176	21	licensee	licensee	PROPN
easat-5823	176	22	learning	learning	NOUN
easat-5823	176	23	gate	gate	VERB
easat-5823	176	24	3.3	3.3	NUM
easat-5823	176	25	.	.	PUNCT
easat-5823	177	1	metric	metric	ADJ
easat-5823	177	2	of	of	ADP
easat-5823	177	3	evaluation	evaluation	NOUN
easat-5823	177	4	to	to	PART
easat-5823	177	5	evaluate	evaluate	VERB
easat-5823	177	6	the	the	DET
easat-5823	177	7	performance	performance	NOUN
easat-5823	177	8	of	of	ADP
easat-5823	177	9	each	each	DET
easat-5823	177	10	model	model	NOUN
easat-5823	177	11	,	,	PUNCT
easat-5823	177	12	there	there	PRON
easat-5823	177	13	are	be	VERB
easat-5823	177	14	several	several	ADJ
easat-5823	177	15	metrics	metric	NOUN
easat-5823	177	16	that	that	PRON
easat-5823	177	17	were	be	AUX
easat-5823	177	18	used	use	VERB
easat-5823	177	19	in	in	ADP
easat-5823	177	20	this	this	DET
easat-5823	177	21	research	research	NOUN
easat-5823	177	22	,	,	PUNCT
easat-5823	177	23	including	include	VERB
easat-5823	177	24	accuracy	accuracy	NOUN
easat-5823	177	25	,	,	PUNCT
easat-5823	177	26	precision	precision	NOUN
easat-5823	177	27	,	,	PUNCT
easat-5823	177	28	recall	recall	NOUN
easat-5823	177	29	and	and	CCONJ
easat-5823	177	30	f1	f1	NOUN
easat-5823	177	31	-	-	PUNCT
easat-5823	177	32	score	score	NOUN
easat-5823	177	33	.	.	PUNCT
easat-5823	178	1	these	these	DET
easat-5823	178	2	evaluation	evaluation	NOUN
easat-5823	178	3	metrics	metric	NOUN
easat-5823	178	4	are	be	AUX
easat-5823	178	5	obtained	obtain	VERB
easat-5823	178	6	from	from	ADP
easat-5823	178	7	the	the	DET
easat-5823	178	8	confusion	confusion	NOUN
easat-5823	178	9	matrix	matrix	NOUN
easat-5823	178	10	.	.	PUNCT
easat-5823	179	1	confusion	confusion	NOUN
easat-5823	179	2	matrix	matrix	NOUN
easat-5823	179	3	is	be	AUX
easat-5823	179	4	method	method	NOUN
easat-5823	179	5	that	that	PRON
easat-5823	179	6	is	be	AUX
easat-5823	179	7	commonly	commonly	ADV
easat-5823	179	8	used	use	VERB
easat-5823	179	9	to	to	PART
easat-5823	179	10	evaluate	evaluate	VERB
easat-5823	179	11	the	the	DET
easat-5823	179	12	performance	performance	NOUN
easat-5823	179	13	of	of	ADP
easat-5823	179	14	machine	machine	NOUN
easat-5823	179	15	learning	learn	VERB
easat-5823	179	16	classification	classification	NOUN
easat-5823	179	17	[	[	X
easat-5823	179	18	21	21	NUM
easat-5823	179	19	]	]	PUNCT
easat-5823	179	20	.	.	PUNCT
easat-5823	180	1	confusion	confusion	NOUN
easat-5823	180	2	matrix	matrix	NOUN
easat-5823	180	3	consists	consist	VERB
easat-5823	180	4	of	of	ADP
easat-5823	180	5	four	four	NUM
easat-5823	180	6	values	value	NOUN
easat-5823	180	7	which	which	PRON
easat-5823	180	8	are	be	AUX
easat-5823	180	9	true	true	ADJ
easat-5823	180	10	positives	positive	NOUN
easat-5823	180	11	,	,	PUNCT
easat-5823	180	12	true	true	ADJ
easat-5823	180	13	negatives	negative	NOUN
easat-5823	180	14	,	,	PUNCT
easat-5823	180	15	false	false	ADJ
easat-5823	180	16	positives	positive	NOUN
easat-5823	180	17	,	,	PUNCT
easat-5823	180	18	and	and	CCONJ
easat-5823	180	19	false	false	ADJ
easat-5823	180	20	negatives	negative	NOUN
easat-5823	180	21	.	.	PUNCT
easat-5823	181	1	the	the	DET
easat-5823	181	2	table	table	NOUN
easat-5823	181	3	of	of	ADP
easat-5823	181	4	confusion	confusion	NOUN
easat-5823	181	5	matrix	matrix	NOUN
easat-5823	181	6	can	can	AUX
easat-5823	181	7	be	be	AUX
easat-5823	181	8	seen	see	VERB
easat-5823	181	9	in	in	ADP
easat-5823	181	10	table	table	NOUN
easat-5823	181	11	1	1	NUM
easat-5823	181	12	.	.	PUNCT
easat-5823	181	13	table	table	NOUN
easat-5823	181	14	1	1	NUM
easat-5823	181	15	.	.	PUNCT
easat-5823	181	16	confusion	confusion	NOUN
easat-5823	181	17	matrix	matrix	NOUN
easat-5823	181	18	table	table	NOUN
easat-5823	181	19	.	.	PUNCT
easat-5823	182	1	class	class	NOUN
easat-5823	182	2	predicted	predict	VERB
easat-5823	182	3	negatives	negative	NOUN
easat-5823	182	4	predicted	predict	VERB
easat-5823	182	5	positives	positive	NOUN
easat-5823	182	6	actual	actual	ADJ
easat-5823	182	7	negatives	negative	NOUN
easat-5823	182	8	true	true	ADJ
easat-5823	182	9	negatives	negative	NOUN
easat-5823	182	10	false	false	ADJ
easat-5823	182	11	positives	positive	NOUN
easat-5823	182	12	actual	actual	ADJ
easat-5823	182	13	positives	positive	NOUN
easat-5823	182	14	false	false	ADJ
easat-5823	182	15	negatives	negative	NOUN
easat-5823	182	16	true	true	ADJ
easat-5823	182	17	positives	positive	NOUN
easat-5823	182	18	using	use	VERB
easat-5823	182	19	the	the	DET
easat-5823	182	20	confusion	confusion	NOUN
easat-5823	182	21	matrix	matrix	NOUN
easat-5823	182	22	,	,	PUNCT
easat-5823	182	23	the	the	DET
easat-5823	182	24	evaluation	evaluation	NOUN
easat-5823	182	25	metrics	metric	NOUN
easat-5823	182	26	then	then	ADV
easat-5823	182	27	can	can	AUX
easat-5823	182	28	be	be	AUX
easat-5823	182	29	obtained	obtain	VERB
easat-5823	182	30	.	.	PUNCT
easat-5823	183	1	accuracy	accuracy	NOUN
easat-5823	183	2	is	be	AUX
easat-5823	183	3	an	an	DET
easat-5823	183	4	evaluation	evaluation	NOUN
easat-5823	183	5	metric	metric	NOUN
easat-5823	183	6	that	that	PRON
easat-5823	183	7	calculates	calculate	VERB
easat-5823	183	8	the	the	DET
easat-5823	183	9	overall	overall	ADJ
easat-5823	183	10	accuracy	accuracy	NOUN
easat-5823	183	11	of	of	ADP
easat-5823	183	12	a	a	DET
easat-5823	183	13	model	model	NOUN
easat-5823	183	14	by	by	ADP
easat-5823	183	15	dividing	divide	VERB
easat-5823	183	16	the	the	DET
easat-5823	183	17	number	number	NOUN
easat-5823	183	18	of	of	ADP
easat-5823	183	19	correct	correct	ADJ
easat-5823	183	20	predictions	prediction	NOUN
easat-5823	183	21	by	by	ADP
easat-5823	183	22	the	the	DET
easat-5823	183	23	total	total	ADJ
easat-5823	183	24	number	number	NOUN
easat-5823	183	25	of	of	ADP
easat-5823	183	26	predictions	prediction	NOUN
easat-5823	183	27	.	.	PUNCT
easat-5823	184	1	after	after	ADP
easat-5823	184	2	the	the	DET
easat-5823	184	3	explanation	explanation	NOUN
easat-5823	184	4	,	,	PUNCT
easat-5823	184	5	the	the	DET
easat-5823	184	6	formula	formula	NOUN
easat-5823	184	7	can	can	AUX
easat-5823	184	8	be	be	AUX
easat-5823	184	9	written	write	VERB
easat-5823	184	10	as	as	ADP
easat-5823	184	11	equation	equation	NOUN
easat-5823	184	12	1	1	NUM
easat-5823	184	13	,	,	PUNCT
easat-5823	184	14	where	where	SCONJ
easat-5823	184	15	tp	tp	NOUN
easat-5823	184	16	is	be	AUX
easat-5823	184	17	true	true	ADJ
easat-5823	184	18	positives	positive	NOUN
easat-5823	184	19	,	,	PUNCT
easat-5823	184	20	tn	tn	PROPN
easat-5823	184	21	is	be	AUX
easat-5823	184	22	true	true	ADJ
easat-5823	184	23	negatives	negative	NOUN
easat-5823	184	24	,	,	PUNCT
easat-5823	184	25	fp	fp	X
easat-5823	184	26	is	be	AUX
easat-5823	184	27	false	false	ADJ
easat-5823	184	28	positives	positive	NOUN
easat-5823	184	29	,	,	PUNCT
easat-5823	184	30	and	and	CCONJ
easat-5823	184	31	fn	fn	NOUN
easat-5823	184	32	is	be	AUX
easat-5823	184	33	false	false	ADJ
easat-5823	184	34	negatives	negative	NOUN
easat-5823	184	35	.	.	PUNCT
easat-5823	185	1	the	the	DET
easat-5823	185	2	second	second	ADJ
easat-5823	185	3	metric	metric	NOUN
easat-5823	185	4	is	be	AUX
easat-5823	185	5	precision	precision	NOUN
easat-5823	185	6	which	which	PRON
easat-5823	185	7	is	be	AUX
easat-5823	185	8	an	an	DET
easat-5823	185	9	evaluation	evaluation	NOUN
easat-5823	185	10	metric	metric	NOUN
easat-5823	185	11	that	that	PRON
easat-5823	185	12	measures	measure	VERB
easat-5823	185	13	the	the	DET
easat-5823	185	14	proportion	proportion	NOUN
easat-5823	185	15	of	of	ADP
easat-5823	185	16	positives	positive	NOUN
easat-5823	185	17	predictions	prediction	NOUN
easat-5823	185	18	that	that	PRON
easat-5823	185	19	were	be	AUX
easat-5823	185	20	correct	correct	ADJ
easat-5823	185	21	by	by	ADP
easat-5823	185	22	dividing	divide	VERB
easat-5823	185	23	the	the	DET
easat-5823	185	24	number	number	NOUN
easat-5823	185	25	of	of	ADP
easat-5823	185	26	correctly	correctly	ADV
easat-5823	185	27	identified	identify	VERB
easat-5823	185	28	positive	positive	ADJ
easat-5823	185	29	predictions	prediction	NOUN
easat-5823	185	30	to	to	ADP
easat-5823	185	31	the	the	DET
easat-5823	185	32	sum	sum	NOUN
easat-5823	185	33	of	of	ADP
easat-5823	185	34	all	all	DET
easat-5823	185	35	predicted	predict	VERB
easat-5823	185	36	positives	positive	NOUN
easat-5823	185	37	.	.	PUNCT
easat-5823	186	1	the	the	DET
easat-5823	186	2	equation	equation	NOUN
easat-5823	186	3	for	for	ADP
easat-5823	186	4	the	the	DET
easat-5823	186	5	precision	precision	NOUN
easat-5823	186	6	metric	metric	NOUN
easat-5823	186	7	can	can	AUX
easat-5823	186	8	be	be	AUX
easat-5823	186	9	seen	see	VERB
easat-5823	186	10	in	in	ADP
easat-5823	186	11	equation	equation	NOUN
easat-5823	186	12	2	2	NUM
easat-5823	186	13	.	.	PUNCT
easat-5823	187	1	the	the	DET
easat-5823	187	2	next	next	ADJ
easat-5823	187	3	metric	metric	NOUN
easat-5823	187	4	used	use	VERB
easat-5823	187	5	in	in	ADP
easat-5823	187	6	the	the	DET
easat-5823	187	7	research	research	NOUN
easat-5823	187	8	was	be	AUX
easat-5823	187	9	recall	recall	ADJ
easat-5823	187	10	which	which	PRON
easat-5823	187	11	is	be	AUX
easat-5823	187	12	an	an	DET
easat-5823	187	13	evaluation	evaluation	NOUN
easat-5823	187	14	metric	metric	NOUN
easat-5823	187	15	that	that	PRON
easat-5823	187	16	measures	measure	VERB
easat-5823	187	17	the	the	DET
easat-5823	187	18	proportion	proportion	NOUN
easat-5823	187	19	of	of	ADP
easat-5823	187	20	actual	actual	ADJ
easat-5823	187	21	positives	positive	NOUN
easat-5823	187	22	that	that	PRON
easat-5823	187	23	were	be	AUX
easat-5823	187	24	correctly	correctly	ADV
easat-5823	187	25	predicted	predict	VERB
easat-5823	187	26	by	by	ADP
easat-5823	187	27	dividing	divide	VERB
easat-5823	187	28	the	the	DET
easat-5823	187	29	correctly	correctly	ADV
easat-5823	187	30	identified	identify	VERB
easat-5823	187	31	positive	positive	ADJ
easat-5823	187	32	predictions	prediction	NOUN
easat-5823	187	33	to	to	ADP
easat-5823	187	34	the	the	DET
easat-5823	187	35	sum	sum	NOUN
easat-5823	187	36	of	of	ADP
easat-5823	187	37	the	the	DET
easat-5823	187	38	actual	actual	ADJ
easat-5823	187	39	positives	positive	NOUN
easat-5823	187	40	.	.	PUNCT
easat-5823	188	1	the	the	DET
easat-5823	188	2	equation	equation	NOUN
easat-5823	188	3	for	for	ADP
easat-5823	188	4	recall	recall	NOUN
easat-5823	188	5	can	can	AUX
easat-5823	188	6	be	be	AUX
easat-5823	188	7	written	write	VERB
easat-5823	188	8	as	as	ADP
easat-5823	188	9	in	in	ADP
easat-5823	188	10	equation	equation	NOUN
easat-5823	188	11	3	3	NUM
easat-5823	188	12	.	.	PUNCT
easat-5823	189	1	the	the	DET
easat-5823	189	2	last	last	ADJ
easat-5823	189	3	metric	metric	NOUN
easat-5823	189	4	is	be	AUX
easat-5823	189	5	f1	f1	NOUN
easat-5823	189	6	-	-	PUNCT
easat-5823	189	7	score	score	NOUN
