id	sid	tid	token	lemma	pos
ajase-2385	1	1	pa	pa	PROPN
ajase-2385	1	2	ge	ge	PROPN
ajase-2385	1	3	1	1	NUM
ajase-2385	1	4	pa	pa	PROPN
ajase-2385	1	5	ge	ge	PROPN
ajase-2385	1	6	51	51	NUM
ajase-2385	1	7	american	american	PROPN
ajase-2385	1	8	journal	journal	PROPN
ajase-2385	1	9	of	of	ADP
ajase-2385	1	10	applied	apply	VERB
ajase-2385	1	11	statistics	statistic	NOUN
ajase-2385	1	12	and	and	CCONJ
ajase-2385	1	13	economics	economic	NOUN
ajase-2385	1	14	(	(	PUNCT
ajase-2385	1	15	ajase	ajase	ADJ
ajase-2385	1	16	)	)	PUNCT
ajase-2385	1	17	evaluating	evaluate	VERB
ajase-2385	1	18	the	the	DET
ajase-2385	1	19	efficacy	efficacy	NOUN
ajase-2385	1	20	of	of	ADP
ajase-2385	1	21	supervised	supervised	ADJ
ajase-2385	1	22	machine	machine	NOUN
ajase-2385	1	23	learning	learning	NOUN
ajase-2385	1	24	models	model	NOUN
ajase-2385	1	25	in	in	ADP
ajase-2385	1	26	inflation	inflation	NOUN
ajase-2385	1	27	forecasting	forecasting	NOUN
ajase-2385	1	28	in	in	ADP
ajase-2385	1	29	sri	sri	PROPN
ajase-2385	1	30	lanka	lanka	PROPN
ajase-2385	1	31	w.	w.	PROPN
ajase-2385	1	32	m.	m.	PROPN
ajase-2385	1	33	s.	s.	PROPN
ajase-2385	1	34	bandara1	bandara1	PROPN
ajase-2385	1	35	*	*	PROPN
ajase-2385	1	36	,	,	PUNCT
ajase-2385	1	37	w.	w.	PROPN
ajase-2385	1	38	a.	a.	PROPN
ajase-2385	1	39	r.	r.	PROPN
ajase-2385	1	40	de	de	PROPN
ajase-2385	1	41	mel1	mel1	PROPN
ajase-2385	1	42	volume	volume	NOUN
ajase-2385	1	43	3	3	NUM
ajase-2385	1	44	issue	issue	NOUN
ajase-2385	1	45	1	1	NUM
ajase-2385	1	46	,	,	PUNCT
ajase-2385	1	47	year	year	NOUN
ajase-2385	1	48	2024	2024	NUM
ajase-2385	1	49	issn	issn	X
ajase-2385	1	50	:	:	PUNCT
ajase-2385	1	51	2992	2992	NUM
ajase-2385	1	52	-	-	PUNCT
ajase-2385	1	53	927x	927x	NOUN
ajase-2385	1	54	(	(	PUNCT
ajase-2385	1	55	online	online	ADJ
ajase-2385	1	56	)	)	PUNCT
ajase-2385	1	57	doi	doi	NOUN
ajase-2385	1	58	:	:	PUNCT
ajase-2385	1	59	https://doi.org/10.54536/ajase.v3i1.2385	https://doi.org/10.54536/ajase.v3i1.2385	PROPN
ajase-2385	1	60	https://journals.e-palli.com/home/index.php/ajase	https://journals.e-palli.com/home/index.php/ajase	PROPN
ajase-2385	1	61	article	article	NOUN
ajase-2385	1	62	information	information	NOUN
ajase-2385	1	63	abstract	abstract	ADV
ajase-2385	1	64	received	receive	VERB
ajase-2385	1	65	:	:	PUNCT
ajase-2385	1	66	january	january	PROPN
ajase-2385	1	67	01	01	NUM
ajase-2385	1	68	,	,	PUNCT
ajase-2385	1	69	2024	2024	NUM
ajase-2385	1	70	accepted	accept	VERB
ajase-2385	1	71	:	:	PUNCT
ajase-2385	1	72	february	february	PROPN
ajase-2385	1	73	09	09	NUM
ajase-2385	1	74	,	,	PUNCT
ajase-2385	1	75	2024	2024	NUM
ajase-2385	1	76	published	publish	VERB
ajase-2385	1	77	:	:	PUNCT
ajase-2385	1	78	february	february	PROPN
ajase-2385	1	79	12	12	NUM
ajase-2385	1	80	,	,	PUNCT
ajase-2385	1	81	2024	2024	NUM
ajase-2385	1	82	this	this	DET
ajase-2385	1	83	study	study	NOUN
ajase-2385	1	84	aims	aim	VERB
ajase-2385	1	85	to	to	PART
ajase-2385	1	86	forecast	forecast	VERB
ajase-2385	1	87	the	the	DET
ajase-2385	1	88	inflation	inflation	NOUN
ajase-2385	1	89	rate	rate	NOUN
ajase-2385	1	90	using	use	VERB
ajase-2385	1	91	supervised	supervised	ADJ
ajase-2385	1	92	machine	machine	NOUN
ajase-2385	1	93	learning	learning	NOUN
ajase-2385	1	94	models	model	NOUN
ajase-2385	1	95	(	(	PUNCT
ajase-2385	1	96	smlm	smlm	ADJ
ajase-2385	1	97	)	)	PUNCT
ajase-2385	1	98	.	.	PUNCT
ajase-2385	2	1	while	while	SCONJ
ajase-2385	2	2	smlms	smlm	NOUN
ajase-2385	2	3	are	be	AUX
ajase-2385	2	4	widely	widely	ADV
ajase-2385	2	5	used	use	VERB
ajase-2385	2	6	in	in	ADP
ajase-2385	2	7	various	various	ADJ
ajase-2385	2	8	fields	field	NOUN
ajase-2385	2	9	,	,	PUNCT
ajase-2385	2	10	they	they	PRON
ajase-2385	2	11	have	have	AUX
ajase-2385	2	12	not	not	PART
ajase-2385	2	13	been	be	AUX
ajase-2385	2	14	widely	widely	ADV
ajase-2385	2	15	applied	apply	VERB
ajase-2385	2	16	in	in	ADP
ajase-2385	2	17	forecasting	forecast	VERB
ajase-2385	2	18	inflation	inflation	NOUN
ajase-2385	2	19	rates	rate	NOUN
ajase-2385	2	20	.	.	PUNCT
ajase-2385	3	1	therefore	therefore	ADV
ajase-2385	3	2	,	,	PUNCT
ajase-2385	3	3	the	the	DET
ajase-2385	3	4	main	main	ADJ
ajase-2385	3	5	objective	objective	NOUN
ajase-2385	3	6	of	of	ADP
ajase-2385	3	7	this	this	DET
ajase-2385	3	8	study	study	NOUN
ajase-2385	3	9	is	be	AUX
ajase-2385	3	10	to	to	PART
ajase-2385	3	11	identify	identify	VERB
ajase-2385	3	12	the	the	DET
ajase-2385	3	13	best	good	ADJ
ajase-2385	3	14	model	model	NOUN
ajase-2385	3	15	for	for	ADP
ajase-2385	3	16	forecasting	forecast	VERB
ajase-2385	3	17	inflation	inflation	NOUN
ajase-2385	3	18	among	among	ADP
ajase-2385	3	19	four	four	NUM
ajase-2385	3	20	different	different	ADJ
ajase-2385	3	21	smlms	smlm	NOUN
ajase-2385	3	22	:	:	PUNCT
ajase-2385	3	23	lasso	lasso	NOUN
ajase-2385	3	24	regression	regression	NOUN
ajase-2385	3	25	(	(	PUNCT
ajase-2385	3	26	lr	lr	NOUN
ajase-2385	3	27	)	)	PUNCT
ajase-2385	3	28	,	,	PUNCT
ajase-2385	3	29	bayesian	bayesian	NOUN
ajase-2385	3	30	ridge	ridge	NOUN
ajase-2385	3	31	regression	regression	PROPN
ajase-2385	3	32	(	(	PUNCT
ajase-2385	3	33	brr	brr	NOUN
ajase-2385	3	34	)	)	PUNCT
ajase-2385	3	35	,	,	PUNCT
ajase-2385	3	36	support	support	NOUN
ajase-2385	3	37	vector	vector	NOUN
ajase-2385	3	38	machine	machine	NOUN
ajase-2385	3	39	regression	regression	NOUN
ajase-2385	3	40	(	(	PUNCT
ajase-2385	3	41	svr	svr	PROPN
ajase-2385	3	42	)	)	PUNCT
ajase-2385	3	43	,	,	PUNCT
ajase-2385	3	44	and	and	CCONJ
ajase-2385	3	45	random	random	ADJ
ajase-2385	3	46	forest	forest	NOUN
ajase-2385	3	47	regression	regression	NOUN
ajase-2385	3	48	(	(	PUNCT
ajase-2385	3	49	rfr	rfr	NOUN
ajase-2385	3	50	)	)	PUNCT
ajase-2385	3	51	models	model	NOUN
ajase-2385	3	52	.	.	PUNCT
ajase-2385	4	1	to	to	PART
ajase-2385	4	2	achieve	achieve	VERB
ajase-2385	4	3	this	this	DET
ajase-2385	4	4	objective	objective	NOUN
ajase-2385	4	5	,	,	PUNCT
ajase-2385	4	6	two	two	NUM
ajase-2385	4	7	different	different	ADJ
ajase-2385	4	8	types	type	NOUN
ajase-2385	4	9	of	of	ADP
ajase-2385	4	10	crossvalidation	crossvalidation	NOUN
ajase-2385	4	11	techniques	technique	NOUN
ajase-2385	4	12	were	be	AUX
ajase-2385	4	13	employed	employ	VERB
ajase-2385	4	14	:	:	PUNCT
ajase-2385	4	15	the	the	DET
ajase-2385	4	16	k	k	ADJ
ajase-2385	4	17	-	-	ADJ
ajase-2385	4	18	fold	fold	ADJ
ajase-2385	4	19	cross	cross	ADJ
ajase-2385	4	20	-	-	ADJ
ajase-2385	4	21	validation	validation	ADJ
ajase-2385	4	22	method	method	NOUN
ajase-2385	4	23	(	(	PUNCT
ajase-2385	4	24	cvk	cvk	ADJ
ajase-2385	4	25	)	)	PUNCT
ajase-2385	4	26	and	and	CCONJ
ajase-2385	4	27	walk	walk	VERB
ajase-2385	4	28	forward	forward	ADV
ajase-2385	4	29	validation	validation	NOUN
ajase-2385	4	30	(	(	PUNCT
ajase-2385	4	31	wfv	wfv	NOUN
ajase-2385	4	32	)	)	PUNCT
ajase-2385	4	33	methods	method	NOUN
ajase-2385	4	34	.	.	PUNCT
ajase-2385	5	1	these	these	DET
ajase-2385	5	2	techniques	technique	NOUN
ajase-2385	5	3	were	be	AUX
ajase-2385	5	4	used	use	VERB
ajase-2385	5	5	to	to	PART
ajase-2385	5	6	estimate	estimate	VERB
ajase-2385	5	7	the	the	DET
ajase-2385	5	8	parameters	parameter	NOUN
ajase-2385	5	9	and	and	CCONJ
ajase-2385	5	10	hyper	hyper	NOUN
ajase-2385	5	11	-	-	NOUN
ajase-2385	5	12	parameters	parameter	NOUN
ajase-2385	5	13	for	for	ADP
ajase-2385	5	14	each	each	DET
ajase-2385	5	15	machine	machine	NOUN
ajase-2385	5	16	learning	learn	VERB
ajase-2385	5	17	model	model	NOUN
ajase-2385	5	18	with	with	ADP
ajase-2385	5	19	root	root	NOUN
ajase-2385	5	20	mean	mean	ADJ
ajase-2385	5	21	square	square	NOUN
ajase-2385	5	22	error	error	NOUN
ajase-2385	5	23	.	.	PUNCT
ajase-2385	6	1	the	the	DET
ajase-2385	6	2	mean	mean	ADJ
ajase-2385	6	3	absolute	absolute	ADJ
ajase-2385	6	4	percentage	percentage	NOUN
ajase-2385	6	5	error	error	NOUN
ajase-2385	6	6	(	(	PUNCT
ajase-2385	6	7	mape	mape	NOUN
ajase-2385	6	8	)	)	PUNCT
ajase-2385	6	9	was	be	AUX
ajase-2385	6	10	used	use	VERB
ajase-2385	6	11	to	to	PART
ajase-2385	6	12	compare	compare	VERB
ajase-2385	6	13	the	the	DET
ajase-2385	6	14	performance	performance	NOUN
ajase-2385	6	15	of	of	ADP
ajase-2385	6	16	the	the	DET
ajase-2385	6	17	different	different	ADJ
ajase-2385	6	18	smlms	smlm	NOUN
ajase-2385	6	19	.	.	PUNCT
ajase-2385	7	1	empirical	empirical	ADJ
ajase-2385	7	2	evidence	evidence	NOUN
ajase-2385	7	3	from	from	ADP
ajase-2385	7	4	sri	sri	PROPN
ajase-2385	7	5	lanka	lanka	PROPN
ajase-2385	7	6	between	between	ADP
ajase-2385	7	7	1988	1988	NUM
ajase-2385	7	8	and	and	CCONJ
ajase-2385	7	9	2021	2021	NUM
ajase-2385	7	10	was	be	AUX
ajase-2385	7	11	used	use	VERB
ajase-2385	7	12	to	to	PART
ajase-2385	7	13	test	test	VERB
ajase-2385	7	14	the	the	DET
ajase-2385	7	15	performance	performance	NOUN
ajase-2385	7	16	of	of	ADP
ajase-2385	7	17	the	the	DET
ajase-2385	7	18	smlms	smlm	NOUN
ajase-2385	7	19	in	in	ADP
ajase-2385	7	20	forecasting	forecast	VERB
ajase-2385	7	21	inflation	inflation	NOUN
ajase-2385	7	22	rates	rate	NOUN
ajase-2385	7	23	.	.	PUNCT
ajase-2385	8	1	the	the	DET
ajase-2385	8	2	results	result	NOUN
ajase-2385	8	3	show	show	VERB
ajase-2385	8	4	that	that	SCONJ
ajase-2385	8	5	the	the	DET
ajase-2385	8	6	svr	svr	PROPN
ajase-2385	8	7	model	model	NOUN
ajase-2385	8	8	with	with	ADP
ajase-2385	8	9	walk	walk	VERB
ajase-2385	8	10	-	-	PUNCT
ajase-2385	8	11	forward	forward	ADP
ajase-2385	8	12	validation	validation	NOUN
ajase-2385	8	13	is	be	AUX
ajase-2385	8	14	the	the	DET
ajase-2385	8	15	best	good	ADJ
ajase-2385	8	16	method	method	NOUN
ajase-2385	8	17	for	for	ADP
ajase-2385	8	18	forecasting	forecast	VERB
ajase-2385	8	19	the	the	DET
ajase-2385	8	20	future	future	ADJ
ajase-2385	8	21	inflation	inflation	NOUN
ajase-2385	8	22	rate	rate	NOUN
ajase-2385	8	23	of	of	ADP
ajase-2385	8	24	sri	sri	PROPN
ajase-2385	8	25	lanka	lanka	PROPN
ajase-2385	8	26	based	base	VERB
ajase-2385	8	27	on	on	ADP
ajase-2385	8	28	the	the	DET
ajase-2385	8	29	mape	mape	NOUN
ajase-2385	8	30	value	value	NOUN
ajase-2385	8	31	.	.	PUNCT
ajase-2385	9	1	overall	overall	ADV
ajase-2385	9	2	,	,	PUNCT
ajase-2385	9	3	this	this	DET
ajase-2385	9	4	study	study	NOUN
ajase-2385	9	5	showcases	showcase	VERB
ajase-2385	9	6	the	the	DET
ajase-2385	9	7	effectiveness	effectiveness	NOUN
ajase-2385	9	8	of	of	ADP
ajase-2385	9	9	supervised	supervised	ADJ
ajase-2385	9	10	machine	machine	NOUN
ajase-2385	9	11	learning	learning	NOUN
ajase-2385	9	12	models	model	NOUN
ajase-2385	9	13	(	(	PUNCT
ajase-2385	9	14	smlms	smlm	NOUN
ajase-2385	9	15	)	)	PUNCT
ajase-2385	9	16	in	in	ADP
ajase-2385	9	17	forecasting	forecast	VERB
ajase-2385	9	18	inflation	inflation	NOUN
ajase-2385	9	19	rates	rate	NOUN
ajase-2385	9	20	,	,	PUNCT
ajase-2385	9	21	emphasizing	emphasize	VERB
ajase-2385	9	22	the	the	DET
ajase-2385	9	23	critical	critical	ADJ
ajase-2385	9	24	role	role	NOUN
ajase-2385	9	25	of	of	ADP
ajase-2385	9	26	precise	precise	ADJ
ajase-2385	9	27	cross	cross	ADJ
ajase-2385	9	28	-	-	ADJ
ajase-2385	9	29	validation	validation	ADJ
ajase-2385	9	30	techniques	technique	NOUN
ajase-2385	9	31	.	.	PUNCT
ajase-2385	10	1	these	these	DET
ajase-2385	10	2	findings	finding	NOUN
ajase-2385	10	3	are	be	AUX
ajase-2385	10	4	invaluable	invaluable	ADJ
ajase-2385	10	5	for	for	ADP
ajase-2385	10	6	policymakers	policymaker	NOUN
ajase-2385	10	7	and	and	CCONJ
ajase-2385	10	8	investors	investor	NOUN
ajase-2385	10	9	,	,	PUNCT
ajase-2385	10	10	offering	offer	VERB
ajase-2385	10	11	advanced	advanced	ADJ
ajase-2385	10	12	tools	tool	NOUN
ajase-2385	10	13	for	for	ADP
ajase-2385	10	14	more	more	ADV
ajase-2385	10	15	informed	informed	ADJ
ajase-2385	10	16	economic	economic	ADJ
ajase-2385	10	17	decision	decision	NOUN
ajase-2385	10	18	-	-	PUNCT
ajase-2385	10	19	making	making	NOUN
ajase-2385	10	20	and	and	CCONJ
ajase-2385	10	21	highlighting	highlight	VERB
ajase-2385	10	22	the	the	DET
ajase-2385	10	23	potential	potential	NOUN
ajase-2385	10	24	of	of	ADP
ajase-2385	10	25	machine	machine	NOUN
ajase-2385	10	26	learning	learning	NOUN
ajase-2385	10	27	in	in	ADP
ajase-2385	10	28	enhancing	enhance	VERB
ajase-2385	10	29	macroeconomic	macroeconomic	ADJ
ajase-2385	10	30	stability	stability	NOUN
ajase-2385	10	31	and	and	CCONJ
ajase-2385	10	32	forecasting	forecasting	NOUN
ajase-2385	10	33	accuracy	accuracy	NOUN
ajase-2385	10	34	.	.	PUNCT
ajase-2385	11	1	keywords	keyword	VERB
ajase-2385	11	2	cross	cross	ADJ
ajase-2385	11	3	-	-	ADJ
ajase-2385	11	4	validation	validation	ADJ
ajase-2385	11	5	,	,	PUNCT
ajase-2385	11	6	macro	macro	ADJ
ajase-2385	11	7	economic	economic	ADJ
ajase-2385	11	8	,	,	PUNCT
ajase-2385	11	9	hyper	hyper	NOUN
ajase-2385	11	10	-	-	NOUN
ajase-2385	11	11	parameter	parameter	NOUN
ajase-2385	11	12	,	,	PUNCT
ajase-2385	11	13	inflation	inflation	NOUN
ajase-2385	11	14	forecasting	forecasting	NOUN
ajase-2385	11	15	,	,	PUNCT
ajase-2385	11	16	machine	machine	NOUN
ajase-2385	11	17	learning	learn	VERB
ajase-2385	11	18	1	1	NUM
ajase-2385	11	19	deportment	deportment	NOUN
ajase-2385	11	20	of	of	ADP
ajase-2385	11	21	mathematics	mathematic	NOUN
ajase-2385	11	22	,	,	PUNCT
ajase-2385	11	23	university	university	PROPN
ajase-2385	11	24	of	of	ADP
ajase-2385	11	25	ruhuna	ruhuna	PROPN
ajase-2385	11	26	,	,	PUNCT
ajase-2385	11	27	sri	sri	PROPN
ajase-2385	11	28	lanka	lanka	PROPN
ajase-2385	11	29	*	*	PUNCT
ajase-2385	11	30	corresponding	correspond	VERB
ajase-2385	11	31	author	author	NOUN
ajase-2385	11	32	’s	’s	PART
ajase-2385	11	33	e	e	NOUN
ajase-2385	11	34	-	-	NOUN
ajase-2385	11	35	mail	mail	NOUN
ajase-2385	11	36	:	:	PUNCT
ajase-2385	11	37	bandarasudarshana009@gmail.com	bandarasudarshana009@gmail.com	X
ajase-2385	11	38	introduction	introduction	NOUN
ajase-2385	11	39	inflation	inflation	NOUN
ajase-2385	11	40	,	,	PUNCT
ajase-2385	11	41	a	a	DET
ajase-2385	11	42	critical	critical	ADJ
ajase-2385	11	43	economic	economic	ADJ
ajase-2385	11	44	indicator	indicator	NOUN
ajase-2385	11	45	,	,	PUNCT
ajase-2385	11	46	measures	measure	VERB
ajase-2385	11	47	the	the	DET
ajase-2385	11	48	rise	rise	NOUN
ajase-2385	11	49	in	in	ADP
ajase-2385	11	50	the	the	DET
ajase-2385	11	51	general	general	ADJ
ajase-2385	11	52	price	price	NOUN
ajase-2385	11	53	level	level	NOUN
ajase-2385	11	54	of	of	ADP
ajase-2385	11	55	goods	good	NOUN
ajase-2385	11	56	and	and	CCONJ
ajase-2385	11	57	services	service	NOUN
ajase-2385	11	58	over	over	ADP
ajase-2385	11	59	time	time	NOUN
ajase-2385	11	60	.	.	PUNCT
ajase-2385	12	1	it	it	PRON
ajase-2385	12	2	impacts	impact	VERB
ajase-2385	12	3	individuals	individual	NOUN
ajase-2385	12	4	,	,	PUNCT
ajase-2385	12	5	businesses	business	NOUN
ajase-2385	12	6	,	,	PUNCT
ajase-2385	12	7	and	and	CCONJ
ajase-2385	12	8	the	the	DET
ajase-2385	12	9	overall	overall	ADJ
ajase-2385	12	10	economy	economy	NOUN
ajase-2385	12	11	of	of	ADP
ajase-2385	12	12	a	a	DET
ajase-2385	12	13	country	country	NOUN
ajase-2385	12	14	.	.	PUNCT
ajase-2385	13	1	high	high	ADJ
ajase-2385	13	2	inflation	inflation	NOUN
ajase-2385	13	3	can	can	AUX
ajase-2385	13	4	lead	lead	VERB
ajase-2385	13	5	to	to	ADP
ajase-2385	13	6	a	a	DET
ajase-2385	13	7	decrease	decrease	NOUN
ajase-2385	13	8	in	in	ADP
ajase-2385	13	9	the	the	DET
ajase-2385	13	10	purchasing	purchase	VERB
ajase-2385	13	11	power	power	NOUN
ajase-2385	13	12	of	of	ADP
ajase-2385	13	13	the	the	DET
ajase-2385	13	14	currency	currency	NOUN
ajase-2385	13	15	,	,	PUNCT
ajase-2385	13	16	potentially	potentially	ADV
ajase-2385	13	17	causing	cause	VERB
ajase-2385	13	18	economic	economic	ADJ
ajase-2385	13	19	instability	instability	NOUN
ajase-2385	13	20	,	,	PUNCT
ajase-2385	13	21	social	social	ADJ
ajase-2385	13	22	unrest	unrest	NOUN
ajase-2385	13	23	,	,	PUNCT
ajase-2385	13	24	and	and	CCONJ
ajase-2385	13	25	political	political	ADJ
ajase-2385	13	26	turmoil	turmoil	NOUN
ajase-2385	13	27	(	(	PUNCT
ajase-2385	13	28	maldeni	maldeni	NOUN
ajase-2385	13	29	,	,	PUNCT
ajase-2385	13	30	2021	2021	NUM
ajase-2385	13	31	)	)	PUNCT
ajase-2385	13	32	(	(	PUNCT
ajase-2385	13	33	malladi	malladi	NOUN
ajase-2385	13	34	,	,	PUNCT
ajase-2385	13	35	2023	2023	NUM
ajase-2385	13	36	)	)	PUNCT
ajase-2385	13	37	(	(	PUNCT
ajase-2385	13	38	jayasooriya	jayasooriya	NOUN
ajase-2385	13	39	,	,	PUNCT
ajase-2385	13	40	2015	2015	NUM
ajase-2385	13	41	)	)	PUNCT
ajase-2385	13	42	.	.	PUNCT
ajase-2385	14	1	therefore	therefore	ADV
ajase-2385	14	2	,	,	PUNCT
ajase-2385	14	3	accurate	accurate	ADJ
ajase-2385	14	4	forecasting	forecasting	NOUN
ajase-2385	14	5	of	of	ADP
ajase-2385	14	6	the	the	DET
ajase-2385	14	7	inflation	inflation	NOUN
ajase-2385	14	8	rate	rate	NOUN
ajase-2385	14	9	is	be	AUX
ajase-2385	14	10	essential	essential	ADJ
ajase-2385	14	11	to	to	PART
ajase-2385	14	12	take	take	VERB
ajase-2385	14	13	preemptive	preemptive	ADJ
ajase-2385	14	14	measures	measure	NOUN
ajase-2385	14	15	to	to	PART
ajase-2385	14	16	mitigate	mitigate	VERB
ajase-2385	14	17	its	its	PRON
ajase-2385	14	18	adverse	adverse	ADJ
ajase-2385	14	19	effects	effect	NOUN
ajase-2385	14	20	(	(	PUNCT
ajase-2385	14	21	bandara	bandara	PROPN
ajase-2385	14	22	&	&	CCONJ
ajase-2385	14	23	de	de	PROPN
ajase-2385	14	24	mel	mel	PROPN
ajase-2385	14	25	,	,	PUNCT
ajase-2385	14	26	2021	2021	NUM
ajase-2385	14	27	;	;	PUNCT
ajase-2385	14	28	jaehyuk	jaehyuk	NOUN
ajase-2385	14	29	choi	choi	NOUN
ajase-2385	14	30	,	,	PUNCT
ajase-2385	14	31	2023	2023	NUM
ajase-2385	14	32	)	)	PUNCT
ajase-2385	14	33	.	.	PUNCT
ajase-2385	15	1	forecasting	forecast	VERB
ajase-2385	15	2	inflation	inflation	NOUN
ajase-2385	15	3	rates	rate	NOUN
ajase-2385	15	4	is	be	AUX
ajase-2385	15	5	a	a	DET
ajase-2385	15	6	challenging	challenging	ADJ
ajase-2385	15	7	task	task	NOUN
ajase-2385	15	8	due	due	ADP
ajase-2385	15	9	to	to	ADP
ajase-2385	15	10	several	several	ADJ
ajase-2385	15	11	factors	factor	NOUN
ajase-2385	15	12	.	.	PUNCT
ajase-2385	16	1	unpredictable	unpredictable	ADJ
ajase-2385	16	2	events	event	NOUN
ajase-2385	16	3	such	such	ADJ
ajase-2385	16	4	as	as	ADP
ajase-2385	16	5	natural	natural	ADJ
ajase-2385	16	6	disasters	disaster	NOUN
ajase-2385	16	7	,	,	PUNCT
ajase-2385	16	8	political	political	ADJ
ajase-2385	16	9	and	and	CCONJ
ajase-2385	16	10	social	social	ADJ
ajase-2385	16	11	conflicts	conflict	NOUN
ajase-2385	16	12	,	,	PUNCT
ajase-2385	16	13	and	and	CCONJ
ajase-2385	16	14	global	global	ADJ
ajase-2385	16	15	economic	economic	ADJ
ajase-2385	16	16	crises	crisis	NOUN
ajase-2385	16	17	can	can	AUX
ajase-2385	16	18	impact	impact	VERB
ajase-2385	16	19	the	the	DET
ajase-2385	16	20	economy	economy	NOUN
ajase-2385	16	21	unexpectedly	unexpectedly	ADV
ajase-2385	16	22	.	.	PUNCT
ajase-2385	17	1	economic	economic	ADJ
ajase-2385	17	2	variables	variable	NOUN
ajase-2385	17	3	’	'	PUNCT
ajase-2385	17	4	complex	complex	ADJ
ajase-2385	17	5	and	and	CCONJ
ajase-2385	17	6	dynamic	dynamic	ADJ
ajase-2385	17	7	relationships	relationship	NOUN
ajase-2385	17	8	(	(	PUNCT
ajase-2385	17	9	jaehyuk	jaehyuk	NOUN
ajase-2385	17	10	choi	choi	NOUN
ajase-2385	17	11	,	,	PUNCT
ajase-2385	17	12	2023	2023	NUM
ajase-2385	17	13	)	)	PUNCT
ajase-2385	17	14	.	.	PUNCT
ajase-2385	18	1	hence	hence	ADV
ajase-2385	18	2	,	,	PUNCT
ajase-2385	18	3	there	there	PRON
ajase-2385	18	4	is	be	VERB
ajase-2385	18	5	a	a	DET
ajase-2385	18	6	need	need	NOUN
ajase-2385	18	7	for	for	ADP
ajase-2385	18	8	advanced	advanced	ADJ
ajase-2385	18	9	forecasting	forecasting	NOUN
ajase-2385	18	10	models	model	NOUN
ajase-2385	18	11	that	that	PRON
ajase-2385	18	12	can	can	AUX
ajase-2385	18	13	handle	handle	VERB
ajase-2385	18	14	the	the	DET
ajase-2385	18	15	complexity	complexity	NOUN
ajase-2385	18	16	of	of	ADP
ajase-2385	18	17	economic	economic	ADJ
ajase-2385	18	18	data	datum	NOUN
ajase-2385	18	19	and	and	CCONJ
ajase-2385	18	20	provide	provide	VERB
ajase-2385	18	21	accurate	accurate	ADJ
ajase-2385	18	22	predictions	prediction	NOUN
ajase-2385	18	23	.	.	PUNCT
ajase-2385	19	1	this	this	DET
ajase-2385	19	2	paper	paper	NOUN
ajase-2385	19	3	focuses	focus	VERB
ajase-2385	19	4	on	on	ADP
ajase-2385	19	5	the	the	DET
ajase-2385	19	6	application	application	NOUN
ajase-2385	19	7	of	of	ADP
ajase-2385	19	8	machine	machine	NOUN
ajase-2385	19	9	learning	learning	NOUN
ajase-2385	19	10	(	(	PUNCT
ajase-2385	19	11	ml	ml	NOUN
ajase-2385	19	12	)	)	PUNCT
ajase-2385	19	13	approaches	approach	NOUN
ajase-2385	19	14	for	for	ADP
ajase-2385	19	15	forecasting	forecast	VERB
ajase-2385	19	16	inflation	inflation	NOUN
ajase-2385	19	17	,	,	PUNCT
ajase-2385	19	18	with	with	ADP
ajase-2385	19	19	empirical	empirical	ADJ
ajase-2385	19	20	evidence	evidence	NOUN
ajase-2385	19	21	from	from	ADP
ajase-2385	19	22	sri	sri	PROPN
ajase-2385	19	23	lanka	lanka	PROPN
ajase-2385	19	24	(	(	PUNCT
ajase-2385	19	25	maldeni	maldeni	PROPN
ajase-2385	19	26	,	,	PUNCT
ajase-2385	19	27	2021	2021	NUM
ajase-2385	19	28	)	)	PUNCT
ajase-2385	19	29	.	.	PUNCT
ajase-2385	20	1	ml	ml	NOUN
ajase-2385	20	2	,	,	PUNCT
ajase-2385	20	3	a	a	DET
ajase-2385	20	4	subset	subset	NOUN
ajase-2385	20	5	of	of	ADP
ajase-2385	20	6	artificial	artificial	ADJ
ajase-2385	20	7	intelligence	intelligence	NOUN
ajase-2385	20	8	,	,	PUNCT
ajase-2385	20	9	has	have	AUX
ajase-2385	20	10	shown	show	VERB
ajase-2385	20	11	promising	promising	ADJ
ajase-2385	20	12	results	result	NOUN