easat-5823	189	8	which	which	PRON
easat-5823	189	9	is	be	AUX
easat-5823	189	10	the	the	DET
easat-5823	189	11	harmonic	harmonic	ADJ
easat-5823	189	12	mean	mean	NOUN
easat-5823	189	13	of	of	ADP
easat-5823	189	14	precision	precision	NOUN
easat-5823	189	15	and	and	CCONJ
easat-5823	189	16	recall	recall	NOUN
easat-5823	189	17	and	and	CCONJ
easat-5823	189	18	is	be	AUX
easat-5823	189	19	used	use	VERB
easat-5823	189	20	especially	especially	ADV
easat-5823	189	21	in	in	ADP
easat-5823	189	22	the	the	DET
easat-5823	189	23	case	case	NOUN
easat-5823	189	24	of	of	ADP
easat-5823	189	25	imbalanced	imbalanced	ADJ
easat-5823	189	26	class	class	NOUN
easat-5823	189	27	distribution	distribution	NOUN
easat-5823	189	28	.	.	PUNCT
easat-5823	190	1	in	in	ADP
easat-5823	190	2	an	an	DET
easat-5823	190	3	imbalanced	imbalanced	ADJ
easat-5823	190	4	dataset	dataset	NOUN
easat-5823	190	5	,	,	PUNCT
easat-5823	190	6	the	the	DET
easat-5823	190	7	balance	balance	NOUN
easat-5823	190	8	of	of	ADP
easat-5823	190	9	precision	precision	NOUN
easat-5823	190	10	and	and	CCONJ
easat-5823	190	11	recall	recall	NOUN
easat-5823	190	12	is	be	AUX
easat-5823	190	13	necessary	necessary	ADJ
easat-5823	190	14	thus	thus	ADV
easat-5823	190	15	making	make	VERB
easat-5823	190	16	this	this	DET
easat-5823	190	17	metric	metric	ADJ
easat-5823	190	18	useful	useful	ADJ
easat-5823	190	19	to	to	PART
easat-5823	190	20	determine	determine	VERB
easat-5823	190	21	the	the	DET
easat-5823	190	22	performance	performance	NOUN
easat-5823	190	23	of	of	ADP
easat-5823	190	24	the	the	DET
easat-5823	190	25	prediction	prediction	NOUN
easat-5823	190	26	models	model	NOUN
easat-5823	190	27	.	.	PUNCT
easat-5823	191	1	the	the	DET
easat-5823	191	2	equation	equation	NOUN
easat-5823	191	3	for	for	ADP
easat-5823	191	4	f1	f1	NOUN
easat-5823	191	5	-	-	PUNCT
easat-5823	191	6	score	score	NOUN
easat-5823	191	7	can	can	AUX
easat-5823	191	8	be	be	AUX
easat-5823	191	9	written	write	VERB
easat-5823	191	10	as	as	ADP
easat-5823	191	11	in	in	ADP
easat-5823	191	12	equation	equation	NOUN
easat-5823	191	13	4	4	NUM
easat-5823	191	14	.	.	PUNCT
easat-5823	192	1	𝐴𝑐𝑐𝑢𝑟𝑎𝑐𝑦	𝐴𝑐𝑐𝑢𝑟𝑎𝑐𝑦	PROPN
easat-5823	192	2	=	=	X
easat-5823	192	3	𝑇𝑃+𝑇𝑁	𝑇𝑃+𝑇𝑁	ADJ
easat-5823	192	4	𝑇𝑃+𝑇𝑁+𝐹𝑃+𝐹𝑁	𝑇𝑃+𝑇𝑁+𝐹𝑃+𝐹𝑁	PUNCT
easat-5823	192	5	(	(	PUNCT
easat-5823	192	6	1	1	X
easat-5823	192	7	)	)	PUNCT
easat-5823	192	8	𝑃𝑟𝑒𝑐𝑖𝑠𝑖𝑜𝑛	𝑃𝑟𝑒𝑐𝑖𝑠𝑖𝑜𝑛	PROPN
easat-5823	192	9	=	=	SYM
easat-5823	192	10	𝑇𝑃	𝑇𝑃	PROPN
easat-5823	192	11	𝑇𝑃+𝐹𝑃	𝑇𝑃+𝐹𝑃	NUM
easat-5823	192	12	(	(	PUNCT
easat-5823	192	13	2	2	NUM
easat-5823	192	14	)	)	PUNCT
easat-5823	192	15	𝑅𝑒𝑐𝑎𝑙𝑙	𝑅𝑒𝑐𝑎𝑙𝑙	PROPN
easat-5823	192	16	=	=	SYM
easat-5823	192	17	𝑇𝑃	𝑇𝑃	NOUN
easat-5823	192	18	𝑇𝑃+𝐹𝑁	𝑇𝑃+𝐹𝑁	NOUN
easat-5823	192	19	(	(	PUNCT
easat-5823	192	20	3	3	NUM
easat-5823	192	21	)	)	PUNCT
easat-5823	192	22	𝐹1	𝐹1	PROPN
easat-5823	193	1	𝑆𝑐𝑜𝑟𝑒	𝑆𝑐𝑜𝑟𝑒	PROPN
easat-5823	193	2	=	=	SYM
easat-5823	193	3	2	2	NUM
easat-5823	193	4	×	×	NOUN
easat-5823	193	5	𝑃𝑟𝑒𝑐𝑖𝑠𝑖𝑜𝑛	𝑃𝑟𝑒𝑐𝑖𝑠𝑖𝑜𝑛	PROPN
easat-5823	193	6	×𝑅𝑒𝑐𝑎𝑙𝑙	×𝑅𝑒𝑐𝑎𝑙𝑙	NOUN
easat-5823	193	7	𝑃𝑟𝑒𝑐𝑖𝑠𝑖𝑜𝑛+𝑅𝑒𝑐𝑎𝑙𝑙	𝑃𝑟𝑒𝑐𝑖𝑠𝑖𝑜𝑛+𝑅𝑒𝑐𝑎𝑙𝑙	X
easat-5823	193	8	(	(	PUNCT
easat-5823	193	9	4	4	NUM
easat-5823	193	10	)	)	SYM
easat-5823	193	11	4	4	NUM
easat-5823	193	12	.	.	NOUN
easat-5823	193	13	results	result	NOUN
easat-5823	193	14	to	to	PART
easat-5823	193	15	evaluate	evaluate	VERB
easat-5823	193	16	the	the	DET
easat-5823	193	17	performance	performance	NOUN
easat-5823	193	18	of	of	ADP
easat-5823	193	19	the	the	DET
easat-5823	193	20	proposed	propose	VERB
easat-5823	193	21	mlp	mlp	NOUN
easat-5823	193	22	-	-	PUNCT
easat-5823	193	23	random	random	ADJ
easat-5823	193	24	forest	forest	NOUN
easat-5823	193	25	model	model	NOUN
easat-5823	193	26	,	,	PUNCT
easat-5823	193	27	a	a	DET
easat-5823	193	28	comparison	comparison	NOUN
easat-5823	193	29	based	base	VERB
easat-5823	193	30	on	on	ADP
easat-5823	193	31	evaluation	evaluation	NOUN
easat-5823	193	32	metrics	metric	NOUN
easat-5823	193	33	is	be	AUX
easat-5823	193	34	needed	need	VERB
easat-5823	193	35	.	.	PUNCT
easat-5823	194	1	using	use	VERB
easat-5823	194	2	the	the	DET
easat-5823	194	3	confusion	confusion	NOUN
easat-5823	194	4	matrix	matrix	NOUN
easat-5823	194	5	,	,	PUNCT
easat-5823	194	6	the	the	DET
easat-5823	194	7	evaluation	evaluation	NOUN
easat-5823	194	8	metrics	metric	NOUN
easat-5823	194	9	can	can	AUX
easat-5823	194	10	be	be	AUX
easat-5823	194	11	calculated	calculate	VERB
easat-5823	194	12	.	.	PUNCT
easat-5823	195	1	all	all	DET
easat-5823	195	2	the	the	DET
easat-5823	195	3	models	model	NOUN
easat-5823	195	4	were	be	AUX
easat-5823	195	5	tested	test	VERB
easat-5823	195	6	on	on	ADP
easat-5823	195	7	20	20	NUM
easat-5823	195	8	%	%	NOUN
easat-5823	195	9	of	of	ADP
easat-5823	195	10	the	the	DET
easat-5823	195	11	dataset	dataset	NOUN
easat-5823	195	12	which	which	PRON
easat-5823	195	13	consists	consist	VERB
easat-5823	195	14	of	of	ADP
easat-5823	195	15	56962	56962	NUM
easat-5823	195	16	instances	instance	NOUN
easat-5823	195	17	.	.	PUNCT
easat-5823	196	1	the	the	DET
easat-5823	196	2	first	first	ADJ
easat-5823	196	3	test	test	NOUN
easat-5823	196	4	was	be	AUX
easat-5823	196	5	conducted	conduct	VERB
easat-5823	196	6	to	to	ADP
easat-5823	196	7	the	the	DET
easat-5823	196	8	standalone	standalone	ADJ
easat-5823	196	9	mlp	mlp	NOUN
easat-5823	196	10	model	model	NOUN
easat-5823	196	11	.	.	PUNCT
easat-5823	197	1	the	the	DET
easat-5823	197	2	mlp	mlp	PROPN
easat-5823	197	3	model	model	NOUN
easat-5823	197	4	achieved	achieve	VERB
easat-5823	197	5	an	an	DET
easat-5823	197	6	evaluation	evaluation	NOUN
easat-5823	197	7	metric	metric	ADJ
easat-5823	197	8	result	result	NOUN
easat-5823	197	9	of	of	ADP
easat-5823	197	10	99.993	99.993	NUM
easat-5823	197	11	%	%	NOUN
easat-5823	197	12	accuracy	accuracy	NOUN
easat-5823	197	13	,	,	PUNCT
easat-5823	197	14	81.914	81.914	NUM
easat-5823	197	15	%	%	NOUN
easat-5823	197	16	precision	precision	NOUN
easat-5823	197	17	,	,	PUNCT
easat-5823	197	18	78.571	78.571	NUM
easat-5823	197	19	%	%	NOUN
easat-5823	197	20	recall	recall	NOUN
easat-5823	197	21	and	and	CCONJ
easat-5823	197	22	80.208	80.208	NUM
easat-5823	197	23	%	%	NOUN
easat-5823	197	24	f1	f1	NOUN
easat-5823	197	25	-	-	PUNCT
easat-5823	197	26	score	score	NOUN
easat-5823	197	27	.	.	PUNCT
easat-5823	198	1	the	the	DET
easat-5823	198	2	confusion	confusion	NOUN
easat-5823	198	3	matrix	matrix	NOUN
easat-5823	198	4	for	for	ADP
easat-5823	198	5	the	the	DET
easat-5823	198	6	mlp	mlp	NOUN
easat-5823	198	7	model	model	NOUN
easat-5823	198	8	can	can	AUX
easat-5823	198	9	be	be	AUX
easat-5823	198	10	seen	see	VERB
easat-5823	198	11	in	in	ADP
easat-5823	198	12	figure	figure	NOUN
easat-5823	198	13	5	5	NUM
easat-5823	198	14	which	which	PRON
easat-5823	198	15	had	have	VERB
easat-5823	198	16	56847	56847	NUM
easat-5823	198	17	transactions	transaction	NOUN
easat-5823	198	18	labelled	label	VERB
easat-5823	198	19	as	as	ADP
easat-5823	198	20	true	true	ADJ
easat-5823	198	21	negatives	negative	NOUN
easat-5823	198	22	,	,	PUNCT
easat-5823	198	23	21	21	NUM
easat-5823	198	24	transactions	transaction	NOUN
easat-5823	198	25	labelled	label	VERB
easat-5823	198	26	as	as	ADP
easat-5823	198	27	false	false	ADJ
easat-5823	198	28	negatives	negative	NOUN
easat-5823	198	29	,	,	PUNCT
easat-5823	198	30	17	17	NUM
easat-5823	198	31	transactions	transaction	NOUN
easat-5823	198	32	labelled	label	VERB
easat-5823	198	33	as	as	ADP
easat-5823	198	34	false	false	ADJ
easat-5823	198	35	positives	positive	NOUN
easat-5823	198	36	,	,	PUNCT
easat-5823	198	37	and	and	CCONJ
easat-5823	198	38	77	77	NUM
easat-5823	198	39	transactions	transaction	NOUN
easat-5823	198	40	labelled	label	VERB
easat-5823	198	41	as	as	ADP
easat-5823	198	42	true	true	ADJ
easat-5823	198	43	positives	positive	NOUN
easat-5823	198	44	.	.	PUNCT
easat-5823	199	1	2489	2489	NUM
easat-5823	199	2	edelweiss	edelweiss	PROPN
easat-5823	199	3	applied	apply	VERB
easat-5823	199	4	science	science	NOUN
easat-5823	199	5	and	and	CCONJ
easat-5823	199	6	technology	technology	NOUN
easat-5823	199	7	issn	issn	PROPN
easat-5823	199	8	:	:	PUNCT
easat-5823	199	9	2576	2576	NUM
easat-5823	199	10	-	-	SYM
easat-5823	199	11	8484	8484	NUM
easat-5823	199	12	vol	vol	NOUN
easat-5823	199	13	.	.	PROPN
easat-5823	200	1	9	9	NUM
easat-5823	200	2	,	,	PUNCT
easat-5823	200	3	no	no	INTJ
easat-5823	200	4	.	.	NOUN
easat-5823	200	5	3	3	NUM
easat-5823	200	6	:	:	PUNCT
easat-5823	200	7	2482	2482	NUM
easat-5823	200	8	-	-	SYM
easat-5823	200	9	2494	2494	NUM
easat-5823	200	10	,	,	PUNCT
easat-5823	200	11	2025	2025	NUM
easat-5823	200	12	doi	doi	NOUN
easat-5823	200	13	:	:	PUNCT
easat-5823	200	14	10.55214/25768484.v9i3.5823	10.55214/25768484.v9i3.5823	NUM
easat-5823	200	15	©	©	PROPN
easat-5823	200	16	2025	2025	NUM
easat-5823	200	17	by	by	ADP
easat-5823	200	18	the	the	DET
easat-5823	200	19	authors	author	NOUN
easat-5823	200	20	;	;	PUNCT
easat-5823	200	21	licensee	licensee	PROPN
easat-5823	200	22	learning	learn	VERB
easat-5823	200	23	gate	gate	PROPN
easat-5823	200	24	figure	figure	NOUN
easat-5823	200	25	5	5	NUM
easat-5823	200	26	.	.	PUNCT
easat-5823	200	27	confusion	confusion	NOUN
easat-5823	200	28	matrix	matrix	NOUN
easat-5823	200	29	for	for	ADP
easat-5823	200	30	standalone	standalone	ADJ
easat-5823	200	31	mlp	mlp	NOUN
easat-5823	200	32	model	model	NOUN
easat-5823	200	33	.	.	PUNCT
easat-5823	201	1	2490	2490	NUM
easat-5823	201	2	edelweiss	edelweiss	PROPN
easat-5823	201	3	applied	apply	VERB
easat-5823	201	4	science	science	NOUN
easat-5823	201	5	and	and	CCONJ
easat-5823	201	6	technology	technology	NOUN
easat-5823	201	7	issn	issn	PROPN
easat-5823	201	8	:	:	PUNCT
easat-5823	201	9	2576	2576	NUM
easat-5823	201	10	-	-	SYM
easat-5823	201	11	8484	8484	NUM
easat-5823	201	12	vol	vol	NOUN
easat-5823	201	13	.	.	PROPN
easat-5823	202	1	9	9	NUM
easat-5823	202	2	,	,	PUNCT
easat-5823	202	3	no	no	INTJ
easat-5823	202	4	.	.	NOUN
easat-5823	202	5	3	3	NUM
easat-5823	202	6	:	:	PUNCT
easat-5823	202	7	2482	2482	NUM
easat-5823	202	8	-	-	SYM
easat-5823	202	9	2494	2494	NUM
easat-5823	202	10	,	,	PUNCT
easat-5823	202	11	2025	2025	NUM
easat-5823	202	12	doi	doi	NOUN
easat-5823	202	13	:	:	PUNCT
easat-5823	202	14	10.55214/25768484.v9i3.5823	10.55214/25768484.v9i3.5823	NUM
easat-5823	202	15	©	©	PROPN
easat-5823	202	16	2025	2025	NUM
easat-5823	202	17	by	by	ADP
easat-5823	202	18	the	the	DET
easat-5823	202	19	authors	author	NOUN
easat-5823	202	20	;	;	PUNCT
easat-5823	202	21	licensee	licensee	PROPN
easat-5823	202	22	learning	learn	VERB
easat-5823	202	23	gate	gate	PROPN
easat-5823	202	24	figure	figure	NOUN
easat-5823	202	25	6	6	NUM
easat-5823	202	26	.	.	PUNCT
easat-5823	202	27	confusion	confusion	NOUN
easat-5823	202	28	matrix	matrix	NOUN
easat-5823	202	29	for	for	ADP