ajase-2385	20	13	in	in	ADP
ajase-2385	20	14	various	various	ADJ
ajase-2385	20	15	fields	field	NOUN
ajase-2385	20	16	,	,	PUNCT
ajase-2385	20	17	including	include	VERB
ajase-2385	20	18	economics	economic	NOUN
ajase-2385	20	19	.	.	PUNCT
ajase-2385	21	1	it	it	PRON
ajase-2385	21	2	can	can	AUX
ajase-2385	21	3	analyze	analyze	VERB
ajase-2385	21	4	large	large	ADJ
ajase-2385	21	5	volumes	volume	NOUN
ajase-2385	21	6	of	of	ADP
ajase-2385	21	7	data	datum	NOUN
ajase-2385	21	8	,	,	PUNCT
ajase-2385	21	9	learn	learn	VERB
ajase-2385	21	10	from	from	ADP
ajase-2385	21	11	it	it	PRON
ajase-2385	21	12	,	,	PUNCT
ajase-2385	21	13	and	and	CCONJ
ajase-2385	21	14	make	make	VERB
ajase-2385	21	15	predictions	prediction	NOUN
ajase-2385	21	16	or	or	CCONJ
ajase-2385	21	17	decisions	decision	NOUN
ajase-2385	21	18	without	without	ADP
ajase-2385	21	19	being	be	AUX
ajase-2385	21	20	explicitly	explicitly	ADV
ajase-2385	21	21	programmed	program	VERB
ajase-2385	21	22	.	.	PUNCT
ajase-2385	22	1	in	in	ADP
ajase-2385	22	2	the	the	DET
ajase-2385	22	3	context	context	NOUN
ajase-2385	22	4	of	of	ADP
ajase-2385	22	5	inflation	inflation	NOUN
ajase-2385	22	6	forecasting	forecasting	NOUN
ajase-2385	22	7	,	,	PUNCT
ajase-2385	22	8	ml	ml	ADP
ajase-2385	22	9	models	model	NOUN
ajase-2385	22	10	can	can	AUX
ajase-2385	22	11	capture	capture	VERB
ajase-2385	22	12	non	non	ADJ
ajase-2385	22	13	-	-	ADJ
ajase-2385	22	14	linear	linear	ADJ
ajase-2385	22	15	relationships	relationship	NOUN
ajase-2385	22	16	between	between	ADP
ajase-2385	22	17	variables	variable	NOUN
ajase-2385	22	18	,	,	PUNCT
ajase-2385	22	19	adapt	adapt	VERB
ajase-2385	22	20	to	to	ADP
ajase-2385	22	21	changes	change	NOUN
ajase-2385	22	22	,	,	PUNCT
ajase-2385	22	23	and	and	CCONJ
ajase-2385	22	24	improve	improve	VERB
ajase-2385	22	25	their	their	PRON
ajase-2385	22	26	performance	performance	NOUN
ajase-2385	22	27	over	over	ADP
ajase-2385	22	28	time	time	NOUN
ajase-2385	22	29	with	with	ADP
ajase-2385	22	30	more	more	ADJ
ajase-2385	22	31	data	datum	NOUN
ajase-2385	22	32	.	.	PUNCT
ajase-2385	23	1	economic	economic	ADJ
ajase-2385	23	2	forecasting	forecasting	NOUN
ajase-2385	23	3	is	be	AUX
ajase-2385	23	4	crucial	crucial	ADJ
ajase-2385	23	5	for	for	ADP
ajase-2385	23	6	policy	policy	NOUN
ajase-2385	23	7	-	-	PUNCT
ajase-2385	23	8	making	make	VERB
ajase-2385	23	9	and	and	CCONJ
ajase-2385	23	10	strategic	strategic	ADJ
ajase-2385	23	11	planning	planning	NOUN
ajase-2385	23	12	(	(	PUNCT
ajase-2385	23	13	anagaw	anagaw	PROPN
ajase-2385	23	14	,	,	PUNCT
ajase-2385	23	15	2023	2023	NUM
ajase-2385	23	16	)	)	PUNCT
ajase-2385	23	17	.	.	PUNCT
ajase-2385	24	1	accurate	accurate	ADJ
ajase-2385	24	2	inflation	inflation	NOUN
ajase-2385	24	3	forecasts	forecast	NOUN
ajase-2385	24	4	can	can	AUX
ajase-2385	24	5	help	help	VERB
ajase-2385	24	6	the	the	DET
ajase-2385	24	7	government	government	NOUN
ajase-2385	24	8	and	and	CCONJ
ajase-2385	24	9	central	central	ADJ
ajase-2385	24	10	banks	bank	NOUN
ajase-2385	24	11	implement	implement	VERB
ajase-2385	24	12	appropriate	appropriate	ADJ
ajase-2385	24	13	monetary	monetary	ADJ
ajase-2385	24	14	policies	policy	NOUN
ajase-2385	24	15	to	to	PART
ajase-2385	24	16	maintain	maintain	VERB
ajase-2385	24	17	price	price	NOUN
ajase-2385	24	18	stability	stability	NOUN
ajase-2385	24	19	.	.	PUNCT
ajase-2385	25	1	businesses	business	NOUN
ajase-2385	25	2	can	can	AUX
ajase-2385	25	3	also	also	ADV
ajase-2385	25	4	benefit	benefit	VERB
ajase-2385	25	5	from	from	ADP
ajase-2385	25	6	accurate	accurate	ADJ
ajase-2385	25	7	inflation	inflation	NOUN
ajase-2385	25	8	forecasts	forecast	NOUN
ajase-2385	25	9	for	for	ADP
ajase-2385	25	10	budgeting	budgeting	NOUN
ajase-2385	25	11	,	,	PUNCT
ajase-2385	25	12	pricing	pricing	NOUN
ajase-2385	25	13	,	,	PUNCT
ajase-2385	25	14	and	and	CCONJ
ajase-2385	25	15	investment	investment	NOUN
ajase-2385	25	16	decisions	decision	NOUN
ajase-2385	25	17	.	.	PUNCT
ajase-2385	26	1	ml	ml	PROPN
ajase-2385	26	2	can	can	AUX
ajase-2385	26	3	contribute	contribute	VERB
ajase-2385	26	4	significantly	significantly	ADV
ajase-2385	26	5	to	to	ADP
ajase-2385	26	6	economic	economic	ADJ
ajase-2385	26	7	forecasting	forecasting	NOUN
ajase-2385	26	8	(	(	PUNCT
ajase-2385	26	9	rahman	rahman	PROPN
ajase-2385	26	10	et	et	PROPN
ajase-2385	26	11	al	al	PROPN
ajase-2385	26	12	.	.	PROPN
ajase-2385	26	13	,	,	PUNCT
ajase-2385	26	14	2021	2021	NUM
ajase-2385	26	15	)	)	PUNCT
ajase-2385	26	16	.	.	PUNCT
ajase-2385	27	1	it	it	PRON
ajase-2385	27	2	can	can	AUX
ajase-2385	27	3	handle	handle	VERB
ajase-2385	27	4	large	large	ADJ
ajase-2385	27	5	datasets	dataset	NOUN
ajase-2385	27	6	,	,	PUNCT
ajase-2385	27	7	including	include	VERB
ajase-2385	27	8	economic	economic	ADJ
ajase-2385	27	9	indicators	indicator	NOUN
ajase-2385	27	10	,	,	PUNCT
ajase-2385	27	11	market	market	NOUN
ajase-2385	27	12	data	datum	NOUN
ajase-2385	27	13	,	,	PUNCT
ajase-2385	27	14	and	and	CCONJ
ajase-2385	27	15	social	social	ADJ
ajase-2385	27	16	media	medium	NOUN
ajase-2385	27	17	sentiment	sentiment	NOUN
ajase-2385	27	18	,	,	PUNCT
ajase-2385	27	19	which	which	PRON
ajase-2385	27	20	traditional	traditional	ADJ
ajase-2385	27	21	econometric	econometric	ADJ
ajase-2385	27	22	models	model	NOUN
ajase-2385	27	23	may	may	AUX
ajase-2385	27	24	find	find	VERB
ajase-2385	27	25	challenging	challenging	ADJ
ajase-2385	27	26	.	.	PUNCT
ajase-2385	28	1	ml	ml	NOUN
ajase-2385	28	2	models	model	NOUN
ajase-2385	28	3	can	can	AUX
ajase-2385	28	4	also	also	ADV
ajase-2385	28	5	adapt	adapt	VERB
ajase-2385	28	6	to	to	ADP
ajase-2385	28	7	new	new	ADJ
ajase-2385	28	8	data	datum	NOUN
ajase-2385	28	9	,	,	PUNCT
ajase-2385	28	10	making	make	VERB
ajase-2385	28	11	them	they	PRON
ajase-2385	28	12	suitable	suitable	ADJ
ajase-2385	28	13	for	for	ADP
ajase-2385	28	14	dynamic	dynamic	ADJ
ajase-2385	28	15	economic	economic	ADJ
ajase-2385	28	16	environments	environment	NOUN
ajase-2385	28	17	.	.	PUNCT
ajase-2385	29	1	inflation	inflation	NOUN
ajase-2385	29	2	forecasting	forecasting	NOUN
ajase-2385	29	3	is	be	AUX
ajase-2385	29	4	a	a	DET
ajase-2385	29	5	critical	critical	ADJ
ajase-2385	29	6	aspect	aspect	NOUN
ajase-2385	29	7	of	of	ADP
ajase-2385	29	8	economic	economic	ADJ
ajase-2385	29	9	stability	stability	NOUN
ajase-2385	29	10	,	,	PUNCT
ajase-2385	29	11	particularly	particularly	ADV
ajase-2385	29	12	for	for	ADP
ajase-2385	29	13	emerging	emerge	VERB
ajase-2385	29	14	economies	economy	NOUN
ajase-2385	29	15	like	like	ADP
ajase-2385	29	16	sri	sri	PROPN
ajase-2385	29	17	lanka	lanka	PROPN
ajase-2385	29	18	.	.	PUNCT
ajase-2385	30	1	the	the	DET
ajase-2385	30	2	country	country	NOUN
ajase-2385	30	3	has	have	AUX
ajase-2385	30	4	faced	face	VERB
ajase-2385	30	5	periods	period	NOUN
ajase-2385	30	6	of	of	ADP
ajase-2385	30	7	high	high	ADJ
ajase-2385	30	8	inflation	inflation	NOUN
ajase-2385	30	9	,	,	PUNCT
ajase-2385	30	10	significantly	significantly	ADV
ajase-2385	30	11	impacting	impact	VERB
ajase-2385	30	12	its	its	PRON
ajase-2385	30	13	economy	economy	NOUN
ajase-2385	30	14	.	.	PUNCT
ajase-2385	31	1	therefore	therefore	ADV
ajase-2385	31	2	,	,	PUNCT
ajase-2385	31	3	accurate	accurate	ADJ
ajase-2385	31	4	and	and	CCONJ
ajase-2385	31	5	timely	timely	ADJ
ajase-2385	31	6	inflation	inflation	NOUN
ajase-2385	31	7	forecasts	forecast	NOUN
ajase-2385	31	8	are	be	AUX
ajase-2385	31	9	vital	vital	ADJ
ajase-2385	31	10	for	for	ADP
ajase-2385	31	11	maintaining	maintain	VERB
ajase-2385	31	12	economic	economic	ADJ
ajase-2385	31	13	growth	growth	NOUN
ajase-2385	31	14	and	and	CCONJ
ajase-2385	31	15	stability	stability	NOUN
ajase-2385	31	16	.	.	PUNCT
ajase-2385	32	1	this	this	DET
ajase-2385	32	2	paper	paper	NOUN
ajase-2385	32	3	aims	aim	VERB
ajase-2385	32	4	to	to	PART
ajase-2385	32	5	enhance	enhance	VERB
ajase-2385	32	6	the	the	DET
ajase-2385	32	7	existing	exist	VERB
ajase-2385	32	8	literature	literature	NOUN
ajase-2385	32	9	by	by	ADP
ajase-2385	32	10	applying	apply	VERB
ajase-2385	32	11	machine	machine	NOUN
ajase-2385	32	12	learning	learning	NOUN
ajase-2385	32	13	(	(	PUNCT
ajase-2385	32	14	ml	ml	NOUN
ajase-2385	32	15	)	)	PUNCT
ajase-2385	32	16	approaches	approach	NOUN
ajase-2385	32	17	to	to	PART
ajase-2385	32	18	forecast	forecast	VERB
ajase-2385	32	19	inflation	inflation	NOUN
ajase-2385	32	20	in	in	ADP
ajase-2385	32	21	sri	sri	PROPN
ajase-2385	32	22	lanka	lanka	PROPN
ajase-2385	32	23	.	.	PUNCT
ajase-2385	33	1	it	it	PRON
ajase-2385	33	2	will	will	AUX
ajase-2385	33	3	assess	assess	VERB
ajase-2385	33	4	various	various	ADJ
ajase-2385	33	5	ml	ml	NOUN
ajase-2385	33	6	models	model	NOUN
ajase-2385	33	7	’	'	PUNCT
ajase-2385	33	8	performance	performance	NOUN
ajase-2385	33	9	and	and	CCONJ
ajase-2385	33	10	juxtapose	juxtapose	VERB
ajase-2385	33	11	them	they	PRON
ajase-2385	33	12	with	with	ADP
ajase-2385	33	13	traditional	traditional	ADJ
ajase-2385	33	14	econometric	econometric	ADJ
ajase-2385	33	15	models	model	NOUN
ajase-2385	33	16	.	.	PUNCT
ajase-2385	34	1	the	the	DET
ajase-2385	34	2	study	study	NOUN
ajase-2385	34	3	’s	’s	PART
ajase-2385	34	4	findings	finding	NOUN
ajase-2385	34	5	could	could	AUX
ajase-2385	34	6	offer	offer	VERB
ajase-2385	34	7	valuable	valuable	ADJ
ajase-2385	34	8	insights	insight	NOUN
ajase-2385	34	9	for	for	ADP
ajase-2385	34	10	policymakers	policymaker	NOUN
ajase-2385	34	11	,	,	PUNCT
ajase-2385	34	12	economists	economist	NOUN
ajase-2385	34	13	,	,	PUNCT
ajase-2385	34	14	and	and	CCONJ
ajase-2385	34	15	businesses	business	NOUN
ajase-2385	34	16	in	in	ADP
ajase-2385	34	17	sri	sri	PROPN
ajase-2385	34	18	lanka	lanka	PROPN
ajase-2385	34	19	and	and	CCONJ
ajase-2385	34	20	other	other	ADJ
ajase-2385	34	21	emerging	emerge	VERB
ajase-2385	34	22	economies	economy	NOUN
ajase-2385	34	23	.	.	PUNCT
ajase-2385	35	1	the	the	DET
ajase-2385	35	2	current	current	ADJ
ajase-2385	35	3	research	research	NOUN
ajase-2385	35	4	intends	intend	VERB
ajase-2385	35	5	to	to	PART
ajase-2385	35	6	develop	develop	VERB
ajase-2385	35	7	and	and	CCONJ
ajase-2385	35	8	evaluate	evaluate	VERB
ajase-2385	35	9	machine	machine	NOUN
ajase-2385	35	10	learning	learning	NOUN
ajase-2385	35	11	models	model	NOUN
ajase-2385	35	12	’	'	PUNCT
ajase-2385	35	13	efficacy	efficacy	NOUN
ajase-2385	35	14	in	in	ADP
ajase-2385	35	15	forecasting	forecast	VERB
ajase-2385	35	16	inflation	inflation	NOUN
ajase-2385	35	17	rates	rate	NOUN
ajase-2385	35	18	in	in	ADP
ajase-2385	35	19	sri	sri	PROPN
ajase-2385	35	20	lanka	lanka	PROPN
ajase-2385	35	21	.	.	PUNCT
ajase-2385	36	1	by	by	ADP
ajase-2385	36	2	addressing	address	VERB
ajase-2385	36	3	the	the	DET
ajase-2385	36	4	limitations	limitation	NOUN
ajase-2385	36	5	of	of	ADP
ajase-2385	36	6	traditional	traditional	ADJ
ajase-2385	36	7	forecasting	forecasting	NOUN
ajase-2385	36	8	methods	method	NOUN
ajase-2385	36	9	and	and	CCONJ
ajase-2385	36	10	exploring	explore	VERB
ajase-2385	36	11	machine	machine	NOUN
ajase-2385	36	12	pa	pa	PROPN
ajase-2385	36	13	ge	ge	PROPN
ajase-2385	36	14	52	52	NUM
ajase-2385	36	15	https://journals.e-palli.com/home/index.php/ajase	https://journals.e-palli.com/home/index.php/ajase	PROPN
ajase-2385	36	16	am	be	AUX
ajase-2385	36	17	.	.	PUNCT
ajase-2385	37	1	j.	j.	PROPN
ajase-2385	37	2	appl	appl	PROPN
ajase-2385	37	3	.	.	PROPN
ajase-2385	38	1	stat	stat	PROPN
ajase-2385	38	2	.	.	PUNCT
ajase-2385	39	1	econ	econ	PROPN
ajase-2385	39	2	.	.	PUNCT
ajase-2385	40	1	3(1	3(1	NUM
ajase-2385	40	2	)	)	PUNCT
ajase-2385	41	1	51	51	NUM
ajase-2385	41	2	-	-	SYM
ajase-2385	41	3	60	60	NUM
ajase-2385	41	4	,	,	PUNCT
ajase-2385	41	5	2024	2024	NUM
ajase-2385	41	6	learning	learning	NOUN
ajase-2385	41	7	models	model	NOUN
ajase-2385	41	8	’	'	PUNCT
ajase-2385	41	9	potential	potential	NOUN
ajase-2385	41	10	,	,	PUNCT
ajase-2385	41	11	this	this	DET
ajase-2385	41	12	study	study	NOUN
ajase-2385	41	13	contributes	contribute	VERB
ajase-2385	41	14	to	to	ADP
ajase-2385	41	15	the	the	DET
ajase-2385	41	16	existing	exist	VERB
ajase-2385	41	17	body	body	NOUN
ajase-2385	41	18	of	of	ADP
ajase-2385	41	19	knowledge	knowledge	NOUN
ajase-2385	41	20	.	.	PUNCT
ajase-2385	42	1	the	the	DET
ajase-2385	42	2	findings	finding	NOUN
ajase-2385	42	3	could	could	AUX
ajase-2385	42	4	have	have	VERB
ajase-2385	42	5	practical	practical	ADJ
ajase-2385	42	6	implications	implication	NOUN
ajase-2385	42	7	for	for	ADP
ajase-2385	42	8	policymakers	policymaker	NOUN
ajase-2385	42	9	,	,	PUNCT
ajase-2385	42	10	central	central	ADJ
ajase-2385	42	11	banks	bank	NOUN
ajase-2385	42	12	,	,	PUNCT
ajase-2385	42	13	and	and	CCONJ
ajase-2385	42	14	investors	investor	NOUN
ajase-2385	42	15	,	,	PUNCT
ajase-2385	42	16	enabling	enable	VERB
ajase-2385	42	17	them	they	PRON
ajase-2385	42	18	to	to	PART
ajase-2385	42	19	make	make	VERB
ajase-2385	42	20	informed	informed	ADJ
ajase-2385	42	21	decisions	decision	NOUN
ajase-2385	42	22	based	base	VERB
ajase-2385	42	23	on	on	ADP
ajase-2385	42	24	more	more	ADV
ajase-2385	42	25	precise	precise	ADJ
ajase-2385	42	26	inflation	inflation	NOUN
ajase-2385	42	27	forecasts	forecast	NOUN
ajase-2385	42	28	.	.	PUNCT
ajase-2385	43	1	therefore	therefore	ADV
ajase-2385	43	2	,	,	PUNCT
ajase-2385	43	3	this	this	DET
ajase-2385	43	4	study	study	NOUN
ajase-2385	43	5	holds	hold	VERB
ajase-2385	43	6	significant	significant	ADJ
ajase-2385	43	7	importance	importance	NOUN
ajase-2385	43	8	,	,	PUNCT
ajase-2385	43	9	and	and	CCONJ
ajase-2385	43	10	the	the	DET
ajase-2385	43	11	application	application	NOUN
ajase-2385	43	12	of	of	ADP
ajase-2385	43	13	machine	machine	NOUN
ajase-2385	43	14	learning	learning	NOUN
ajase-2385	43	15	models	model	NOUN
ajase-2385	43	16	in	in	ADP
ajase-2385	43	17	forecasting	forecast	VERB
ajase-2385	43	18	inflation	inflation	NOUN
ajase-2385	43	19	rates	rate	NOUN
ajase-2385	43	20	is	be	AUX
ajase-2385	43	21	necessary	necessary	ADJ
ajase-2385	43	22	to	to	PART
ajase-2385	43	23	address	address	VERB
ajase-2385	43	24	traditional	traditional	ADJ
ajase-2385	43	25	forecasting	forecasting	NOUN
ajase-2385	43	26	methods	method	NOUN
ajase-2385	43	27	’	'	PUNCT
ajase-2385	43	28	limitations	limitation	NOUN
ajase-2385	43	29	.	.	PUNCT
ajase-2385	44	1	the	the	DET
ajase-2385	44	2	study	study	NOUN
ajase-2385	44	3	’s	’s	PART
ajase-2385	44	4	results	result	NOUN
ajase-2385	44	5	could	could	AUX
ajase-2385	44	6	lead	lead	VERB
ajase-2385	44	7	to	to	ADP
ajase-2385	44	8	more	more	ADV
ajase-2385	44	9	accurate	accurate	ADJ
ajase-2385	44	10	inflation	inflation	NOUN
ajase-2385	44	11	forecasts	forecast	NOUN
ajase-2385	44	12	,	,	PUNCT
ajase-2385	44	13	contributing	contribute	VERB
ajase-2385	44	14	to	to	ADP
ajase-2385	44	15	economic	economic	ADJ
ajase-2385	44	16	stability	stability	NOUN
ajase-2385	44	17	and	and	CCONJ
ajase-2385	44	18	informed	informed	ADJ
ajase-2385	44	19	decision	decision	NOUN
ajase-2385	44	20	-	-	PUNCT
ajase-2385	44	21	making	make	VERB
ajase-2385	44	22	processes	process	NOUN
ajase-2385	44	23	.	.	PUNCT
ajase-2385	45	1	best	good	ADJ
ajase-2385	45	2	predicting	predict	VERB
ajase-2385	45	3	performance	performance	NOUN
ajase-2385	45	4	was	be	AUX
ajase-2385	45	5	achieved	achieve	VERB
ajase-2385	45	6	with	with	ADP
ajase-2385	45	7	the	the	DET
ajase-2385	45	8	blocked	block	VERB
ajase-2385	45	9	cross	cross	ADJ
ajase-2385	45	10	-	-	ADJ
ajase-2385	45	11	validation	validation	ADJ
ajase-2385	45	12	method	method	NOUN
ajase-2385	45	13	with	with	ADP
ajase-2385	45	14	respect	respect	NOUN
ajase-2385	45	15	to	to	ADP
ajase-2385	45	16	the	the	DET
ajase-2385	45	17	rmse	rmse	PROPN
ajase-2385	45	18	statistic	statistic	NOUN
ajase-2385	45	19	.	.	PUNCT
ajase-2385	46	1	literature	literature	PROPN
ajase-2385	46	2	review	review	VERB
ajase-2385	46	3	the	the	DET
ajase-2385	46	4	current	current	ADJ
ajase-2385	46	5	study	study	NOUN
ajase-2385	46	6	aims	aim	VERB
ajase-2385	46	7	to	to	PART
ajase-2385	46	8	develop	develop	VERB
ajase-2385	46	9	and	and	CCONJ
ajase-2385	46	10	evaluate	evaluate	VERB
ajase-2385	46	11	the	the	DET
ajase-2385	46	12	performance	performance	NOUN
ajase-2385	46	13	of	of	ADP
ajase-2385	46	14	machine	machine	NOUN
ajase-2385	46	15	learning	learning	NOUN
ajase-2385	46	16	models	model	NOUN
ajase-2385	46	17	in	in	ADP
ajase-2385	46	18	forecasting	forecast	VERB
ajase-2385	46	19	inflation	inflation	NOUN
ajase-2385	46	20	rates	rate	NOUN
ajase-2385	46	21	in	in	ADP
ajase-2385	46	22	sri	sri	PROPN
ajase-2385	46	23	lanka	lanka	PROPN
ajase-2385	46	24	.	.	PUNCT
ajase-2385	47	1	the	the	DET
ajase-2385	47	2	study	study	NOUN
ajase-2385	47	3	contributes	contribute	VERB
ajase-2385	47	4	to	to	ADP
ajase-2385	47	5	the	the	DET
ajase-2385	47	6	existing	exist	VERB
ajase-2385	47	7	literature	literature	NOUN
ajase-2385	47	8	by	by	ADP
ajase-2385	47	9	addressing	address	VERB
ajase-2385	47	10	the	the	DET
ajase-2385	47	11	limitations	limitation	NOUN
ajase-2385	47	12	of	of	ADP
ajase-2385	47	13	traditional	traditional	ADJ
ajase-2385	47	14	forecasting	forecasting	NOUN
ajase-2385	47	15	methods	method	NOUN
ajase-2385	47	16	and	and	CCONJ
ajase-2385	47	17	exploring	explore	VERB
ajase-2385	47	18	the	the	DET
ajase-2385	47	19	potential	potential	NOUN
ajase-2385	47	20	of	of	ADP
ajase-2385	47	21	machine	machine	NOUN
ajase-2385	47	22	learning	learning	NOUN
ajase-2385	47	23	models	model	NOUN
ajase-2385	47	24	in	in	ADP
ajase-2385	47	25	improving	improve	VERB
ajase-2385	47	26	inflation	inflation	NOUN
ajase-2385	47	27	forecasts	forecast	NOUN
ajase-2385	47	28	.	.	PUNCT
ajase-2385	48	1	the	the	DET
ajase-2385	48	2	findings	finding	NOUN
ajase-2385	48	3	of	of	ADP
ajase-2385	48	4	this	this	DET
ajase-2385	48	5	study	study	NOUN
ajase-2385	48	6	could	could	AUX
ajase-2385	48	7	have	have	VERB
ajase-2385	48	8	practical	practical	ADJ
ajase-2385	48	9	implications	implication	NOUN
ajase-2385	48	10	for	for	ADP
ajase-2385	48	11	policymakers	policymaker	NOUN
ajase-2385	48	12	,	,	PUNCT
ajase-2385	48	13	central	central	ADJ
ajase-2385	48	14	banks	bank	NOUN
ajase-2385	48	15	,	,	PUNCT
ajase-2385	48	16	and	and	CCONJ
ajase-2385	48	17	investors	investor	NOUN
ajase-2385	48	18	in	in	ADP
ajase-2385	48	19	making	make	VERB
ajase-2385	48	20	informed	informed	ADJ
ajase-2385	48	21	decisions	decision	NOUN
ajase-2385	48	22	based	base	VERB
ajase-2385	48	23	on	on	ADP
ajase-2385	48	24	more	more	ADV
ajase-2385	48	25	accurate	accurate	ADJ
ajase-2385	48	26	inflation	inflation	NOUN
ajase-2385	48	27	forecasts	forecast	NOUN
ajase-2385	48	28	.	.	PUNCT
ajase-2385	49	1	therefore	therefore	ADV
ajase-2385	49	2	,	,	PUNCT
ajase-2385	49	3	this	this	DET
ajase-2385	49	4	study	study	NOUN
ajase-2385	49	5	is	be	AUX
ajase-2385	49	6	significant	significant	ADJ
ajase-2385	49	7	importance	importance	NOUN
ajase-2385	49	8	,	,	PUNCT
ajase-2385	49	9	and	and	CCONJ
ajase-2385	49	10	the	the	DET
ajase-2385	49	11	application	application	NOUN
ajase-2385	49	12	of	of	ADP
ajase-2385	49	13	machine	machine	NOUN
ajase-2385	49	14	learning	learning	NOUN
ajase-2385	49	15	models	model	NOUN
ajase-2385	49	16	in	in	ADP
ajase-2385	49	17	forecasting	forecast	VERB
ajase-2385	49	18	inflation	inflation	NOUN
ajase-2385	49	19	rates	rate	NOUN
ajase-2385	49	20	is	be	AUX
ajase-2385	49	21	necessary	necessary	ADJ
ajase-2385	49	22	to	to	PART
ajase-2385	49	23	address	address	VERB
ajase-2385	49	24	the	the	DET
ajase-2385	49	25	limitations	limitation	NOUN
ajase-2385	49	26	of	of	ADP
ajase-2385	49	27	traditional	traditional	ADJ
ajase-2385	49	28	forecasting	forecasting	NOUN
ajase-2385	49	29	methods	method	NOUN
ajase-2385	49	30	.	.	PUNCT
ajase-2385	50	1	in	in	ADP
ajase-2385	50	2	seminal	seminal	ADJ
ajase-2385	50	3	studies	study	NOUN
ajase-2385	50	4	,	,	PUNCT
ajase-2385	50	5	various	various	ADJ
ajase-2385	50	6	models	model	NOUN
ajase-2385	50	7	such	such	ADJ
ajase-2385	50	8	as	as	ADP
ajase-2385	50	9	univariate	univariate	ADJ
ajase-2385	50	10	models	model	NOUN
ajase-2385	50	11	and	and	CCONJ
ajase-2385	50	12	phillips	phillip	NOUN
ajase-2385	50	13	curve	curve	NOUN
ajase-2385	50	14	models	model	NOUN
ajase-2385	50	15	have	have	AUX
ajase-2385	50	16	been	be	AUX
ajase-2385	50	17	utilized	utilize	VERB
ajase-2385	50	18	in	in	ADP
ajase-2385	50	19	forecasting	forecast	VERB
ajase-2385	50	20	inflation	inflation	NOUN
ajase-2385	50	21	rates	rate	NOUN
ajase-2385	50	22	.	.	PUNCT
ajase-2385	51	1	(	(	PUNCT
ajase-2385	51	2	jesmy	jesmy	ADJ
ajase-2385	51	3	,	,	PUNCT
ajase-2385	51	4	2010	2010	NUM
ajase-2385	51	5	)	)	PUNCT
ajase-2385	51	6	used	use	VERB
ajase-2385	51	7	box	box	PROPN
ajase-2385	51	8	–	–	PUNCT
ajase-2385	51	9	jenkins	jenkins	PROPN
ajase-2385	51	10	’s	’s	PART
ajase-2385	51	11	method	method	NOUN
ajase-2385	51	12	to	to	PART
ajase-2385	51	13	forecast	forecast	VERB
ajase-2385	51	14	the	the	DET
ajase-2385	51	15	monthly	monthly	ADJ
ajase-2385	51	16	mean	mean	ADJ
ajase-2385	51	17	inflation	inflation	NOUN
ajase-2385	51	18	rate	rate	NOUN
ajase-2385	51	19	of	of	ADP
ajase-2385	51	20	sri	sri	PROPN
ajase-2385	51	21	lanka	lanka	PROPN
ajase-2385	51	22	by	by	ADP
ajase-2385	51	23	using	use	VERB
ajase-2385	51	24	the	the	DET
ajase-2385	51	25	historical	historical	ADJ
ajase-2385	51	26	inflation	inflation	NOUN
ajase-2385	51	27	data	datum	NOUN
ajase-2385	51	28	(	(	PUNCT
ajase-2385	51	29	1952	1952	NUM
ajase-2385	51	30	-	-	SYM
ajase-2385	51	31	2009	2009	NUM
ajase-2385	51	32	)	)	PUNCT
ajase-2385	51	33	.	.	PUNCT
ajase-2385	52	1	in	in	ADP
ajase-2385	52	2	this	this	DET
ajase-2385	52	3	study	study	NOUN
ajase-2385	52	4	,	,	PUNCT
ajase-2385	52	5	the	the	DET
ajase-2385	52	6	univariate	univariate	ADJ
ajase-2385	52	7	arima(1	arima(1	NOUN
ajase-2385	52	8	,	,	PUNCT
ajase-2385	52	9	1	1	NUM
ajase-2385	52	10	,	,	PUNCT
ajase-2385	52	11	2	2	NUM
ajase-2385	52	12	)	)	PUNCT
ajase-2385	52	13	was	be	AUX
ajase-2385	52	14	selected	select	VERB
ajase-2385	52	15	as	as	ADP
ajase-2385	52	16	the	the	DET
ajase-2385	52	17	best	good	ADJ
ajase-2385	52	18	model	model	NOUN
ajase-2385	52	19	using	use	VERB
ajase-2385	52	20	adjusted	adjust	VERB
ajase-2385	52	21	r	r	NOUN
ajase-2385	52	22	-	-	PUNCT
ajase-2385	52	23	squared	square	VERB
ajase-2385	52	24	statistics	statistic	NOUN
ajase-2385	52	25	.	.	PUNCT
ajase-2385	53	1	(	(	PUNCT
ajase-2385	53	2	bandara	bandara	PROPN
ajase-2385	53	3	,	,	PUNCT
ajase-2385	53	4	2011)used	2011)use	VERB
ajase-2385	53	5	the	the	DET
ajase-2385	53	6	var	var	NOUN
ajase-2385	53	7	models	model	NOUN
ajase-2385	53	8	to	to	PART
ajase-2385	53	9	forecast	forecast	VERB
ajase-2385	53	10	the	the	DET
ajase-2385	53	11	inflation	inflation	NOUN
ajase-2385	53	12	rate	rate	NOUN
ajase-2385	53	13	of	of	ADP
ajase-2385	53	14	sri	sri	PROPN
ajase-2385	53	15	lanka	lanka	PROPN
ajase-2385	53	16	using	use	VERB
ajase-2385	53	17	the	the	DET
ajase-2385	53	18	monthly	monthly	ADJ
ajase-2385	53	19	mean	mean	ADJ
ajase-2385	53	20	historical	historical	ADJ
ajase-2385	53	21	data	datum	NOUN
ajase-2385	53	22	(	(	PUNCT
ajase-2385	53	23	1985	1985	NUM
ajase-2385	53	24	-	-	SYM
ajase-2385	53	25	2005	2005	NUM
ajase-2385	53	26	)	)	PUNCT
ajase-2385	53	27	.	.	PUNCT
ajase-2385	54	1	(	(	PUNCT
ajase-2385	54	2	jere	jere	PROPN
ajase-2385	54	3	,	,	PUNCT
ajase-2385	54	4	2016	2016	NUM
ajase-2385	54	5	)	)	PUNCT
ajase-2385	54	6	used	use	VERB
ajase-2385	54	7	the	the	DET
ajase-2385	54	8	univariate	univariate	ADJ
ajase-2385	54	9	time	time	NOUN
ajase-2385	54	10	series	series	NOUN
ajase-2385	54	11	models	model	NOUN
ajase-2385	54	12	to	to	PART
ajase-2385	54	13	forecast	forecast	VERB
ajase-2385	54	14	the	the	DET
ajase-2385	54	15	inflation	inflation	NOUN
ajase-2385	54	16	rate	rate	NOUN
ajase-2385	54	17	of	of	ADP
ajase-2385	54	18	zambia	zambia	PROPN
ajase-2385	54	19	by	by	ADP
ajase-2385	54	20	using	use	VERB
ajase-2385	54	21	holt	holt	PROPN
ajase-2385	54	22	’s	’s	PART
ajase-2385	54	23	exponential	exponential	ADJ
ajase-2385	54	24	smoothing	smoothing	NOUN
ajase-2385	54	25	.	.	PUNCT
ajase-2385	55	1	however	however	ADV
ajase-2385	55	2	,	,	PUNCT
ajase-2385	55	3	due	due	ADP
ajase-2385	55	4	to	to	ADP
ajase-2385	55	5	differences	difference	NOUN
ajase-2385	55	6	between	between	ADP
ajase-2385	55	7	global	global	ADJ
ajase-2385	55	8	and	and	CCONJ
ajase-2385	55	9	domestic	domestic	ADJ
ajase-2385	55	10	political	political	ADJ
ajase-2385	55	11	,	,	PUNCT
ajase-2385	55	12	social	social	ADJ
ajase-2385	55	13	,	,	PUNCT
ajase-2385	55	14	environmental	environmental	ADJ
ajase-2385	55	15	,	,	PUNCT
ajase-2385	55	16	country	country	NOUN
ajase-2385	55	17	-	-	PUNCT
ajase-2385	55	18	specific	specific	ADJ
ajase-2385	55	19	conditions	condition	NOUN
ajase-2385	55	20	,	,	PUNCT
ajase-2385	55	21	and	and	CCONJ
ajase-2385	55	22	sample	sample	NOUN
ajase-2385	55	23	periods	period	NOUN
ajase-2385	55	24	it	it	PRON
ajase-2385	55	25	becomes	become	VERB
ajase-2385	55	26	difficult	difficult	ADJ
ajase-2385	55	27	to	to	PART
ajase-2385	55	28	compare	compare	VERB
ajase-2385	55	29	different	different	ADJ
ajase-2385	55	30	models	model	NOUN
ajase-2385	55	31	.	.	PUNCT
ajase-2385	56	1	standard	standard	ADJ
ajase-2385	56	2	phillips	phillips	PROPN
ajase-2385	56	3	curve	curve	NOUN
ajase-2385	56	4	models	model	NOUN
ajase-2385	56	5	(	(	PUNCT
ajase-2385	56	6	pcm	pcm	NOUN
ajase-2385	56	7	)	)	PUNCT
ajase-2385	56	8	,	,	PUNCT
ajase-2385	56	9	which	which	PRON
ajase-2385	56	10	rely	rely	VERB
ajase-2385	56	11	on	on	ADP
ajase-2385	56	12	economic	economic	ADJ
ajase-2385	56	13	activity	activity	NOUN
ajase-2385	56	14	,	,	PUNCT
ajase-2385	56	15	have	have	AUX
ajase-2385	56	16	acted	act	VERB
ajase-2385	56	17	as	as	ADP
ajase-2385	56	18	a	a	DET
ajase-2385	56	19	basis	basis	NOUN
ajase-2385	56	20	to	to	ADP
ajase-2385	56	21	the	the	DET
ajase-2385	56	22	typical	typical	ADJ
ajase-2385	56	23	forecasting	forecasting	NOUN
ajase-2385	56	24	models	model	NOUN
ajase-2385	56	25	of	of	ADP
ajase-2385	56	26	inflation	inflation	NOUN
ajase-2385	56	27	.	.	PUNCT
ajase-2385	57	1	(	(	PUNCT
ajase-2385	57	2	stock	stock	NOUN
ajase-2385	57	3	,	,	PUNCT
ajase-2385	57	4	1999	1999	NUM
ajase-2385	57	5	)	)	PUNCT
ajase-2385	57	6	also	also	ADV
ajase-2385	57	7	argue	argue	VERB
ajase-2385	57	8	that	that	SCONJ
ajase-2385	57	9	these	these	DET
ajase-2385	57	10	pcm	pcm	NOUN
ajase-2385	57	11	based	base	VERB
ajase-2385	57	12	models	model	NOUN
ajase-2385	57	13	outperform	outperform	VERB
ajase-2385	57	14	the	the	DET
ajase-2385	57	15	traditional	traditional	ADJ
ajase-2385	57	16	inflation	inflation	NOUN
ajase-2385	57	17	forecasting	forecasting	NOUN
ajase-2385	57	18	models	model	NOUN
ajase-2385	57	19	.	.	PUNCT
ajase-2385	58	1	(	(	PUNCT
ajase-2385	58	2	atkeson	atkeson	NOUN
ajase-2385	58	3	,	,	PUNCT
ajase-2385	58	4	2001	2001	NUM
ajase-2385	58	5	)	)	PUNCT
ajase-2385	58	6	,	,	PUNCT
ajase-2385	58	7	however	however	ADV
ajase-2385	58	8	,	,	PUNCT
ajase-2385	58	9	criticize	criticize	VERB
ajase-2385	58	10	this	this	DET
ajase-2385	58	11	claim	claim	NOUN
ajase-2385	58	12	by	by	ADP
ajase-2385	58	13	showing	show	VERB
ajase-2385	58	14	that	that	SCONJ
ajase-2385	58	15	phillips	phillip	NOUN
ajase-2385	58	16	curve	curve	PROPN
ajase-2385	58	17	forecast	forecast	PROPN
ajase-2385	58	18	of	of	ADP
ajase-2385	58	19	u.s	u.s	PROPN
ajase-2385	58	20	.	.	PROPN
ajase-2385	58	21	inflation	inflation	NOUN
ajase-2385	58	22	over	over	ADP
ajase-2385	58	23	a	a	DET
ajase-2385	58	24	15	15	NUM
ajase-2385	58	25	-	-	PUNCT
ajase-2385	58	26	year	year	NOUN
ajase-2385	58	27	period	period	NOUN
ajase-2385	58	28	are	be	AUX
ajase-2385	58	29	no	no	ADV
ajase-2385	58	30	better	well	ADJ
ajase-2385	58	31	than	than	ADP
ajase-2385	58	32	those	those	PRON
ajase-2385	58	33	obtained	obtain	VERB
ajase-2385	58	34	from	from	ADP
ajase-2385	58	35	a	a	DET
ajase-2385	58	36	random	random	ADJ
ajase-2385	58	37	walk	walk	NOUN
ajase-2385	58	38	model	model	NOUN
ajase-2385	58	39	.	.	PUNCT
ajase-2385	59	1	nevertheless	nevertheless	ADV
ajase-2385	59	2	,	,	PUNCT
ajase-2385	59	3	this	this	DET
ajase-2385	59	4	instability	instability	NOUN
ajase-2385	59	5	of	of	ADP
ajase-2385	59	6	forecasting	forecasting	NOUN
ajase-2385	59	7	relationships	relationship	NOUN
ajase-2385	59	8	is	be	AUX
ajase-2385	59	9	not	not	PART
ajase-2385	59	10	limited	limit	VERB
ajase-2385	59	11	to	to	ADP
ajase-2385	59	12	traditional	traditional	ADJ
ajase-2385	59	13	phillips	phillip	NOUN
ajase-2385	59	14	curve	curve	NOUN
ajase-2385	59	15	-	-	PUNCT
ajase-2385	59	16	based	base	VERB
ajase-2385	59	17	models	model	NOUN
ajase-2385	59	18	but	but	CCONJ
ajase-2385	59	19	extends	extend	VERB
ajase-2385	59	20	to	to	ADP
ajase-2385	59	21	other	other	ADJ
ajase-2385	59	22	theoretical	theoretical	ADJ
ajase-2385	59	23	or	or	CCONJ
ajase-2385	59	24	ad	ad	X
ajase-2385	59	25	hoc	hoc	X
ajase-2385	59	26	empirical	empirical	ADJ
ajase-2385	59	27	models	model	NOUN
ajase-2385	59	28	used	use	VERB
ajase-2385	59	29	in	in	ADP
ajase-2385	59	30	the	the	DET
ajase-2385	59	31	literature	literature	NOUN
ajase-2385	59	32	as	as	ADV
ajase-2385	59	33	well	well	ADV
ajase-2385	60	1	[	[	X
ajase-2385	60	2	see	see	VERB
ajase-2385	60	3	,	,	PUNCT
ajase-2385	60	4	e.g.	e.g.	ADV
ajase-2385	60	5	,	,	PUNCT
ajase-2385	60	6	models	model	NOUN
ajase-2385	60	7	that	that	PRON
ajase-2385	60	8	include	include	VERB
ajase-2385	60	9	asset	asset	NOUN
ajase-2385	60	10	prices	price	NOUN
ajase-2385	60	11	,	,	PUNCT
ajase-2385	60	12	for	for	ADP
ajase-2385	60	13	example	example	NOUN
ajase-2385	60	14	,	,	PUNCT
ajase-2385	60	15	(	(	PUNCT
ajase-2385	60	16	marcellino	marcellino	PROPN
ajase-2385	60	17	m.	m.	PROPN
ajase-2385	60	18	s.	s.	PROPN
ajase-2385	60	19	,	,	PUNCT
ajase-2385	60	20	2000	2000	NUM
ajase-2385	60	21	)	)	PUNCT
ajase-2385	60	22	,	,	PUNCT
ajase-2385	60	23	(	(	PUNCT
ajase-2385	60	24	goodhart	goodhart	NOUN
ajase-2385	60	25	,	,	PUNCT
ajase-2385	60	26	2000	2000	NUM
ajase-2385	60	27	)	)	PUNCT
ajase-2385	60	28	(	(	PUNCT
ajase-2385	60	29	marcellino	marcellino	NOUN
ajase-2385	60	30	m.	m.	NOUN
ajase-2385	60	31	,	,	PUNCT
ajase-2385	60	32	2002	2002	NUM
ajase-2385	60	33	)	)	PUNCT
ajase-2385	60	34	,	,	PUNCT
ajase-2385	60	35	]	]	PUNCT
ajase-2385	60	36	.	.	PUNCT
ajase-2385	61	1	although	although	SCONJ
ajase-2385	61	2	forecasting	forecasting	NOUN
ajase-2385	61	3	specifications	specification	NOUN
ajase-2385	61	4	built	build	VERB
ajase-2385	61	5	adding	add	VERB
ajase-2385	61	6	one	one	NUM
ajase-2385	61	7	indicator	indicator	NOUN
ajase-2385	61	8	of	of	ADP
ajase-2385	61	9	real	real	ADJ
ajase-2385	61	10	activity	activity	NOUN
ajase-2385	61	11	at	at	ADP
ajase-2385	61	12	the	the	DET
ajase-2385	61	13	time	time	NOUN
ajase-2385	61	14	work	work	NOUN
ajase-2385	61	15	poorly	poorly	ADV
ajase-2385	61	16	and	and	CCONJ
ajase-2385	61	17	tend	tend	VERB
ajase-2385	61	18	to	to	PART
ajase-2385	61	19	be	be	AUX
ajase-2385	61	20	unstable	unstable	ADJ
ajase-2385	61	21	,	,	PUNCT
ajase-2385	61	22	some	some	DET
ajase-2385	61	23	improvements	improvement	NOUN
ajase-2385	61	24	have	have	AUX
ajase-2385	61	25	been	be	AUX
ajase-2385	61	26	documented	document	VERB
ajase-2385	61	27	by	by	ADP
ajase-2385	61	28	(	(	PUNCT
ajase-2385	61	29	cristadoro	cristadoro	NOUN
ajase-2385	61	30	,	,	PUNCT
ajase-2385	61	31	2005	2005	NUM
ajase-2385	61	32	)	)	PUNCT
ajase-2385	61	33	(	(	PUNCT
ajase-2385	61	34	wright	wright	PROPN
ajase-2385	61	35	,	,	PUNCT
ajase-2385	61	36	2003	2003	NUM
ajase-2385	61	37	)	)	PUNCT
ajase-2385	61	38	,	,	PUNCT
ajase-2385	61	39	(	(	PUNCT
ajase-2385	61	40	granger	granger	NOUN
ajase-2385	61	41	,	,	PUNCT
ajase-2385	61	42	2004	2004	NUM
ajase-2385	61	43	)	)	PUNCT
ajase-2385	61	44	,	,	PUNCT
ajase-2385	61	45	and	and	CCONJ
ajase-2385	61	46	(	(	PUNCT
ajase-2385	61	47	inoue	inoue	PROPN
ajase-2385	61	48	&	&	CCONJ
ajase-2385	61	49	kilian	kilian	PROPN
ajase-2385	61	50	,	,	PUNCT
ajase-2385	61	51	2006	2006	NUM
ajase-2385	61	52	)	)	PUNCT
ajase-2385	61	53	,	,	PUNCT
ajase-2385	61	54	using	use	VERB
ajase-2385	61	55	methods	method	NOUN
ajase-2385	61	56	that	that	PRON
ajase-2385	61	57	combine	combine	VERB
ajase-2385	61	58	information	information	NOUN
ajase-2385	61	59	obtained	obtain	VERB
ajase-2385	61	60	from	from	ADP
ajase-2385	61	61	many	many	ADJ
ajase-2385	61	62	predictors	predictor	NOUN
ajase-2385	61	63	.	.	PUNCT
ajase-2385	62	1	in	in	ADP
ajase-2385	62	2	literature	literature	NOUN
ajase-2385	62	3	,	,	PUNCT
ajase-2385	62	4	various	various	ADJ
ajase-2385	62	5	types	type	NOUN
ajase-2385	62	6	of	of	ADP
ajase-2385	62	7	cross	cross	ADJ
ajase-2385	62	8	-	-	ADJ
ajase-2385	62	9	validation	validation	ADJ
ajase-2385	62	10	methods	method	NOUN
ajase-2385	62	11	with	with	ADP
ajase-2385	62	12	traditional	traditional	ADJ
ajase-2385	62	13	forecasting	forecasting	NOUN
ajase-2385	62	14	methods	method	NOUN
ajase-2385	62	15	were	be	AUX
ajase-2385	62	16	used	use	VERB
ajase-2385	62	17	to	to	PART
ajase-2385	62	18	forecast	forecast	VERB
ajase-2385	62	19	inflation	inflation	NOUN
ajase-2385	62	20	.	.	PUNCT
ajase-2385	63	1	for	for	ADP
ajase-2385	63	2	example	example	NOUN
ajase-2385	63	3	,	,	PUNCT
ajase-2385	63	4	(	(	PUNCT
ajase-2385	63	5	bergmeir	bergmeir	PROPN
ajase-2385	63	6	&	&	CCONJ
ajase-2385	63	7	benítez	benítez	PROPN
ajase-2385	63	8	,	,	PUNCT
ajase-2385	63	9	2012)used	2012)use	VERB
ajase-2385	63	10	the	the	DET
ajase-2385	63	11	cross	cross	ADJ
ajase-2385	63	12	-	-	ADJ
ajase-2385	63	13	validation	validation	ADJ
ajase-2385	63	14	techniques	technique	NOUN
ajase-2385	63	15	with	with	ADP
ajase-2385	63	16	time	time	NOUN
ajase-2385	63	17	series	series	NOUN
ajase-2385	63	18	models	model	NOUN
ajase-2385	63	19	where	where	SCONJ
ajase-2385	63	20	the	the	DET
ajase-2385	63	21	stranded	strand	VERB
ajase-2385	63	22	5fold	5fold	NUM
ajase-2385	63	23	cross	cross	NOUN
ajase-2385	63	24	-	-	NOUN
ajase-2385	63	25	validation	validation	ADJ
ajase-2385	63	26	,	,	PUNCT
ajase-2385	63	27	blocked	block	VERB
ajase-2385	63	28	cross	cross	NOUN
ajase-2385	63	29	-	-	NOUN
ajase-2385	63	30	validation	validation	ADJ
ajase-2385	63	31	,	,	PUNCT
ajase-2385	63	32	last	last	ADJ
ajase-2385	63	33	block	block	NOUN
ajase-2385	63	34	cross	cross	NOUN
ajase-2385	63	35	-	-	NOUN
ajase-2385	63	36	validation	validation	ADJ
ajase-2385	63	37	,	,	PUNCT
ajase-2385	63	38	second	second	ADJ
ajase-2385	63	39	block	block	NOUN
ajase-2385	63	40	cross	cross	NOUN
ajase-2385	63	41	-	-	NOUN
ajase-2385	63	42	validation	validation	ADJ
ajase-2385	63	43	,	,	PUNCT
ajase-2385	63	44	and	and	CCONJ
ajase-2385	63	45	second	second	ADJ
ajase-2385	63	46	cross	cross	ADJ
ajase-2385	63	47	-	-	ADJ
ajase-2385	63	48	validation	validation	ADJ
ajase-2385	63	49	methods	method	NOUN
ajase-2385	63	50	were	be	AUX
ajase-2385	63	51	used	use	VERB
ajase-2385	63	52	.	.	PUNCT
ajase-2385	64	1	the	the	DET
ajase-2385	64	2	best	good	ADJ
ajase-2385	64	3	predicting	predicting	NOUN
ajase-2385	64	4	performance	performance	NOUN
ajase-2385	64	5	was	be	AUX
ajase-2385	64	6	achieved	achieve	VERB
ajase-2385	64	7	with	with	ADP
ajase-2385	64	8	the	the	DET
ajase-2385	64	9	blocked	block	VERB
ajase-2385	64	10	cross	cross	ADJ
ajase-2385	64	11	-	-	ADJ
ajase-2385	64	12	validation	validation	ADJ
ajase-2385	64	13	method	method	NOUN
ajase-2385	64	14	with	with	ADP
ajase-2385	64	15	respect	respect	NOUN
ajase-2385	64	16	to	to	ADP
ajase-2385	64	17	the	the	DET
ajase-2385	64	18	rmse	rmse	PROPN
ajase-2385	64	19	statistic	statistic	PROPN
ajase-2385	64	20	.	.	PUNCT
ajase-2385	65	1	machine	machine	NOUN
ajase-2385	65	2	learning	learning	NOUN
ajase-2385	65	3	models	model	NOUN
ajase-2385	65	4	are	be	AUX
ajase-2385	65	5	rarely	rarely	ADV
ajase-2385	65	6	used	use	VERB
ajase-2385	65	7	in	in	ADP
ajase-2385	65	8	forecasting	forecast	VERB
ajase-2385	65	9	inflation	inflation	NOUN
ajase-2385	65	10	data	datum	NOUN
ajase-2385	65	11	.	.	PUNCT
ajase-2385	66	1	(	(	PUNCT
ajase-2385	66	2	volkan	volkan	PROPN
ajase-2385	66	3	et	et	PROPN
ajase-2385	66	4	al	al	PROPN
ajase-2385	66	5	.	.	PROPN
ajase-2385	66	6	,	,	PUNCT
ajase-2385	66	7	2018	2018	NUM
ajase-2385	66	8	)	)	PUNCT
ajase-2385	66	9	forecasted	forecast	VERB
ajase-2385	66	10	the	the	DET
ajase-2385	66	11	core	core	NOUN
ajase-2385	66	12	and	and	CCONJ
ajase-2385	66	13	non	non	ADJ
ajase-2385	66	14	-	-	ADJ
ajase-2385	66	15	core	core	ADJ
ajase-2385	66	16	versions	version	NOUN
ajase-2385	66	17	of	of	ADP
ajase-2385	66	18	inflation	inflation	NOUN
ajase-2385	66	19	in	in	ADP
ajase-2385	66	20	the	the	DET
ajase-2385	66	21	usa	usa	PROPN
ajase-2385	66	22	by	by	ADP
ajase-2385	66	23	using	use	VERB
ajase-2385	66	24	univariate	univariate	ADJ
ajase-2385	66	25	auto	auto	NOUN
ajase-2385	66	26	regressive	regressive	ADJ
ajase-2385	66	27	distributed	distribute	VERB
ajase-2385	66	28	lag	lag	NOUN
ajase-2385	66	29	(	(	PUNCT
ajase-2385	66	30	ardl	ardl	NOUN
ajase-2385	66	31	)	)	PUNCT
ajase-2385	66	32	,	,	PUNCT
ajase-2385	66	33	multivariate	multivariate	NOUN
ajase-2385	66	34	time	time	NOUN
ajase-2385	66	35	series	series	PROPN
ajase-2385	66	36	(	(	PUNCT
ajase-2385	66	37	var	var	PROPN
ajase-2385	66	38	)	)	PUNCT
ajase-2385	66	39	,	,	PUNCT
ajase-2385	66	40	svr	svr	PROPN
ajase-2385	66	41	,	,	PUNCT
ajase-2385	66	42	k	k	PROPN
ajase-2385	66	43	-	-	PUNCT
ajase-2385	66	44	nearest	near	ADJ
ajase-2385	66	45	neighbour	neighbour	NOUN
ajase-2385	66	46	,	,	PUNCT
ajase-2385	66	47	and	and	CCONJ
ajase-2385	66	48	artificial	artificial	ADJ
ajase-2385	66	49	neural	neural	ADJ
ajase-2385	66	50	network	network	NOUN
ajase-2385	66	51	models	model	NOUN
ajase-2385	66	52	.	.	PUNCT
ajase-2385	67	1	according	accord	VERB
ajase-2385	67	2	to	to	ADP
ajase-2385	67	3	their	their	PRON
ajase-2385	67	4	results	result	NOUN
ajase-2385	67	5	,	,	PUNCT
ajase-2385	67	6	ardl	ardl	NOUN
ajase-2385	67	7	provided	provide	VERB
ajase-2385	67	8	the	the	DET
ajase-2385	67	9	highest	high	ADJ
ajase-2385	67	10	prediction	prediction	NOUN
ajase-2385	67	11	accuracy	accuracy	NOUN
ajase-2385	67	12	for	for	ADP
ajase-2385	67	13	forecasting	forecast	VERB
ajase-2385	67	14	core	core	NOUN
ajase-2385	67	15	-	-	PUNCT
ajase-2385	67	16	cpi	cpi	NOUN
ajase-2385	67	17	inflation	inflation	NOUN
ajase-2385	67	18	,	,	PUNCT
ajase-2385	67	19	while	while	SCONJ
ajase-2385	67	20	svr	svr	PROPN
ajase-2385	67	21	outperformed	outperform	VERB
ajase-2385	67	22	the	the	DET
ajase-2385	67	23	other	other	ADJ
ajase-2385	67	24	models	model	NOUN
ajase-2385	67	25	in	in	ADP
ajase-2385	67	26	forecasting	forecast	VERB
ajase-2385	67	27	core	core	NOUN
ajase-2385	67	28	inflation	inflation	NOUN
ajase-2385	67	29	.	.	PUNCT
ajase-2385	68	1	all	all	DET
ajase-2385	68	2	these	these	DET
ajase-2385	68	3	machine	machine	NOUN
ajase-2385	68	4	learning	learning	NOUN
ajase-2385	68	5	models	model	NOUN
ajase-2385	68	6	work	work	VERB
ajase-2385	68	7	better	well	ADV
ajase-2385	68	8	with	with	ADP
ajase-2385	68	9	more	more	ADV
ajase-2385	68	10	volatile	volatile	ADJ
ajase-2385	68	11	and	and	CCONJ
ajase-2385	68	12	irregular	irregular	ADJ
ajase-2385	68	13	series	series	NOUN
ajase-2385	68	14	.	.	PUNCT
ajase-2385	69	1	in	in	ADP
ajase-2385	69	2	this	this	DET
ajase-2385	69	3	study	study	NOUN
ajase-2385	69	4	,	,	PUNCT
ajase-2385	69	5	we	we	PRON
ajase-2385	69	6	conducted	conduct	VERB
ajase-2385	69	7	a	a	DET
ajase-2385	69	8	simulation	simulation	NOUN
ajase-2385	69	9	to	to	PART
ajase-2385	69	10	evaluate	evaluate	VERB
ajase-2385	69	11	the	the	DET
ajase-2385	69	12	performance	performance	NOUN
ajase-2385	69	13	of	of	ADP
ajase-2385	69	14	four	four	NUM
ajase-2385	69	15	different	different	ADJ
ajase-2385	69	16	supervised	supervised	ADJ
ajase-2385	69	17	machine	machine	NOUN
ajase-2385	69	18	learning	learning	NOUN
ajase-2385	69	19	models	model	NOUN
ajase-2385	69	20	,	,	PUNCT
ajase-2385	69	21	lr	lr	PROPN
ajase-2385	69	22	,	,	PUNCT
ajase-2385	69	23	brr	brr	PROPN
ajase-2385	69	24	,	,	PUNCT
ajase-2385	69	25	svr	svr	PROPN
ajase-2385	69	26	,	,	PUNCT
ajase-2385	69	27	and	and	CCONJ
ajase-2385	69	28	rfr	rfr	PROPN
ajase-2385	69	29	,	,	PUNCT
ajase-2385	69	30	for	for	ADP
ajase-2385	69	31	inflation	inflation	NOUN
ajase-2385	69	32	forecasting	forecasting	NOUN
ajase-2385	69	33	.	.	PUNCT
ajase-2385	70	1	the	the	DET
ajase-2385	70	2	simulation	simulation	NOUN
ajase-2385	70	3	involved	involve	VERB
ajase-2385	70	4	training	training	NOUN
ajase-2385	70	5	and	and	CCONJ
ajase-2385	70	6	testing	test	VERB
ajase-2385	70	7	each	each	DET
ajase-2385	70	8	model	model	NOUN
ajase-2385	70	9	using	use	VERB
ajase-2385	70	10	two	two	NUM
ajase-2385	70	11	types	type	NOUN
ajase-2385	70	12	of	of	ADP
ajase-2385	70	13	cross	cross	ADJ
ajase-2385	70	14	-	-	ADJ
ajase-2385	70	15	validation	validation	ADJ
ajase-2385	70	16	methods	method	NOUN
ajase-2385	70	17	,	,	PUNCT
ajase-2385	70	18	walk	walk	VERB
ajase-2385	70	19	forward	forward	ADV
ajase-2385	70	20	validation	validation	NOUN
ajase-2385	70	21	(	(	PUNCT
ajase-2385	70	22	wfv	wfv	NOUN
ajase-2385	70	23	)	)	PUNCT
ajase-2385	70	24	and	and	CCONJ
ajase-2385	70	25	k	k	ADJ
ajase-2385	70	26	-	-	ADJ
ajase-2385	70	27	fold	fold	ADJ
ajase-2385	70	28	cross	cross	NOUN
ajase-2385	70	29	-	-	NOUN
ajase-2385	70	30	validation	validation	ADJ
ajase-2385	70	31	(	(	PUNCT
ajase-2385	70	32	cvk	cvk	ADJ
ajase-2385	70	33	)	)	PUNCT
ajase-2385	70	34	,	,	PUNCT
ajase-2385	70	35	to	to	PART
ajase-2385	70	36	estimate	estimate	VERB
ajase-2385	70	37	the	the	DET
ajase-2385	70	38	models	model	NOUN
ajase-2385	70	39	’	'	PUNCT
ajase-2385	70	40	hyperparameters	hyperparameter	NOUN
ajase-2385	70	41	.	.	PUNCT
ajase-2385	71	1	to	to	PART
ajase-2385	71	2	compare	compare	VERB
ajase-2385	71	3	the	the	DET
ajase-2385	71	4	models	model	NOUN
ajase-2385	71	5	and	and	CCONJ
ajase-2385	71	6	their	their	PRON
ajase-2385	71	7	performances	performance	NOUN
ajase-2385	71	8	,	,	PUNCT
ajase-2385	71	9	we	we	PRON
ajase-2385	71	10	used	use	VERB
ajase-2385	71	11	the	the	DET
ajase-2385	71	12	mean	mean	ADJ
ajase-2385	71	13	absolute	absolute	ADJ
ajase-2385	71	14	percentage	percentage	NOUN
ajase-2385	71	15	error	error	NOUN
ajase-2385	71	16	(	(	PUNCT
ajase-2385	71	17	mape	mape	NOUN
ajase-2385	71	18	)	)	PUNCT
ajase-2385	71	19	statistic	statistic	NOUN
ajase-2385	71	20	.	.	PUNCT
ajase-2385	72	1	we	we	PRON
ajase-2385	72	2	also	also	ADV
ajase-2385	72	3	evaluated	evaluate	VERB
ajase-2385	72	4	the	the	DET
ajase-2385	72	5	stability	stability	NOUN
ajase-2385	72	6	and	and	CCONJ