easat-5823	202	30	standalone	standalone	ADJ
easat-5823	202	31	rf	rf	NOUN
easat-5823	202	32	model	model	NOUN
easat-5823	202	33	.	.	PUNCT
easat-5823	203	1	for	for	ADP
easat-5823	203	2	the	the	DET
easat-5823	203	3	standalone	standalone	ADJ
easat-5823	203	4	random	random	ADJ
easat-5823	203	5	forest	forest	NOUN
easat-5823	203	6	model	model	NOUN
easat-5823	203	7	,	,	PUNCT
easat-5823	203	8	the	the	DET
easat-5823	203	9	model	model	NOUN
easat-5823	203	10	achieved	achieve	VERB
easat-5823	203	11	an	an	DET
easat-5823	203	12	evaluation	evaluation	NOUN
easat-5823	203	13	metric	metric	ADJ
easat-5823	203	14	score	score	NOUN
easat-5823	203	15	of	of	ADP
easat-5823	203	16	99.947	99.947	NUM
easat-5823	203	17	%	%	NOUN
easat-5823	203	18	accuracy	accuracy	NOUN
easat-5823	203	19	,	,	PUNCT
easat-5823	203	20	84.694	84.694	NUM
easat-5823	203	21	%	%	NOUN
easat-5823	203	22	precision	precision	NOUN
easat-5823	203	23	,	,	PUNCT
easat-5823	203	24	84.694	84.694	NUM
easat-5823	203	25	%	%	NOUN
easat-5823	203	26	recall	recall	NOUN
easat-5823	203	27	and	and	CCONJ
easat-5823	203	28	84.694	84.694	NUM
easat-5823	203	29	%	%	NOUN
easat-5823	203	30	f1	f1	NOUN
easat-5823	203	31	-	-	PUNCT
easat-5823	203	32	score	score	NOUN
easat-5823	203	33	.	.	PUNCT
easat-5823	204	1	the	the	DET
easat-5823	204	2	confusion	confusion	NOUN
easat-5823	204	3	metric	metric	NOUN
easat-5823	204	4	of	of	ADP
easat-5823	204	5	the	the	DET
easat-5823	204	6	random	random	ADJ
easat-5823	204	7	forest	forest	NOUN
easat-5823	204	8	model	model	NOUN
easat-5823	204	9	can	can	AUX
easat-5823	204	10	be	be	AUX
easat-5823	204	11	seen	see	VERB
easat-5823	204	12	in	in	ADP
easat-5823	204	13	figure	figure	NOUN
easat-5823	204	14	6	6	NUM
easat-5823	204	15	where	where	SCONJ
easat-5823	204	16	there	there	PRON
easat-5823	204	17	were	be	VERB
easat-5823	204	18	56849	56849	NUM
easat-5823	204	19	transactions	transaction	NOUN
easat-5823	204	20	labelled	label	VERB
easat-5823	204	21	as	as	ADP
easat-5823	204	22	true	true	ADJ
easat-5823	204	23	negatives	negative	NOUN
easat-5823	204	24	,	,	PUNCT
easat-5823	204	25	15	15	NUM
easat-5823	204	26	transactions	transaction	NOUN
easat-5823	204	27	labelled	label	VERB
easat-5823	204	28	as	as	ADP
easat-5823	204	29	false	false	ADJ
easat-5823	204	30	negatives	negative	NOUN
easat-5823	204	31	,	,	PUNCT
easat-5823	204	32	15	15	NUM
easat-5823	204	33	transactions	transaction	NOUN
easat-5823	204	34	labelled	label	VERB
easat-5823	204	35	as	as	ADP
easat-5823	204	36	false	false	ADJ
easat-5823	204	37	positives	positive	NOUN
easat-5823	204	38	,	,	PUNCT
easat-5823	204	39	and	and	CCONJ
easat-5823	204	40	83	83	NUM
easat-5823	204	41	transactions	transaction	NOUN
easat-5823	204	42	labelled	label	VERB
easat-5823	204	43	as	as	ADP
easat-5823	204	44	true	true	ADJ
easat-5823	204	45	positives	positive	NOUN
easat-5823	204	46	.	.	PUNCT
easat-5823	205	1	2491	2491	NUM
easat-5823	205	2	edelweiss	edelweiss	PROPN
easat-5823	205	3	applied	apply	VERB
easat-5823	205	4	science	science	NOUN
easat-5823	205	5	and	and	CCONJ
easat-5823	205	6	technology	technology	NOUN
easat-5823	205	7	issn	issn	PROPN
easat-5823	205	8	:	:	PUNCT
easat-5823	205	9	2576	2576	NUM
easat-5823	205	10	-	-	SYM
easat-5823	205	11	8484	8484	NUM
easat-5823	205	12	vol	vol	NOUN
easat-5823	205	13	.	.	PROPN
easat-5823	206	1	9	9	NUM
easat-5823	206	2	,	,	PUNCT
easat-5823	206	3	no	no	INTJ
easat-5823	206	4	.	.	NOUN
easat-5823	206	5	3	3	NUM
easat-5823	206	6	:	:	PUNCT
easat-5823	206	7	2482	2482	NUM
easat-5823	206	8	-	-	SYM
easat-5823	206	9	2494	2494	NUM
easat-5823	206	10	,	,	PUNCT
easat-5823	206	11	2025	2025	NUM
easat-5823	206	12	doi	doi	NOUN
easat-5823	206	13	:	:	PUNCT
easat-5823	206	14	10.55214/25768484.v9i3.5823	10.55214/25768484.v9i3.5823	NUM
easat-5823	206	15	©	©	PROPN
easat-5823	206	16	2025	2025	NUM
easat-5823	206	17	by	by	ADP
easat-5823	206	18	the	the	DET
easat-5823	206	19	authors	author	NOUN
easat-5823	206	20	;	;	PUNCT
easat-5823	206	21	licensee	licensee	PROPN
easat-5823	206	22	learning	learn	VERB
easat-5823	206	23	gate	gate	NOUN
easat-5823	206	24	figure	figure	NOUN
easat-5823	206	25	7	7	NUM
easat-5823	206	26	.	.	PUNCT
easat-5823	206	27	confusion	confusion	NOUN
easat-5823	206	28	matrix	matrix	NOUN
easat-5823	206	29	for	for	ADP
easat-5823	206	30	proposed	propose	VERB
easat-5823	206	31	mlp	mlp	PROPN
easat-5823	206	32	-	-	PUNCT
easat-5823	206	33	rf	rf	ADJ
easat-5823	206	34	model	model	NOUN
easat-5823	206	35	lastly	lastly	ADV
easat-5823	206	36	,	,	PUNCT
easat-5823	206	37	the	the	DET
easat-5823	206	38	proposed	propose	VERB
easat-5823	206	39	mlp	mlp	NOUN
easat-5823	206	40	-	-	PUNCT
easat-5823	206	41	random	random	ADJ
easat-5823	206	42	forest	forest	NOUN
easat-5823	206	43	model	model	NOUN
easat-5823	206	44	achieved	achieve	VERB
easat-5823	206	45	an	an	DET
easat-5823	206	46	evaluation	evaluation	NOUN
easat-5823	206	47	metric	metric	ADJ
easat-5823	206	48	result	result	NOUN
easat-5823	206	49	of	of	ADP
easat-5823	206	50	99.949	99.949	NUM
easat-5823	206	51	%	%	NOUN
easat-5823	206	52	in	in	ADP
easat-5823	206	53	accuracy	accuracy	NOUN
easat-5823	206	54	,	,	PUNCT
easat-5823	206	55	87.097	87.097	NUM
easat-5823	206	56	%	%	NOUN
easat-5823	206	57	in	in	ADP
easat-5823	206	58	precision	precision	NOUN
easat-5823	206	59	,	,	PUNCT
easat-5823	206	60	82.653	82.653	NUM
easat-5823	206	61	%	%	NOUN
easat-5823	206	62	in	in	ADP
easat-5823	206	63	recall	recall	NOUN
easat-5823	206	64	and	and	CCONJ
easat-5823	206	65	84.817	84.817	NUM
easat-5823	206	66	%	%	NOUN
easat-5823	206	67	in	in	ADP
easat-5823	206	68	f1	f1	NOUN
easat-5823	206	69	-	-	PUNCT
easat-5823	206	70	score	score	NOUN
easat-5823	206	71	.	.	PUNCT
easat-5823	207	1	the	the	DET
easat-5823	207	2	confusion	confusion	NOUN
easat-5823	207	3	matrix	matrix	NOUN
easat-5823	207	4	for	for	ADP
easat-5823	207	5	the	the	DET
easat-5823	207	6	proposed	propose	VERB
easat-5823	207	7	mlp	mlp	NOUN
easat-5823	207	8	-	-	PUNCT
easat-5823	207	9	random	random	ADJ
easat-5823	207	10	forest	forest	NOUN
easat-5823	207	11	can	can	AUX
easat-5823	207	12	be	be	AUX
easat-5823	207	13	seen	see	VERB
easat-5823	207	14	in	in	ADP
easat-5823	207	15	figure	figure	NOUN
easat-5823	207	16	7	7	NUM
easat-5823	207	17	.	.	PUNCT
easat-5823	208	1	the	the	DET
easat-5823	208	2	confusion	confusion	NOUN
easat-5823	208	3	matrix	matrix	NOUN
easat-5823	208	4	showed	show	VERB
easat-5823	208	5	that	that	SCONJ
easat-5823	208	6	the	the	DET
easat-5823	208	7	proposed	propose	VERB
easat-5823	208	8	mlp	mlp	NOUN
easat-5823	208	9	-	-	PUNCT
easat-5823	208	10	random	random	ADJ
easat-5823	208	11	forest	forest	NOUN
easat-5823	208	12	model	model	NOUN
easat-5823	208	13	was	be	AUX
easat-5823	208	14	able	able	ADJ
easat-5823	208	15	to	to	PART
easat-5823	208	16	correctly	correctly	ADV
easat-5823	208	17	identify	identify	VERB
easat-5823	208	18	56852	56852	NUM
easat-5823	208	19	transactions	transaction	NOUN
easat-5823	208	20	as	as	ADP
easat-5823	208	21	non	non	ADJ
easat-5823	208	22	-	-	NOUN
easat-5823	208	23	fraud	fraud	ADJ
easat-5823	208	24	(	(	PUNCT
easat-5823	208	25	true	true	ADJ
easat-5823	208	26	negatives	negative	NOUN
easat-5823	208	27	)	)	PUNCT
easat-5823	208	28	,	,	PUNCT
easat-5823	208	29	17	17	NUM
easat-5823	208	30	transactions	transaction	NOUN
easat-5823	208	31	were	be	AUX
easat-5823	208	32	mistakenly	mistakenly	ADV
easat-5823	208	33	identified	identify	VERB
easat-5823	208	34	as	as	ADP
easat-5823	208	35	non	non	ADJ
easat-5823	208	36	-	-	NOUN
easat-5823	208	37	fraud	fraud	ADJ
easat-5823	208	38	(	(	PUNCT
easat-5823	208	39	false	false	ADJ
easat-5823	208	40	negatives	negative	NOUN
easat-5823	208	41	)	)	PUNCT
easat-5823	208	42	,	,	PUNCT
easat-5823	208	43	12	12	NUM
easat-5823	208	44	transactions	transaction	NOUN
easat-5823	208	45	mistakenly	mistakenly	ADV
easat-5823	208	46	identified	identify	VERB
easat-5823	208	47	as	as	ADP
easat-5823	208	48	fraud	fraud	NOUN
easat-5823	208	49	(	(	PUNCT
easat-5823	208	50	false	false	ADJ
easat-5823	208	51	positives	positive	NOUN
easat-5823	208	52	)	)	PUNCT
easat-5823	208	53	and	and	CCONJ
easat-5823	208	54	81	81	NUM
easat-5823	208	55	transactions	transaction	NOUN
easat-5823	208	56	correctly	correctly	ADV
easat-5823	208	57	identified	identify	VERB
easat-5823	208	58	as	as	ADP
easat-5823	208	59	fraud	fraud	NOUN
easat-5823	208	60	(	(	PUNCT
easat-5823	208	61	true	true	ADJ
easat-5823	208	62	positives	positive	NOUN
easat-5823	208	63	)	)	PUNCT
easat-5823	208	64	.	.	PUNCT
easat-5823	209	1	table	table	NOUN
easat-5823	209	2	2	2	NUM
easat-5823	209	3	.	.	PUNCT
easat-5823	209	4	performance	performance	NOUN
easat-5823	209	5	comparison	comparison	NOUN
easat-5823	209	6	for	for	ADP
easat-5823	209	7	each	each	DET
easat-5823	209	8	model	model	NOUN
easat-5823	209	9	.	.	PUNCT
easat-5823	210	1	accuracy	accuracy	NOUN
easat-5823	210	2	precision	precision	NOUN
easat-5823	210	3	recall	recall	NOUN
easat-5823	210	4	f1	f1	PROPN
easat-5823	210	5	score	score	NOUN
easat-5823	210	6	standalone	standalone	ADJ
easat-5823	210	7	mlp	mlp	NOUN
easat-5823	210	8	99.933	99.933	NUM
easat-5823	210	9	%	%	NOUN
easat-5823	210	10	81.914	81.914	NUM
easat-5823	210	11	%	%	NOUN
easat-5823	210	12	78.571	78.571	NUM
easat-5823	210	13	%	%	NOUN
easat-5823	210	14	80.208	80.208	NUM
easat-5823	210	15	%	%	NOUN
easat-5823	210	16	standalone	standalone	NOUN
easat-5823	210	17	rf	rf	NUM
easat-5823	210	18	99.947	99.947	NUM
easat-5823	210	19	%	%	NOUN
easat-5823	210	20	84.694	84.694	NUM
easat-5823	210	21	%	%	NOUN
easat-5823	210	22	84.694	84.694	NUM
easat-5823	210	23	%	%	NOUN
easat-5823	210	24	84.694	84.694	NUM
easat-5823	210	25	%	%	NOUN
easat-5823	210	26	proposed	propose	VERB
easat-5823	210	27	mlp	mlp	PROPN
easat-5823	210	28	-	-	PUNCT
easat-5823	210	29	rf	rf	ADJ
easat-5823	210	30	99.949	99.949	NUM
easat-5823	210	31	%	%	NOUN
easat-5823	210	32	87.097	87.097	NUM
easat-5823	210	33	%	%	NOUN
easat-5823	210	34	82.653	82.653	NUM
easat-5823	210	35	%	%	NOUN
easat-5823	210	36	84.817	84.817	NUM
easat-5823	210	37	%	%	NOUN
easat-5823	210	38	2492	2492	NUM
easat-5823	210	39	edelweiss	edelweiss	PROPN
easat-5823	210	40	applied	apply	VERB
easat-5823	210	41	science	science	NOUN
easat-5823	210	42	and	and	CCONJ
easat-5823	210	43	technology	technology	NOUN
easat-5823	210	44	issn	issn	PROPN
easat-5823	210	45	:	:	PUNCT
easat-5823	210	46	2576	2576	NUM
easat-5823	210	47	-	-	SYM
easat-5823	210	48	8484	8484	NUM
easat-5823	210	49	vol	vol	NOUN
easat-5823	210	50	.	.	PROPN
easat-5823	211	1	9	9	NUM
easat-5823	211	2	,	,	PUNCT
easat-5823	211	3	no	no	INTJ
easat-5823	211	4	.	.	NOUN
easat-5823	211	5	3	3	NUM
easat-5823	211	6	:	:	PUNCT
easat-5823	211	7	2482	2482	NUM
easat-5823	211	8	-	-	SYM
easat-5823	211	9	2494	2494	NUM
easat-5823	211	10	,	,	PUNCT
easat-5823	211	11	2025	2025	NUM
easat-5823	211	12	doi	doi	NOUN
easat-5823	211	13	:	:	PUNCT
easat-5823	211	14	10.55214/25768484.v9i3.5823	10.55214/25768484.v9i3.5823	NUM
easat-5823	211	15	©	©	PROPN
easat-5823	211	16	2025	2025	NUM
easat-5823	211	17	by	by	ADP
easat-5823	211	18	the	the	DET
easat-5823	211	19	authors	author	NOUN
easat-5823	211	20	;	;	PUNCT
easat-5823	211	21	licensee	licensee	PROPN
easat-5823	211	22	learning	learning	NOUN
easat-5823	211	23	gate	gate	NOUN
easat-5823	211	24	5	5	NUM
easat-5823	211	25	.	.	PUNCT
easat-5823	211	26	discussion	discussion	NOUN
easat-5823	211	27	to	to	PART
easat-5823	211	28	analyze	analyze	VERB
easat-5823	211	29	the	the	DET
easat-5823	211	30	performance	performance	NOUN
easat-5823	211	31	of	of	ADP
easat-5823	211	32	each	each	DET
easat-5823	211	33	model	model	NOUN
easat-5823	211	34	,	,	PUNCT
easat-5823	211	35	a	a	DET
easat-5823	211	36	performance	performance	NOUN
easat-5823	211	37	comparison	comparison	NOUN
easat-5823	211	38	is	be	AUX
easat-5823	211	39	done	do	VERB
easat-5823	211	40	in	in	ADP
easat-5823	211	41	the	the	DET
easat-5823	211	42	form	form	NOUN
easat-5823	211	43	of	of	ADP
easat-5823	211	44	table	table	NOUN
easat-5823	211	45	2	2	NUM
easat-5823	211	46	.	.	PUNCT
easat-5823	212	1	for	for	ADP
easat-5823	212	2	the	the	DET
easat-5823	212	3	accuracy	accuracy	NOUN
easat-5823	212	4	metric	metric	ADJ
easat-5823	212	5	,	,	PUNCT
easat-5823	212	6	all	all	PRON
easat-5823	212	7	of	of	ADP
easat-5823	212	8	the	the	DET
easat-5823	212	9	models	model	NOUN
easat-5823	212	10	had	have	VERB
easat-5823	212	11	a	a	DET
easat-5823	212	12	similar	similar	ADJ
easat-5823	212	13	but	but	CCONJ
easat-5823	212	14	great	great	ADJ
easat-5823	212	15	performance	performance	NOUN
easat-5823	212	16	.	.	PUNCT
easat-5823	213	1	the	the	DET
easat-5823	213	2	proposed	propose	VERB
easat-5823	213	3	mlp	mlp	NOUN
easat-5823	213	4	-	-	PUNCT
easat-5823	213	5	rf	rf	ADJ
easat-5823	213	6	model	model	NOUN
easat-5823	213	7	had	have	VERB
easat-5823	213	8	the	the	DET
easat-5823	213	9	best	good	ADJ
easat-5823	213	10	performance	performance	NOUN
easat-5823	213	11	of	of	ADP
easat-5823	213	12	99.949	99.949	NUM
easat-5823	213	13	%	%	NOUN
easat-5823	213	14	accuracy	accuracy	NOUN
easat-5823	213	15	which	which	PRON
easat-5823	213	16	means	mean	VERB
easat-5823	213	17	that	that	SCONJ
easat-5823	213	18	the	the	DET
easat-5823	213	19	proposed	propose	VERB
easat-5823	213	20	model	model	NOUN
easat-5823	213	21	was	be	AUX
easat-5823	213	22	able	able	ADJ
easat-5823	213	23	to	to	PART
easat-5823	213	24	correctly	correctly	ADV
easat-5823	213	25	classifies	classify	VERB
easat-5823	213	26	almost	almost	ADV
easat-5823	213	27	all	all	DET
easat-5823	213	28	transactions	transaction	NOUN
easat-5823	213	29	.	.	PUNCT
easat-5823	214	1	although	although	SCONJ
easat-5823	214	2	only	only	ADV
easat-5823	214	3	a	a	DET
easat-5823	214	4	slight	slight	ADJ
easat-5823	214	5	improvement	improvement	NOUN
easat-5823	214	6	,	,	PUNCT
easat-5823	214	7	the	the	DET
easat-5823	214	8	proposed	propose	VERB
easat-5823	214	9	model	model	NOUN
easat-5823	214	10	had	have	VERB
easat-5823	214	11	a	a	DET
easat-5823	214	12	better	well	ADJ
easat-5823	214	13	performance	performance	NOUN
easat-5823	214	14	against	against	ADP
easat-5823	214	15	mlp	mlp	PROPN
easat-5823	214	16	model	model	NOUN
easat-5823	214	17	with	with	ADP
easat-5823	214	18	99.933	99.933	NUM
easat-5823	214	19	%	%	NOUN
easat-5823	214	20	and	and	CCONJ
easat-5823	214	21	rf	rf	NOUN
easat-5823	214	22	model	model	NOUN
easat-5823	214	23	with	with	ADP
easat-5823	214	24	99.947	99.947	NUM
easat-5823	214	25	%	%	NOUN
easat-5823	214	26	.	.	PUNCT
easat-5823	215	1	in	in	ADP
easat-5823	215	2	the	the	DET
easat-5823	215	3	precision	precision	NOUN
easat-5823	215	4	metric	metric	NOUN
easat-5823	215	5	,	,	PUNCT
easat-5823	215	6	the	the	DET
easat-5823	215	7	proposed	propose	VERB
easat-5823	215	8	mlp	mlp	NOUN
easat-5823	215	9	-	-	PUNCT
easat-5823	215	10	rf	rf	ADJ
easat-5823	215	11	model	model	NOUN
easat-5823	215	12	had	have	VERB
easat-5823	215	13	the	the	DET
easat-5823	215	14	best	good	ADJ
easat-5823	215	15	performance	performance	NOUN
easat-5823	215	16	with	with	ADP
easat-5823	215	17	good	good	ADJ
easat-5823	215	18	precision	precision	NOUN
easat-5823	215	19	of	of	ADP
easat-5823	215	20	87.097	87.097	NUM
easat-5823	215	21	%	%	NOUN
easat-5823	215	22	.	.	PUNCT
easat-5823	216	1	this	this	PRON
easat-5823	216	2	indicates	indicate	VERB
easat-5823	216	3	that	that	SCONJ
easat-5823	216	4	the	the	DET
easat-5823	216	5	proposed	propose	VERB
easat-5823	216	6	model	model	NOUN
easat-5823	216	7	had	have	VERB
easat-5823	216	8	superior	superior	ADJ
easat-5823	216	9	capability	capability	NOUN
easat-5823	216	10	to	to	PART
easat-5823	216	11	minimize	minimize	VERB
easat-5823	216	12	false	false	ADJ
easat-5823	216	13	positives	positive	NOUN
easat-5823	216	14	.	.	PUNCT
easat-5823	217	1	compared	compare	VERB
easat-5823	217	2	to	to	ADP
easat-5823	217	3	the	the	DET
easat-5823	217	4	accuracy	accuracy	NOUN
easat-5823	217	5	of	of	ADP
easat-5823	217	6	mlp	mlp	PROPN
easat-5823	217	7	model	model	NOUN
easat-5823	217	8	with	with	ADP
easat-5823	217	9	81.914	81.914	NUM
easat-5823	217	10	%	%	NOUN
easat-5823	217	11	and	and	CCONJ
easat-5823	217	12	rf	rf	VERB
easat-5823	217	13	with	with	ADP
easat-5823	217	14	84.694	84.694	NUM
easat-5823	217	15	%	%	NOUN
easat-5823	217	16	,	,	PUNCT
easat-5823	217	17	it	it	PRON
easat-5823	217	18	is	be	AUX
easat-5823	217	19	a	a	DET
easat-5823	217	20	significant	significant	ADJ
easat-5823	217	21	improvement	improvement	NOUN
easat-5823	217	22	that	that	PRON
easat-5823	217	23	shows	show	VERB
easat-5823	217	24	that	that	SCONJ
easat-5823	217	25	combining	combine	VERB
easat-5823	217	26	the	the	DET
easat-5823	217	27	two	two	NUM
easat-5823	217	28	standalone	standalone	ADJ
easat-5823	217	29	methods	method	NOUN
easat-5823	217	30	can	can	AUX
easat-5823	217	31	improve	improve	VERB
easat-5823	217	32	the	the	DET
easat-5823	217	33	precision	precision	NOUN
easat-5823	217	34	capability	capability	NOUN
easat-5823	217	35	.	.	PUNCT
easat-5823	218	1	however	however	ADV
easat-5823	218	2	,	,	PUNCT
easat-5823	218	3	for	for	ADP
easat-5823	218	4	the	the	DET
easat-5823	218	5	recall	recall	NOUN
easat-5823	218	6	metric	metric	PROPN
easat-5823	218	7	,	,	PUNCT
easat-5823	218	8	the	the	DET
easat-5823	218	9	rf	rf	NOUN
easat-5823	218	10	model	model	NOUN
easat-5823	218	11	was	be	AUX
easat-5823	218	12	able	able	ADJ
easat-5823	218	13	to	to	PART
easat-5823	218	14	beat	beat	VERB
easat-5823	218	15	the	the	DET
easat-5823	218	16	standalone	standalone	ADJ
easat-5823	218	17	mlp	mlp	NOUN
easat-5823	218	18	and	and	CCONJ
easat-5823	218	19	proposed	propose	VERB
easat-5823	218	20	mlp	mlp	PROPN
easat-5823	218	21	-	-	PUNCT
easat-5823	218	22	rf	rf	NOUN
easat-5823	218	23	model	model	NOUN
easat-5823	218	24	and	and	CCONJ
easat-5823	218	25	achieved	achieve	VERB
easat-5823	218	26	the	the	DET
easat-5823	218	27	best	good	ADJ
easat-5823	218	28	result	result	NOUN
easat-5823	218	29	.	.	PUNCT
easat-5823	219	1	the	the	DET
easat-5823	219	2	rf	rf	NOUN
easat-5823	219	3	model	model	NOUN
easat-5823	219	4	achieved	achieve	VERB
easat-5823	219	5	84.694	84.694	NUM
easat-5823	219	6	%	%	NOUN
easat-5823	219	7	while	while	SCONJ
easat-5823	219	8	with	with	ADP
easat-5823	219	9	a	a	DET
easat-5823	219	10	slightly	slightly	ADV
easat-5823	219	11	lower	low	ADJ
easat-5823	219	12	recall	recall	NOUN
easat-5823	219	13	,	,	PUNCT
easat-5823	219	14	the	the	DET
easat-5823	219	15	proposed	propose	VERB
easat-5823	219	16	mlp	mlp	NOUN
easat-5823	219	17	-	-	PUNCT
easat-5823	219	18	rf	rf	ADJ
easat-5823	219	19	model	model	NOUN
easat-5823	219	20	achieved	achieve	VERB
easat-5823	219	21	a	a	DET
easat-5823	219	22	score	score	NOUN
easat-5823	219	23	of	of	ADP
easat-5823	219	24	82.653	82.653	NUM
easat-5823	219	25	%	%	NOUN
easat-5823	219	26	and	and	CCONJ
easat-5823	219	27	the	the	DET
easat-5823	219	28	mlp	mlp	NOUN
easat-5823	219	29	achieved	achieve	VERB
easat-5823	219	30	an	an	DET
easat-5823	219	31	even	even	ADV
easat-5823	219	32	lower	low	ADJ
easat-5823	219	33	recall	recall	NOUN
easat-5823	219	34	of	of	ADP
easat-5823	219	35	78.571	78.571	NUM
easat-5823	219	36	%	%	NOUN
easat-5823	219	37	.	.	PUNCT
easat-5823	220	1	with	with	ADP
easat-5823	220	2	only	only	ADV
easat-5823	220	3	slightly	slightly	ADV
easat-5823	220	4	lower	low	ADJ
easat-5823	220	5	recall	recall	NOUN
easat-5823	220	6	,	,	PUNCT
easat-5823	220	7	the	the	DET
easat-5823	220	8	proposed	propose	VERB
easat-5823	220	9	model	model	NOUN
easat-5823	220	10	still	still	ADV
easat-5823	220	11	had	have	VERB
easat-5823	220	12	a	a	DET
easat-5823	220	13	good	good	ADJ
easat-5823	220	14	recall	recall	NOUN
easat-5823	220	15	and	and	CCONJ
easat-5823	220	16	still	still	ADV
easat-5823	220	17	able	able	ADJ
easat-5823	220	18	to	to	PART
easat-5823	220	19	identify	identify	VERB
easat-5823	220	20	a	a	DET
easat-5823	220	21	good	good	ADJ
easat-5823	220	22	portion	portion	NOUN
easat-5823	220	23	of	of	ADP
easat-5823	220	24	fraudulent	fraudulent	ADJ
easat-5823	220	25	transactions	transaction	NOUN
easat-5823	220	26	.	.	PUNCT
easat-5823	221	1	for	for	ADP
easat-5823	221	2	the	the	DET
easat-5823	221	3	last	last	ADJ
easat-5823	221	4	metric	metric	NOUN
easat-5823	221	5	,	,	PUNCT
easat-5823	221	6	which	which	PRON
easat-5823	221	7	is	be	AUX
easat-5823	221	8	f1	f1	ADJ
easat-5823	221	9	score	score	NOUN
easat-5823	221	10	,	,	PUNCT
easat-5823	221	11	the	the	DET
easat-5823	221	12	proposed	propose	VERB
easat-5823	221	13	mlp	mlp	NOUN
easat-5823	221	14	–	–	PUNCT
easat-5823	221	15	rf	rf	NOUN
easat-5823	221	16	model	model	NOUN
easat-5823	221	17	had	have	VERB
easat-5823	221	18	the	the	DET
easat-5823	221	19	best	good	ADJ
easat-5823	221	20	performance	performance	NOUN
easat-5823	221	21	followed	follow	VERB
easat-5823	221	22	up	up	ADP
easat-5823	221	23	by	by	ADP
easat-5823	221	24	rf	rf	NOUN
easat-5823	221	25	model	model	NOUN
easat-5823	221	26	with	with	ADP
easat-5823	221	27	a	a	DET
easat-5823	221	28	slight	slight	ADJ
easat-5823	221	29	difference	difference	NOUN
easat-5823	221	30	and	and	CCONJ
easat-5823	221	31	in	in	ADP
easat-5823	221	32	the	the	DET
easat-5823	221	33	last	last	ADJ
easat-5823	221	34	place	place	NOUN
easat-5823	221	35	was	be	AUX
easat-5823	221	36	mlp	mlp	PROPN
easat-5823	221	37	model	model	NOUN
easat-5823	221	38	with	with	ADP
easat-5823	221	39	the	the	DET
easat-5823	221	40	worst	bad	ADJ
easat-5823	221	41	performance	performance	NOUN
easat-5823	221	42	.	.	PUNCT
easat-5823	222	1	the	the	DET
easat-5823	222	2	proposed	propose	VERB