ajase-2385	72	7	consistency	consistency	NOUN
ajase-2385	72	8	of	of	ADP
ajase-2385	72	9	each	each	DET
ajase-2385	72	10	model	model	NOUN
ajase-2385	72	11	’s	’s	PART
ajase-2385	72	12	performance	performance	NOUN
ajase-2385	72	13	across	across	ADP
ajase-2385	72	14	different	different	ADJ
ajase-2385	72	15	time	time	NOUN
ajase-2385	72	16	splits	split	VERB
ajase-2385	72	17	using	use	VERB
ajase-2385	72	18	the	the	DET
ajase-2385	72	19	mean	mean	ADJ
ajase-2385	72	20	root	root	NOUN
ajase-2385	72	21	mean	mean	VERB
ajase-2385	72	22	square	square	ADJ
ajase-2385	72	23	error	error	NOUN
ajase-2385	72	24	(	(	PUNCT
ajase-2385	72	25	rmse	rmse	NOUN
ajase-2385	72	26	)	)	PUNCT
ajase-2385	72	27	metric	metric	NOUN
ajase-2385	72	28	.	.	PUNCT
ajase-2385	73	1	overall	overall	ADV
ajase-2385	73	2	,	,	PUNCT
ajase-2385	73	3	our	our	PRON
ajase-2385	73	4	simulation	simulation	NOUN
ajase-2385	73	5	aimed	aim	VERB
ajase-2385	73	6	to	to	PART
ajase-2385	73	7	identify	identify	VERB
ajase-2385	73	8	the	the	DET
ajase-2385	73	9	best	good	ADJ
ajase-2385	73	10	machine	machine	NOUN
ajase-2385	73	11	learning	learning	NOUN
ajase-2385	73	12	model	model	NOUN
ajase-2385	73	13	for	for	ADP
ajase-2385	73	14	forecasting	forecast	VERB
ajase-2385	73	15	the	the	DET
ajase-2385	73	16	monthly	monthly	ADJ
ajase-2385	73	17	mean	mean	NOUN
ajase-2385	73	18	inflation	inflation	NOUN
ajase-2385	73	19	rate	rate	NOUN
ajase-2385	73	20	in	in	ADP
ajase-2385	73	21	sri	sri	PROPN
ajase-2385	73	22	lanka	lanka	PROPN
ajase-2385	73	23	,	,	PUNCT
ajase-2385	73	24	considering	consider	VERB
ajase-2385	73	25	different	different	ADJ
ajase-2385	73	26	cross	cross	ADJ
ajase-2385	73	27	-	-	ADJ
ajase-2385	73	28	validation	validation	ADJ
ajase-2385	73	29	methods	method	NOUN
ajase-2385	73	30	and	and	CCONJ
ajase-2385	73	31	performance	performance	NOUN
ajase-2385	73	32	metrics	metric	NOUN
ajase-2385	73	33	.	.	PUNCT
ajase-2385	74	1	our	our	PRON
ajase-2385	74	2	results	result	NOUN
ajase-2385	74	3	provide	provide	VERB
ajase-2385	74	4	useful	useful	ADJ
ajase-2385	74	5	insights	insight	NOUN
ajase-2385	74	6	into	into	ADP
ajase-2385	74	7	the	the	DET
ajase-2385	74	8	effectiveness	effectiveness	NOUN
ajase-2385	74	9	of	of	ADP
ajase-2385	74	10	different	different	ADJ
ajase-2385	74	11	machine	machine	NOUN
ajase-2385	74	12	learning	learning	NOUN
ajase-2385	74	13	models	model	NOUN
ajase-2385	74	14	for	for	ADP
ajase-2385	74	15	time	time	NOUN
ajase-2385	74	16	-	-	PUNCT
ajase-2385	74	17	series	series	NOUN
ajase-2385	74	18	data	datum	NOUN
ajase-2385	74	19	and	and	CCONJ
ajase-2385	74	20	can	can	AUX
ajase-2385	74	21	guide	guide	VERB
ajase-2385	74	22	practitioners	practitioner	NOUN
ajase-2385	74	23	in	in	ADP
ajase-2385	74	24	selecting	select	VERB
ajase-2385	74	25	the	the	DET
ajase-2385	74	26	most	most	ADV
ajase-2385	74	27	suitable	suitable	ADJ
ajase-2385	74	28	model	model	NOUN
ajase-2385	74	29	for	for	ADP
ajase-2385	74	30	their	their	PRON
ajase-2385	74	31	specific	specific	ADJ
ajase-2385	74	32	application	application	NOUN
ajase-2385	74	33	.	.	PUNCT
ajase-2385	75	1	the	the	DET
ajase-2385	75	2	layout	layout	NOUN
ajase-2385	75	3	of	of	ADP
ajase-2385	75	4	this	this	DET
ajase-2385	75	5	article	article	NOUN
ajase-2385	75	6	is	be	AUX
ajase-2385	75	7	as	as	SCONJ
ajase-2385	75	8	follows	follow	VERB
ajase-2385	75	9	.	.	PUNCT
ajase-2385	76	1	section	section	NOUN
ajase-2385	76	2	2	2	NUM
ajase-2385	76	3	provides	provide	VERB
ajase-2385	76	4	a	a	DET
ajase-2385	76	5	brief	brief	ADJ
ajase-2385	76	6	overview	overview	NOUN
ajase-2385	76	7	of	of	ADP
ajase-2385	76	8	machine	machine	NOUN
ajase-2385	76	9	learning	learning	NOUN
ajase-2385	76	10	models	model	NOUN
ajase-2385	76	11	,	,	PUNCT
ajase-2385	76	12	crossvalidation	crossvalidation	NOUN
ajase-2385	76	13	techniques	technique	NOUN
ajase-2385	76	14	and	and	CCONJ
ajase-2385	76	15	error	error	NOUN
ajase-2385	76	16	calculated	calculate	VERB
ajase-2385	76	17	statistics	statistic	NOUN
ajase-2385	76	18	,	,	PUNCT
ajase-2385	76	19	section	section	NOUN
ajase-2385	76	20	3	3	NUM
ajase-2385	76	21	presents	present	VERB
ajase-2385	76	22	the	the	DET
ajase-2385	76	23	inflation	inflation	NOUN
ajase-2385	76	24	data	datum	NOUN
ajase-2385	76	25	set	set	VERB
ajase-2385	76	26	and	and	CCONJ
ajase-2385	76	27	the	the	DET
ajase-2385	76	28	four	four	NUM
ajase-2385	76	29	covariates	covariate	NOUN
ajase-2385	76	30	that	that	PRON
ajase-2385	76	31	are	be	AUX
ajase-2385	76	32	used	use	VERB
ajase-2385	76	33	in	in	ADP
ajase-2385	76	34	simulation	simulation	NOUN
ajase-2385	76	35	study	study	NOUN
ajase-2385	76	36	,	,	PUNCT
ajase-2385	76	37	the	the	DET
ajase-2385	76	38	results	result	NOUN
ajase-2385	76	39	of	of	ADP
ajase-2385	76	40	a	a	DET
ajase-2385	76	41	simulation	simulation	NOUN
ajase-2385	76	42	study	study	NOUN
ajase-2385	76	43	and	and	CCONJ
ajase-2385	76	44	algorithms	algorithm	NOUN
ajase-2385	76	45	are	be	AUX
ajase-2385	76	46	presented	present	VERB
ajase-2385	76	47	in	in	ADP
ajase-2385	76	48	section	section	NOUN
ajase-2385	76	49	4	4	NUM
ajase-2385	76	50	,	,	PUNCT
ajase-2385	76	51	and	and	CCONJ
ajase-2385	76	52	section	section	NOUN
ajase-2385	76	53	5	5	NUM
ajase-2385	76	54	is	be	AUX
ajase-2385	76	55	devoted	devote	VERB
ajase-2385	76	56	to	to	ADP
ajase-2385	76	57	the	the	DET
ajase-2385	76	58	conclusion	conclusion	NOUN
ajase-2385	76	59	and	and	CCONJ
ajase-2385	76	60	future	future	ADJ
ajase-2385	76	61	work	work	NOUN
ajase-2385	76	62	.	.	PUNCT
ajase-2385	77	1	pa	pa	PROPN
ajase-2385	77	2	ge	ge	PROPN
ajase-2385	77	3	53	53	NUM
ajase-2385	77	4	https://journals.e-palli.com/home/index.php/ajase	https://journals.e-palli.com/home/index.php/ajase	PROPN
ajase-2385	77	5	am	be	AUX
ajase-2385	77	6	.	.	PUNCT
ajase-2385	78	1	j.	j.	PROPN
ajase-2385	78	2	appl	appl	PROPN
ajase-2385	78	3	.	.	PROPN
ajase-2385	79	1	stat	stat	PROPN
ajase-2385	79	2	.	.	PUNCT
ajase-2385	80	1	econ	econ	PROPN
ajase-2385	80	2	.	.	PUNCT
ajase-2385	81	1	3(1	3(1	NUM
ajase-2385	81	2	)	)	PUNCT
ajase-2385	81	3	51	51	NUM
ajase-2385	81	4	-	-	SYM
ajase-2385	81	5	60	60	NUM
ajase-2385	81	6	,	,	PUNCT
ajase-2385	81	7	2024	2024	NUM
ajase-2385	81	8	materials	material	NOUN
ajase-2385	81	9	and	and	CCONJ
ajase-2385	81	10	methods	method	NOUN
ajase-2385	81	11	models	model	NOUN
ajase-2385	81	12	in	in	ADP
ajase-2385	81	13	this	this	DET
ajase-2385	81	14	subsection	subsection	NOUN
ajase-2385	81	15	,	,	PUNCT
ajase-2385	81	16	we	we	PRON
ajase-2385	81	17	briefly	briefly	ADV
ajase-2385	81	18	explain	explain	VERB
ajase-2385	81	19	supervised	supervised	ADJ
ajase-2385	81	20	machine	machine	NOUN
ajase-2385	81	21	learning	learning	NOUN
ajase-2385	81	22	models	model	NOUN
ajase-2385	81	23	,	,	PUNCT
ajase-2385	81	24	which	which	PRON
ajase-2385	81	25	are	be	AUX
ajase-2385	81	26	used	use	VERB
ajase-2385	81	27	to	to	PART
ajase-2385	81	28	forecast	forecast	VERB
ajase-2385	81	29	inflation	inflation	NOUN
ajase-2385	81	30	data	datum	NOUN
ajase-2385	81	31	,	,	PUNCT
ajase-2385	81	32	and	and	CCONJ
ajase-2385	81	33	two	two	NUM
ajase-2385	81	34	cross	cross	NOUN
ajase-2385	81	35	validation	validation	NOUN
ajase-2385	81	36	techniques	technique	NOUN
ajase-2385	81	37	.	.	PUNCT
ajase-2385	82	1	lasso	lasso	NOUN
ajase-2385	82	2	regression	regression	NOUN
ajase-2385	82	3	(	(	PUNCT
ajase-2385	82	4	lr	lr	PROPN
ajase-2385	82	5	)	)	PUNCT
ajase-2385	82	6	according	accord	VERB
ajase-2385	82	7	to	to	ADP
ajase-2385	82	8	(	(	PUNCT
ajase-2385	82	9	ogutu	ogutu	X
ajase-2385	82	10	et	et	PROPN
ajase-2385	82	11	al	al	PROPN
ajase-2385	82	12	.	.	PROPN
ajase-2385	82	13	,	,	PUNCT
ajase-2385	82	14	2012	2012	NUM
ajase-2385	82	15	)	)	PUNCT
ajase-2385	82	16	,	,	PUNCT
ajase-2385	82	17	“	"	PUNCT
ajase-2385	82	18	lasso	lasso	NOUN
ajase-2385	82	19	”	"	PUNCT
ajase-2385	82	20	,	,	PUNCT
ajase-2385	82	21	“	"	PUNCT
ajase-2385	82	22	least	least	ADJ
ajase-2385	82	23	absolute	absolute	ADJ
ajase-2385	82	24	shrinkage	shrinkage	NOUN
ajase-2385	82	25	and	and	CCONJ
ajase-2385	82	26	selection	selection	NOUN
ajase-2385	82	27	operator	operator	NOUN
ajase-2385	82	28	”	"	PUNCT
ajase-2385	82	29	,	,	PUNCT
ajase-2385	82	30	is	be	AUX
ajase-2385	82	31	an	an	DET
ajase-2385	82	32	l1	l1	PROPN
ajase-2385	82	33	regularization	regularization	NOUN
ajase-2385	82	34	technique	technique	NOUN
ajase-2385	82	35	that	that	PRON
ajase-2385	82	36	uses	use	VERB
ajase-2385	82	37	shrinkage	shrinkage	NOUN
ajase-2385	82	38	,	,	PUNCT
ajase-2385	82	39	and	and	CCONJ
ajase-2385	82	40	because	because	SCONJ
ajase-2385	82	41	it	it	PRON
ajase-2385	82	42	automatically	automatically	ADV
ajase-2385	82	43	performs	perform	VERB
ajase-2385	82	44	feature	feature	NOUN
ajase-2385	82	45	selection	selection	NOUN
ajase-2385	82	46	,	,	PUNCT
ajase-2385	82	47	lasso	lasso	NOUN
ajase-2385	82	48	can	can	AUX
ajase-2385	82	49	use	use	VERB
ajase-2385	82	50	a	a	DET
ajase-2385	82	51	greater	great	ADJ
ajase-2385	82	52	number	number	NOUN
ajase-2385	82	53	of	of	ADP
ajase-2385	82	54	variables	variable	NOUN
ajase-2385	82	55	.	.	PUNCT
ajase-2385	83	1	the	the	DET
ajase-2385	83	2	lr	lr	PROPN
ajase-2385	83	3	parameter	parameter	NOUN
ajase-2385	83	4	estimate	estimate	NOUN
ajase-2385	83	5	can	can	AUX
ajase-2385	83	6	be	be	AUX
ajase-2385	83	7	defined	define	VERB
ajase-2385	83	8	as	as	SCONJ
ajase-2385	83	9	follows	follow	VERB
ajase-2385	83	10	;	;	PUNCT
ajase-2385	83	11	(	(	PUNCT
ajase-2385	83	12	1	1	X
ajase-2385	83	13	)	)	PUNCT
ajase-2385	83	14	effectiveness	effectiveness	NOUN
ajase-2385	83	15	of	of	ADP
ajase-2385	83	16	a	a	DET
ajase-2385	83	17	machine	machine	NOUN
ajase-2385	83	18	learning	learn	VERB
ajase-2385	83	19	model	model	NOUN
ajase-2385	83	20	.	.	PUNCT
ajase-2385	84	1	it	it	PRON
ajase-2385	84	2	is	be	AUX
ajase-2385	84	3	based	base	VERB
ajase-2385	84	4	on	on	ADP
ajase-2385	84	5	re	re	VERB
ajase-2385	84	6	-	-	ADJ
ajase-2385	84	7	sampling	sample	VERB
ajase-2385	84	8	training	training	NOUN
ajase-2385	84	9	data	datum	NOUN
ajase-2385	84	10	to	to	PART
ajase-2385	84	11	train	train	VERB
ajase-2385	84	12	and	and	CCONJ
ajase-2385	84	13	test	test	NOUN
ajase-2385	84	14	groups	group	NOUN
ajase-2385	84	15	and	and	CCONJ
ajase-2385	84	16	evaluating	evaluate	VERB
ajase-2385	84	17	model	model	NOUN
ajase-2385	84	18	performance	performance	NOUN
ajase-2385	84	19	under	under	ADP
ajase-2385	84	20	over	over	ADV
ajase-2385	84	21	-	-	PUNCT
ajase-2385	84	22	fitting	fit	VERB
ajase-2385	84	23	and	and	CCONJ
ajase-2385	84	24	under	under	ADV
ajase-2385	84	25	-	-	PUNCT
ajase-2385	84	26	fitting	fit	VERB
ajase-2385	84	27	conditions	condition	NOUN
ajase-2385	84	28	.	.	PUNCT
ajase-2385	85	1	in	in	ADP
ajase-2385	85	2	this	this	DET
ajase-2385	85	3	study	study	NOUN
ajase-2385	85	4	,	,	PUNCT
ajase-2385	85	5	we	we	PRON
ajase-2385	85	6	use	use	VERB
ajase-2385	85	7	two	two	NUM
ajase-2385	85	8	types	type	NOUN
ajase-2385	85	9	of	of	ADP
ajase-2385	85	10	cross	cross	NOUN
ajase-2385	85	11	validation	validation	NOUN
ajase-2385	85	12	methods	method	NOUN
ajase-2385	85	13	,	,	PUNCT
ajase-2385	85	14	namely	namely	ADV
ajase-2385	85	15	,	,	PUNCT
ajase-2385	85	16	k	k	ADJ
ajase-2385	85	17	-	-	ADJ
ajase-2385	85	18	fold	fold	ADJ
ajase-2385	85	19	crossvalidation	crossvalidation	NOUN
ajase-2385	85	20	and	and	CCONJ
ajase-2385	85	21	walk	walk	VERB
ajase-2385	85	22	forward	forward	ADV
ajase-2385	85	23	validation	validation	NOUN
ajase-2385	85	24	.	.	PUNCT
ajase-2385	86	1	k	k	ADJ
ajase-2385	86	2	-	-	PUNCT
ajase-2385	86	3	folds	fold	NOUN
ajase-2385	86	4	cross	cross	NOUN
ajase-2385	86	5	validation	validation	NOUN
ajase-2385	86	6	(	(	PUNCT
ajase-2385	86	7	cvk	cvk	ADJ
ajase-2385	86	8	)	)	PUNCT
ajase-2385	86	9	in	in	ADP
ajase-2385	86	10	regression	regression	NOUN
ajase-2385	86	11	and	and	CCONJ
ajase-2385	86	12	classification	classification	NOUN
ajase-2385	86	13	settings	setting	NOUN
ajase-2385	86	14	,	,	PUNCT
ajase-2385	86	15	the	the	DET
ajase-2385	86	16	k	k	ADJ
ajase-2385	86	17	-	-	ADJ
ajase-2385	86	18	fold	fold	ADJ
ajase-2385	86	19	cross	cross	NOUN
ajase-2385	86	20	-	-	NOUN
ajase-2385	86	21	validation	validation	ADJ
ajase-2385	86	22	(	(	PUNCT
ajase-2385	86	23	trevor	trevor	NOUN
ajase-2385	86	24	hastie	hastie	PROPN
ajase-2385	86	25	,	,	PUNCT
ajase-2385	86	26	2009	2009	NUM
ajase-2385	86	27	)	)	PUNCT
ajase-2385	86	28	(	(	PUNCT
ajase-2385	86	29	cvk	cvk	ADJ
ajase-2385	86	30	)	)	PUNCT
ajase-2385	86	31	technique	technique	NOUN
ajase-2385	86	32	is	be	AUX
ajase-2385	86	33	commonly	commonly	ADV
ajase-2385	86	34	used	use	VERB
ajase-2385	86	35	due	due	ADP
ajase-2385	86	36	to	to	ADP
ajase-2385	86	37	its	its	PRON
ajase-2385	86	38	simplicity	simplicity	NOUN
ajase-2385	86	39	,	,	PUNCT
ajase-2385	86	40	fairness	fairness	NOUN
ajase-2385	86	41	,	,	PUNCT
ajase-2385	86	42	and	and	CCONJ
ajase-2385	86	43	high	high	ADJ
ajase-2385	86	44	effectiveness	effectiveness	NOUN
ajase-2385	86	45	.	.	PUNCT
ajase-2385	87	1	the	the	DET
ajase-2385	87	2	dataset	dataset	NOUN
ajase-2385	87	3	is	be	AUX
ajase-2385	87	4	divided	divide	VERB
ajase-2385	87	5	into	into	ADP
ajase-2385	87	6	k	k	PROPN
ajase-2385	87	7	intervals	interval	NOUN
ajase-2385	87	8	,	,	PUNCT
ajase-2385	87	9	and	and	CCONJ
ajase-2385	87	10	one	one	NUM
ajase-2385	87	11	subinterval	subinterval	NOUN
ajase-2385	87	12	is	be	AUX
ajase-2385	87	13	used	use	VERB
ajase-2385	87	14	as	as	ADP
ajase-2385	87	15	test	test	NOUN
ajase-2385	87	16	data	datum	NOUN
ajase-2385	87	17	while	while	SCONJ
ajase-2385	87	18	the	the	DET
ajase-2385	87	19	remaining	remain	VERB
ajase-2385	87	20	k-1	k-1	PROPN
ajase-2385	87	21	intervals	interval	NOUN
ajase-2385	87	22	are	be	AUX
ajase-2385	87	23	used	use	VERB
ajase-2385	87	24	as	as	ADP
ajase-2385	87	25	training	training	NOUN
ajase-2385	87	26	data	datum	NOUN
ajase-2385	87	27	.	.	PUNCT
ajase-2385	88	1	by	by	ADP
ajase-2385	88	2	fitting	fit	VERB
ajase-2385	88	3	the	the	DET
ajase-2385	88	4	model	model	NOUN
ajase-2385	88	5	k	k	PROPN
ajase-2385	88	6	times	times	PROPN
ajase-2385	88	7	and	and	CCONJ
ajase-2385	88	8	selecting	select	VERB
ajase-2385	88	9	the	the	DET
ajase-2385	88	10	optimal	optimal	ADJ
ajase-2385	88	11	k	k	PROPN
ajase-2385	88	12	value	value	NOUN
ajase-2385	88	13	that	that	PRON
ajase-2385	88	14	minimizes	minimize	VERB
ajase-2385	88	15	the	the	DET
ajase-2385	88	16	root	root	NOUN
ajase-2385	88	17	mean	mean	ADJ
ajase-2385	88	18	square	square	ADJ
ajase-2385	88	19	error	error	NOUN
ajase-2385	88	20	(	(	PUNCT
ajase-2385	88	21	rmse	rmse	NOUN
ajase-2385	88	22	)	)	PUNCT
ajase-2385	88	23	,	,	PUNCT
ajase-2385	88	24	we	we	PRON
ajase-2385	88	25	can	can	AUX
ajase-2385	88	26	evaluate	evaluate	VERB
ajase-2385	88	27	the	the	DET
ajase-2385	88	28	model	model	NOUN
ajase-2385	88	29	’s	’s	PART
ajase-2385	88	30	performance	performance	NOUN
ajase-2385	88	31	.	.	PUNCT
ajase-2385	89	1	walk	walk	VERB
ajase-2385	89	2	forward	forward	ADV
ajase-2385	89	3	validation	validation	NOUN
ajase-2385	89	4	(	(	PUNCT
ajase-2385	89	5	wfv	wfv	NOUN
ajase-2385	89	6	)	)	PUNCT
ajase-2385	89	7	walk	walk	VERB
ajase-2385	89	8	forward	forward	ADV
ajase-2385	89	9	validation	validation	NOUN
ajase-2385	89	10	(	(	PUNCT
ajase-2385	89	11	wfv	wfv	NOUN
ajase-2385	89	12	)	)	PUNCT
ajase-2385	89	13	,	,	PUNCT
ajase-2385	89	14	also	also	ADV
ajase-2385	89	15	known	know	VERB
ajase-2385	89	16	as	as	ADP
ajase-2385	89	17	time	time	NOUN
ajase-2385	89	18	-	-	PUNCT
ajase-2385	89	19	series	series	NOUN
ajase-2385	89	20	validation	validation	NOUN
ajase-2385	89	21	,	,	PUNCT
ajase-2385	89	22	is	be	AUX
ajase-2385	89	23	a	a	DET
ajase-2385	89	24	technique	technique	NOUN
ajase-2385	89	25	commonly	commonly	ADV
ajase-2385	89	26	used	use	VERB
ajase-2385	89	27	for	for	ADP
ajase-2385	89	28	evaluating	evaluate	VERB
ajase-2385	89	29	time	time	NOUN
ajase-2385	89	30	series	series	PROPN
ajase-2385	89	31	data	data	PROPN
ajase-2385	89	32	.	.	PUNCT
ajase-2385	90	1	in	in	ADP
ajase-2385	90	2	this	this	DET
ajase-2385	90	3	method	method	NOUN
ajase-2385	90	4	,	,	PUNCT
ajase-2385	90	5	the	the	DET
ajase-2385	90	6	entire	entire	ADJ
ajase-2385	90	7	dataset	dataset	NOUN
ajase-2385	90	8	is	be	AUX
ajase-2385	90	9	divided	divide	VERB
ajase-2385	90	10	into	into	ADP
ajase-2385	90	11	k	k	PROPN
ajase-2385	90	12	intervals	interval	NOUN
ajase-2385	90	13	.	.	PUNCT
ajase-2385	91	1	the	the	DET
ajase-2385	91	2	model	model	NOUN
ajase-2385	91	3	is	be	AUX
ajase-2385	91	4	trained	train	VERB
ajase-2385	91	5	on	on	ADP
ajase-2385	91	6	the	the	DET
ajase-2385	91	7	first	first	ADJ
ajase-2385	91	8	interval	interval	NOUN
ajase-2385	91	9	and	and	CCONJ
ajase-2385	91	10	tested	test	VERB
ajase-2385	91	11	on	on	ADP
ajase-2385	91	12	the	the	DET
ajase-2385	91	13	second	second	NOUN
ajase-2385	91	14	.	.	PUNCT
ajase-2385	92	1	then	then	ADV
ajase-2385	92	2	,	,	PUNCT
ajase-2385	92	3	the	the	DET
ajase-2385	92	4	first	first	ADJ
ajase-2385	92	5	two	two	NUM
ajase-2385	92	6	intervals	interval	NOUN
ajase-2385	92	7	are	be	AUX
ajase-2385	92	8	combined	combine	VERB
ajase-2385	92	9	to	to	PART
ajase-2385	92	10	train	train	VERB
ajase-2385	92	11	the	the	DET
ajase-2385	92	12	model	model	NOUN
ajase-2385	92	13	,	,	PUNCT
ajase-2385	92	14	which	which	PRON
ajase-2385	92	15	is	be	AUX
ajase-2385	92	16	tested	test	VERB
ajase-2385	92	17	on	on	ADP
ajase-2385	92	18	the	the	DET
ajase-2385	92	19	third	third	NOUN
ajase-2385	92	20	.	.	PUNCT
ajase-2385	93	1	this	this	DET
ajase-2385	93	2	process	process	NOUN
ajase-2385	93	3	is	be	AUX
ajase-2385	93	4	repeated	repeat	VERB
ajase-2385	93	5	until	until	SCONJ
ajase-2385	93	6	the	the	DET
ajase-2385	93	7	first	first	ADJ
ajase-2385	93	8	k	k	PROPN
ajase-2385	93	9	1	1	NUM
ajase-2385	93	10	intervals	interval	NOUN
ajase-2385	93	11	are	be	AUX
ajase-2385	93	12	used	use	VERB
ajase-2385	93	13	for	for	ADP
ajase-2385	93	14	training	training	NOUN
ajase-2385	93	15	,	,	PUNCT
ajase-2385	93	16	and	and	CCONJ
ajase-2385	93	17	the	the	DET
ajase-2385	93	18	remaining	remain	VERB
ajase-2385	93	19	interval	interval	NOUN
ajase-2385	93	20	is	be	AUX
ajase-2385	93	21	used	use	VERB
ajase-2385	93	22	for	for	ADP
ajase-2385	93	23	testing	testing	NOUN
ajase-2385	93	24	.	.	PUNCT
ajase-2385	94	1	at	at	ADP
ajase-2385	94	2	each	each	DET
ajase-2385	94	3	step	step	NOUN
ajase-2385	94	4	,	,	PUNCT
ajase-2385	94	5	the	the	DET
ajase-2385	94	6	model	model	NOUN
ajase-2385	94	7	is	be	AUX
ajase-2385	94	8	fit	fit	ADJ
ajase-2385	94	9	,	,	PUNCT
ajase-2385	94	10	and	and	CCONJ
ajase-2385	94	11	the	the	DET
ajase-2385	94	12	root	root	NOUN
ajase-2385	94	13	mean	mean	VERB
ajase-2385	94	14	square	square	ADJ
ajase-2385	94	15	error	error	NOUN
ajase-2385	94	16	(	(	PUNCT
ajase-2385	94	17	rmse	rmse	NOUN
ajase-2385	94	18	)	)	PUNCT
ajase-2385	94	19	is	be	AUX
ajase-2385	94	20	computed	compute	VERB
ajase-2385	94	21	.	.	PUNCT
ajase-2385	95	1	the	the	DET
ajase-2385	95	2	optimal	optimal	ADJ
ajase-2385	95	3	k	k	PROPN
ajase-2385	95	4	value	value	NOUN
ajase-2385	95	5	is	be	AUX
ajase-2385	95	6	selected	select	VERB
ajase-2385	95	7	based	base	VERB
ajase-2385	95	8	on	on	ADP
ajase-2385	95	9	the	the	DET
ajase-2385	95	10	minimum	minimum	NOUN
ajase-2385	95	11	rmse	rmse	NOUN
ajase-2385	95	12	.	.	PUNCT
ajase-2385	96	1	hyper	hyper	ADJ
ajase-2385	96	2	-	-	ADJ
ajase-2385	96	3	parameter	parameter	NOUN
ajase-2385	96	4	tuning	tune	VERB
ajase-2385	96	5	these	these	PRON
ajase-2385	96	6	hyper	hyper	ADJ
ajase-2385	96	7	-	-	NOUN
ajase-2385	96	8	parameters	parameter	NOUN
ajase-2385	96	9	control	control	VERB
ajase-2385	96	10	various	various	ADJ
ajase-2385	96	11	aspects	aspect	NOUN
ajase-2385	96	12	of	of	ADP
ajase-2385	96	13	the	the	DET
ajase-2385	96	14	model	model	NOUN
ajase-2385	96	15	,	,	PUNCT
ajase-2385	96	16	such	such	ADJ
ajase-2385	96	17	as	as	ADP
ajase-2385	96	18	the	the	DET
ajase-2385	96	19	regularization	regularization	NOUN
ajase-2385	96	20	strength	strength	NOUN
ajase-2385	96	21	,	,	PUNCT
ajase-2385	96	22	learning	learn	VERB
ajase-2385	96	23	rate	rate	NOUN
ajase-2385	96	24	,	,	PUNCT
ajase-2385	96	25	and	and	CCONJ
ajase-2385	96	26	number	number	NOUN
ajase-2385	96	27	of	of	ADP
ajase-2385	96	28	hidden	hidden	ADJ
ajase-2385	96	29	layers	layer	NOUN
ajase-2385	96	30	in	in	ADP
ajase-2385	96	31	neural	neural	ADJ
ajase-2385	96	32	networks	network	NOUN
ajase-2385	96	33	.	.	PUNCT
ajase-2385	97	1	selecting	select	VERB
ajase-2385	97	2	optimal	optimal	ADJ
ajase-2385	97	3	hyper	hyper	NOUN
ajase-2385	97	4	-	-	NOUN
ajase-2385	97	5	parameters	parameter	NOUN
ajase-2385	97	6	is	be	AUX
ajase-2385	97	7	crucial	crucial	ADJ
ajase-2385	97	8	for	for	ADP
ajase-2385	97	9	achieving	achieve	VERB
ajase-2385	97	10	high	high	ADJ
ajase-2385	97	11	model	model	NOUN
ajase-2385	97	12	performance	performance	NOUN
ajase-2385	97	13	,	,	PUNCT
ajase-2385	97	14	and	and	CCONJ
ajase-2385	97	15	grid	grid	NOUN
ajase-2385	97	16	search	search	NOUN
ajase-2385	97	17	or	or	CCONJ
ajase-2385	97	18	random	random	ADJ
ajase-2385	97	19	search	search	NOUN
ajase-2385	97	20	techniques	technique	NOUN
ajase-2385	97	21	are	be	AUX
ajase-2385	97	22	often	often	ADV
ajase-2385	97	23	used	use	VERB
ajase-2385	97	24	to	to	PART
ajase-2385	97	25	explore	explore	VERB