easat-5823	222	3	model	model	NOUN
easat-5823	222	4	achieved	achieve	VERB
easat-5823	222	5	84.817	84.817	NUM
easat-5823	222	6	%	%	NOUN
easat-5823	222	7	in	in	ADP
easat-5823	222	8	f1	f1	ADJ
easat-5823	222	9	score	score	NOUN
easat-5823	222	10	and	and	CCONJ
easat-5823	222	11	the	the	DET
easat-5823	222	12	rf	rf	NOUN
easat-5823	222	13	model	model	NOUN
easat-5823	222	14	achieved	achieve	VERB
easat-5823	222	15	84.694	84.694	NUM
easat-5823	222	16	%	%	NOUN
easat-5823	222	17	which	which	PRON
easat-5823	222	18	demonstrated	demonstrate	VERB
easat-5823	222	19	that	that	SCONJ
easat-5823	222	20	both	both	CCONJ
easat-5823	222	21	the	the	DET
easat-5823	222	22	model	model	NOUN
easat-5823	222	23	had	have	VERB
easat-5823	222	24	a	a	DET
easat-5823	222	25	really	really	ADV
easat-5823	222	26	good	good	ADJ
easat-5823	222	27	balance	balance	NOUN
easat-5823	222	28	of	of	ADP
easat-5823	222	29	precision	precision	NOUN
easat-5823	222	30	and	and	CCONJ
easat-5823	222	31	recall	recall	NOUN
easat-5823	222	32	,	,	PUNCT
easat-5823	222	33	thus	thus	ADV
easat-5823	222	34	indicating	indicate	VERB
easat-5823	222	35	that	that	SCONJ
easat-5823	222	36	the	the	DET
easat-5823	222	37	models	model	NOUN
easat-5823	222	38	are	be	AUX
easat-5823	222	39	better	well	ADJ
easat-5823	222	40	at	at	ADP
easat-5823	222	41	minimizing	minimize	VERB
easat-5823	222	42	false	false	ADJ
easat-5823	222	43	positives	positive	NOUN
easat-5823	222	44	while	while	SCONJ
easat-5823	222	45	also	also	ADV
easat-5823	222	46	able	able	ADJ
easat-5823	222	47	to	to	PART
easat-5823	222	48	correctly	correctly	ADV
easat-5823	222	49	identify	identify	VERB
easat-5823	222	50	fraudulent	fraudulent	ADJ
easat-5823	222	51	cases	case	NOUN
easat-5823	222	52	.	.	PUNCT
easat-5823	223	1	meanwhile	meanwhile	ADV
easat-5823	223	2	,	,	PUNCT
easat-5823	223	3	mlp	mlp	PROPN
easat-5823	223	4	had	have	VERB
easat-5823	223	5	the	the	DET
easat-5823	223	6	worst	bad	ADJ
easat-5823	223	7	f1	f1	NOUN
easat-5823	223	8	score	score	NOUN
easat-5823	223	9	with	with	ADP
easat-5823	223	10	80.208	80.208	NUM
easat-5823	223	11	%	%	NOUN
easat-5823	223	12	due	due	ADP
easat-5823	223	13	to	to	ADP
easat-5823	223	14	its	its	PRON
easat-5823	223	15	relatively	relatively	ADV
easat-5823	223	16	lower	low	ADJ
easat-5823	223	17	precision	precision	NOUN
easat-5823	223	18	and	and	CCONJ
easat-5823	223	19	recall	recall	NOUN
easat-5823	223	20	.	.	PUNCT
easat-5823	224	1	based	base	VERB
easat-5823	224	2	on	on	ADP
easat-5823	224	3	the	the	DET
easat-5823	224	4	result	result	NOUN
easat-5823	224	5	of	of	ADP
easat-5823	224	6	the	the	DET
easat-5823	224	7	performance	performance	NOUN
easat-5823	224	8	comparison	comparison	NOUN
easat-5823	224	9	,	,	PUNCT
easat-5823	224	10	the	the	DET
easat-5823	224	11	proposed	propose	VERB
easat-5823	224	12	mlp	mlp	NOUN
easat-5823	224	13	-	-	PUNCT
easat-5823	224	14	rf	rf	ADJ
easat-5823	224	15	model	model	NOUN
easat-5823	224	16	has	have	VERB
easat-5823	224	17	the	the	DET
easat-5823	224	18	best	good	ADJ
easat-5823	224	19	overall	overall	ADJ
easat-5823	224	20	result	result	NOUN
easat-5823	224	21	compared	compare	VERB
easat-5823	224	22	to	to	ADP
easat-5823	224	23	standalone	standalone	NOUN
easat-5823	224	24	mlp	mlp	NOUN
easat-5823	224	25	and	and	CCONJ
easat-5823	224	26	rf	rf	NOUN
easat-5823	224	27	models	model	NOUN
easat-5823	224	28	.	.	PUNCT
easat-5823	225	1	the	the	DET
easat-5823	225	2	proposed	propose	VERB
easat-5823	225	3	model	model	NOUN
easat-5823	225	4	combines	combine	VERB
easat-5823	225	5	the	the	DET
easat-5823	225	6	mlp	mlp	NOUN
easat-5823	225	7	’s	’s	PART
easat-5823	225	8	capabilities	capability	NOUN
easat-5823	225	9	at	at	ADP
easat-5823	225	10	extracting	extract	VERB
easat-5823	225	11	features	feature	NOUN
easat-5823	225	12	to	to	PART
easat-5823	225	13	identify	identify	VERB
easat-5823	225	14	the	the	DET
easat-5823	225	15	complex	complex	ADJ
easat-5823	225	16	patterns	pattern	NOUN
easat-5823	225	17	in	in	ADP
easat-5823	225	18	data	datum	NOUN
easat-5823	225	19	and	and	CCONJ
easat-5823	225	20	the	the	DET
easat-5823	225	21	effective	effective	ADJ
easat-5823	225	22	classifying	classify	VERB
easat-5823	225	23	capabilities	capability	NOUN
easat-5823	225	24	of	of	ADP
easat-5823	225	25	rf	rf	NOUN
easat-5823	225	26	.	.	PUNCT
easat-5823	225	27	by	by	ADP
easat-5823	225	28	leveraging	leverage	VERB
easat-5823	225	29	the	the	DET
easat-5823	225	30	strength	strength	NOUN
easat-5823	225	31	of	of	ADP
easat-5823	225	32	each	each	DET
easat-5823	225	33	standalone	standalone	NOUN
easat-5823	225	34	model	model	NOUN
easat-5823	225	35	,	,	PUNCT
easat-5823	225	36	the	the	DET
easat-5823	225	37	proposed	propose	VERB
easat-5823	225	38	model	model	NOUN
easat-5823	225	39	is	be	AUX
easat-5823	225	40	able	able	ADJ
easat-5823	225	41	to	to	PART
easat-5823	225	42	further	far	ADV
easat-5823	225	43	enhance	enhance	VERB
easat-5823	225	44	the	the	DET
easat-5823	225	45	performance	performance	NOUN
easat-5823	225	46	by	by	ADP
easat-5823	225	47	reducing	reduce	VERB
easat-5823	225	48	false	false	ADJ
easat-5823	225	49	positives	positive	NOUN
easat-5823	225	50	which	which	PRON
easat-5823	225	51	is	be	AUX
easat-5823	225	52	evidenced	evidence	VERB
easat-5823	225	53	by	by	ADP
easat-5823	225	54	its	its	PRON
easat-5823	225	55	high	high	ADJ
easat-5823	225	56	result	result	NOUN
easat-5823	225	57	in	in	ADP
easat-5823	225	58	precision	precision	NOUN
easat-5823	225	59	while	while	SCONJ
easat-5823	225	60	still	still	ADV
easat-5823	225	61	maintaining	maintain	VERB
easat-5823	225	62	a	a	DET
easat-5823	225	63	good	good	ADJ
easat-5823	225	64	recall	recall	NOUN
easat-5823	225	65	.	.	PUNCT
easat-5823	226	1	this	this	DET
easat-5823	226	2	good	good	ADJ
easat-5823	226	3	performance	performance	NOUN
easat-5823	226	4	of	of	ADP
easat-5823	226	5	the	the	DET
easat-5823	226	6	proposed	propose	VERB
easat-5823	226	7	model	model	NOUN
easat-5823	226	8	is	be	AUX
easat-5823	226	9	influenced	influence	VERB
easat-5823	226	10	directly	directly	ADV
easat-5823	226	11	by	by	ADP
easat-5823	226	12	the	the	DET
easat-5823	226	13	parameter	parameter	NOUN
easat-5823	226	14	of	of	ADP
easat-5823	226	15	both	both	CCONJ
easat-5823	226	16	the	the	DET
easat-5823	226	17	mlp	mlp	NOUN
easat-5823	226	18	feature	feature	NOUN
easat-5823	226	19	extractor	extractor	NOUN
easat-5823	226	20	and	and	CCONJ
easat-5823	226	21	the	the	DET
easat-5823	226	22	rf	rf	NOUN
easat-5823	226	23	classifier	classifier	NOUN
easat-5823	226	24	.	.	PUNCT
easat-5823	227	1	based	base	VERB
easat-5823	227	2	on	on	ADP
easat-5823	227	3	the	the	DET
easat-5823	227	4	experiment	experiment	NOUN
easat-5823	227	5	that	that	PRON
easat-5823	227	6	have	have	AUX
easat-5823	227	7	been	be	AUX
easat-5823	227	8	done	do	VERB
easat-5823	227	9	,	,	PUNCT
easat-5823	227	10	mlp	mlp	NOUN
easat-5823	227	11	feature	feature	NOUN
easat-5823	227	12	extractor	extractor	NOUN
easat-5823	227	13	was	be	AUX
easat-5823	227	14	influenced	influence	VERB
easat-5823	227	15	by	by	ADP
easat-5823	227	16	the	the	DET
easat-5823	227	17	assigned	assign	VERB
easat-5823	227	18	number	number	NOUN
easat-5823	227	19	of	of	ADP
easat-5823	227	20	neurons	neuron	NOUN
easat-5823	227	21	in	in	ADP
easat-5823	227	22	a	a	DET
easat-5823	227	23	hidden	hide	VERB
easat-5823	227	24	layer	layer	NOUN
easat-5823	227	25	.	.	PUNCT
easat-5823	228	1	with	with	ADP
easat-5823	228	2	higher	high	ADJ
easat-5823	228	3	number	number	NOUN
easat-5823	228	4	of	of	ADP
easat-5823	228	5	neurons	neuron	NOUN
easat-5823	228	6	,	,	PUNCT
easat-5823	228	7	mlp	mlp	PROPN
easat-5823	228	8	was	be	AUX
easat-5823	228	9	able	able	ADJ
easat-5823	228	10	to	to	PART
easat-5823	228	11	capture	capture	VERB
easat-5823	228	12	complex	complex	ADJ
easat-5823	228	13	patterns	pattern	NOUN
easat-5823	228	14	in	in	ADP
easat-5823	228	15	the	the	DET
easat-5823	228	16	input	input	NOUN
easat-5823	228	17	data	datum	NOUN
easat-5823	228	18	more	more	ADV
easat-5823	228	19	effectively	effectively	ADV
easat-5823	228	20	.	.	PUNCT
easat-5823	229	1	other	other	ADJ
easat-5823	229	2	than	than	ADP
easat-5823	229	3	that	that	PRON
easat-5823	229	4	,	,	PUNCT
easat-5823	229	5	using	use	VERB
easat-5823	229	6	tanh	tanh	NOUN
easat-5823	229	7	activation	activation	NOUN
easat-5823	229	8	function	function	NOUN
easat-5823	229	9	allows	allow	VERB
easat-5823	229	10	mlp	mlp	PROPN
easat-5823	229	11	to	to	PART
easat-5823	229	12	model	model	VERB
easat-5823	229	13	both	both	CCONJ
easat-5823	229	14	positive	positive	ADJ
easat-5823	229	15	and	and	CCONJ
easat-5823	229	16	negative	negative	ADJ
easat-5823	229	17	relationships	relationship	NOUN
easat-5823	229	18	which	which	PRON
easat-5823	229	19	can	can	AUX
easat-5823	229	20	be	be	AUX
easat-5823	229	21	found	find	VERB
easat-5823	229	22	in	in	ADP
easat-5823	229	23	the	the	DET
easat-5823	229	24	input	input	NOUN
easat-5823	229	25	data	datum	NOUN
easat-5823	229	26	.	.	PUNCT
easat-5823	230	1	furthermore	furthermore	ADV
easat-5823	230	2	,	,	PUNCT
easat-5823	230	3	using	use	VERB
easat-5823	230	4	the	the	DET
easat-5823	230	5	adam	adam	PROPN
easat-5823	230	6	solver	solver	PROPN
easat-5823	230	7	also	also	ADV
easat-5823	230	8	improves	improve	VERB
easat-5823	230	9	the	the	DET
easat-5823	230	10	model	model	NOUN
easat-5823	230	11	performance	performance	NOUN
easat-5823	230	12	by	by	ADP
easat-5823	230	13	optimizing	optimize	VERB
easat-5823	230	14	weight	weight	NOUN
easat-5823	230	15	efficiently	efficiently	ADV
easat-5823	230	16	and	and	CCONJ
easat-5823	230	17	are	be	AUX
easat-5823	230	18	more	more	ADV
easat-5823	230	19	suited	suited	ADJ
easat-5823	230	20	for	for	ADP
easat-5823	230	21	larger	large	ADJ
easat-5823	230	22	dataset	dataset	NOUN
easat-5823	230	23	like	like	ADP
easat-5823	230	24	the	the	DET
easat-5823	230	25	transaction	transaction	NOUN
easat-5823	230	26	data	datum	NOUN
easat-5823	230	27	used	use	VERB
easat-5823	230	28	in	in	ADP
easat-5823	230	29	this	this	DET
easat-5823	230	30	study	study	NOUN
easat-5823	230	31	.	.	PUNCT
easat-5823	231	1	for	for	ADP
easat-5823	231	2	the	the	DET
easat-5823	231	3	rf	rf	NOUN
easat-5823	231	4	classifier	classifier	NOUN
easat-5823	231	5	,	,	PUNCT
easat-5823	231	6	the	the	DET
easat-5823	231	7	parameter	parameter	NOUN
easat-5823	231	8	that	that	PRON
easat-5823	231	9	influenced	influence	VERB
easat-5823	231	10	the	the	DET
easat-5823	231	11	model	model	NOUN
easat-5823	231	12	greatly	greatly	ADV
easat-5823	231	13	is	be	AUX
easat-5823	231	14	the	the	DET
easat-5823	231	15	number	number	NOUN
easat-5823	231	16	of	of	ADP
easat-5823	231	17	trees	tree	NOUN
easat-5823	231	18	and	and	CCONJ
easat-5823	231	19	maximum	maximum	ADJ
easat-5823	231	20	depth	depth	NOUN
easat-5823	231	21	which	which	PRON
easat-5823	231	22	with	with	ADP
easat-5823	231	23	the	the	DET
easat-5823	231	24	balance	balance	NOUN
easat-5823	231	25	of	of	ADP
easat-5823	231	26	the	the	DET
easat-5823	231	27	two	two	NUM
easat-5823	231	28	,	,	PUNCT
easat-5823	231	29	the	the	DET
easat-5823	231	30	model	model	NOUN
easat-5823	231	31	is	be	AUX
easat-5823	231	32	more	more	ADV
easat-5823	231	33	balanced	balanced	ADJ
easat-5823	231	34	and	and	CCONJ
easat-5823	231	35	can	can	AUX
easat-5823	231	36	generalize	generalize	VERB
easat-5823	231	37	better	well	ADV
easat-5823	231	38	.	.	PUNCT
easat-5823	232	1	furthermore	furthermore	ADV
easat-5823	232	2	,	,	PUNCT
easat-5823	232	3	by	by	ADP
easat-5823	232	4	increasing	increase	VERB
easat-5823	232	5	the	the	DET
easat-5823	232	6	number	number	NOUN
easat-5823	232	7	of	of	ADP
easat-5823	232	8	minimum	minimum	ADJ
easat-5823	232	9	samples	sample	NOUN
easat-5823	232	10	in	in	ADP
easat-5823	232	11	a	a	DET
easat-5823	232	12	leaf	leaf	NOUN
easat-5823	232	13	node	node	NOUN
easat-5823	232	14	,	,	PUNCT
easat-5823	232	15	the	the	DET
easat-5823	232	16	model	model	NOUN
easat-5823	232	17	can	can	AUX
easat-5823	232	18	be	be	AUX
easat-5823	232	19	further	far	ADV
easat-5823	232	20	generalized	generalize	VERB
easat-5823	232	21	by	by	ADP
easat-5823	232	22	preventing	prevent	VERB
easat-5823	232	23	the	the	DET
easat-5823	232	24	trees	tree	NOUN
easat-5823	232	25	from	from	ADP
easat-5823	232	26	being	be	AUX
easat-5823	232	27	overly	overly	ADV
easat-5823	232	28	sensitive	sensitive	ADJ
easat-5823	232	29	.	.	PUNCT
easat-5823	233	1	with	with	ADP
easat-5823	233	2	these	these	DET
easat-5823	233	3	parameters	parameter	NOUN
easat-5823	233	4	’	’	PART
easat-5823	233	5	optimization	optimization	NOUN
easat-5823	233	6	,	,	PUNCT
easat-5823	233	7	the	the	DET
easat-5823	233	8	proposed	propose	VERB
easat-5823	233	9	model	model	NOUN
easat-5823	233	10	is	be	AUX
easat-5823	233	11	trained	train	VERB
easat-5823	233	12	to	to	PART
easat-5823	233	13	be	be	AUX
easat-5823	233	14	accurate	accurate	ADJ
easat-5823	233	15	and	and	CCONJ
easat-5823	233	16	robust	robust	ADJ
easat-5823	233	17	as	as	ADV
easat-5823	233	18	well	well	ADV
easat-5823	233	19	as	as	ADP
easat-5823	233	20	reliable	reliable	ADJ
easat-5823	233	21	at	at	ADP
easat-5823	233	22	predicting	predict	VERB
easat-5823	233	23	fraudulent	fraudulent	ADJ
easat-5823	233	24	transactions	transaction	NOUN
easat-5823	233	25	.	.	PUNCT
easat-5823	234	1	6	6	X
easat-5823	234	2	.	.	X
easat-5823	234	3	conclusions	conclusion	NOUN
easat-5823	234	4	this	this	DET
easat-5823	234	5	research	research	NOUN
easat-5823	234	6	was	be	AUX
easat-5823	234	7	conducted	conduct	VERB
easat-5823	234	8	to	to	PART
easat-5823	234	9	test	test	VERB
easat-5823	234	10	the	the	DET
easat-5823	234	11	performance	performance	NOUN
easat-5823	234	12	of	of	ADP
easat-5823	234	13	the	the	DET
easat-5823	234	14	proposed	propose	VERB
easat-5823	234	15	method	method	NOUN
easat-5823	234	16	which	which	PRON
easat-5823	234	17	combines	combine	VERB
easat-5823	234	18	multilayer	multilayer	ADJ
easat-5823	234	19	perceptron	perceptron	PROPN
easat-5823	234	20	neural	neural	ADJ
easat-5823	234	21	network	network	NOUN
easat-5823	234	22	with	with	ADP
easat-5823	234	23	random	random	ADJ
easat-5823	234	24	forest	forest	NOUN
easat-5823	234	25	to	to	PART
easat-5823	234	26	detect	detect	VERB
easat-5823	234	27	fraud	fraud	NOUN
easat-5823	234	28	credit	credit	NOUN
easat-5823	234	29	card	card	NOUN
easat-5823	234	30	transaction	transaction	NOUN
easat-5823	234	31	.	.	PUNCT
easat-5823	235	1	the	the	DET
easat-5823	235	2	mlp	mlp	NOUN
easat-5823	235	3	was	be	AUX
easat-5823	235	4	used	use	VERB
easat-5823	235	5	to	to	PART
easat-5823	235	6	effectively	effectively	ADV
easat-5823	235	7	capture	capture	VERB
easat-5823	235	8	the	the	DET
easat-5823	235	9	complex	complex	ADJ
easat-5823	235	10	patterns	pattern	NOUN
easat-5823	235	11	in	in	ADP
easat-5823	235	12	the	the	DET
easat-5823	235	13	data	datum	NOUN
easat-5823	235	14	by	by	ADP
easat-5823	235	15	extracting	extract	VERB
easat-5823	235	16	the	the	DET
easat-5823	235	17	meaningful	meaningful	ADJ
easat-5823	235	18	features	feature	NOUN
easat-5823	235	19	,	,	PUNCT
easat-5823	235	20	while	while	SCONJ
easat-5823	235	21	the	the	DET
easat-5823	235	22	rf	rf	NOUN
easat-5823	235	23	classifier	classifier	NOUN
easat-5823	235	24	used	use	VERB
easat-5823	235	25	these	these	DET
easat-5823	235	26	features	feature	NOUN
easat-5823	235	27	to	to	PART
easat-5823	235	28	make	make	VERB
easat-5823	235	29	a	a	DET
easat-5823	235	30	robust	robust	ADJ
easat-5823	235	31	and	and	CCONJ
easat-5823	235	32	accurate	accurate	ADJ
easat-5823	235	33	classifications	classification	NOUN
easat-5823	235	34	.	.	PUNCT
easat-5823	236	1	the	the	DET
easat-5823	236	2	proposed	propose	VERB
easat-5823	236	3	mlp	mlp	NOUN
easat-5823	236	4	–	–	PUNCT
easat-5823	236	5	rf	rf	NOUN
easat-5823	236	6	method	method	NOUN
easat-5823	236	7	was	be	AUX
easat-5823	236	8	compared	compare	VERB
easat-5823	236	9	with	with	ADP
easat-5823	236	10	the	the	DET
easat-5823	236	11	standalone	standalone	ADJ
easat-5823	236	12	mlp	mlp	NOUN
easat-5823	236	13	and	and	CCONJ
easat-5823	236	14	random	random	ADJ
easat-5823	236	15	forest	forest	NOUN
easat-5823	236	16	method	method	NOUN
easat-5823	236	17	using	use	VERB
easat-5823	236	18	several	several	ADJ
easat-5823	236	19	metrics	metric	NOUN
easat-5823	236	20	that	that	PRON
easat-5823	236	21	includes	include	VERB
easat-5823	236	22	accuracy	accuracy	NOUN
easat-5823	236	23	,	,	PUNCT
easat-5823	236	24	precision	precision	NOUN
easat-5823	236	25	,	,	PUNCT
easat-5823	236	26	recall	recall	NOUN
easat-5823	236	27	and	and	CCONJ
easat-5823	236	28	f1	f1	PROPN
easat-5823	236	29	score	score	NOUN
easat-5823	236	30	.	.	PUNCT
easat-5823	237	1	the	the	DET
easat-5823	237	2	result	result	NOUN
easat-5823	237	3	of	of	ADP
easat-5823	237	4	the	the	DET
easat-5823	237	5	research	research	NOUN
easat-5823	237	6	concluded	conclude	VERB
easat-5823	237	7	that	that	SCONJ
easat-5823	237	8	the	the	DET
easat-5823	237	9	proposed	propose	VERB
easat-5823	237	10	mlp	mlp	NOUN
easat-5823	237	11	–	–	PUNCT
easat-5823	237	12	rf	rf	NOUN
easat-5823	237	13	method	method	NOUN
easat-5823	237	14	achieved	achieve	VERB
easat-5823	237	15	the	the	DET
easat-5823	237	16	best	good	ADJ
easat-5823	237	17	result	result	NOUN
easat-5823	237	18	with	with	ADP
easat-5823	237	19	an	an	DET
easat-5823	237	20	exceptional	exceptional	ADJ
easat-5823	237	21	2493	2493	NUM
easat-5823	237	22	edelweiss	edelweiss	PROPN
easat-5823	237	23	applied	apply	VERB
easat-5823	237	24	science	science	NOUN
easat-5823	237	25	and	and	CCONJ
easat-5823	237	26	technology	technology	NOUN
easat-5823	237	27	issn	issn	PROPN
easat-5823	237	28	:	:	PUNCT
easat-5823	237	29	2576	2576	NUM
easat-5823	237	30	-	-	SYM
easat-5823	237	31	8484	8484	NUM
easat-5823	237	32	vol	vol	NOUN
easat-5823	237	33	.	.	PROPN
easat-5823	238	1	9	9	NUM
easat-5823	238	2	,	,	PUNCT
easat-5823	238	3	no	no	INTJ
easat-5823	238	4	.	.	NOUN
easat-5823	238	5	3	3	NUM
easat-5823	238	6	:	:	PUNCT
easat-5823	238	7	2482	2482	NUM
easat-5823	238	8	-	-	SYM
easat-5823	238	9	2494	2494	NUM
easat-5823	238	10	,	,	PUNCT
easat-5823	238	11	2025	2025	NUM
easat-5823	238	12	doi	doi	NOUN
easat-5823	238	13	:	:	PUNCT
easat-5823	238	14	10.55214/25768484.v9i3.5823	10.55214/25768484.v9i3.5823	NUM
easat-5823	238	15	©	©	PROPN
easat-5823	238	16	2025	2025	NUM
easat-5823	238	17	by	by	ADP
easat-5823	238	18	the	the	DET
easat-5823	238	19	authors	author	NOUN
easat-5823	238	20	;	;	PUNCT
easat-5823	238	21	licensee	licensee	PROPN
easat-5823	238	22	learning	learn	VERB
easat-5823	238	23	gate	gate	PROPN
easat-5823	238	24	accuracy	accuracy	NOUN
easat-5823	238	25	of	of	ADP
easat-5823	238	26	99.949	99.949	NUM
easat-5823	238	27	%	%	NOUN
easat-5823	238	28	,	,	PUNCT
easat-5823	238	29	great	great	ADJ
easat-5823	238	30	precision	precision	NOUN
easat-5823	238	31	of	of	ADP
easat-5823	238	32	87.097	87.097	NUM
easat-5823	238	33	%	%	NOUN
easat-5823	238	34	,	,	PUNCT
easat-5823	238	35	good	good	ADJ
easat-5823	238	36	recall	recall	NOUN
easat-5823	238	37	of	of	ADP
easat-5823	238	38	82.653	82.653	NUM
easat-5823	238	39	%	%	NOUN
easat-5823	238	40	and	and	CCONJ
easat-5823	238	41	great	great	ADJ
easat-5823	238	42	f1	f1	ADJ
easat-5823	238	43	score	score	NOUN
easat-5823	238	44	of	of	ADP
easat-5823	238	45	84.817	84.817	NUM
easat-5823	238	46	%	%	NOUN
easat-5823	238	47	.	.	PUNCT
easat-5823	239	1	these	these	DET
easat-5823	239	2	results	result	NOUN
easat-5823	239	3	indicated	indicate	VERB
easat-5823	239	4	that	that	SCONJ
easat-5823	239	5	the	the	DET
easat-5823	239	6	proposed	propose	VERB
easat-5823	239	7	mlp	mlp	NOUN
easat-5823	239	8	–	–	PUNCT
easat-5823	239	9	rf	rf	NOUN
easat-5823	239	10	method	method	NOUN
easat-5823	239	11	was	be	AUX
easat-5823	239	12	able	able	ADJ
easat-5823	239	13	to	to	PART
easat-5823	239	14	balance	balance	VERB
easat-5823	239	15	the	the	DET
easat-5823	239	16	detection	detection	NOUN
easat-5823	239	17	of	of	ADP
easat-5823	239	18	fraudulent	fraudulent	ADJ
easat-5823	239	19	transactions	transaction	NOUN
easat-5823	239	20	with	with	ADP
easat-5823	239	21	minimum	minimum	ADJ
easat-5823	239	22	false	false	ADJ
easat-5823	239	23	positives	positive	NOUN
easat-5823	239	24	,	,	PUNCT
easat-5823	239	25	which	which	PRON
easat-5823	239	26	is	be	AUX
easat-5823	239	27	critical	critical	ADJ
easat-5823	239	28	in	in	ADP
easat-5823	239	29	fraud	fraud	NOUN
easat-5823	239	30	detection	detection	NOUN
easat-5823	239	31	systems	system	NOUN
easat-5823	239	32	.	.	PUNCT
easat-5823	240	1	this	this	DET
easat-5823	240	2	research	research	NOUN
easat-5823	240	3	demonstrated	demonstrate	VERB
easat-5823	240	4	the	the	DET
easat-5823	240	5	potential	potential	NOUN
easat-5823	240	6	of	of	ADP
easat-5823	240	7	hybrid	hybrid	ADJ
easat-5823	240	8	machine	machine	NOUN
easat-5823	240	9	learning	learning	NOUN
easat-5823	240	10	models	model	NOUN
easat-5823	240	11	in	in	ADP
easat-5823	240	12	addressing	address	VERB
easat-5823	240	13	real	real	ADJ
easat-5823	240	14	-	-	PUNCT
easat-5823	240	15	world	world	NOUN
easat-5823	240	16	challenges	challenge	NOUN
easat-5823	240	17	in	in	ADP
easat-5823	240	18	fraud	fraud	NOUN
easat-5823	240	19	detection	detection	NOUN
easat-5823	240	20	,	,	PUNCT
easat-5823	240	21	opening	open	VERB
easat-5823	240	22	up	up	ADP
easat-5823	240	23	further	further	ADJ
easat-5823	240	24	advancement	advancement	NOUN
easat-5823	240	25	in	in	ADP
easat-5823	240	26	this	this	DET
easat-5823	240	27	field	field	NOUN
easat-5823	240	28	.	.	PUNCT
easat-5823	241	1	transparency	transparency	NOUN