ajase-2385	97	26	the	the	DET
ajase-2385	97	27	hyper	hyper	ADJ
ajase-2385	97	28	-	-	ADJ
ajase-2385	97	29	parameter	parameter	NOUN
ajase-2385	97	30	space	space	NOUN
ajase-2385	97	31	and	and	CCONJ
ajase-2385	97	32	find	find	VERB
ajase-2385	97	33	the	the	DET
ajase-2385	97	34	optimal	optimal	ADJ
ajase-2385	97	35	values	value	NOUN
ajase-2385	97	36	.	.	PUNCT
ajase-2385	98	1	error	error	NOUN
ajase-2385	98	2	calculation	calculation	NOUN
ajase-2385	98	3	methods	method	NOUN
ajase-2385	98	4	let	let	VERB
ajase-2385	98	5	n	n	CCONJ
ajase-2385	98	6	,	,	PUNCT
ajase-2385	98	7	yt	yt	NOUN
ajase-2385	98	8	,	,	PUNCT
ajase-2385	98	9	and	and	CCONJ
ajase-2385	98	10	ŷt	ŷt	NOUN
ajase-2385	98	11	be	be	AUX
ajase-2385	98	12	the	the	DET
ajase-2385	98	13	number	number	NOUN
ajase-2385	98	14	of	of	ADP
ajase-2385	98	15	fitted	fit	VERB
ajase-2385	98	16	points	point	NOUN
ajase-2385	98	17	,	,	PUNCT
ajase-2385	98	18	the	the	DET
ajase-2385	98	19	actual	actual	ADJ
ajase-2385	98	20	value	value	NOUN
ajase-2385	98	21	of	of	ADP
ajase-2385	98	22	the	the	DET
ajase-2385	98	23	response	response	NOUN
ajase-2385	98	24	variable	variable	PROPN
ajase-2385	98	25	y	y	PROPN
ajase-2385	98	26	at	at	ADP
ajase-2385	98	27	time	time	NOUN
ajase-2385	98	28	t	t	PROPN
ajase-2385	98	29	,	,	PUNCT
ajase-2385	98	30	and	and	CCONJ
ajase-2385	98	31	the	the	DET
ajase-2385	98	32	predicted	predict	VERB
ajase-2385	98	33	value	value	NOUN
ajase-2385	98	34	of	of	ADP
ajase-2385	98	35	yt	yt	PROPN
ajase-2385	98	36	,	,	PUNCT
ajase-2385	98	37	respectively	respectively	ADV
ajase-2385	98	38	.	.	PUNCT
ajase-2385	99	1	mean	mean	VERB
ajase-2385	99	2	absolute	absolute	ADJ
ajase-2385	99	3	percentage	percentage	NOUN
ajase-2385	99	4	error	error	NOUN
ajase-2385	99	5	(	(	PUNCT
ajase-2385	99	6	mape	mape	NOUN
ajase-2385	99	7	)	)	PUNCT
ajase-2385	99	8	the	the	DET
ajase-2385	99	9	mean	mean	ADJ
ajase-2385	99	10	absolute	absolute	ADJ
ajase-2385	99	11	percentage	percentage	NOUN
ajase-2385	99	12	(	(	PUNCT
ajase-2385	99	13	armstrong	armstrong	PROPN
ajase-2385	99	14	,	,	PUNCT
ajase-2385	99	15	1992	1992	NUM
ajase-2385	99	16	)	)	PUNCT
ajase-2385	99	17	error	error	NOUN
ajase-2385	99	18	(	(	PUNCT
ajase-2385	99	19	mape	mape	NOUN
ajase-2385	99	20	)	)	PUNCT
ajase-2385	99	21	can	can	AUX
ajase-2385	99	22	be	be	AUX
ajase-2385	99	23	calculated	calculate	VERB
ajase-2385	99	24	by	by	ADP
ajase-2385	99	25	using	use	VERB
ajase-2385	99	26	the	the	DET
ajase-2385	99	27	following	follow	VERB
ajase-2385	99	28	formula	formula	NOUN
ajase-2385	99	29	.	.	PUNCT
ajase-2385	100	1	mape=	mape=	NUM
ajase-2385	100	2	1	1	NUM
ajase-2385	100	3	/	/	SYM
ajase-2385	100	4	n	n	CCONJ
ajase-2385	100	5	∑n	∑n	PROPN
ajase-2385	100	6	(	(	PUNCT
ajase-2385	100	7	i=1	i=1	PROPN
ajase-2385	100	8	)	)	PUNCT
ajase-2385	100	9	(	(	PUNCT
ajase-2385	100	10	|yt	|yt	NOUN
ajase-2385	100	11	-	-	PUNCT
ajase-2385	100	12	ŷt|)/yt	ŷt|)/yt	NOUN
ajase-2385	100	13	.	.	PUNCT
ajase-2385	100	14	mape	mape	NOUN
ajase-2385	100	15	works	work	VERB
ajase-2385	100	16	best	well	ADV
ajase-2385	100	17	in	in	ADP
ajase-2385	100	18	the	the	DET
ajase-2385	100	19	absence	absence	NOUN
ajase-2385	100	20	of	of	ADP
ajase-2385	100	21	extreme	extreme	ADJ
ajase-2385	100	22	values	value	NOUN
ajase-2385	100	23	in	in	ADP
ajase-2385	100	24	the	the	DET
ajase-2385	100	25	data	datum	NOUN
ajase-2385	100	26	set	set	VERB
ajase-2385	100	27	.	.	PUNCT
ajase-2385	101	1	root	root	NOUN
ajase-2385	101	2	mean	mean	VERB
ajase-2385	101	3	square	square	ADJ
ajase-2385	101	4	error	error	NOUN
ajase-2385	101	5	(	(	PUNCT
ajase-2385	101	6	rmse	rmse	NOUN
ajase-2385	101	7	)	)	PUNCT
ajase-2385	101	8	the	the	DET
ajase-2385	101	9	root	root	NOUN
ajase-2385	101	10	mean	mean	VERB
ajase-2385	101	11	square	square	ADJ
ajase-2385	101	12	error	error	NOUN
ajase-2385	101	13	(	(	PUNCT
ajase-2385	101	14	hyndman	hyndman	NOUN
ajase-2385	101	15	,	,	PUNCT
ajase-2385	101	16	2006	2006	NUM
ajase-2385	101	17	)	)	PUNCT
ajase-2385	101	18	(	(	PUNCT
ajase-2385	101	19	rmse	rmse	NOUN
ajase-2385	101	20	)	)	PUNCT
ajase-2385	101	21	is	be	AUX
ajase-2385	101	22	given	give	VERB
ajase-2385	101	23	by	by	ADP
ajase-2385	101	24	;	;	PUNCT
ajase-2385	102	1	where	where	SCONJ
ajase-2385	102	2	||β||1=∑n	||β||1=∑n	NOUN
ajase-2385	102	3	1|βi	1|βi	NUM
ajase-2385	102	4	|	|	ADV
ajase-2385	102	5	is	be	AUX
ajase-2385	102	6	the	the	DET
ajase-2385	102	7	l1norm	l1norm	NOUN
ajase-2385	102	8	penalty	penalty	NOUN
ajase-2385	102	9	on	on	ADP
ajase-2385	102	10	β	β	X
ajase-2385	102	11	,	,	PUNCT
ajase-2385	102	12	which	which	PRON
ajase-2385	102	13	induces	induce	VERB
ajase-2385	102	14	sparsity	sparsity	NOUN
ajase-2385	102	15	in	in	ADP
ajase-2385	102	16	the	the	DET
ajase-2385	102	17	solution	solution	NOUN
ajase-2385	102	18	and	and	CCONJ
ajase-2385	102	19	λ≥0	λ≥0	PROPN
ajase-2385	102	20	.	.	PUNCT
ajase-2385	103	1	bayesian	bayesian	NOUN
ajase-2385	103	2	ridge	ridge	NOUN
ajase-2385	103	3	regression	regression	PROPN
ajase-2385	103	4	(	(	PUNCT
ajase-2385	103	5	brr	brr	NOUN
ajase-2385	103	6	)	)	PUNCT
ajase-2385	103	7	in	in	ADP
ajase-2385	103	8	bayesian	bayesian	NOUN
ajase-2385	103	9	ridge	ridge	NOUN
ajase-2385	103	10	regression	regression	NOUN
ajase-2385	103	11	(	(	PUNCT
ajase-2385	103	12	hoerl	hoerl	NOUN
ajase-2385	103	13	,	,	PUNCT
ajase-2385	103	14	1970	1970	NUM
ajase-2385	103	15	)	)	PUNCT
ajase-2385	103	16	,	,	PUNCT
ajase-2385	103	17	the	the	DET
ajase-2385	103	18	estimate	estimate	NOUN
ajase-2385	103	19	β	β	X
ajase-2385	103	20	is	be	AUX
ajase-2385	103	21	obtained	obtain	VERB
ajase-2385	103	22	by	by	ADP
ajase-2385	103	23	using	use	VERB
ajase-2385	103	24	the	the	DET
ajase-2385	103	25	l2	l2	NOUN
ajase-2385	103	26	norm	norm	NOUN
ajase-2385	103	27	,	,	PUNCT
ajase-2385	103	28	and	and	CCONJ
ajase-2385	103	29	it	it	PRON
ajase-2385	103	30	is	be	AUX
ajase-2385	103	31	given	give	VERB
ajase-2385	103	32	by	by	ADP
ajase-2385	103	33	;	;	PUNCT
ajase-2385	103	34	(	(	PUNCT
ajase-2385	103	35	2	2	X
ajase-2385	103	36	)	)	PUNCT
ajase-2385	103	37	where	where	SCONJ
ajase-2385	103	38	||β||2=∑n	||β||2=∑n	NOUN
ajase-2385	103	39	1	1	NUM
ajase-2385	103	40	β	β	SYM
ajase-2385	103	41	2	2	NUM
ajase-2385	103	42	i	i	PRON
ajase-2385	103	43	is	be	AUX
ajase-2385	103	44	the	the	DET
ajase-2385	103	45	l2norm	l2norm	ADJ
ajase-2385	103	46	penalty	penalty	NOUN
ajase-2385	103	47	on	on	ADP
ajase-2385	103	48	β	β	PROPN
ajase-2385	103	49	and	and	CCONJ
ajase-2385	103	50	λ≥0	λ≥0	PROPN
ajase-2385	103	51	.	.	PUNCT
ajase-2385	104	1	in	in	ADP
ajase-2385	104	2	this	this	DET
ajase-2385	104	3	case	case	NOUN
ajase-2385	104	4	,	,	PUNCT
ajase-2385	104	5	we	we	PRON
ajase-2385	104	6	obtain	obtain	VERB
ajase-2385	104	7	the	the	DET
ajase-2385	104	8	posterior	posterior	ADJ
ajase-2385	104	9	distribution	distribution	NOUN
ajase-2385	104	10	to	to	PART
ajase-2385	104	11	estimate	estimate	VERB
ajase-2385	104	12	β	β	X
ajase-2385	104	13	with	with	ADP
ajase-2385	104	14	normal	normal	ADJ
ajase-2385	104	15	likelihood	likelihood	NOUN
ajase-2385	104	16	and	and	CCONJ
ajase-2385	104	17	normal	normal	ADJ
ajase-2385	104	18	prior	prior	ADJ
ajase-2385	104	19	distribution	distribution	NOUN
ajase-2385	104	20	.	.	PUNCT
ajase-2385	105	1	support	support	NOUN
ajase-2385	105	2	vector	vector	NOUN
ajase-2385	105	3	regression	regression	NOUN
ajase-2385	105	4	(	(	PUNCT
ajase-2385	105	5	svr	svr	PROPN
ajase-2385	105	6	)	)	PUNCT
ajase-2385	105	7	svr	svr	PROPN
ajase-2385	105	8	(	(	PUNCT
ajase-2385	105	9	smola	smola	PROPN
ajase-2385	105	10	&	&	CCONJ
ajase-2385	105	11	schölkopf	schölkopf	PROPN
ajase-2385	105	12	,	,	PUNCT
ajase-2385	105	13	2003	2003	NUM
ajase-2385	105	14	)	)	PUNCT
ajase-2385	105	15	gives	give	VERB
ajase-2385	105	16	us	we	PRON
ajase-2385	105	17	the	the	DET
ajase-2385	105	18	flexibility	flexibility	NOUN
ajase-2385	105	19	to	to	PART
ajase-2385	105	20	define	define	VERB
ajase-2385	105	21	how	how	SCONJ
ajase-2385	105	22	much	much	ADJ
ajase-2385	105	23	error	error	NOUN
ajase-2385	105	24	is	be	AUX
ajase-2385	105	25	acceptable	acceptable	ADJ
ajase-2385	105	26	in	in	ADP
ajase-2385	105	27	our	our	PRON
ajase-2385	105	28	model	model	NOUN
ajase-2385	105	29	.	.	PUNCT
ajase-2385	106	1	it	it	PRON
ajase-2385	106	2	will	will	AUX
ajase-2385	106	3	compute	compute	VERB
ajase-2385	106	4	the	the	DET
ajase-2385	106	5	parameter	parameter	NOUN
ajase-2385	106	6	estimates	estimate	NOUN
ajase-2385	106	7	by	by	ADP
ajase-2385	106	8	utilizing	utilize	VERB
ajase-2385	106	9	the	the	DET
ajase-2385	106	10	following	follow	VERB
ajase-2385	106	11	minimization	minimization	NOUN
ajase-2385	106	12	problem	problem	NOUN
ajase-2385	106	13	.	.	PUNCT
ajase-2385	107	1	minimize	minimize	VERB
ajase-2385	107	2	min	min	PROPN
ajase-2385	107	3	1/2	1/2	NUM
ajase-2385	107	4	||β||2	||β||2	NOUN
ajase-2385	107	5	(	(	PUNCT
ajase-2385	107	6	3	3	NUM
ajase-2385	107	7	)	)	PUNCT
ajase-2385	107	8	under	under	ADP
ajase-2385	107	9	constant	constant	ADJ
ajase-2385	107	10	|yi	|yi	NUM
ajase-2385	107	11	-	-	PUNCT
ajase-2385	107	12	βi	βi	PRON
ajase-2385	107	13	xi≤ϵ|	xi≤ϵ|	X
ajase-2385	107	14	(	(	PUNCT
ajase-2385	107	15	4	4	NUM
ajase-2385	107	16	)	)	PUNCT
ajase-2385	107	17	where	where	SCONJ
ajase-2385	107	18	we	we	PRON
ajase-2385	107	19	set	set	VERB
ajase-2385	107	20	the	the	DET
ajase-2385	107	21	absolute	absolute	ADJ
ajase-2385	107	22	error	error	NOUN
ajase-2385	107	23	less	less	ADJ
ajase-2385	107	24	than	than	ADP
ajase-2385	107	25	or	or	CCONJ
ajase-2385	107	26	equal	equal	ADJ
ajase-2385	107	27	to	to	ADP
ajase-2385	107	28	a	a	DET
ajase-2385	107	29	specified	specified	ADJ
ajase-2385	107	30	margin	margin	NOUN
ajase-2385	107	31	,	,	PUNCT
ajase-2385	107	32	called	call	VERB
ajase-2385	107	33	the	the	DET
ajase-2385	107	34	maximum	maximum	ADJ
ajase-2385	107	35	error	error	NOUN
ajase-2385	107	36	,	,	PUNCT
ajase-2385	107	37	ϵ.	ϵ.	NOUN
ajase-2385	107	38	we	we	PRON
ajase-2385	107	39	can	can	AUX
ajase-2385	107	40	tune	tune	VERB
ajase-2385	107	41	ϵ	ϵ	NOUN
ajase-2385	107	42	to	to	PART
ajase-2385	107	43	gain	gain	VERB
ajase-2385	107	44	the	the	DET
ajase-2385	107	45	desired	desire	VERB
ajase-2385	107	46	accuracy	accuracy	NOUN
ajase-2385	107	47	of	of	ADP
ajase-2385	107	48	our	our	PRON
ajase-2385	107	49	model	model	NOUN
ajase-2385	107	50	.	.	PUNCT
ajase-2385	108	1	random	random	ADJ
ajase-2385	108	2	forests	forest	NOUN
ajase-2385	108	3	regression	regression	VERB
ajase-2385	108	4	(	(	PUNCT
ajase-2385	108	5	rfr	rfr	PROPN
ajase-2385	108	6	)	)	PUNCT
ajase-2385	108	7	rfr	rfr	PROPN
ajase-2385	108	8	is	be	AUX
ajase-2385	108	9	a	a	DET
ajase-2385	108	10	tree	tree	NOUN
ajase-2385	108	11	-	-	PUNCT
ajase-2385	108	12	based	base	VERB
ajase-2385	108	13	algorithm	algorithm	NOUN
ajase-2385	108	14	with	with	ADP
ajase-2385	108	15	each	each	DET
ajase-2385	108	16	tree	tree	NOUN
ajase-2385	108	17	depending	depend	VERB
ajase-2385	108	18	on	on	ADP
ajase-2385	108	19	a	a	DET
ajase-2385	108	20	set	set	NOUN
ajase-2385	108	21	of	of	ADP
ajase-2385	108	22	random	random	ADJ
ajase-2385	108	23	variables	variable	NOUN
ajase-2385	108	24	(	(	PUNCT
ajase-2385	108	25	cutler	cutler	NOUN
ajase-2385	108	26	et	et	PROPN
ajase-2385	108	27	al	al	PROPN
ajase-2385	108	28	.	.	PROPN
ajase-2385	108	29	,	,	PUNCT
ajase-2385	108	30	2012	2012	NUM
ajase-2385	108	31	)	)	PUNCT
ajase-2385	108	32	.	.	PUNCT
ajase-2385	109	1	let	let	VERB
ajase-2385	109	2	x	x	PUNCT
ajase-2385	109	3	=	=	PRON
ajase-2385	109	4	(	(	PUNCT
ajase-2385	109	5	x1,x2,	x1,x2,	PROPN
ajase-2385	109	6	...	...	PUNCT
ajase-2385	109	7	,xp	,xp	PUNCT
ajase-2385	109	8	)	)	PUNCT
ajase-2385	109	9	’	'	PUNCT
ajase-2385	109	10	be	be	AUX
ajase-2385	109	11	a	a	DET
ajase-2385	109	12	p	p	ADJ
ajase-2385	109	13	-	-	PUNCT
ajase-2385	109	14	dimensional	dimensional	ADJ
ajase-2385	109	15	random	random	ADJ
ajase-2385	109	16	input	input	NOUN
ajase-2385	109	17	vector	vector	NOUN
ajase-2385	109	18	and	and	CCONJ
ajase-2385	109	19	y	y	PROPN
ajase-2385	109	20	be	be	AUX
ajase-2385	109	21	the	the	DET
ajase-2385	109	22	response	response	NOUN
ajase-2385	109	23	variable	variable	NOUN
ajase-2385	109	24	.	.	PUNCT
ajase-2385	110	1	moreover	moreover	ADV
ajase-2385	110	2	,	,	PUNCT
ajase-2385	110	3	we	we	PRON
ajase-2385	110	4	assume	assume	VERB
ajase-2385	110	5	that	that	SCONJ
ajase-2385	110	6	pxy	pxy	X
ajase-2385	110	7	(	(	PUNCT
ajase-2385	110	8	x	x	NOUN
ajase-2385	110	9	,	,	PUNCT
ajase-2385	110	10	y	y	PROPN
ajase-2385	110	11	)	)	PUNCT
ajase-2385	110	12	is	be	AUX
ajase-2385	110	13	the	the	DET
ajase-2385	110	14	unknown	unknown	ADJ
ajase-2385	110	15	joint	joint	ADJ
ajase-2385	110	16	distribution	distribution	NOUN
ajase-2385	110	17	of	of	ADP
ajase-2385	110	18	x	x	X
ajase-2385	110	19	and	and	CCONJ
ajase-2385	110	20	y	y	PROPN
ajase-2385	110	21	.	.	PUNCT
ajase-2385	111	1	the	the	DET
ajase-2385	111	2	objective	objective	NOUN
ajase-2385	111	3	of	of	ADP
ajase-2385	111	4	the	the	DET
ajase-2385	111	5	rfr	rfr	PROPN
ajase-2385	111	6	is	be	AUX
ajase-2385	111	7	to	to	PART
ajase-2385	111	8	find	find	VERB
ajase-2385	111	9	a	a	DET
ajase-2385	111	10	function	function	NOUN
ajase-2385	111	11	f(x	f(x	PROPN
ajase-2385	111	12	)	)	PUNCT
ajase-2385	111	13	to	to	PART
ajase-2385	111	14	predict	predict	VERB
ajase-2385	111	15	the	the	DET
ajase-2385	111	16	response	response	NOUN
ajase-2385	111	17	variable	variable	ADJ
ajase-2385	111	18	y	y	PROPN
ajase-2385	111	19	by	by	ADP
ajase-2385	111	20	minimizing	minimize	VERB
ajase-2385	111	21	the	the	DET
ajase-2385	111	22	risk	risk	NOUN
ajase-2385	111	23	function	function	NOUN
ajase-2385	111	24	.	.	PUNCT
ajase-2385	112	1	exy	exy	ADJ
ajase-2385	112	2	(	(	PUNCT
ajase-2385	112	3	l(y	l(y	PROPN
ajase-2385	112	4	,	,	PUNCT
ajase-2385	112	5	f(x	f(x	PROPN
ajase-2385	112	6	)	)	PUNCT
ajase-2385	112	7	)	)	PUNCT
ajase-2385	112	8	)	)	PUNCT
ajase-2385	113	1	(	(	PUNCT
ajase-2385	113	2	5	5	X
ajase-2385	113	3	)	)	PUNCT
ajase-2385	113	4	where	where	SCONJ
ajase-2385	113	5	l(y	l(y	PROPN
ajase-2385	113	6	,	,	PUNCT
ajase-2385	113	7	f(x	f(x	PROPN
ajase-2385	113	8	)	)	PUNCT
ajase-2385	113	9	)	)	PUNCT
ajase-2385	114	1	=	=	PUNCT
ajase-2385	114	2	(	(	PUNCT
ajase-2385	114	3	y	y	PROPN
ajase-2385	114	4	f(x))2	f(x))2	PROPN
ajase-2385	114	5	is	be	AUX
ajase-2385	114	6	the	the	DET
ajase-2385	114	7	squared	square	VERB
ajase-2385	114	8	error	error	NOUN
ajase-2385	114	9	loss	loss	NOUN
ajase-2385	114	10	function	function	NOUN
ajase-2385	114	11	.	.	PUNCT
ajase-2385	115	1	here	here	ADV
ajase-2385	115	2	,	,	PUNCT
ajase-2385	115	3	one	one	PRON
ajase-2385	115	4	can	can	AUX
ajase-2385	115	5	define	define	VERB
ajase-2385	115	6	f(x	f(x	PROPN
ajase-2385	115	7	)	)	PUNCT
ajase-2385	115	8	as	as	ADP
ajase-2385	115	9	f(x	f(x	PROPN
ajase-2385	115	10	)	)	PUNCT
ajase-2385	115	11	=	=	PUNCT
ajase-2385	116	1	e(y	e(y	ADJ
ajase-2385	116	2	|x=	|x=	NOUN
ajase-2385	116	3	x	x	NOUN
ajase-2385	116	4	)	)	PUNCT
ajase-2385	116	5	,	,	PUNCT
ajase-2385	116	6	and	and	CCONJ
ajase-2385	116	7	in	in	ADP
ajase-2385	116	8	regression	regression	NOUN
ajase-2385	116	9	setting	setting	NOUN
ajase-2385	116	10	,	,	PUNCT
ajase-2385	116	11	f(x	f(x	PROPN
ajase-2385	116	12	)	)	PUNCT
ajase-2385	116	13	can	can	AUX
ajase-2385	116	14	be	be	AUX
ajase-2385	116	15	written	write	VERB
ajase-2385	116	16	as	as	ADP
ajase-2385	116	17	f(x)=1	f(x)=1	NOUN
ajase-2385	116	18	/	/	SYM
ajase-2385	116	19	j	j	NOUN
ajase-2385	116	20	∑j	∑j	PROPN
ajase-2385	116	21	(	(	PUNCT
ajase-2385	116	22	j=1	j=1	PROPN
ajase-2385	116	23	)	)	PUNCT
ajase-2385	116	24	hj	hj	PROPN
ajase-2385	116	25	(	(	PUNCT
ajase-2385	116	26	x	x	NOUN
ajase-2385	116	27	)	)	PUNCT
ajase-2385	116	28	(	(	PUNCT
ajase-2385	116	29	6	6	NUM
ajase-2385	116	30	)	)	PUNCT
ajase-2385	116	31	with	with	ADP
ajase-2385	116	32	respect	respect	NOUN
ajase-2385	116	33	to	to	ADP
ajase-2385	116	34	a	a	DET
ajase-2385	116	35	collection	collection	NOUN
ajase-2385	116	36	of	of	ADP
ajase-2385	116	37	basis	basis	NOUN
ajase-2385	116	38	functions	function	NOUN
ajase-2385	116	39	h1	h1	VERB
ajase-2385	116	40	(	(	PUNCT
ajase-2385	116	41	x	x	NOUN
ajase-2385	116	42	)	)	PUNCT
ajase-2385	116	43	,	,	PUNCT
ajase-2385	116	44	h2	h2	NOUN
ajase-2385	116	45	(	(	PUNCT
ajase-2385	116	46	x),	x),	PROPN
ajase-2385	116	47	...	...	PUNCT
ajase-2385	116	48	,hj	,hj	PUNCT
ajase-2385	116	49	(	(	PUNCT
ajase-2385	116	50	x	x	NOUN
ajase-2385	116	51	)	)	PUNCT
ajase-2385	116	52	.	.	PUNCT
ajase-2385	117	1	cross	cross	NOUN
ajase-2385	117	2	validation	validation	PROPN
ajase-2385	117	3	methods	method	NOUN
ajase-2385	117	4	cross	cross	VERB
ajase-2385	117	5	validation	validation	NOUN
ajase-2385	117	6	is	be	AUX
ajase-2385	117	7	a	a	DET
ajase-2385	117	8	method	method	NOUN
ajase-2385	117	9	used	use	VERB
ajase-2385	117	10	to	to	PART
ajase-2385	117	11	increase	increase	VERB
ajase-2385	117	12	the	the	DET
ajase-2385	117	13	pa	pa	PROPN
ajase-2385	117	14	ge	ge	PROPN
ajase-2385	117	15	54	54	NUM
ajase-2385	117	16	https://journals.e-palli.com/home/index.php/ajase	https://journals.e-palli.com/home/index.php/ajase	PROPN
ajase-2385	117	17	am	be	AUX
ajase-2385	117	18	.	.	PUNCT
ajase-2385	118	1	j.	j.	PROPN
ajase-2385	118	2	appl	appl	PROPN
ajase-2385	118	3	.	.	PROPN
ajase-2385	119	1	stat	stat	PROPN
ajase-2385	119	2	.	.	PUNCT
ajase-2385	120	1	econ	econ	PROPN
ajase-2385	120	2	.	.	PUNCT
ajase-2385	121	1	3(1	3(1	NUM
ajase-2385	121	2	)	)	PUNCT
ajase-2385	121	3	51	51	NUM
ajase-2385	121	4	-	-	SYM
ajase-2385	121	5	60	60	NUM
ajase-2385	121	6	,	,	PUNCT
ajase-2385	121	7	2024	2024	NUM
ajase-2385	121	8	the	the	DET
ajase-2385	121	9	rmse	rmse	NOUN
ajase-2385	121	10	and	and	CCONJ
ajase-2385	121	11	mape	mape	NOUN
ajase-2385	122	1	are	be	AUX
ajase-2385	122	2	commonly	commonly	ADV
ajase-2385	122	3	used	use	VERB
ajase-2385	122	4	measures	measure	NOUN
ajase-2385	122	5	of	of	ADP
ajase-2385	122	6	the	the	DET
ajase-2385	122	7	forecasting	forecasting	NOUN
ajase-2385	122	8	error	error	NOUN
ajase-2385	122	9	.	.	PUNCT
ajase-2385	123	1	data	datum	NOUN
ajase-2385	123	2	set	set	VERB
ajase-2385	123	3	in	in	ADP
ajase-2385	123	4	this	this	DET
ajase-2385	123	5	study	study	NOUN
ajase-2385	123	6	,	,	PUNCT
ajase-2385	123	7	we	we	PRON
ajase-2385	123	8	consider	consider	VERB
ajase-2385	123	9	the	the	DET
ajase-2385	123	10	monthly	monthly	ADJ
ajase-2385	123	11	inflation	inflation	NOUN
ajase-2385	123	12	rate	rate	NOUN
ajase-2385	123	13	data	datum	NOUN
ajase-2385	123	14	in	in	ADP
ajase-2385	123	15	sri	sri	PROPN
ajase-2385	123	16	lanka	lanka	PROPN
ajase-2385	123	17	from	from	ADP
ajase-2385	123	18	january	january	PROPN
ajase-2385	123	19	1988	1988	NUM
ajase-2385	123	20	to	to	ADP
ajase-2385	123	21	august	august	PROPN
ajase-2385	123	22	2021	2021	NUM
ajase-2385	123	23	(	(	PUNCT
ajase-2385	123	24	tradingview	tradingview	NOUN
ajase-2385	123	25	,	,	PUNCT
ajase-2385	123	26	2023	2023	NUM
ajase-2385	123	27	)	)	PUNCT
ajase-2385	123	28	figure	figure	NOUN
ajase-2385	123	29	1	1	NUM
ajase-2385	123	30	depicts	depict	VERB
ajase-2385	123	31	this	this	DET
ajase-2385	123	32	data	datum	NOUN
ajase-2385	123	33	.	.	PUNCT
ajase-2385	124	1	simulation	simulation	NOUN
ajase-2385	124	2	study	study	VERB
ajase-2385	124	3	the	the	DET
ajase-2385	124	4	dataset	dataset	NOUN
ajase-2385	124	5	used	use	VERB
ajase-2385	124	6	for	for	ADP
ajase-2385	124	7	the	the	DET
ajase-2385	124	8	simulation	simulation	NOUN
ajase-2385	124	9	study	study	NOUN
ajase-2385	124	10	includes	include	VERB
ajase-2385	124	11	monthly	monthly	ADJ
ajase-2385	124	12	data	datum	NOUN
ajase-2385	124	13	starting	start	VERB
ajase-2385	124	14	from	from	ADP
ajase-2385	124	15	january	january	PROPN
ajase-2385	124	16	1988	1988	NUM
ajase-2385	124	17	.	.	PUNCT
ajase-2385	125	1	the	the	DET
ajase-2385	125	2	dataset	dataset	NOUN
ajase-2385	125	3	contains	contain	VERB
ajase-2385	125	4	a	a	DET
ajase-2385	125	5	total	total	NOUN
ajase-2385	125	6	of	of	ADP
ajase-2385	125	7	405	405	NUM
ajase-2385	125	8	data	datum	NOUN
ajase-2385	125	9	points	point	NOUN
ajase-2385	125	10	.	.	PUNCT
ajase-2385	126	1	to	to	PART
ajase-2385	126	2	evaluate	evaluate	VERB
ajase-2385	126	3	the	the	DET
ajase-2385	126	4	performance	performance	NOUN
ajase-2385	126	5	of	of	ADP
ajase-2385	126	6	the	the	DET
ajase-2385	126	7	model	model	NOUN
ajase-2385	126	8	,	,	PUNCT
ajase-2385	126	9	the	the	DET
ajase-2385	126	10	dataset	dataset	NOUN
ajase-2385	126	11	was	be	AUX
ajase-2385	126	12	divided	divide	VERB
ajase-2385	126	13	into	into	ADP
ajase-2385	126	14	three	three	NUM
ajase-2385	126	15	subsets	subset	NOUN
ajase-2385	126	16	:	:	PUNCT
ajase-2385	126	17	a	a	DET
ajase-2385	126	18	training	training	NOUN
ajase-2385	126	19	dataset	dataset	NOUN
ajase-2385	126	20	consisting	consist	VERB
ajase-2385	126	21	of	of	ADP
ajase-2385	126	22	368	368	NUM
ajase-2385	126	23	data	datum	NOUN
ajase-2385	126	24	points	point	NOUN
ajase-2385	126	25	from	from	ADP
ajase-2385	126	26	january	january	PROPN
ajase-2385	126	27	1988	1988	NUM
ajase-2385	126	28	to	to	ADP
ajase-2385	126	29	february	february	PROPN
ajase-2385	126	30	2018	2018	NUM
ajase-2385	126	31	,	,	PUNCT
ajase-2385	126	32	a	a	DET
ajase-2385	126	33	test	test	NOUN
ajase-2385	126	34	dataset	dataset	NOUN