easat-5823	241	2	:	:	PUNCT
easat-5823	241	3	the	the	DET
easat-5823	241	4	authors	author	NOUN
easat-5823	241	5	confirm	confirm	VERB
easat-5823	241	6	that	that	SCONJ
easat-5823	241	7	the	the	DET
easat-5823	241	8	manuscript	manuscript	NOUN
easat-5823	241	9	is	be	AUX
easat-5823	241	10	an	an	DET
easat-5823	241	11	honest	honest	ADJ
easat-5823	241	12	,	,	PUNCT
easat-5823	241	13	accurate	accurate	ADJ
easat-5823	241	14	,	,	PUNCT
easat-5823	241	15	and	and	CCONJ
easat-5823	241	16	transparent	transparent	ADJ
easat-5823	241	17	account	account	NOUN
easat-5823	241	18	of	of	ADP
easat-5823	241	19	the	the	DET
easat-5823	241	20	study	study	NOUN
easat-5823	241	21	;	;	PUNCT
easat-5823	241	22	that	that	SCONJ
easat-5823	241	23	no	no	DET
easat-5823	241	24	vital	vital	ADJ
easat-5823	241	25	features	feature	NOUN
easat-5823	241	26	of	of	ADP
easat-5823	241	27	the	the	DET
easat-5823	241	28	study	study	NOUN
easat-5823	241	29	have	have	AUX
easat-5823	241	30	been	be	AUX
easat-5823	241	31	omitted	omit	VERB
easat-5823	241	32	;	;	PUNCT
easat-5823	241	33	and	and	CCONJ
easat-5823	241	34	that	that	SCONJ
easat-5823	241	35	any	any	DET
easat-5823	241	36	discrepancies	discrepancy	NOUN
easat-5823	241	37	from	from	ADP
easat-5823	241	38	the	the	DET
easat-5823	241	39	study	study	NOUN
easat-5823	241	40	as	as	SCONJ
easat-5823	241	41	planned	plan	VERB
easat-5823	241	42	have	have	AUX
easat-5823	241	43	been	be	AUX
easat-5823	241	44	explained	explain	VERB
easat-5823	241	45	.	.	PUNCT
easat-5823	242	1	this	this	DET
easat-5823	242	2	study	study	NOUN
easat-5823	242	3	followed	follow	VERB
easat-5823	242	4	all	all	DET
easat-5823	242	5	ethical	ethical	ADJ
easat-5823	242	6	practices	practice	NOUN
easat-5823	242	7	during	during	ADP
easat-5823	242	8	writing	writing	NOUN
easat-5823	242	9	.	.	PUNCT
easat-5823	243	1	copyright	copyright	NOUN
easat-5823	243	2	:	:	PUNCT
easat-5823	243	3	©	©	PROPN
easat-5823	243	4	2025	2025	NUM
easat-5823	243	5	by	by	ADP
easat-5823	243	6	the	the	DET
easat-5823	243	7	authors	author	NOUN
easat-5823	243	8	.	.	PUNCT
easat-5823	244	1	this	this	DET
easat-5823	244	2	open	open	ADJ
easat-5823	244	3	-	-	PUNCT
easat-5823	244	4	access	access	NOUN
easat-5823	244	5	article	article	NOUN
easat-5823	244	6	is	be	AUX
easat-5823	244	7	distributed	distribute	VERB
easat-5823	244	8	under	under	ADP
easat-5823	244	9	the	the	DET
easat-5823	244	10	terms	term	NOUN
easat-5823	244	11	and	and	CCONJ
easat-5823	244	12	conditions	condition	NOUN
easat-5823	244	13	of	of	ADP
easat-5823	244	14	the	the	DET
easat-5823	244	15	creative	creative	ADJ
easat-5823	244	16	commons	common	NOUN
easat-5823	244	17	attribution	attribution	NOUN
easat-5823	244	18	(	(	PUNCT
easat-5823	244	19	cc	cc	NOUN
easat-5823	244	20	by	by	ADP
easat-5823	244	21	)	)	PUNCT
easat-5823	244	22	license	license	NOUN
easat-5823	244	23	(	(	PUNCT
easat-5823	244	24	https://creativecommons.org/licenses/by/4.0/	https://creativecommons.org/licenses/by/4.0/	PROPN
easat-5823	244	25	)	)	PUNCT
easat-5823	244	26	.	.	PUNCT
easat-5823	245	1	references	reference	NOUN
easat-5823	245	2	[	[	X
easat-5823	245	3	1	1	NUM
easat-5823	245	4	]	]	PUNCT
easat-5823	245	5	precedence	precedence	NOUN
easat-5823	245	6	research	research	NOUN
easat-5823	245	7	,	,	PUNCT
easat-5823	245	8	"	"	PUNCT
easat-5823	245	9	credit	credit	NOUN
easat-5823	245	10	card	card	NOUN
easat-5823	245	11	payments	payment	NOUN
easat-5823	245	12	market	market	NOUN
easat-5823	245	13	size	size	NOUN
easat-5823	245	14	to	to	PART
easat-5823	245	15	hit	hit	VERB
easat-5823	245	16	usd	usd	PROPN
easat-5823	245	17	1,331.50	1,331.50	NUM
easat-5823	245	18	bn	bn	NOUN
easat-5823	245	19	by	by	ADP
easat-5823	245	20	2033	2033	NUM
easat-5823	245	21	.	.	PUNCT
easat-5823	246	1	precedenceresearch.com	precedenceresearch.com	X
easat-5823	246	2	,	,	PUNCT
easat-5823	246	3	"	"	PUNCT
easat-5823	246	4	retrieved	retrieve	VERB
easat-5823	246	5	:	:	PUNCT
easat-5823	246	6	https://www.precedenceresearch.com/credit-card-payments-market	https://www.precedenceresearch.com/credit-card-payments-market	NOUN
easat-5823	246	7	,	,	PUNCT
easat-5823	246	8	2024	2024	NUM
easat-5823	246	9	.	.	PUNCT
easat-5823	247	1	[	[	X
easat-5823	247	2	2	2	NUM
easat-5823	247	3	]	]	PUNCT
easat-5823	247	4	m.	m.	NOUN
easat-5823	247	5	rej	rej	PROPN
easat-5823	247	6	,	,	PUNCT
easat-5823	247	7	"	"	PUNCT
easat-5823	247	8	credit	credit	NOUN
easat-5823	247	9	card	card	NOUN
easat-5823	247	10	fraud	fraud	NOUN
easat-5823	247	11	statistics	statistic	NOUN
easat-5823	247	12	(	(	PUNCT
easat-5823	247	13	2023	2023	NUM
easat-5823	247	14	)	)	PUNCT
easat-5823	247	15	|	|	ADV
easat-5823	247	16	merchant	merchant	NOUN
easat-5823	247	17	cost	cost	NOUN
easat-5823	247	18	consulting	consulting	NOUN
easat-5823	247	19	.	.	PUNCT
easat-5823	248	1	merchantcostconsulting.com	merchantcostconsulting.com	X
easat-5823	248	2	,	,	PUNCT
easat-5823	248	3	"	"	PUNCT
easat-5823	248	4	retrieved	retrieve	VERB
easat-5823	248	5	:	:	PUNCT
easat-5823	248	6	https://merchantcostconsulting.com/lower-credit-card-processing-fees/credit-card-fraud-statistics/	https://merchantcostconsulting.com/lower-credit-card-processing-fees/credit-card-fraud-statistics/	PROPN
easat-5823	248	7	,	,	PUNCT
easat-5823	248	8	2023	2023	NUM
easat-5823	248	9	.	.	PUNCT
easat-5823	249	1	[	[	X
easat-5823	249	2	3	3	X
easat-5823	249	3	]	]	X
easat-5823	249	4	r.	r.	PROPN
easat-5823	249	5	j.	j.	PROPN
easat-5823	249	6	bolton	bolton	PROPN
easat-5823	249	7	and	and	CCONJ
easat-5823	249	8	d.	d.	PROPN
easat-5823	249	9	j.	j.	PROPN
easat-5823	249	10	hand	hand	PROPN
easat-5823	249	11	,	,	PUNCT
easat-5823	249	12	"	"	PUNCT
easat-5823	249	13	statistical	statistical	ADJ
easat-5823	249	14	fraud	fraud	NOUN
easat-5823	249	15	detection	detection	NOUN
easat-5823	249	16	:	:	PUNCT
easat-5823	249	17	a	a	DET
easat-5823	249	18	review	review	NOUN
easat-5823	249	19	,	,	PUNCT
easat-5823	249	20	"	"	PUNCT
easat-5823	249	21	statistical	statistical	ADJ
easat-5823	249	22	science	science	NOUN
easat-5823	249	23	,	,	PUNCT
easat-5823	249	24	vol	vol	NOUN
easat-5823	249	25	.	.	PROPN
easat-5823	249	26	17	17	NUM
easat-5823	249	27	,	,	PUNCT
easat-5823	249	28	no	no	INTJ
easat-5823	249	29	.	.	NOUN
easat-5823	249	30	3	3	NUM
easat-5823	249	31	,	,	PUNCT
easat-5823	249	32	pp	pp	ADJ
easat-5823	249	33	.	.	PUNCT
easat-5823	250	1	235	235	NUM
easat-5823	250	2	-	-	SYM
easat-5823	250	3	255	255	NUM
easat-5823	250	4	,	,	PUNCT
easat-5823	250	5	2002	2002	NUM
easat-5823	250	6	.	.	PUNCT
easat-5823	251	1	https://doi.org/10.1214/ss/1042727940	https://doi.org/10.1214/ss/1042727940	NOUN
easat-5823	251	2	[	[	X
easat-5823	251	3	4	4	X
easat-5823	251	4	]	]	PUNCT
easat-5823	251	5	p.	p.	NOUN
easat-5823	251	6	t.	t.	PROPN
easat-5823	251	7	s.	s.	PROPN
easat-5823	251	8	ningsih	ningsih	PROPN
easat-5823	251	9	,	,	PUNCT
easat-5823	251	10	m.	m.	NOUN
easat-5823	251	11	gusvarizon	gusvarizon	NOUN
easat-5823	251	12	,	,	PUNCT
easat-5823	251	13	and	and	CCONJ
easat-5823	251	14	r.	r.	PROPN
easat-5823	251	15	hermawan	hermawan	NOUN
easat-5823	251	16	,	,	PUNCT
easat-5823	251	17	"	"	PUNCT
easat-5823	251	18	analysis	analysis	NOUN
easat-5823	251	19	of	of	ADP
easat-5823	251	20	credit	credit	NOUN
easat-5823	251	21	card	card	NOUN
easat-5823	251	22	transaction	transaction	NOUN
easat-5823	251	23	fraud	fraud	NOUN
easat-5823	251	24	detection	detection	NOUN
easat-5823	251	25	system	system	NOUN
easat-5823	251	26	with	with	ADP
easat-5823	251	27	machine	machine	NOUN
easat-5823	251	28	learning	learning	NOUN
easat-5823	251	29	algorithm	algorithm	NOUN
easat-5823	251	30	,	,	PUNCT
easat-5823	251	31	"	"	PUNCT
easat-5823	251	32	jurnal	jurnal	ADJ
easat-5823	251	33	teknologi	teknologi	PROPN
easat-5823	251	34	informatika	informatika	PROPN
easat-5823	251	35	dan	dan	PROPN
easat-5823	251	36	komputer	komputer	PROPN
easat-5823	251	37	,	,	PUNCT
easat-5823	251	38	vol	vol	NOUN
easat-5823	251	39	.	.	PROPN
easat-5823	251	40	8	8	NUM
easat-5823	251	41	,	,	PUNCT
easat-5823	251	42	no	no	INTJ
easat-5823	251	43	.	.	NOUN
easat-5823	251	44	2	2	NUM
easat-5823	251	45	,	,	PUNCT
easat-5823	251	46	pp	pp	ADJ
easat-5823	251	47	.	.	PUNCT
easat-5823	252	1	386	386	NUM
easat-5823	252	2	-	-	SYM
easat-5823	252	3	401	401	NUM
easat-5823	252	4	,	,	PUNCT
easat-5823	252	5	2022	2022	NUM
easat-5823	252	6	.	.	PUNCT
easat-5823	253	1	https://doi.org/10.37012/jtik.v8i2.1306	https://doi.org/10.37012/jtik.v8i2.1306	X
easat-5823	254	1	[	[	X
easat-5823	254	2	5	5	NUM
easat-5823	254	3	]	]	PUNCT
easat-5823	254	4	z.	z.	PROPN
easat-5823	254	5	zhu	zhu	PROPN
easat-5823	254	6	,	,	PUNCT
easat-5823	254	7	q.	q.	PROPN
easat-5823	254	8	zhao	zhao	PROPN
easat-5823	254	9	,	,	PUNCT
easat-5823	254	10	j.	j.	PROPN
easat-5823	254	11	wang	wang	PROPN
easat-5823	254	12	,	,	PUNCT
easat-5823	254	13	and	and	CCONJ
easat-5823	254	14	a.	a.	PROPN
easat-5823	254	15	yang	yang	PROPN
easat-5823	254	16	,	,	PUNCT
easat-5823	254	17	a	a	DET
easat-5823	254	18	comparative	comparative	ADJ
easat-5823	254	19	study	study	NOUN
easat-5823	254	20	of	of	ADP
easat-5823	254	21	machine	machine	NOUN
easat-5823	254	22	learning	learning	NOUN
easat-5823	254	23	methods	method	NOUN
easat-5823	254	24	.	.	PUNCT
easat-5823	255	1	atlantis	atlantis	PROPN
easat-5823	255	2	press	press	PROPN
easat-5823	255	3	international	international	PROPN
easat-5823	255	4	bv	bv	PROPN
easat-5823	255	5	.	.	PROPN
easat-5823	255	6	https://doi.org/10.2991/978-94-6463-546-1	https://doi.org/10.2991/978-94-6463-546-1	PROPN
easat-5823	255	7	,	,	PUNCT
easat-5823	255	8	2024	2024	NUM
easat-5823	255	9	.	.	PUNCT
easat-5823	256	1	[	[	X
easat-5823	256	2	6	6	NUM
easat-5823	256	3	]	]	X
easat-5823	256	4	d.	d.	PROPN
easat-5823	256	5	varmedja	varmedja	PROPN
easat-5823	256	6	,	,	PUNCT
easat-5823	256	7	m.	m.	PROPN
easat-5823	256	8	karanovic	karanovic	PROPN
easat-5823	256	9	,	,	PUNCT
easat-5823	256	10	s.	s.	PROPN
easat-5823	256	11	sladojevic	sladojevic	PROPN
easat-5823	256	12	,	,	PUNCT
easat-5823	256	13	m.	m.	NOUN
easat-5823	256	14	arsenovic	arsenovic	ADJ
easat-5823	256	15	,	,	PUNCT
easat-5823	256	16	and	and	CCONJ
easat-5823	256	17	a.	a.	PROPN
easat-5823	256	18	anderla	anderla	PROPN
easat-5823	256	19	,	,	PUNCT
easat-5823	256	20	"	"	PUNCT
easat-5823	256	21	credit	credit	NOUN
easat-5823	256	22	card	card	NOUN
easat-5823	256	23	fraud	fraud	NOUN
easat-5823	256	24	detection	detection	NOUN
easat-5823	256	25	machine	machine	NOUN
easat-5823	256	26	learning	learning	NOUN
easat-5823	256	27	methods	method	NOUN
easat-5823	256	28	,	,	PUNCT
easat-5823	256	29	"	"	PUNCT
easat-5823	256	30	in	in	ADP
easat-5823	256	31	2019	2019	NUM
easat-5823	256	32	18th	18th	ADJ
easat-5823	256	33	international	international	ADJ