ajase-2385	126	35	consisting	consist	VERB
ajase-2385	126	36	of	of	ADP
ajase-2385	126	37	24	24	NUM
ajase-2385	126	38	data	datum	NOUN
ajase-2385	126	39	points	point	NOUN
ajase-2385	126	40	from	from	ADP
ajase-2385	126	41	march	march	PROPN
ajase-2385	126	42	2018	2018	NUM
ajase-2385	126	43	to	to	ADP
ajase-2385	126	44	march	march	PROPN
ajase-2385	126	45	2020	2020	NUM
ajase-2385	126	46	,	,	PUNCT
ajase-2385	126	47	and	and	CCONJ
ajase-2385	126	48	a	a	DET
ajase-2385	126	49	validation	validation	NOUN
ajase-2385	126	50	dataset	dataset	NOUN
ajase-2385	126	51	consisting	consist	VERB
ajase-2385	126	52	of	of	ADP
ajase-2385	126	53	12	12	NUM
ajase-2385	126	54	data	datum	NOUN
ajase-2385	126	55	points	point	NOUN
ajase-2385	126	56	from	from	ADP
ajase-2385	126	57	april	april	PROPN
ajase-2385	126	58	2020	2020	NUM
ajase-2385	126	59	to	to	ADP
ajase-2385	126	60	august	august	PROPN
ajase-2385	126	61	2021	2021	NUM
ajase-2385	126	62	.	.	PUNCT
ajase-2385	127	1	the	the	DET
ajase-2385	127	2	simulation	simulation	NOUN
ajase-2385	127	3	studies	study	NOUN
ajase-2385	127	4	were	be	AUX
ajase-2385	127	5	performed	perform	VERB
ajase-2385	127	6	using	use	VERB
ajase-2385	127	7	python	python	PROPN
ajase-2385	127	8	3.8.5	3.8.5	NOUN
ajase-2385	127	9	.	.	PUNCT
ajase-2385	128	1	in	in	ADP
ajase-2385	128	2	this	this	DET
ajase-2385	128	3	simulation	simulation	NOUN
ajase-2385	128	4	,	,	PUNCT
ajase-2385	128	5	we	we	PRON
ajase-2385	128	6	extend	extend	VERB
ajase-2385	128	7	our	our	PRON
ajase-2385	128	8	previous	previous	ADJ
ajase-2385	128	9	study	study	NOUN
ajase-2385	128	10	by	by	ADP
ajase-2385	128	11	exploring	explore	VERB
ajase-2385	128	12	four	four	NUM
ajase-2385	128	13	different	different	ADJ
ajase-2385	128	14	supervised	supervised	ADJ
ajase-2385	128	15	machine	machine	NOUN
ajase-2385	128	16	learning	learning	NOUN
ajase-2385	128	17	models	model	NOUN
ajase-2385	128	18	:	:	PUNCT
ajase-2385	128	19	lasso	lasso	NOUN
ajase-2385	128	20	,	,	PUNCT
ajase-2385	128	21	bayesian	bayesian	NOUN
ajase-2385	128	22	ridge	ridge	NOUN
ajase-2385	128	23	regression	regression	PROPN
ajase-2385	128	24	(	(	PUNCT
ajase-2385	128	25	brr	brr	NOUN
ajase-2385	128	26	)	)	PUNCT
ajase-2385	128	27	,	,	PUNCT
ajase-2385	128	28	support	support	NOUN
ajase-2385	128	29	vector	vector	NOUN
ajase-2385	128	30	regression	regression	NOUN
ajase-2385	128	31	(	(	PUNCT
ajase-2385	128	32	svr	svr	PROPN
ajase-2385	128	33	)	)	PUNCT
ajase-2385	128	34	,	,	PUNCT
ajase-2385	128	35	and	and	CCONJ
ajase-2385	128	36	random	random	ADJ
ajase-2385	128	37	forest	forest	NOUN
ajase-2385	128	38	regression	regression	NOUN
ajase-2385	128	39	(	(	PUNCT
ajase-2385	128	40	rfr	rfr	PROPN
ajase-2385	128	41	)	)	PUNCT
ajase-2385	128	42	to	to	PART
ajase-2385	128	43	forecast	forecast	VERB
ajase-2385	128	44	the	the	DET
ajase-2385	128	45	monthly	monthly	ADJ
ajase-2385	128	46	mean	mean	NOUN
ajase-2385	128	47	inflation	inflation	NOUN
ajase-2385	128	48	rate	rate	NOUN
ajase-2385	128	49	in	in	ADP
ajase-2385	128	50	sri	sri	PROPN
ajase-2385	128	51	lanka	lanka	PROPN
ajase-2385	128	52	.	.	PUNCT
ajase-2385	129	1	in	in	ADP
ajase-2385	129	2	the	the	DET
ajase-2385	129	3	simulation	simulation	NOUN
ajase-2385	129	4	,	,	PUNCT
ajase-2385	129	5	we	we	PRON
ajase-2385	129	6	randomly	randomly	VERB
ajase-2385	129	7	select	select	VERB
ajase-2385	129	8	n	n	PRON
ajase-2385	129	9	rows	row	VERB
ajase-2385	129	10	from	from	ADP
ajase-2385	129	11	the	the	DET
ajase-2385	129	12	whole	whole	ADJ
ajase-2385	129	13	data	datum	NOUN
ajase-2385	129	14	set	set	VERB
ajase-2385	129	15	for	for	ADP
ajase-2385	129	16	different	different	ADJ
ajase-2385	129	17	sample	sample	NOUN
ajase-2385	129	18	sizes	size	NOUN
ajase-2385	129	19	ranging	range	VERB
ajase-2385	129	20	from	from	ADP
ajase-2385	129	21	50	50	NUM
ajase-2385	129	22	to	to	ADP
ajase-2385	129	23	405	405	NUM
ajase-2385	129	24	.	.	PUNCT
ajase-2385	130	1	we	we	PRON
ajase-2385	130	2	repeat	repeat	VERB
ajase-2385	130	3	each	each	DET
ajase-2385	130	4	sample	sample	NOUN
ajase-2385	130	5	size	size	NOUN
ajase-2385	130	6	100	100	NUM
ajase-2385	130	7	times	time	NOUN
ajase-2385	130	8	and	and	CCONJ
ajase-2385	130	9	calculate	calculate	VERB
ajase-2385	130	10	the	the	DET
ajase-2385	130	11	mean	mean	NOUN
ajase-2385	130	12	of	of	ADP
ajase-2385	130	13	the	the	DET
ajase-2385	130	14	rmse	rmse	NOUN
ajase-2385	130	15	for	for	ADP
ajase-2385	130	16	each	each	DET
ajase-2385	130	17	machine	machine	NOUN
ajase-2385	130	18	learning	learn	VERB
ajase-2385	130	19	model	model	NOUN
ajase-2385	130	20	.	.	PUNCT
ajase-2385	131	1	the	the	DET
ajase-2385	131	2	results	result	NOUN
ajase-2385	131	3	for	for	ADP
ajase-2385	131	4	each	each	DET
ajase-2385	131	5	machine	machine	NOUN
ajase-2385	131	6	learning	learning	NOUN
ajase-2385	131	7	model	model	NOUN
ajase-2385	131	8	are	be	AUX
ajase-2385	131	9	plotted	plot	VERB
ajase-2385	131	10	against	against	ADP
ajase-2385	131	11	the	the	DET
ajase-2385	131	12	sample	sample	NOUN
ajase-2385	131	13	size	size	NOUN
ajase-2385	131	14	,	,	PUNCT
ajase-2385	131	15	and	and	CCONJ
ajase-2385	131	16	the	the	DET
ajase-2385	131	17	mean	mean	ADJ
ajase-2385	131	18	rmse	rmse	NOUN
ajase-2385	131	19	is	be	AUX
ajase-2385	131	20	used	use	VERB
ajase-2385	131	21	as	as	ADP
ajase-2385	131	22	a	a	DET
ajase-2385	131	23	measure	measure	NOUN
ajase-2385	131	24	of	of	ADP
ajase-2385	131	25	the	the	DET
ajase-2385	131	26	model	model	NOUN
ajase-2385	131	27	’s	’s	PART
ajase-2385	131	28	performance	performance	NOUN
ajase-2385	131	29	.	.	PUNCT
ajase-2385	132	1	the	the	DET
ajase-2385	132	2	plots	plot	NOUN
ajase-2385	132	3	show	show	VERB
ajase-2385	132	4	the	the	DET
ajase-2385	132	5	model	model	NOUN
ajase-2385	132	6	performance	performance	NOUN
ajase-2385	132	7	for	for	ADP
ajase-2385	132	8	different	different	ADJ
ajase-2385	132	9	sample	sample	NOUN
ajase-2385	132	10	sizes	size	NOUN
ajase-2385	132	11	and	and	CCONJ
ajase-2385	132	12	highlight	highlight	VERB
ajase-2385	132	13	the	the	DET
ajase-2385	132	14	optimal	optimal	ADJ
ajase-2385	132	15	sample	sample	NOUN
ajase-2385	132	16	size	size	NOUN
ajase-2385	132	17	required	require	VERB
ajase-2385	132	18	for	for	ADP
ajase-2385	132	19	each	each	DET
ajase-2385	132	20	model	model	NOUN
ajase-2385	132	21	.	.	PUNCT
ajase-2385	133	1	overall	overall	ADV
ajase-2385	133	2	,	,	PUNCT
ajase-2385	133	3	this	this	DET
ajase-2385	133	4	simulation	simulation	NOUN
ajase-2385	133	5	aims	aim	VERB
ajase-2385	133	6	to	to	PART
ajase-2385	133	7	evaluate	evaluate	VERB
ajase-2385	133	8	the	the	DET
ajase-2385	133	9	performance	performance	NOUN
ajase-2385	133	10	of	of	ADP
ajase-2385	133	11	four	four	NUM
ajase-2385	133	12	different	different	ADJ
ajase-2385	133	13	machine	machine	NOUN
ajase-2385	133	14	learning	learning	NOUN
ajase-2385	133	15	models	model	NOUN
ajase-2385	133	16	and	and	CCONJ
ajase-2385	133	17	identify	identify	VERB
ajase-2385	133	18	the	the	DET
ajase-2385	133	19	best	good	ADJ
ajase-2385	133	20	model	model	NOUN
ajase-2385	133	21	for	for	ADP
ajase-2385	133	22	forecasting	forecast	VERB
ajase-2385	133	23	the	the	DET
ajase-2385	133	24	monthly	monthly	ADJ
ajase-2385	133	25	mean	mean	NOUN
ajase-2385	133	26	inflation	inflation	NOUN
ajase-2385	133	27	rate	rate	NOUN
ajase-2385	133	28	in	in	ADP
ajase-2385	133	29	sri	sri	PROPN
ajase-2385	133	30	lanka	lanka	PROPN
ajase-2385	133	31	using	use	VERB
ajase-2385	133	32	cvk	cvk	PROPN
ajase-2385	133	33	.	.	PUNCT
ajase-2385	134	1	figure	figure	NOUN
ajase-2385	134	2	2	2	NUM
ajase-2385	134	3	compares	compare	VERB
ajase-2385	134	4	the	the	DET
ajase-2385	134	5	performance	performance	NOUN
ajase-2385	134	6	of	of	ADP
ajase-2385	134	7	the	the	DET
ajase-2385	134	8	lr	lr	PROPN
ajase-2385	134	9	,	,	PUNCT
ajase-2385	134	10	brr	brr	PROPN
ajase-2385	134	11	,	,	PUNCT
ajase-2385	134	12	svr	svr	PROPN
ajase-2385	134	13	,	,	PUNCT
ajase-2385	134	14	and	and	CCONJ
ajase-2385	134	15	rf	rf	NOUN
ajase-2385	134	16	models	model	NOUN
ajase-2385	134	17	using	use	VERB
ajase-2385	134	18	the	the	DET
ajase-2385	134	19	cvk	cvk	ADJ
ajase-2385	134	20	approach	approach	NOUN
ajase-2385	134	21	at	at	ADP
ajase-2385	134	22	different	different	ADJ
ajase-2385	134	23	figure	figure	NOUN
ajase-2385	134	24	1	1	NUM
ajase-2385	134	25	:	:	PUNCT
ajase-2385	134	26	monthly	monthly	ADJ
ajase-2385	134	27	mean	mean	ADJ
ajase-2385	134	28	inflation	inflation	NOUN
ajase-2385	134	29	rate	rate	NOUN
ajase-2385	134	30	of	of	ADP
ajase-2385	134	31	sri	sri	PROPN
ajase-2385	134	32	lanka	lanka	PROPN
ajase-2385	134	33	(	(	PUNCT
ajase-2385	134	34	1988	1988	NUM
ajase-2385	134	35	-	-	SYM
ajase-2385	134	36	2021	2021	NUM
ajase-2385	134	37	)	)	PUNCT
ajase-2385	134	38	the	the	DET
ajase-2385	134	39	time	time	NOUN
ajase-2385	134	40	series	series	PROPN
ajase-2385	134	41	plot	plot	NOUN
ajase-2385	134	42	in	in	ADP
ajase-2385	134	43	figure	figure	NOUN
ajase-2385	134	44	1	1	NUM
ajase-2385	134	45	shows	show	VERB
ajase-2385	134	46	a	a	DET
ajase-2385	134	47	stochastic	stochastic	ADJ
ajase-2385	134	48	behaviour	behaviour	NOUN
ajase-2385	134	49	of	of	ADP
ajase-2385	134	50	the	the	DET
ajase-2385	134	51	inflation	inflation	NOUN
ajase-2385	134	52	data	datum	NOUN
ajase-2385	134	53	,	,	PUNCT
ajase-2385	134	54	and	and	CCONJ
ajase-2385	134	55	one	one	PRON
ajase-2385	134	56	can	can	AUX
ajase-2385	134	57	notice	notice	VERB
ajase-2385	134	58	that	that	SCONJ
ajase-2385	134	59	there	there	PRON
ajase-2385	134	60	are	be	VERB
ajase-2385	134	61	a	a	DET
ajase-2385	134	62	few	few	ADJ
ajase-2385	134	63	unusual	unusual	ADJ
ajase-2385	134	64	data	datum	NOUN
ajase-2385	134	65	points	point	NOUN
ajase-2385	134	66	,	,	PUNCT
ajase-2385	134	67	especially	especially	ADV
ajase-2385	134	68	one	one	NUM
ajase-2385	134	69	at	at	ADP
ajase-2385	134	70	june	june	PROPN
ajase-2385	134	71	in	in	ADP
ajase-2385	134	72	2008	2008	NUM
ajase-2385	134	73	.	.	PUNCT
ajase-2385	135	1	the	the	DET
ajase-2385	135	2	reasoning	reasoning	NOUN
ajase-2385	135	3	for	for	ADP
ajase-2385	135	4	this	this	PRON
ajase-2385	135	5	may	may	AUX
ajase-2385	135	6	be	be	AUX
ajase-2385	135	7	that	that	SCONJ
ajase-2385	135	8	during	during	ADP
ajase-2385	135	9	this	this	DET
ajase-2385	135	10	time	time	NOUN
ajase-2385	135	11	period	period	NOUN
ajase-2385	135	12	,	,	PUNCT
ajase-2385	135	13	the	the	DET
ajase-2385	135	14	war	war	NOUN
ajase-2385	135	15	in	in	ADP
ajase-2385	135	16	sri	sri	PROPN
ajase-2385	135	17	lanka	lanka	PROPN
ajase-2385	135	18	was	be	AUX
ajase-2385	135	19	at	at	ADP
ajase-2385	135	20	a	a	DET
ajase-2385	135	21	critical	critical	ADJ
ajase-2385	135	22	stage	stage	NOUN
ajase-2385	135	23	.	.	PUNCT
ajase-2385	136	1	in	in	ADP
ajase-2385	136	2	order	order	NOUN
ajase-2385	136	3	to	to	PART
ajase-2385	136	4	fit	fit	VERB
ajase-2385	136	5	the	the	DET
ajase-2385	136	6	above	above	ADJ
ajase-2385	136	7	four	four	NUM
ajase-2385	136	8	machining	machining	NOUN
ajase-2385	136	9	learning	learning	NOUN
ajase-2385	136	10	models	model	NOUN
ajase-2385	136	11	,	,	PUNCT
ajase-2385	136	12	we	we	PRON
ajase-2385	136	13	have	have	VERB
ajase-2385	136	14	to	to	PART
ajase-2385	136	15	convert	convert	VERB
ajase-2385	136	16	the	the	DET
ajase-2385	136	17	inflation	inflation	NOUN
ajase-2385	136	18	rate	rate	NOUN
ajase-2385	136	19	data	datum	NOUN
ajase-2385	136	20	into	into	ADP
ajase-2385	136	21	a	a	DET
ajase-2385	136	22	machine	machine	NOUN
ajase-2385	136	23	learning	learn	VERB
ajase-2385	136	24	data	datum	NOUN
ajase-2385	136	25	set	set	VERB
ajase-2385	136	26	by	by	ADP
ajase-2385	136	27	introducing	introduce	VERB
ajase-2385	136	28	a	a	DET
ajase-2385	136	29	new	new	ADJ
ajase-2385	136	30	set	set	NOUN
ajase-2385	136	31	of	of	ADP
ajase-2385	136	32	variables	variable	NOUN
ajase-2385	136	33	.	.	PUNCT
ajase-2385	137	1	the	the	DET
ajase-2385	137	2	response	response	NOUN
ajase-2385	137	3	variable	variable	NOUN
ajase-2385	137	4	,	,	PUNCT
ajase-2385	137	5	y	y	PROPN
ajase-2385	137	6	(	(	PUNCT
ajase-2385	137	7	t	t	PROPN
ajase-2385	137	8	)	)	PUNCT
ajase-2385	137	9	is	be	AUX
ajase-2385	137	10	the	the	DET
ajase-2385	137	11	inflation	inflation	NOUN
ajase-2385	137	12	rate	rate	NOUN
ajase-2385	137	13	at	at	ADP
ajase-2385	137	14	time	time	NOUN
ajase-2385	137	15	t.	t.	PROPN
ajase-2385	137	16	here	here	ADV
ajase-2385	137	17	,	,	PUNCT
ajase-2385	137	18	we	we	PRON
ajase-2385	137	19	use	use	VERB
ajase-2385	137	20	four	four	NUM
ajase-2385	137	21	predictor	predictor	NOUN
ajase-2385	137	22	variables	variable	NOUN
ajase-2385	137	23	:	:	PUNCT
ajase-2385	137	24	the	the	DET
ajase-2385	137	25	first	first	ADJ
ajase-2385	137	26	,	,	PUNCT
ajase-2385	137	27	second	second	ADJ
ajase-2385	137	28	,	,	PUNCT
ajase-2385	137	29	third	third	ADJ
ajase-2385	137	30	,	,	PUNCT
ajase-2385	137	31	and	and	CCONJ
ajase-2385	137	32	fourth	fourth	ADJ
ajase-2385	137	33	differences	difference	NOUN
ajase-2385	137	34	of	of	ADP
ajase-2385	137	35	y	y	PROPN
ajase-2385	137	36	(	(	PUNCT
ajase-2385	137	37	t	t	PROPN
ajase-2385	137	38	)	)	PUNCT
ajase-2385	137	39	and	and	CCONJ
ajase-2385	137	40	denote	denote	VERB
ajase-2385	137	41	them	they	PRON
ajase-2385	137	42	as	as	ADP
ajase-2385	137	43	y	y	PROPN
ajase-2385	137	44	(	(	PUNCT
ajase-2385	137	45	t	t	PROPN
ajase-2385	137	46	1),y	1),y	NUM
ajase-2385	137	47	(	(	PUNCT
ajase-2385	137	48	t	t	PROPN
ajase-2385	137	49	2),y	2),y	NUM
ajase-2385	137	50	(	(	PUNCT
ajase-2385	137	51	t	t	PROPN
ajase-2385	137	52	3	3	NUM
ajase-2385	137	53	)	)	PUNCT
ajase-2385	137	54	and	and	CCONJ
ajase-2385	137	55	y	y	PROPN
ajase-2385	137	56	(	(	PUNCT
ajase-2385	137	57	t	t	PROPN
ajase-2385	137	58	4	4	NUM
ajase-2385	137	59	)	)	PUNCT
ajase-2385	137	60	,	,	PUNCT
ajase-2385	137	61	respectively	respectively	ADV
ajase-2385	137	62	.	.	PUNCT
ajase-2385	138	1	figure	figure	NOUN
ajase-2385	138	2	2	2	NUM
ajase-2385	138	3	:	:	PUNCT
ajase-2385	138	4	comparison	comparison	NOUN
ajase-2385	138	5	of	of	ADP
ajase-2385	138	6	model	model	NOUN
ajase-2385	138	7	performance	performance	NOUN
ajase-2385	138	8	using	use	VERB
ajase-2385	138	9	k	k	ADJ
ajase-2385	138	10	-	-	ADJ
ajase-2385	138	11	fold	fold	ADJ
ajase-2385	138	12	cross	cross	ADJ
ajase-2385	138	13	-	-	ADJ
ajase-2385	138	14	validation	validation	ADJ
ajase-2385	138	15	sample	sample	NOUN
ajase-2385	138	16	sizes	size	NOUN
ajase-2385	138	17	ranging	range	VERB
ajase-2385	138	18	from	from	ADP
ajase-2385	138	19	50	50	NUM
ajase-2385	138	20	to	to	ADP
ajase-2385	138	21	405	405	NUM
ajase-2385	138	22	.	.	PUNCT
ajase-2385	139	1	the	the	DET
ajase-2385	139	2	figure	figure	NOUN
ajase-2385	139	3	includes	include	VERB
ajase-2385	139	4	four	four	NUM
ajase-2385	139	5	subplots	subplot	NOUN
ajase-2385	139	6	,	,	PUNCT
ajase-2385	139	7	each	each	PRON
ajase-2385	139	8	representing	represent	VERB
ajase-2385	139	9	a	a	DET
ajase-2385	139	10	different	different	ADJ
ajase-2385	139	11	machine	machine	NOUN
ajase-2385	139	12	learning	learn	VERB
ajase-2385	139	13	model	model	NOUN
ajase-2385	139	14	.	.	PUNCT
ajase-2385	140	1	the	the	DET
ajase-2385	140	2	x	x	X
ajase-2385	140	3	-	-	NOUN
ajase-2385	140	4	axis	axis	NOUN
ajase-2385	140	5	represents	represent	VERB
ajase-2385	140	6	the	the	DET
ajase-2385	140	7	sample	sample	NOUN
ajase-2385	140	8	size	size	NOUN
ajase-2385	140	9	,	,	PUNCT
ajase-2385	140	10	while	while	SCONJ
ajase-2385	140	11	the	the	DET
ajase-2385	140	12	y	y	NOUN
ajase-2385	140	13	-	-	PUNCT
ajase-2385	140	14	axis	axis	NOUN
ajase-2385	140	15	represents	represent	VERB
ajase-2385	140	16	the	the	DET
ajase-2385	140	17	mean	mean	ADJ
ajase-2385	140	18	rmse	rmse	NOUN
ajase-2385	140	19	value	value	NOUN
ajase-2385	140	20	obtained	obtain	VERB
ajase-2385	140	21	for	for	ADP
ajase-2385	140	22	each	each	DET
ajase-2385	140	23	sample	sample	NOUN
ajase-2385	140	24	size	size	NOUN
ajase-2385	140	25	.	.	PUNCT
ajase-2385	141	1	the	the	DET
ajase-2385	141	2	results	result	NOUN
ajase-2385	141	3	demonstrate	demonstrate	VERB
ajase-2385	141	4	that	that	SCONJ
ajase-2385	141	5	the	the	DET
ajase-2385	141	6	performance	performance	NOUN
ajase-2385	141	7	of	of	ADP
ajase-2385	141	8	each	each	DET
ajase-2385	141	9	model	model	NOUN
ajase-2385	141	10	varies	vary	VERB
ajase-2385	141	11	with	with	ADP
ajase-2385	141	12	the	the	DET
ajase-2385	141	13	sample	sample	NOUN
ajase-2385	141	14	size	size	NOUN
ajase-2385	141	15	,	,	PUNCT
ajase-2385	141	16	with	with	ADP
ajase-2385	141	17	some	some	DET
ajase-2385	141	18	models	model	NOUN
ajase-2385	141	19	performing	perform	VERB
ajase-2385	141	20	better	well	ADV
ajase-2385	141	21	than	than	ADP
ajase-2385	141	22	others	other	NOUN
ajase-2385	141	23	at	at	ADP
ajase-2385	141	24	certain	certain	ADJ
ajase-2385	141	25	sample	sample	NOUN
ajase-2385	141	26	sizes	size	NOUN
ajase-2385	141	27	.	.	PUNCT
ajase-2385	142	1	the	the	DET
ajase-2385	142	2	lr	lr	PROPN
ajase-2385	142	3	and	and	CCONJ
ajase-2385	142	4	brr	brr	NOUN
ajase-2385	142	5	models	model	NOUN
ajase-2385	142	6	consistently	consistently	ADV
ajase-2385	142	7	exhibit	exhibit	VERB
ajase-2385	142	8	the	the	DET
ajase-2385	142	9	lowest	low	ADJ
ajase-2385	142	10	mean	mean	ADJ
ajase-2385	142	11	rmse	rmse	NOUN
ajase-2385	142	12	values	value	NOUN
ajase-2385	142	13	across	across	ADP
ajase-2385	142	14	all	all	DET
ajase-2385	142	15	sample	sample	NOUN
ajase-2385	142	16	sizes	size	NOUN
ajase-2385	142	17	.	.	PUNCT
ajase-2385	143	1	on	on	ADP
ajase-2385	143	2	the	the	DET
ajase-2385	143	3	other	other	ADJ
ajase-2385	143	4	hand	hand	NOUN
ajase-2385	143	5	,	,	PUNCT
ajase-2385	143	6	the	the	DET
ajase-2385	143	7	svr	svr	PROPN
ajase-2385	143	8	and	and	CCONJ
ajase-2385	143	9	rf	rf	NOUN
ajase-2385	143	10	models	model	NOUN
ajase-2385	143	11	perform	perform	VERB
ajase-2385	143	12	comparatively	comparatively	ADV
ajase-2385	143	13	worse	bad	ADJ
ajase-2385	143	14	,	,	PUNCT
ajase-2385	143	15	particularly	particularly	ADV
ajase-2385	143	16	at	at	ADP
ajase-2385	143	17	smaller	small	ADJ
ajase-2385	143	18	sample	sample	NOUN
ajase-2385	143	19	sizes	size	NOUN
ajase-2385	143	20	.	.	PUNCT
ajase-2385	144	1	these	these	DET
ajase-2385	144	2	findings	finding	NOUN
ajase-2385	144	3	suggest	suggest	VERB
ajase-2385	144	4	that	that	SCONJ
ajase-2385	144	5	the	the	DET
ajase-2385	144	6	lr	lr	PROPN
ajase-2385	144	7	and	and	CCONJ
ajase-2385	144	8	brr	brr	NOUN
ajase-2385	144	9	models	model	NOUN
ajase-2385	144	10	may	may	AUX
ajase-2385	144	11	be	be	AUX
ajase-2385	144	12	more	more	ADV
ajase-2385	144	13	suitable	suitable	ADJ
ajase-2385	144	14	for	for	ADP
ajase-2385	144	15	predicting	predict	VERB
ajase-2385	144	16	the	the	DET
ajase-2385	144	17	monthly	monthly	ADJ
ajase-2385	144	18	mean	mean	NOUN
ajase-2385	144	19	inflation	inflation	NOUN
ajase-2385	144	20	rate	rate	NOUN
ajase-2385	144	21	in	in	ADP
ajase-2385	144	22	sri	sri	PROPN
ajase-2385	144	23	lanka	lanka	PROPN
ajase-2385	144	24	,	,	PUNCT
ajase-2385	144	25	especially	especially	ADV
ajase-2385	144	26	when	when	SCONJ
ajase-2385	144	27	dealing	deal	VERB
ajase-2385	144	28	with	with	ADP
ajase-2385	144	29	smaller	small	ADJ
ajase-2385	144	30	sample	sample	NOUN
ajase-2385	144	31	sizes	size	NOUN
ajase-2385	144	32	with	with	ADP
ajase-2385	144	33	cvk	cvk	PROPN
ajase-2385	144	34	.	.	PUNCT
ajase-2385	145	1	pa	pa	PROPN
ajase-2385	145	2	ge	ge	PROPN
ajase-2385	145	3	55	55	NUM
ajase-2385	145	4	https://journals.e-palli.com/home/index.php/ajase	https://journals.e-palli.com/home/index.php/ajase	PROPN
ajase-2385	145	5	am	be	AUX
ajase-2385	145	6	.	.	PUNCT
ajase-2385	146	1	j.	j.	PROPN
ajase-2385	146	2	appl	appl	PROPN
ajase-2385	146	3	.	.	PROPN
ajase-2385	147	1	stat	stat	PROPN
ajase-2385	147	2	.	.	PUNCT
ajase-2385	148	1	econ	econ	PROPN
ajase-2385	148	2	.	.	PUNCT
ajase-2385	149	1	3(1	3(1	NUM
ajase-2385	149	2	)	)	PUNCT
ajase-2385	149	3	51	51	NUM
ajase-2385	149	4	-	-	SYM
ajase-2385	149	5	60	60	NUM
ajase-2385	149	6	,	,	PUNCT
ajase-2385	149	7	2024	2024	NUM
ajase-2385	149	8	figure	figure	NOUN
ajase-2385	149	9	3	3	NUM
ajase-2385	149	10	is	be	AUX
ajase-2385	149	11	presented	present	VERB
ajase-2385	149	12	to	to	PART
ajase-2385	149	13	compare	compare	VERB
ajase-2385	149	14	the	the	DET
ajase-2385	149	15	performance	performance	NOUN
ajase-2385	149	16	of	of	ADP
ajase-2385	149	17	lr	lr	PROPN
ajase-2385	149	18	,	,	PUNCT
ajase-2385	149	19	brr	brr	PROPN
ajase-2385	149	20	,	,	PUNCT
ajase-2385	149	21	svr	svr	PROPN
ajase-2385	149	22	,	,	PUNCT
ajase-2385	149	23	and	and	CCONJ
ajase-2385	149	24	rfr	rfr	PROPN
ajase-2385	149	25	models	model	NOUN
ajase-2385	149	26	using	use	VERB
ajase-2385	149	27	the	the	DET
ajase-2385	149	28	wfv	wfv	NOUN
ajase-2385	149	29	technique	technique	NOUN
ajase-2385	149	30	.	.	PUNCT
ajase-2385	150	1	each	each	DET
ajase-2385	150	2	subplot	subplot	NOUN
ajase-2385	150	3	in	in	ADP
ajase-2385	150	4	the	the	DET
ajase-2385	150	5	figure	figure	NOUN
ajase-2385	150	6	represents	represent	VERB
ajase-2385	150	7	a	a	DET
ajase-2385	150	8	different	different	ADJ
ajase-2385	150	9	time	time	NOUN
ajase-2385	150	10	split	split	NOUN
ajase-2385	150	11	,	,	PUNCT
ajase-2385	150	12	and	and	CCONJ
ajase-2385	150	13	the	the	DET
ajase-2385	150	14	mean	mean	ADJ