easat-5823	256	34	symposium	symposium	NOUN
easat-5823	256	35	infoteh	infoteh	NOUN
easat-5823	256	36	-	-	PUNCT
easat-5823	256	37	jahorina	jahorina	PROPN
easat-5823	256	38	(	(	PUNCT
easat-5823	256	39	infoteh	infoteh	NOUN
easat-5823	256	40	2019	2019	NUM
easat-5823	256	41	)	)	PUNCT
easat-5823	256	42	proceedings	proceeding	NOUN
easat-5823	256	43	.	.	PUNCT
easat-5823	257	1	https://doi.org/10.1109/infoteh.2019.8717766	https://doi.org/10.1109/infoteh.2019.8717766	PROPN
easat-5823	257	2	,	,	PUNCT
easat-5823	257	3	2019	2019	NUM
easat-5823	257	4	.	.	PUNCT
easat-5823	258	1	[	[	X
easat-5823	258	2	7	7	X
easat-5823	258	3	]	]	X
easat-5823	258	4	i.	i.	NOUN
easat-5823	258	5	sadgali	sadgali	PROPN
easat-5823	258	6	,	,	PUNCT
easat-5823	258	7	n.	n.	PROPN
easat-5823	258	8	sael	sael	PROPN
easat-5823	258	9	,	,	PUNCT
easat-5823	258	10	and	and	CCONJ
easat-5823	258	11	f.	f.	PROPN
easat-5823	258	12	benabbou	benabbou	PROPN
easat-5823	258	13	,	,	PUNCT
easat-5823	258	14	"	"	PUNCT
easat-5823	258	15	fraud	fraud	NOUN
easat-5823	258	16	detection	detection	NOUN
easat-5823	258	17	in	in	ADP
easat-5823	258	18	credit	credit	NOUN
easat-5823	258	19	card	card	NOUN
easat-5823	258	20	transaction	transaction	NOUN
easat-5823	258	21	using	use	VERB
easat-5823	258	22	neural	neural	ADJ
easat-5823	258	23	networks	network	NOUN
easat-5823	258	24	,	,	PUNCT
easat-5823	258	25	"	"	PUNCT
easat-5823	258	26	in	in	ADP
easat-5823	258	27	acm	acm	PROPN
easat-5823	258	28	international	international	PROPN
easat-5823	258	29	conference	conference	PROPN
easat-5823	258	30	proceeding	proceeding	NOUN
easat-5823	258	31	series	series	PROPN
easat-5823	258	32	.	.	PUNCT
easat-5823	259	1	https://doi.org/10.1145/3368756.3369082	https://doi.org/10.1145/3368756.3369082	PROPN
easat-5823	259	2	,	,	PUNCT
easat-5823	259	3	2019	2019	NUM
easat-5823	259	4	,	,	PUNCT
easat-5823	259	5	pp	pp	ADJ
easat-5823	259	6	.	.	PUNCT
easat-5823	260	1	1	1	NUM
easat-5823	260	2	-	-	SYM
easat-5823	260	3	4	4	NUM
easat-5823	260	4	.	.	PUNCT
easat-5823	261	1	[	[	X
easat-5823	261	2	8	8	X
easat-5823	261	3	]	]	PUNCT
easat-5823	261	4	j.	j.	PROPN
easat-5823	261	5	p.	p.	PROPN
easat-5823	261	6	a.	a.	PROPN
easat-5823	261	7	andrade	andrade	PROPN
easat-5823	261	8	et	et	PROPN
easat-5823	261	9	al	al	PROPN
easat-5823	261	10	.	.	PROPN
easat-5823	261	11	,	,	PUNCT
easat-5823	261	12	"	"	PUNCT
easat-5823	261	13	a	a	DET
easat-5823	261	14	machine	machine	NOUN
easat-5823	261	15	learning	learning	NOUN
easat-5823	261	16	-	-	PUNCT
easat-5823	261	17	based	base	VERB
easat-5823	261	18	system	system	NOUN
easat-5823	261	19	for	for	ADP
easat-5823	261	20	financial	financial	ADJ
easat-5823	261	21	fraud	fraud	NOUN
easat-5823	261	22	detection	detection	NOUN
easat-5823	261	23	,	,	PUNCT
easat-5823	261	24	"	"	PUNCT
easat-5823	261	25	in	in	ADP
easat-5823	261	26	encontro	encontro	ADJ
easat-5823	261	27	nacional	nacional	ADJ
easat-5823	261	28	de	de	X
easat-5823	261	29	inteligência	inteligência	PROPN
easat-5823	261	30	artificial	artificial	PROPN
easat-5823	261	31	e	e	X
easat-5823	261	32	computacional	computacional	X
easat-5823	261	33	(	(	PUNCT
easat-5823	261	34	eniac	eniac	PROPN
easat-5823	261	35	)	)	PUNCT
easat-5823	261	36	,	,	PUNCT
easat-5823	261	37	2021	2021	NUM
easat-5823	261	38	:	:	PUNCT
easat-5823	261	39	sbc	sbc	NOUN
easat-5823	261	40	,	,	PUNCT
easat-5823	261	41	pp	pp	ADJ
easat-5823	261	42	.	.	PUNCT
easat-5823	262	1	165	165	NUM
easat-5823	262	2	-	-	SYM
easat-5823	262	3	176	176	NUM
easat-5823	262	4	.	.	PUNCT
easat-5823	263	1	[	[	X
easat-5823	263	2	9	9	NUM
easat-5823	263	3	]	]	X
easat-5823	263	4	g.	g.	PROPN
easat-5823	263	5	e.	e.	PROPN
easat-5823	263	6	hinton	hinton	PROPN
easat-5823	263	7	,	,	PUNCT
easat-5823	263	8	s.	s.	PROPN
easat-5823	263	9	osindero	osindero	PROPN
easat-5823	263	10	,	,	PUNCT
easat-5823	263	11	and	and	CCONJ
easat-5823	263	12	y.	y.	PROPN
easat-5823	263	13	w.	w.	PROPN
easat-5823	263	14	teh	teh	PROPN
easat-5823	263	15	,	,	PUNCT
easat-5823	263	16	"	"	PUNCT
easat-5823	263	17	a	a	DET
easat-5823	263	18	fast	fast	ADJ
easat-5823	263	19	learning	learning	NOUN
easat-5823	263	20	algorithm	algorithm	NOUN
easat-5823	263	21	for	for	ADP
easat-5823	263	22	deep	deep	ADJ
easat-5823	263	23	belief	belief	NOUN
easat-5823	263	24	nets	net	NOUN
easat-5823	263	25	,	,	PUNCT
easat-5823	263	26	"	"	PUNCT
easat-5823	263	27	neural	neural	ADJ
easat-5823	263	28	computation	computation	NOUN
easat-5823	263	29	,	,	PUNCT
easat-5823	263	30	vol	vol	NOUN
easat-5823	263	31	.	.	PROPN
easat-5823	263	32	18	18	NUM
easat-5823	263	33	,	,	PUNCT
easat-5823	263	34	no	no	INTJ
easat-5823	263	35	.	.	NOUN
easat-5823	263	36	7	7	NUM
easat-5823	263	37	,	,	PUNCT
easat-5823	263	38	pp	pp	ADJ
easat-5823	263	39	.	.	PUNCT
easat-5823	264	1	1527–1554	1527–1554	NUM
easat-5823	264	2	,	,	PUNCT
easat-5823	264	3	2006	2006	NUM
easat-5823	264	4	.	.	PUNCT
easat-5823	265	1	https://doi.org/10.1162/neco.2006.18.7.1527	https://doi.org/10.1162/neco.2006.18.7.1527	PROPN
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easat-5823	266	2	10	10	NUM
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easat-5823	266	4	s.	s.	PROPN
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easat-5823	266	6	and	and	CCONJ
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easat-5823	266	9	,	,	PUNCT
easat-5823	266	10	"	"	PUNCT
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easat-5823	266	12	of	of	ADP
easat-5823	266	13	fraud	fraud	NOUN
easat-5823	266	14	card	card	NOUN
easat-5823	266	15	and	and	CCONJ
easat-5823	266	16	data	datum	NOUN
easat-5823	266	17	breaches	breach	NOUN
easat-5823	266	18	in	in	ADP
easat-5823	266	19	credit	credit	NOUN
easat-5823	266	20	card	card	NOUN
easat-5823	266	21	transactions	transaction	NOUN
easat-5823	266	22	,	,	PUNCT
easat-5823	266	23	"	"	PUNCT
easat-5823	266	24	international	international	ADJ
easat-5823	266	25	journal	journal	NOUN
easat-5823	266	26	of	of	ADP
easat-5823	266	27	science	science	NOUN
easat-5823	266	28	and	and	CCONJ
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easat-5823	266	39	,	,	PUNCT
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easat-5823	266	41	.	.	PUNCT
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easat-5823	267	2	-	-	SYM
easat-5823	267	3	582	582	NUM
easat-5823	267	4	,	,	PUNCT
easat-5823	267	5	2023	2023	NUM
easat-5823	267	6	.	.	PUNCT
easat-5823	268	1	https://doi.org/10.30574/ijsra.2023.9.2.0603	https://doi.org/10.30574/ijsra.2023.9.2.0603	NOUN
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easat-5823	269	2	11	11	NUM
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easat-5823	269	6	,	,	PUNCT
easat-5823	269	7	m.	m.	NOUN
easat-5823	269	8	agrawal	agrawal	PROPN
easat-5823	269	9	,	,	PUNCT
easat-5823	269	10	and	and	CCONJ
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easat-5823	269	13	,	,	PUNCT
easat-5823	269	14	"	"	PUNCT
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easat-5823	269	16	analysis	analysis	NOUN
easat-5823	269	17	of	of	ADP
easat-5823	269	18	machine	machine	NOUN
easat-5823	269	19	learning	learn	VERB
easat-5823	269	20	algorithms	algorithm	NOUN
easat-5823	269	21	in	in	ADP
easat-5823	269	22	credit	credit	NOUN
easat-5823	269	23	cards	card	NOUN
easat-5823	269	24	fraud	fraud	NOUN
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easat-5823	269	26	,	,	PUNCT
easat-5823	269	27	"	"	PUNCT
easat-5823	269	28	in	in	ADP
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easat-5823	269	30	8th	8th	ADJ
easat-5823	269	31	international	international	ADJ
easat-5823	269	32	conference	conference	NOUN
easat-5823	269	33	on	on	ADP
easat-5823	269	34	reliability	reliability	NOUN
easat-5823	269	35	,	,	PUNCT
easat-5823	269	36	infocom	infocom	NOUN
easat-5823	269	37	technologies	technology	NOUN
easat-5823	269	38	and	and	CCONJ
easat-5823	269	39	optimization	optimization	NOUN
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easat-5823	269	41	trends	trend	NOUN
easat-5823	269	42	and	and	CCONJ
easat-5823	269	43	future	future	ADJ
easat-5823	269	44	directions)(icrito	directions)(icrito	PROPN
easat-5823	269	45	)	)	PUNCT
easat-5823	269	46	,	,	PUNCT
easat-5823	269	47	2020	2020	NUM
easat-5823	269	48	:	:	PUNCT
easat-5823	269	49	ieee	ieee	NOUN
easat-5823	269	50	,	,	PUNCT
easat-5823	269	51	pp	pp	ADJ
easat-5823	269	52	.	.	PUNCT
easat-5823	270	1	86	86	NUM
easat-5823	270	2	-	-	SYM
easat-5823	270	3	88	88	NUM
easat-5823	270	4	.	.	PUNCT
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easat-5823	271	2	12	12	NUM
easat-5823	271	3	]	]	PUNCT
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easat-5823	271	5	m.	m.	NOUN
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easat-5823	271	8	a.	a.	NOUN
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easat-5823	271	13	card	card	NOUN
easat-5823	271	14	fraud	fraud	NOUN
easat-5823	271	15	detection	detection	NOUN
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easat-5823	271	17	deep	deep	ADJ
easat-5823	271	18	learning	learning	NOUN
easat-5823	271	19	,	,	PUNCT
easat-5823	271	20	"	"	PUNCT
easat-5823	271	21	in	in	ADP
easat-5823	271	22	2020	2020	NUM
easat-5823	271	23	ieee	ieee	NOUN
easat-5823	271	24	recent	recent	ADJ
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easat-5823	271	26	in	in	ADP
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easat-5823	271	30	(	(	PUNCT
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easat-5823	271	33	,	,	PUNCT
easat-5823	271	34	2020	2020	NUM
easat-5823	271	35	:	:	PUNCT
easat-5823	271	36	ieee	ieee	NOUN
easat-5823	271	37	,	,	PUNCT
easat-5823	271	38	pp	pp	ADJ
easat-5823	271	39	.	.	PUNCT
easat-5823	272	1	32	32	NUM
easat-5823	272	2	-	-	SYM
easat-5823	272	3	36	36	NUM
easat-5823	272	4	.	.	PUNCT
easat-5823	273	1	[	[	X
easat-5823	273	2	13	13	NUM
easat-5823	273	3	]	]	PUNCT
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easat-5823	273	35	"	"	PUNCT
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easat-5823	273	37	journal	journal	NOUN
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easat-5823	273	45	and	and	CCONJ
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easat-5823	273	47	,	,	PUNCT
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easat-5823	273	49	.	.	PUNCT
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easat-5823	275	7	s.	s.	PROPN
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easat-5823	275	10	k.	k.	PROPN
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easat-5823	277	2	-	-	SYM
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easat-5823	280	2	-	-	SYM
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easat-5823	283	46	.	.	PUNCT
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