ajase-2385	150	15	rmse	rmse	NOUN
ajase-2385	150	16	is	be	AUX
ajase-2385	150	17	used	use	VERB
ajase-2385	150	18	to	to	PART
ajase-2385	150	19	measure	measure	VERB
ajase-2385	150	20	the	the	DET
ajase-2385	150	21	model	model	NOUN
ajase-2385	150	22	’s	’s	PART
ajase-2385	150	23	performance	performance	NOUN
ajase-2385	150	24	.	.	PUNCT
ajase-2385	151	1	the	the	DET
ajase-2385	151	2	plots	plot	NOUN
ajase-2385	151	3	demonstrate	demonstrate	VERB
ajase-2385	151	4	the	the	DET
ajase-2385	151	5	stability	stability	NOUN
ajase-2385	151	6	and	and	CCONJ
ajase-2385	151	7	consistency	consistency	NOUN
ajase-2385	151	8	of	of	ADP
ajase-2385	151	9	the	the	DET
ajase-2385	151	10	models	model	NOUN
ajase-2385	151	11	’	'	PUNCT
ajase-2385	151	12	performance	performance	NOUN
ajase-2385	151	13	across	across	ADP
ajase-2385	151	14	different	different	ADJ
ajase-2385	151	15	time	time	NOUN
ajase-2385	151	16	splits	split	VERB
ajase-2385	151	17	,	,	PUNCT
ajase-2385	151	18	indicating	indicate	VERB
ajase-2385	151	19	that	that	SCONJ
ajase-2385	151	20	wfv	wfv	PROPN
ajase-2385	151	21	is	be	AUX
ajase-2385	151	22	a	a	DET
ajase-2385	151	23	valuable	valuable	ADJ
ajase-2385	151	24	technique	technique	NOUN
ajase-2385	151	25	for	for	ADP
ajase-2385	151	26	evaluating	evaluate	VERB
ajase-2385	151	27	the	the	DET
ajase-2385	151	28	performance	performance	NOUN
ajase-2385	151	29	of	of	ADP
ajase-2385	151	30	time	time	NOUN
ajase-2385	151	31	-	-	PUNCT
ajase-2385	151	32	series	series	NOUN
ajase-2385	151	33	data	datum	NOUN
ajase-2385	151	34	models	model	NOUN
ajase-2385	151	35	.	.	PUNCT
ajase-2385	152	1	the	the	DET
ajase-2385	152	2	simulation	simulation	NOUN
ajase-2385	152	3	’s	’s	PART
ajase-2385	152	4	objective	objective	NOUN
ajase-2385	152	5	is	be	AUX
ajase-2385	152	6	to	to	PART
ajase-2385	152	7	assess	assess	VERB
ajase-2385	152	8	the	the	DET
ajase-2385	152	9	effectiveness	effectiveness	NOUN
ajase-2385	152	10	of	of	ADP
ajase-2385	152	11	the	the	DET
ajase-2385	152	12	four	four	NUM
ajase-2385	152	13	machine	machine	NOUN
ajase-2385	152	14	learning	learning	NOUN
ajase-2385	152	15	models	model	NOUN
ajase-2385	152	16	and	and	CCONJ
ajase-2385	152	17	identify	identify	VERB
ajase-2385	152	18	the	the	DET
ajase-2385	152	19	most	most	ADV
ajase-2385	152	20	suitable	suitable	ADJ
ajase-2385	152	21	model	model	NOUN
ajase-2385	152	22	for	for	ADP
ajase-2385	152	23	predicting	predict	VERB
ajase-2385	152	24	the	the	DET
ajase-2385	152	25	monthly	monthly	ADJ
ajase-2385	152	26	mean	mean	NOUN
ajase-2385	152	27	inflation	inflation	NOUN
ajase-2385	152	28	rate	rate	NOUN
ajase-2385	152	29	in	in	ADP
ajase-2385	152	30	sri	sri	PROPN
ajase-2385	152	31	lanka	lanka	PROPN
ajase-2385	152	32	using	use	VERB
ajase-2385	152	33	wfv	wfv	PROPN
ajase-2385	152	34	.	.	PUNCT
ajase-2385	153	1	figure	figure	VERB
ajase-2385	153	2	3	3	NUM
ajase-2385	153	3	:	:	PUNCT
ajase-2385	153	4	comparison	comparison	NOUN
ajase-2385	153	5	of	of	ADP
ajase-2385	153	6	model	model	NOUN
ajase-2385	153	7	performance	performance	NOUN
ajase-2385	153	8	using	use	VERB
ajase-2385	153	9	wfv	wfv	NOUN
ajase-2385	153	10	table	table	NOUN
ajase-2385	153	11	1	1	NUM
ajase-2385	153	12	:	:	PUNCT
ajase-2385	153	13	comparison	comparison	NOUN
ajase-2385	153	14	of	of	ADP
ajase-2385	153	15	smlm	smlm	PROPN
ajase-2385	153	16	‘s	‘s	PART
ajase-2385	154	1	rmse	rmse	PROPN
ajase-2385	154	2	with	with	ADP
ajase-2385	154	3	cvk	cvk	ADJ
ajase-2385	154	4	and	and	CCONJ
ajase-2385	154	5	wfv	wfv	NOUN
ajase-2385	154	6	techniques	technique	NOUN
ajase-2385	154	7	at	at	ADP
ajase-2385	154	8	different	different	ADJ
ajase-2385	154	9	sample	sample	NOUN
ajase-2385	154	10	sizes	size	NOUN
ajase-2385	154	11	rmse	rmse	PROPN
ajase-2385	154	12	sample	sample	NOUN
ajase-2385	154	13	size	size	NOUN
ajase-2385	154	14	50	50	NUM
ajase-2385	154	15	100	100	NUM
ajase-2385	154	16	200	200	NUM
ajase-2385	154	17	350	350	NUM
ajase-2385	154	18	405	405	NUM
ajase-2385	154	19	lr_cvk	lr_cvk	ADJ
ajase-2385	154	20	0.091351	0.091351	NOUN
ajase-2385	155	1	0.082883	0.082883	NUM
ajase-2385	155	2	0.079515	0.079515	NUM
ajase-2385	155	3	0.078016	0.078016	NUM
ajase-2385	155	4	0.077575	0.077575	NUM
ajase-2385	155	5	lr	lr	NOUN
ajase-2385	155	6	_	_	X
ajase-2385	155	7	wfv	wfv	NOUN
ajase-2385	155	8	0.08694	0.08694	NUM
ajase-2385	155	9	0.083908	0.083908	NUM
ajase-2385	155	10	0.078658	0.078658	NUM
ajase-2385	155	11	0.07758	0.07758	NUM
ajase-2385	155	12	0.078942	0.078942	NUM
ajase-2385	155	13	brr_cvk	brr_cvk	ADJ
ajase-2385	155	14	0.092358	0.092358	NUM
ajase-2385	155	15	0.078415	0.078415	NUM
ajase-2385	155	16	0.078144	0.078144	NUM
ajase-2385	155	17	0.076632	0.076632	NUM
ajase-2385	155	18	0.077401	0.077401	NUM
ajase-2385	155	19	brr_wfv	brr_wfv	NOUN
ajase-2385	155	20	0.084405	0.084405	NUM
ajase-2385	155	21	0.08116	0.08116	NUM
ajase-2385	155	22	0.079336	0.079336	NUM
ajase-2385	155	23	0.076359	0.076359	NUM
ajase-2385	155	24	0.075956	0.075956	NUM
ajase-2385	155	25	svr_cvk	svr_cvk	ADJ
ajase-2385	155	26	0.093935	0.093935	NUM
ajase-2385	155	27	0.080772	0.080772	NUM
ajase-2385	155	28	0.074827	0.074827	NUM
ajase-2385	156	1	0.073928	0.073928	NUM
ajase-2385	156	2	0.076598	0.076598	NUM
ajase-2385	156	3	svr	svr	PROPN
ajase-2385	156	4	_	_	PRON
ajase-2385	156	5	wfv	wfv	NOUN
ajase-2385	156	6	0.100356	0.100356	NUM
ajase-2385	156	7	0.078344	0.078344	NUM
ajase-2385	156	8	0.076048	0.076048	NUM
ajase-2385	156	9	0.07283	0.07283	NUM
ajase-2385	156	10	0.071805	0.071805	NUM
ajase-2385	156	11	rf_cvk	rf_cvk	ADJ
ajase-2385	156	12	0.120294	0.120294	NUM
ajase-2385	156	13	0.099488	0.099488	NUM
ajase-2385	156	14	0.086512	0.086512	NUM
ajase-2385	156	15	0.082122	0.082122	NUM
ajase-2385	156	16	0.081185	0.081185	NUM
ajase-2385	156	17	rf	rf	NUM
ajase-2385	156	18	_	_	NOUN
ajase-2385	156	19	wfv	wfv	NOUN
ajase-2385	156	20	0.111612	0.111612	NUM
ajase-2385	156	21	0.101143	0.101143	NUM
ajase-2385	156	22	0.091514	0.091514	NUM
ajase-2385	156	23	0.083301	0.083301	NUM
ajase-2385	156	24	0.080442	0.080442	NUM
ajase-2385	156	25	the	the	DET
ajase-2385	156	26	table	table	NOUN
ajase-2385	156	27	1	1	NUM
ajase-2385	156	28	presents	present	VERB
ajase-2385	156	29	the	the	DET
ajase-2385	156	30	performance	performance	NOUN
ajase-2385	156	31	of	of	ADP
ajase-2385	156	32	four	four	NUM
ajase-2385	156	33	different	different	ADJ
ajase-2385	156	34	machine	machine	NOUN
ajase-2385	156	35	learning	learning	NOUN
ajase-2385	156	36	models	model	NOUN
ajase-2385	156	37	,	,	PUNCT
ajase-2385	156	38	lr	lr	PROPN
ajase-2385	156	39	,	,	PUNCT
ajase-2385	156	40	brr	brr	PROPN
ajase-2385	156	41	,	,	PUNCT
ajase-2385	156	42	svr	svr	PROPN
ajase-2385	156	43	,	,	PUNCT
ajase-2385	156	44	and	and	CCONJ
ajase-2385	156	45	rf	rf	NOUN
ajase-2385	156	46	,	,	PUNCT
ajase-2385	156	47	using	use	VERB
ajase-2385	156	48	two	two	NUM
ajase-2385	156	49	different	different	ADJ
ajase-2385	156	50	techniques	technique	NOUN
ajase-2385	156	51	:	:	PUNCT
ajase-2385	156	52	cvk	cvk	ADJ
ajase-2385	156	53	and	and	CCONJ
ajase-2385	156	54	wfv	wfv	X
ajase-2385	156	55	.	.	PUNCT
ajase-2385	157	1	the	the	DET
ajase-2385	157	2	models	model	NOUN
ajase-2385	157	3	were	be	AUX
ajase-2385	157	4	tested	test	VERB
ajase-2385	157	5	on	on	ADP
ajase-2385	157	6	five	five	NUM
ajase-2385	157	7	different	different	ADJ
ajase-2385	157	8	sample	sample	NOUN
ajase-2385	157	9	sizes	size	NOUN
ajase-2385	157	10	ranging	range	VERB
ajase-2385	157	11	from	from	ADP
ajase-2385	157	12	50	50	NUM
ajase-2385	157	13	to	to	ADP
ajase-2385	157	14	405	405	NUM
ajase-2385	157	15	.	.	PUNCT
ajase-2385	158	1	the	the	DET
ajase-2385	158	2	performance	performance	NOUN
ajase-2385	158	3	of	of	ADP
ajase-2385	158	4	each	each	DET
ajase-2385	158	5	model	model	NOUN
ajase-2385	158	6	was	be	AUX
ajase-2385	158	7	measured	measure	VERB
ajase-2385	158	8	using	use	VERB
ajase-2385	158	9	mean	mean	NOUN
ajase-2385	158	10	rmse	rmse	NOUN
ajase-2385	158	11	.	.	PUNCT
ajase-2385	159	1	the	the	DET
ajase-2385	159	2	results	result	NOUN
ajase-2385	159	3	indicate	indicate	VERB
ajase-2385	159	4	that	that	SCONJ
ajase-2385	159	5	,	,	PUNCT
ajase-2385	159	6	in	in	ADP
ajase-2385	159	7	general	general	ADJ
ajase-2385	159	8	,	,	PUNCT
ajase-2385	159	9	the	the	DET
ajase-2385	159	10	models	model	NOUN
ajase-2385	159	11	performed	perform	VERB
ajase-2385	159	12	better	well	ADV
ajase-2385	159	13	with	with	ADP
ajase-2385	159	14	larger	large	ADJ
ajase-2385	159	15	sample	sample	NOUN
ajase-2385	159	16	sizes	size	NOUN
ajase-2385	159	17	.	.	PUNCT
ajase-2385	160	1	additionally	additionally	ADV
ajase-2385	160	2	,	,	PUNCT
ajase-2385	160	3	some	some	DET
ajase-2385	160	4	models	model	NOUN
ajase-2385	160	5	showed	show	VERB
ajase-2385	160	6	better	well	ADJ
ajase-2385	160	7	performance	performance	NOUN
ajase-2385	160	8	with	with	ADP
ajase-2385	160	9	a	a	DET
ajase-2385	160	10	particular	particular	ADJ
ajase-2385	160	11	technique	technique	NOUN
ajase-2385	160	12	.	.	PUNCT
ajase-2385	161	1	for	for	ADP
ajase-2385	161	2	example	example	NOUN
ajase-2385	161	3	,	,	PUNCT
ajase-2385	161	4	lr	lr	PROPN
ajase-2385	161	5	,	,	PUNCT
ajase-2385	161	6	brr	brr	PROPN
ajase-2385	161	7	,	,	PUNCT
ajase-2385	161	8	and	and	CCONJ
ajase-2385	161	9	rf	rf	NOUN
ajase-2385	161	10	models	model	NOUN
ajase-2385	161	11	achieved	achieve	VERB
ajase-2385	161	12	lower	low	ADJ
ajase-2385	161	13	rmse	rmse	NOUN
ajase-2385	161	14	values	value	NOUN
ajase-2385	161	15	using	use	VERB
ajase-2385	161	16	wfv	wfv	NOUN
ajase-2385	161	17	technique	technique	NOUN
ajase-2385	161	18	,	,	PUNCT
ajase-2385	161	19	while	while	SCONJ
ajase-2385	161	20	svr	svr	PROPN
ajase-2385	161	21	showed	show	VERB
ajase-2385	161	22	better	well	ADJ
ajase-2385	161	23	performance	performance	NOUN
ajase-2385	161	24	using	use	VERB
ajase-2385	161	25	cvk	cvk	ADJ
ajase-2385	161	26	technique	technique	NOUN
ajase-2385	161	27	.	.	PUNCT
ajase-2385	162	1	overall	overall	ADV
ajase-2385	162	2	,	,	PUNCT
ajase-2385	162	3	the	the	DET
ajase-2385	162	4	table	table	NOUN
ajase-2385	162	5	highlights	highlight	VERB
ajase-2385	162	6	the	the	DET
ajase-2385	162	7	importance	importance	NOUN
ajase-2385	162	8	of	of	ADP
ajase-2385	162	9	selecting	select	VERB
ajase-2385	162	10	an	an	DET
ajase-2385	162	11	appropriate	appropriate	ADJ
ajase-2385	162	12	technique	technique	NOUN
ajase-2385	162	13	and	and	CCONJ
ajase-2385	162	14	sample	sample	NOUN
ajase-2385	162	15	size	size	NOUN
ajase-2385	162	16	when	when	SCONJ
ajase-2385	162	17	building	building	NOUN
ajase-2385	162	18	machine	machine	NOUN
ajase-2385	162	19	learning	learning	NOUN
ajase-2385	162	20	models	model	NOUN
ajase-2385	162	21	for	for	ADP
ajase-2385	162	22	time	time	NOUN
ajase-2385	162	23	-	-	PUNCT
ajase-2385	162	24	series	series	NOUN
ajase-2385	162	25	data	datum	NOUN
ajase-2385	162	26	.	.	PUNCT
ajase-2385	163	1	it	it	PRON
ajase-2385	163	2	also	also	ADV
ajase-2385	163	3	provides	provide	VERB
ajase-2385	163	4	useful	useful	ADJ
ajase-2385	163	5	insights	insight	NOUN
ajase-2385	163	6	into	into	ADP
ajase-2385	163	7	the	the	DET
ajase-2385	163	8	performance	performance	NOUN
ajase-2385	163	9	of	of	ADP
ajase-2385	163	10	different	different	ADJ
ajase-2385	163	11	models	model	NOUN
ajase-2385	163	12	under	under	ADP
ajase-2385	163	13	different	different	ADJ
ajase-2385	163	14	conditions	condition	NOUN
ajase-2385	163	15	,	,	PUNCT
ajase-2385	163	16	which	which	PRON
ajase-2385	163	17	can	can	AUX
ajase-2385	163	18	be	be	AUX
ajase-2385	163	19	helpful	helpful	ADJ
ajase-2385	163	20	in	in	ADP
ajase-2385	163	21	selecting	select	VERB
ajase-2385	163	22	the	the	DET
ajase-2385	163	23	most	most	ADV
ajase-2385	163	24	suitable	suitable	ADJ
ajase-2385	163	25	model	model	NOUN
ajase-2385	163	26	for	for	ADP
ajase-2385	163	27	specific	specific	ADJ
ajase-2385	163	28	applications	application	NOUN
ajase-2385	163	29	.	.	PUNCT
ajase-2385	164	1	algorithm	algorithm	NOUN
ajase-2385	164	2	1	1	NUM
ajase-2385	164	3	is	be	AUX
ajase-2385	164	4	a	a	DET
ajase-2385	164	5	pseudo	pseudo	NOUN
ajase-2385	164	6	code	code	NOUN
ajase-2385	164	7	for	for	ADP
ajase-2385	164	8	the	the	DET
ajase-2385	164	9	lr	lr	NOUN
ajase-2385	164	10	algorithm	algorithm	NOUN
ajase-2385	164	11	,	,	PUNCT
ajase-2385	164	12	which	which	PRON
ajase-2385	164	13	is	be	AUX
ajase-2385	164	14	used	use	VERB
ajase-2385	164	15	to	to	PART
ajase-2385	164	16	predict	predict	VERB
ajase-2385	164	17	the	the	DET
ajase-2385	164	18	response	response	NOUN
ajase-2385	164	19	(	(	PUNCT
ajase-2385	164	20	y	y	NOUN
ajase-2385	164	21	)	)	PUNCT
ajase-2385	164	22	dependent	dependent	ADJ
ajase-2385	164	23	on	on	ADP
ajase-2385	164	24	predictor	predictor	NOUN
ajase-2385	164	25	(	(	PUNCT
ajase-2385	164	26	x	x	NOUN
ajase-2385	164	27	)	)	PUNCT
ajase-2385	164	28	with	with	ADP
ajase-2385	164	29	an	an	DET
ajase-2385	164	30	error	error	NOUN
ajase-2385	164	31	tolerance	tolerance	NOUN
ajase-2385	164	32	ϵ.	ϵ.	NOUN
ajase-2385	164	33	the	the	DET
ajase-2385	164	34	algorithm	algorithm	NOUN
ajase-2385	164	35	starts	start	VERB
ajase-2385	164	36	with	with	ADP
ajase-2385	164	37	data	data	NOUN
ajase-2385	164	38	preprocessing	preprocessing	NOUN
ajase-2385	164	39	and	and	CCONJ
ajase-2385	164	40	initialization	initialization	NOUN
ajase-2385	164	41	,	,	PUNCT
ajase-2385	164	42	followed	follow	VERB
ajase-2385	164	43	by	by	ADP
ajase-2385	164	44	weight	weight	NOUN
ajase-2385	164	45	calculation	calculation	NOUN
ajase-2385	164	46	based	base	VERB
ajase-2385	164	47	on	on	ADP
ajase-2385	164	48	the	the	DET
ajase-2385	164	49	chosen	choose	VERB
ajase-2385	164	50	method	method	NOUN
ajase-2385	164	51	.	.	PUNCT
ajase-2385	165	1	the	the	DET
ajase-2385	165	2	lr	lr	PROPN
ajase-2385	165	3	algorithm	algorithm	NOUN
ajase-2385	165	4	iteratively	iteratively	ADV
ajase-2385	165	5	cycles	cycle	VERB
ajase-2385	165	6	through	through	ADP
ajase-2385	165	7	β	β	PRON
ajase-2385	165	8	until	until	SCONJ
ajase-2385	165	9	the	the	DET
ajase-2385	165	10	desired	desire	VERB
ajase-2385	165	11	result	result	NOUN
ajase-2385	165	12	is	be	AUX
ajase-2385	165	13	achieved	achieve	VERB
ajase-2385	165	14	.	.	PUNCT
ajase-2385	166	1	finally	finally	ADV
ajase-2385	166	2	,	,	PUNCT
ajase-2385	166	3	the	the	DET
ajase-2385	166	4	algorithm	algorithm	NOUN
ajase-2385	166	5	returns	return	VERB
ajase-2385	166	6	the	the	DET
ajase-2385	166	7	calculated	calculated	ADJ
ajase-2385	166	8	β	β	NOUN
ajase-2385	166	9	values	value	NOUN
ajase-2385	166	10	.	.	PUNCT
ajase-2385	167	1	pa	pa	PROPN
ajase-2385	167	2	ge	ge	PROPN
ajase-2385	167	3	56	56	NUM
ajase-2385	167	4	https://journals.e-palli.com/home/index.php/ajase	https://journals.e-palli.com/home/index.php/ajase	PROPN
ajase-2385	167	5	am	be	AUX
ajase-2385	167	6	.	.	PUNCT
ajase-2385	168	1	j.	j.	PROPN
ajase-2385	168	2	appl	appl	PROPN
ajase-2385	168	3	.	.	PROPN
ajase-2385	169	1	stat	stat	PROPN
ajase-2385	169	2	.	.	PUNCT
ajase-2385	170	1	econ	econ	PROPN
ajase-2385	170	2	.	.	PUNCT
ajase-2385	171	1	3(1	3(1	NUM
ajase-2385	171	2	)	)	PUNCT
ajase-2385	171	3	51	51	NUM
ajase-2385	171	4	-	-	SYM
ajase-2385	171	5	60	60	NUM
ajase-2385	171	6	,	,	PUNCT
ajase-2385	171	7	2024	2024	NUM
ajase-2385	171	8	figure	figure	NOUN
ajase-2385	171	9	4	4	NUM
ajase-2385	171	10	shows	show	VERB
ajase-2385	171	11	the	the	DET
ajase-2385	171	12	fitted	fit	VERB
ajase-2385	171	13	test	test	NOUN
ajase-2385	171	14	inflation	inflation	NOUN
ajase-2385	171	15	rates	rate	NOUN
ajase-2385	171	16	data	datum	NOUN
ajase-2385	171	17	for	for	ADP
ajase-2385	171	18	the	the	DET
ajase-2385	171	19	lr	lr	PROPN
ajase-2385	171	20	and	and	CCONJ
ajase-2385	171	21	brr	brr	NOUN
ajase-2385	171	22	models	model	NOUN
ajase-2385	171	23	using	use	VERB
ajase-2385	171	24	two	two	NUM
ajase-2385	171	25	different	different	ADJ
ajase-2385	171	26	techniques	technique	NOUN
ajase-2385	171	27	:	:	PUNCT
ajase-2385	171	28	cvk	cvk	ADJ
ajase-2385	171	29	and	and	CCONJ
ajase-2385	171	30	wfv	wfv	PROPN
ajase-2385	171	31	.	.	PUNCT
ajase-2385	172	1	the	the	DET
ajase-2385	172	2	lr	lr	PROPN
ajase-2385	172	3	model	model	NOUN
ajase-2385	172	4	with	with	ADP
ajase-2385	172	5	cvk	cvk	ADJ
ajase-2385	172	6	technique	technique	NOUN
ajase-2385	172	7	predicts	predict	VERB
ajase-2385	172	8	the	the	DET
ajase-2385	172	9	inflation	inflation	NOUN
ajase-2385	172	10	rates	rate	NOUN
ajase-2385	172	11	data	datum	NOUN
ajase-2385	172	12	using	use	VERB
ajase-2385	172	13	lasso	lasso	NOUN
ajase-2385	172	14	regression	regression	NOUN
ajase-2385	172	15	while	while	SCONJ
ajase-2385	172	16	minimizing	minimize	VERB
ajase-2385	172	17	the	the	DET
ajase-2385	172	18	prediction	prediction	NOUN
ajase-2385	172	19	error	error	NOUN
ajase-2385	172	20	with	with	ADP
ajase-2385	172	21	k	k	ADJ
ajase-2385	172	22	-	-	ADJ
ajase-2385	172	23	fold	fold	ADJ
ajase-2385	172	24	crossvalidation	crossvalidation	NOUN
ajase-2385	172	25	.	.	PUNCT
ajase-2385	173	1	on	on	ADP
ajase-2385	173	2	the	the	DET
ajase-2385	173	3	other	other	ADJ
ajase-2385	173	4	hand	hand	NOUN
ajase-2385	173	5	,	,	PUNCT
ajase-2385	173	6	the	the	DET
ajase-2385	173	7	brr	brr	PROPN
ajase-2385	173	8	model	model	NOUN
ajase-2385	173	9	with	with	ADP
ajase-2385	173	10	wfv	wfv	NOUN
ajase-2385	173	11	technique	technique	NOUN
ajase-2385	173	12	uses	use	VERB
ajase-2385	173	13	bayesian	bayesian	NOUN
ajase-2385	173	14	ridge	ridge	NOUN
ajase-2385	173	15	regression	regression	NOUN
ajase-2385	173	16	to	to	PART
ajase-2385	173	17	predict	predict	VERB
ajase-2385	173	18	the	the	DET
ajase-2385	173	19	inflation	inflation	NOUN
ajase-2385	173	20	rates	rate	NOUN
ajase-2385	173	21	data	datum	NOUN
ajase-2385	173	22	while	while	SCONJ
ajase-2385	173	23	weighing	weigh	VERB
ajase-2385	173	24	the	the	DET
ajase-2385	173	25	features	feature	NOUN
ajase-2385	173	26	by	by	ADP
ajase-2385	173	27	their	their	PRON
ajase-2385	173	28	variance	variance	NOUN
ajase-2385	173	29	.	.	PUNCT
ajase-2385	174	1	from	from	ADP
ajase-2385	174	2	the	the	DET
ajase-2385	174	3	graph	graph	NOUN
ajase-2385	174	4	,	,	PUNCT
ajase-2385	174	5	both	both	PRON
ajase-2385	174	6	lr	lr	NOUN
ajase-2385	174	7	and	and	CCONJ
ajase-2385	174	8	brr	brr	NOUN
ajase-2385	174	9	models	model	NOUN
ajase-2385	174	10	with	with	ADP
ajase-2385	174	11	cvk	cvk	ADJ
ajase-2385	174	12	technique	technique	NOUN
ajase-2385	174	13	provide	provide	VERB
ajase-2385	174	14	similar	similar	ADJ
ajase-2385	174	15	fitted	fit	VERB
ajase-2385	174	16	test	test	NOUN
ajase-2385	174	17	inflation	inflation	NOUN
ajase-2385	174	18	rates	rate	NOUN
ajase-2385	174	19	data	datum	NOUN
ajase-2385	174	20	for	for	ADP
ajase-2385	174	21	the	the	DET
ajase-2385	174	22	entire	entire	ADJ
ajase-2385	174	23	period	period	NOUN
ajase-2385	174	24	from	from	ADP
ajase-2385	174	25	october	october	PROPN
ajase-2385	174	26	2018	2018	NUM
ajase-2385	174	27	to	to	ADP
ajase-2385	174	28	september	september	PROPN
ajase-2385	174	29	2020	2020	NUM
ajase-2385	174	30	.	.	PUNCT
ajase-2385	175	1	however	however	ADV
ajase-2385	175	2	,	,	PUNCT
ajase-2385	175	3	the	the	DET
ajase-2385	175	4	lr	lr	NOUN
ajase-2385	175	5	model	model	NOUN
ajase-2385	175	6	with	with	ADP
ajase-2385	175	7	cvk	cvk	ADJ
ajase-2385	175	8	technique	technique	NOUN
ajase-2385	175	9	predicts	predict	NOUN
ajase-2385	175	10	slightly	slightly	ADV
ajase-2385	175	11	higher	high	ADJ
ajase-2385	175	12	inflation	inflation	NOUN
ajase-2385	175	13	rates	rate	NOUN
ajase-2385	175	14	compared	compare	VERB
ajase-2385	175	15	to	to	ADP
ajase-2385	175	16	the	the	DET
ajase-2385	175	17	brr	brr	NOUN
ajase-2385	175	18	model	model	NOUN
ajase-2385	175	19	with	with	ADP
ajase-2385	175	20	cvk	cvk	ADJ
ajase-2385	175	21	technique	technique	NOUN
ajase-2385	175	22	.	.	PUNCT
ajase-2385	176	1	on	on	ADP
ajase-2385	176	2	the	the	DET
ajase-2385	176	3	other	other	ADJ
ajase-2385	176	4	hand	hand	NOUN
ajase-2385	176	5	,	,	PUNCT
ajase-2385	176	6	the	the	DET
ajase-2385	176	7	brr	brr	PROPN
ajase-2385	176	8	model	model	NOUN
ajase-2385	176	9	with	with	ADP
ajase-2385	176	10	wfv	wfv	NOUN
ajase-2385	176	11	technique	technique	NOUN
ajase-2385	176	12	predicts	predict	NOUN
ajase-2385	176	13	lower	low	ADJ
ajase-2385	176	14	inflation	inflation	NOUN
ajase-2385	176	15	rates	rate	NOUN
ajase-2385	176	16	than	than	ADP
ajase-2385	176	17	the	the	DET
ajase-2385	176	18	lr	lr	NOUN
ajase-2385	176	19	model	model	NOUN
ajase-2385	176	20	with	with	ADP
ajase-2385	176	21	cvk	cvk	ADJ
ajase-2385	176	22	technique	technique	NOUN
ajase-2385	176	23	,	,	PUNCT
ajase-2385	176	24	especially	especially	ADV
ajase-2385	176	25	from	from	ADP
ajase-2385	176	26	february	february	PROPN
ajase-2385	176	27	2019	2019	NUM
ajase-2385	176	28	to	to	ADP
ajase-2385	176	29	september	september	PROPN
ajase-2385	176	30	2020	2020	NUM
ajase-2385	176	31	.	.	PUNCT
ajase-2385	177	1	overall	overall	ADV
ajase-2385	177	2	,	,	PUNCT
ajase-2385	177	3	the	the	DET
ajase-2385	177	4	lr	lr	NOUN
ajase-2385	177	5	model	model	NOUN
ajase-2385	177	6	with	with	ADP
ajase-2385	177	7	cvk	cvk	ADJ
ajase-2385	177	8	technique	technique	NOUN
ajase-2385	177	9	and	and	CCONJ
ajase-2385	177	10	the	the	DET
ajase-2385	177	11	brr	brr	PROPN
ajase-2385	177	12	model	model	NOUN
ajase-2385	177	13	with	with	ADP
ajase-2385	177	14	wfv	wfv	NOUN
ajase-2385	177	15	technique	technique	NOUN
ajase-2385	177	16	provide	provide	VERB
ajase-2385	177	17	different	different	ADJ
ajase-2385	177	18	predictions	prediction	NOUN
ajase-2385	177	19	for	for	ADP
ajase-2385	177	20	the	the	DET
ajase-2385	177	21	inflation	inflation	NOUN
ajase-2385	177	22	rates	rate	NOUN
ajase-2385	177	23	data	datum	NOUN
ajase-2385	177	24	,	,	PUNCT
ajase-2385	177	25	indicating	indicate	VERB
ajase-2385	177	26	the	the	DET
ajase-2385	177	27	importance	importance	NOUN
ajase-2385	177	28	of	of	ADP
ajase-2385	177	29	choosing	choose	VERB
ajase-2385	177	30	the	the	DET
ajase-2385	177	31	appropriate	appropriate	ADJ
ajase-2385	177	32	model	model	NOUN
ajase-2385	177	33	and	and	CCONJ
ajase-2385	177	34	technique	technique	NOUN
ajase-2385	177	35	for	for	ADP
ajase-2385	177	36	inflation	inflation	NOUN
ajase-2385	177	37	rate	rate	NOUN
ajase-2385	177	38	prediction	prediction	NOUN
ajase-2385	177	39	.	.	PUNCT
ajase-2385	178	1	performs	perform	VERB
ajase-2385	178	2	the	the	DET
ajase-2385	178	3	β	β	NOUN
ajase-2385	178	4	cycle	cycle	NOUN
ajase-2385	178	5	until	until	SCONJ
ajase-2385	178	6	specific	specific	ADJ
ajase-2385	178	7	conditions	condition	NOUN
ajase-2385	178	8	are	be	AUX
ajase-2385	178	9	met	meet	VERB
ajase-2385	178	10	.	.	PUNCT
ajase-2385	179	1	overall	overall	ADV
ajase-2385	179	2	,	,	PUNCT
ajase-2385	179	3	the	the	DET
ajase-2385	179	4	brr	brr	PROPN
ajase-2385	179	5	algorithm	algorithm	NOUN
ajase-2385	179	6	provides	provide	VERB
ajase-2385	179	7	a	a	DET
ajase-2385	179	8	robust	robust	ADJ
ajase-2385	179	9	and	and	CCONJ
ajase-2385	179	10	efficient	efficient	ADJ
ajase-2385	179	11	solution	solution	NOUN
ajase-2385	179	12	for	for	ADP
ajase-2385	179	13	linear	linear	ADJ
ajase-2385	179	14	regression	regression	NOUN
ajase-2385	179	15	analysis	analysis	NOUN
ajase-2385	179	16	,	,	PUNCT
ajase-2385	179	17	and	and	CCONJ
ajase-2385	179	18	its	its	PRON
ajase-2385	179	19	implementation	implementation	NOUN
ajase-2385	179	20	can	can	AUX
ajase-2385	179	21	be	be	AUX
ajase-2385	179	22	tailored	tailor	VERB
ajase-2385	179	23	to	to	ADP
ajase-2385	179	24	different	different	ADJ
ajase-2385	179	25	research	research	NOUN
ajase-2385	179	26	needs	need	NOUN
ajase-2385	179	27	based	base	VERB
ajase-2385	179	28	on	on	ADP
ajase-2385	179	29	the	the	DET
ajase-2385	179	30	choice	choice	NOUN
ajase-2385	179	31	of	of	ADP
ajase-2385	179	32	weight	weight	NOUN
ajase-2385	179	33	calculation	calculation	NOUN
ajase-2385	179	34	method	method	NOUN
ajase-2385	179	35	.	.	PUNCT
ajase-2385	180	1	figure	figure	NOUN
ajase-2385	180	2	4	4	NUM
ajase-2385	180	3	:	:	PUNCT
ajase-2385	180	4	fitted	fit	VERB
ajase-2385	180	5	test	test	NOUN
ajase-2385	180	6	inflation	inflation	NOUN
ajase-2385	180	7	rates	rate	NOUN
ajase-2385	180	8	data	datum	NOUN
ajase-2385	180	9	for	for	ADP
ajase-2385	180	10	lr	lr	NOUN
ajase-2385	180	11	and	and	CCONJ
ajase-2385	180	12	bbr	bbr	PROPN
ajase-2385	180	13	models	model	NOUN
ajase-2385	180	14	with	with	ADP
ajase-2385	180	15	cvk	cvk	ADJ
ajase-2385	180	16	and	and	CCONJ
ajase-2385	180	17	wfv	wfv	PROPN
ajase-2385	180	18	techniques	technique	NOUN
ajase-2385	180	19	the	the	DET
ajase-2385	180	20	presented	present	VERB
ajase-2385	180	21	pseudo	pseudo	NOUN
ajase-2385	180	22	(	(	PUNCT
ajase-2385	180	23	algorithm	algorithm	NOUN
ajase-2385	180	24	2	2	NUM
ajase-2385	180	25	)	)	PUNCT
ajase-2385	180	26	code	code	NOUN
ajase-2385	180	27	outlines	outline	VERB
ajase-2385	180	28	the	the	DET
ajase-2385	180	29	implementation	implementation	NOUN
ajase-2385	180	30	of	of	ADP
ajase-2385	180	31	brr	brr	PROPN
ajase-2385	180	32	algorithm	algorithm	PROPN
ajase-2385	180	33	,	,	PUNCT
ajase-2385	180	34	which	which	PRON
ajase-2385	180	35	is	be	AUX
ajase-2385	180	36	a	a	DET
ajase-2385	180	37	popular	popular	ADJ
ajase-2385	180	38	technique	technique	NOUN
ajase-2385	180	39	for	for	ADP
ajase-2385	180	40	linear	linear	ADJ
ajase-2385	180	41	regression	regression	NOUN
ajase-2385	180	42	analysis	analysis	NOUN
ajase-2385	180	43	.	.	PUNCT
ajase-2385	181	1	the	the	DET
ajase-2385	181	2	algorithm	algorithm	NOUN
ajase-2385	181	3	takes	take	VERB
ajase-2385	181	4	input	input	NOUN
ajase-2385	181	5	of	of	ADP
ajase-2385	181	6	response	response	NOUN
ajase-2385	181	7	y	y	PROPN
ajase-2385	181	8	dependent	dependent	ADJ
ajase-2385	181	9	on	on	ADP
ajase-2385	181	10	predictor	predictor	NOUN
ajase-2385	181	11	x	x	PUNCT
ajase-2385	181	12	and	and	CCONJ
ajase-2385	181	13	error	error	NOUN
ajase-2385	181	14	tolerance	tolerance	NOUN
ajase-2385	181	15	ϵ	ϵ	NOUN
ajase-2385	181	16	,	,	PUNCT
ajase-2385	181	17	and	and	CCONJ
ajase-2385	181	18	outputs	output	VERB
ajase-2385	181	19	the	the	DET
ajase-2385	181	20	brr	brr	NOUN
ajase-2385	181	21	solution	solution	NOUN
ajase-2385	181	22	.	.	PUNCT
ajase-2385	182	1	the	the	DET
ajase-2385	182	2	algorithm	algorithm	NOUN
ajase-2385	182	3	involves	involve	VERB
ajase-2385	182	4	preprocessing	preprocessing	NOUN
ajase-2385	182	5	of	of	ADP
ajase-2385	182	6	data	datum	NOUN
ajase-2385	182	7	by	by	ADP
ajase-2385	182	8	normalizing	normalize	VERB
ajase-2385	182	9	x	x	PUNCT
ajase-2385	182	10	and	and	CCONJ
ajase-2385	182	11	y	y	PROPN
ajase-2385	182	12	,	,	PUNCT
ajase-2385	182	13	followed	follow	VERB
ajase-2385	182	14	by	by	ADP
ajase-2385	182	15	initialization	initialization	NOUN
ajase-2385	182	16	of	of	ADP
ajase-2385	182	17	u	u	PROPN
ajase-2385	182	18	,	,	PUNCT
ajase-2385	182	19	ŷ	ŷ	PROPN
ajase-2385	182	20	,	,	PUNCT
ajase-2385	182	21	and	and	CCONJ
ajase-2385	182	22	other	other	ADJ
ajase-2385	182	23	variables	variable	NOUN
ajase-2385	182	24	.	.	PUNCT
ajase-2385	183	1	it	it	PRON
ajase-2385	183	2	then	then	ADV
ajase-2385	183	3	calculates	calculate	VERB
ajase-2385	183	4	the	the	DET
ajase-2385	183	5	weight	weight	NOUN
ajase-2385	183	6	by	by	ADP
ajase-2385	183	7	either	either	DET
ajase-2385	183	8	part_pac	part_pac	PROPN
ajase-2385	183	9	,	,	PUNCT
ajase-2385	183	10	iw	iw	INTJ
ajase-2385	183	11	,	,	PUNCT
ajase-2385	183	12	or	or	CCONJ
ajase-2385	183	13	critic	critic	NOUN
ajase-2385	183	14	method	method	NOUN
ajase-2385	183	15	,	,	PUNCT
ajase-2385	183	16	centralizes	centralize	VERB
ajase-2385	183	17	rw	rw	NOUN
ajase-2385	183	18	,	,	PUNCT
ajase-2385	183	19	and	and	CCONJ
ajase-2385	183	20	algorithm	algorithm	NOUN
ajase-2385	183	21	3	3	NUM
ajase-2385	183	22	is	be	AUX
ajase-2385	183	23	the	the	DET
ajase-2385	183	24	pseudo	pseudo	NOUN
ajase-2385	183	25	code	code	NOUN
ajase-2385	183	26	for	for	ADP
ajase-2385	183	27	svr	svr	PROPN
ajase-2385	183	28	,	,	PUNCT
ajase-2385	183	29	a	a	DET
ajase-2385	183	30	popular	popular	ADJ
ajase-2385	183	31	regression	regression	NOUN
ajase-2385	183	32	algorithm	algorithm	NOUN
ajase-2385	183	33	used	use	VERB
ajase-2385	183	34	in	in	ADP
ajase-2385	183	35	machine	machine	NOUN
ajase-2385	183	36	learning	learning	NOUN
ajase-2385	183	37	.	.	PUNCT
ajase-2385	184	1	svr	svr	PROPN
ajase-2385	184	2	involves	involve	VERB
ajase-2385	184	3	choosing	choose	VERB
ajase-2385	184	4	a	a	DET
ajase-2385	184	5	set	set	NOUN
ajase-2385	184	6	of	of	ADP
ajase-2385	184	7	support	support	NOUN
ajase-2385	184	8	vectors	vector	NOUN
ajase-2385	184	9	from	from	ADP
ajase-2385	184	10	the	the	DET
ajase-2385	184	11	input	input	NOUN
ajase-2385	184	12	data	datum	NOUN
ajase-2385	184	13	and	and	CCONJ
ajase-2385	184	14	constructing	construct	VERB
ajase-2385	184	15	a	a	DET
ajase-2385	184	16	linear	linear	ADJ
ajase-2385	184	17	model	model	NOUN
ajase-2385	184	18	to	to	PART
ajase-2385	184	19	minimize	minimize	VERB
ajase-2385	184	20	the	the	DET
ajase-2385	184	21	error	error	NOUN
ajase-2385	184	22	between	between	ADP
ajase-2385	184	23	the	the	DET
ajase-2385	184	24	predicted	predict	VERB
ajase-2385	184	25	values	value	NOUN
ajase-2385	184	26	and	and	CCONJ
ajase-2385	184	27	the	the	DET
ajase-2385	184	28	actual	actual	ADJ
ajase-2385	184	29	values	value	NOUN
ajase-2385	184	30	.	.	PUNCT
ajase-2385	185	1	the	the	DET
ajase-2385	185	2	algorithm	algorithm	NOUN
ajase-2385	185	3	involves	involve	VERB
ajase-2385	185	4	several	several	ADJ
ajase-2385	185	5	iterations	iteration	NOUN
ajase-2385	185	6	where	where	SCONJ
ajase-2385	185	7	support	support	NOUN
ajase-2385	185	8	vectors	vector	NOUN
ajase-2385	185	9	are	be	AUX
ajase-2385	185	10	chosen	choose	VERB
ajase-2385	185	11	,	,	PUNCT
ajase-2385	185	12	and	and	CCONJ
ajase-2385	185	13	the	the	DET
ajase-2385	185	14	model	model	NOUN
ajase-2385	185	15	is	be	AUX
ajase-2385	185	16	updated	update	VERB
ajase-2385	185	17	with	with	ADP
ajase-2385	185	18	the	the	DET
ajase-2385	185	19	chosen	choose	VERB
ajase-2385	185	20	support	support	NOUN
ajase-2385	185	21	vectors	vector	NOUN
ajase-2385	185	22	until	until	SCONJ
ajase-2385	185	23	convergence	convergence	NOUN
ajase-2385	185	24	is	be	AUX
ajase-2385	185	25	reached	reach	VERB
ajase-2385	185	26	.	.	PUNCT
ajase-2385	186	1	figure	figure	NOUN
ajase-2385	186	2	5	5	NUM
ajase-2385	186	3	displays	display	NOUN
ajase-2385	186	4	the	the	DET
ajase-2385	186	5	fitted	fit	VERB
ajase-2385	186	6	test	test	NOUN
ajase-2385	186	7	inflation	inflation	NOUN
ajase-2385	186	8	rates	rate	NOUN
ajase-2385	186	9	data	datum	NOUN
ajase-2385	186	10	for	for	ADP
ajase-2385	186	11	the	the	DET
ajase-2385	186	12	svr	svr	PROPN
ajase-2385	186	13	and	and	CCONJ
ajase-2385	186	14	rfr	rfr	PROPN
ajase-2385	186	15	models	model	NOUN
ajase-2385	186	16	using	use	VERB
ajase-2385	186	17	two	two	NUM
ajase-2385	186	18	different	different	ADJ
ajase-2385	186	19	techniques	technique	NOUN
ajase-2385	186	20	:	:	PUNCT
ajase-2385	186	21	cvk	cvk	ADJ
ajase-2385	186	22	and	and	CCONJ
ajase-2385	186	23	wfv	wfv	PROPN
ajase-2385	186	24	.	.	PUNCT
ajase-2385	187	1	the	the	DET
ajase-2385	187	2	svr	svr	PROPN
ajase-2385	187	3	model	model	NOUN
ajase-2385	187	4	with	with	ADP
ajase-2385	187	5	cvk	cvk	ADJ
ajase-2385	187	6	technique	technique	NOUN
ajase-2385	187	7	predicts	predict	VERB
ajase-2385	187	8	the	the	DET
ajase-2385	187	9	inflation	inflation	NOUN
ajase-2385	187	10	rates	rate	NOUN
ajase-2385	187	11	data	datum	NOUN
ajase-2385	187	12	using	use	VERB
ajase-2385	187	13	support	support	NOUN
ajase-2385	187	14	vector	vector	NOUN
ajase-2385	187	15	regression	regression	NOUN
ajase-2385	187	16	while	while	SCONJ
ajase-2385	187	17	minimizing	minimize	VERB
ajase-2385	187	18	the	the	DET
ajase-2385	187	19	prediction	prediction	NOUN
ajase-2385	187	20	error	error	NOUN
ajase-2385	187	21	with	with	ADP
ajase-2385	187	22	cvk	cvk	ADJ
ajase-2385	187	23	.	.	PUNCT
ajase-2385	188	1	on	on	ADP
ajase-2385	188	2	the	the	DET
ajase-2385	188	3	other	other	ADJ
ajase-2385	188	4	hand	hand	NOUN
ajase-2385	188	5	,	,	PUNCT
ajase-2385	188	6	the	the	DET
ajase-2385	188	7	rfr	rfr	PROPN
ajase-2385	188	8	model	model	NOUN
ajase-2385	188	9	with	with	ADP
ajase-2385	188	10	wfv	wfv	NOUN
ajase-2385	188	11	technique	technique	NOUN
ajase-2385	188	12	uses	use	VERB
ajase-2385	188	13	random	random	ADJ
ajase-2385	188	14	forest	forest	NOUN
ajase-2385	188	15	regression	regression	NOUN
ajase-2385	188	16	to	to	PART
ajase-2385	188	17	predict	predict	VERB
ajase-2385	188	18	the	the	DET
ajase-2385	188	19	inflation	inflation	NOUN
ajase-2385	188	20	rates	rate	NOUN
ajase-2385	188	21	data	datum	NOUN
ajase-2385	188	22	while	while	SCONJ
ajase-2385	188	23	weighing	weigh	VERB
ajase-2385	188	24	the	the	DET
ajase-2385	188	25	features	feature	NOUN
ajase-2385	188	26	by	by	ADP
ajase-2385	188	27	their	their	PRON
ajase-2385	188	28	variance	variance	NOUN
ajase-2385	188	29	.	.	PUNCT
ajase-2385	189	1	from	from	ADP
ajase-2385	189	2	the	the	DET
ajase-2385	189	3	graph	graph	NOUN
ajase-2385	189	4	,	,	PUNCT
ajase-2385	189	5	both	both	DET
ajase-2385	189	6	svr	svr	PROPN
ajase-2385	189	7	and	and	CCONJ
ajase-2385	189	8	rfr	rfr	PROPN
ajase-2385	189	9	models	model	NOUN
ajase-2385	189	10	with	with	ADP
ajase-2385	189	11	cvk	cvk	ADJ
ajase-2385	189	12	technique	technique	NOUN
ajase-2385	189	13	provide	provide	VERB
ajase-2385	189	14	similar	similar	ADJ
ajase-2385	189	15	fitted	fit	VERB
ajase-2385	189	16	test	test	NOUN
ajase-2385	189	17	inflation	inflation	NOUN
ajase-2385	189	18	rates	rate	NOUN
ajase-2385	189	19	data	datum	NOUN
ajase-2385	189	20	for	for	ADP
ajase-2385	189	21	the	the	DET
ajase-2385	189	22	entire	entire	ADJ
ajase-2385	189	23	period	period	NOUN
ajase-2385	189	24	from	from	ADP
ajase-2385	189	25	october	october	PROPN
ajase-2385	189	26	2018	2018	NUM
ajase-2385	189	27	to	to	ADP
ajase-2385	189	28	september	september	PROPN
ajase-2385	189	29	2020	2020	NUM
ajase-2385	189	30	.	.	PUNCT
ajase-2385	190	1	however	however	ADV
ajase-2385	190	2	,	,	PUNCT
ajase-2385	190	3	the	the	DET
ajase-2385	190	4	svr	svr	PROPN
ajase-2385	190	5	model	model	NOUN
ajase-2385	190	6	with	with	ADP
ajase-2385	190	7	cvk	cvk	ADJ
ajase-2385	190	8	technique	technique	NOUN
ajase-2385	190	9	predicts	predict	NOUN
ajase-2385	190	10	slightly	slightly	ADV
ajase-2385	190	11	higher	high	ADJ
ajase-2385	190	12	inflation	inflation	NOUN
ajase-2385	190	13	rates	rate	NOUN
ajase-2385	190	14	compared	compare	VERB
ajase-2385	190	15	to	to	ADP
ajase-2385	190	16	the	the	DET
ajase-2385	190	17	rfr	rfr	PROPN
ajase-2385	190	18	model	model	NOUN
ajase-2385	190	19	with	with	ADP
ajase-2385	190	20	wfv	wfv	NOUN
ajase-2385	190	21	technique	technique	NOUN
ajase-2385	190	22	.	.	PUNCT
ajase-2385	191	1	on	on	ADP
ajase-2385	191	2	the	the	DET
ajase-2385	191	3	other	other	ADJ
ajase-2385	191	4	hand	hand	NOUN
ajase-2385	191	5	,	,	PUNCT
ajase-2385	191	6	the	the	DET
ajase-2385	191	7	rfr	rfr	PROPN
ajase-2385	191	8	model	model	NOUN
ajase-2385	191	9	with	with	ADP
ajase-2385	191	10	wfv	wfv	NOUN
ajase-2385	191	11	technique	technique	NOUN
ajase-2385	191	12	predicts	predict	NOUN
ajase-2385	191	13	lower	low	ADJ
ajase-2385	191	14	inflation	inflation	NOUN
ajase-2385	191	15	rates	rate	NOUN
ajase-2385	191	16	than	than	ADP
ajase-2385	191	17	the	the	DET
ajase-2385	191	18	svr	svr	PROPN
ajase-2385	191	19	model	model	NOUN
ajase-2385	191	20	with	with	ADP
ajase-2385	191	21	cvk	cvk	ADJ
ajase-2385	191	22	technique	technique	NOUN
ajase-2385	191	23	,	,	PUNCT
ajase-2385	191	24	especially	especially	ADV
ajase-2385	191	25	from	from	ADP
ajase-2385	191	26	february	february	PROPN
ajase-2385	191	27	2019	2019	NUM
ajase-2385	191	28	to	to	ADP
ajase-2385	191	29	september	september	PROPN
ajase-2385	191	30	2020	2020	NUM
ajase-2385	191	31	.	.	PUNCT
ajase-2385	192	1	pa	pa	PROPN
ajase-2385	192	2	ge	ge	PROPN
ajase-2385	192	3	57	57	NUM
ajase-2385	192	4	https://journals.e-palli.com/home/index.php/ajase	https://journals.e-palli.com/home/index.php/ajase	PROPN
ajase-2385	192	5	am	am	NOUN
ajase-2385	192	6	.	.	PUNCT
ajase-2385	193	1	j.	j.	PROPN
ajase-2385	193	2	appl	appl	PROPN
ajase-2385	193	3	.	.	PROPN
ajase-2385	194	1	stat	stat	PROPN
ajase-2385	194	2	.	.	PUNCT
ajase-2385	195	1	econ	econ	PROPN
ajase-2385	195	2	.	.	PUNCT
ajase-2385	196	1	3(1	3(1	NUM
ajase-2385	196	2	)	)	PUNCT
ajase-2385	196	3	51	51	NUM
ajase-2385	196	4	-	-	SYM
ajase-2385	196	5	60	60	NUM
ajase-2385	196	6	,	,	PUNCT
ajase-2385	196	7	2024	2024	NUM
ajase-2385	196	8	overall	overall	NOUN
ajase-2385	196	9	,	,	PUNCT
ajase-2385	196	10	the	the	DET
ajase-2385	196	11	svr	svr	PROPN
ajase-2385	196	12	model	model	NOUN
ajase-2385	196	13	with	with	ADP
ajase-2385	196	14	cvk	cvk	ADJ
ajase-2385	196	15	technique	technique	NOUN
ajase-2385	196	16	and	and	CCONJ
ajase-2385	196	17	the	the	DET
ajase-2385	196	18	rfr	rfr	PROPN
ajase-2385	196	19	model	model	NOUN
ajase-2385	196	20	with	with	ADP
ajase-2385	196	21	wfv	wfv	NOUN
ajase-2385	196	22	technique	technique	NOUN
ajase-2385	196	23	provide	provide	VERB
ajase-2385	196	24	different	different	ADJ
ajase-2385	196	25	predictions	prediction	NOUN
ajase-2385	196	26	for	for	ADP
ajase-2385	196	27	the	the	DET
ajase-2385	196	28	inflation	inflation	NOUN
ajase-2385	196	29	rates	rate	NOUN
ajase-2385	196	30	data	datum	NOUN
ajase-2385	196	31	,	,	PUNCT
ajase-2385	196	32	indicating	indicate	VERB
ajase-2385	196	33	the	the	DET
ajase-2385	196	34	importance	importance	NOUN
ajase-2385	196	35	of	of	ADP
ajase-2385	196	36	choosing	choose	VERB
ajase-2385	196	37	the	the	DET
ajase-2385	196	38	appropriate	appropriate	ADJ
ajase-2385	196	39	model	model	NOUN
ajase-2385	196	40	and	and	CCONJ
ajase-2385	196	41	technique	technique	NOUN
ajase-2385	196	42	for	for	ADP
ajase-2385	196	43	inflation	inflation	NOUN
ajase-2385	196	44	rate	rate	NOUN
ajase-2385	196	45	prediction	prediction	NOUN
ajase-2385	196	46	.	.	PUNCT
ajase-2385	197	1	the	the	DET
ajase-2385	197	2	choice	choice	NOUN
ajase-2385	197	3	between	between	ADP
ajase-2385	197	4	these	these	DET
ajase-2385	197	5	models	model	NOUN
ajase-2385	197	6	and	and	CCONJ
ajase-2385	197	7	techniques	technique	NOUN
ajase-2385	197	8	may	may	AUX
ajase-2385	197	9	depend	depend	VERB
ajase-2385	197	10	on	on	ADP
ajase-2385	197	11	the	the	DET
ajase-2385	197	12	specific	specific	ADJ
ajase-2385	197	13	requirements	requirement	NOUN
ajase-2385	197	14	of	of	ADP
ajase-2385	197	15	the	the	DET
ajase-2385	197	16	application	application	NOUN
ajase-2385	197	17	and	and	CCONJ
ajase-2385	197	18	the	the	DET
ajase-2385	197	19	underlying	underlying	ADJ
ajase-2385	197	20	data	data	NOUN
ajase-2385	197	21	characteristics	characteristic	NOUN
ajase-2385	197	22	.	.	PUNCT
ajase-2385	198	1	table	table	NOUN
ajase-2385	198	2	2	2	NUM
ajase-2385	198	3	presents	present	VERB
ajase-2385	198	4	the	the	DET
ajase-2385	198	5	predicted	predict	VERB
ajase-2385	198	6	values	value	NOUN
ajase-2385	198	7	of	of	ADP
ajase-2385	198	8	the	the	DET
ajase-2385	198	9	test	test	NOUN
ajase-2385	198	10	data	datum	NOUN
ajase-2385	198	11	for	for	ADP
ajase-2385	198	12	four	four	NUM
ajase-2385	198	13	different	different	ADJ
ajase-2385	198	14	machine	machine	NOUN
ajase-2385	198	15	learning	learning	NOUN
ajase-2385	198	16	models	model	NOUN
ajase-2385	198	17	:	:	PUNCT
ajase-2385	198	18	rfr	rfr	PROPN
ajase-2385	198	19	,	,	PUNCT
ajase-2385	198	20	svr	svr	PROPN
ajase-2385	198	21	,	,	PUNCT
ajase-2385	198	22	lasso	lasso	NOUN
ajase-2385	198	23	,	,	PUNCT
ajase-2385	198	24	and	and	CCONJ
ajase-2385	198	25	brr	brr	NOUN
ajase-2385	198	26	.	.	PUNCT
ajase-2385	199	1	the	the	DET
ajase-2385	199	2	table	table	NOUN
ajase-2385	199	3	includes	include	VERB
ajase-2385	199	4	the	the	DET
ajase-2385	199	5	actual	actual	ADJ
ajase-2385	199	6	values	value	NOUN
ajase-2385	199	7	and	and	CCONJ
ajase-2385	199	8	predicted	predict	VERB
ajase-2385	199	9	values	value	NOUN
ajase-2385	199	10	for	for	ADP
ajase-2385	199	11	each	each	DET
ajase-2385	199	12	model	model	NOUN
ajase-2385	199	13	with	with	ADP
ajase-2385	199	14	cvk	cvk	PROPN
ajase-2385	199	15	.	.	PUNCT
ajase-2385	200	1	and	and	CCONJ
ajase-2385	200	2	wfv	wfv	X
ajase-2385	200	3	.	.	PUNCT
ajase-2385	201	1	the	the	DET
ajase-2385	201	2	table	table	NOUN
ajase-2385	201	3	spans	span	VERB
ajase-2385	201	4	from	from	ADP
ajase-2385	201	5	october	october	PROPN
ajase-2385	201	6	2018	2018	NUM
ajase-2385	201	7	to	to	ADP
ajase-2385	201	8	september	september	PROPN
ajase-2385	201	9	2020	2020	NUM
ajase-2385	201	10	,	,	PUNCT
ajase-2385	201	11	with	with	ADP
ajase-2385	201	12	monthly	monthly	ADJ
ajase-2385	201	13	predictions	prediction	NOUN
ajase-2385	201	14	for	for	ADP
ajase-2385	201	15	each	each	DET
ajase-2385	201	16	model	model	NOUN
ajase-2385	201	17	.	.	PUNCT
ajase-2385	202	1	overall	overall	ADV
ajase-2385	202	2	,	,	PUNCT
ajase-2385	202	3	the	the	DET
ajase-2385	202	4	table	table	NOUN
ajase-2385	202	5	provides	provide	VERB
ajase-2385	202	6	a	a	DET
ajase-2385	202	7	comparison	comparison	NOUN
ajase-2385	202	8	of	of	ADP
ajase-2385	202	9	the	the	DET
ajase-2385	202	10	performance	performance	NOUN
ajase-2385	202	11	of	of	ADP
ajase-2385	202	12	the	the	DET
ajase-2385	202	13	different	different	ADJ
ajase-2385	202	14	models	model	NOUN
ajase-2385	202	15	in	in	ADP
ajase-2385	202	16	predicting	predict	VERB
ajase-2385	202	17	the	the	DET
ajase-2385	202	18	test	test	NOUN
ajase-2385	202	19	data	datum	NOUN
ajase-2385	202	20	over	over	ADP
ajase-2385	202	21	the	the	DET
ajase-2385	202	22	twoyear	twoyear	ADJ
ajase-2385	202	23	period	period	NOUN
ajase-2385	202	24	.	.	PUNCT
ajase-2385	203	1	figure	figure	NOUN
ajase-2385	203	2	5	5	NUM
ajase-2385	203	3	:	:	PUNCT
ajase-2385	203	4	fitted	fit	VERB
ajase-2385	203	5	test	test	NOUN
ajase-2385	203	6	inflation	inflation	NOUN
ajase-2385	203	7	rates	rate	NOUN
ajase-2385	203	8	data	datum	NOUN
ajase-2385	203	9	for	for	ADP
ajase-2385	203	10	svr	svr	PROPN
ajase-2385	203	11	and	and	CCONJ
ajase-2385	203	12	rfr	rfr	PROPN
ajase-2385	203	13	models	model	NOUN
ajase-2385	203	14	with	with	ADP
ajase-2385	203	15	cvk	cvk	ADJ
ajase-2385	203	16	and	and	CCONJ
ajase-2385	203	17	wfv	wfv	PROPN
ajase-2385	203	18	techniques	technique	NOUN
ajase-2385	203	19	table	table	NOUN
ajase-2385	203	20	2	2	NUM
ajase-2385	203	21	:	:	PUNCT
ajase-2385	203	22	predicted	predict	VERB
ajase-2385	203	23	values	value	NOUN
ajase-2385	203	24	of	of	ADP
ajase-2385	203	25	the	the	DET
ajase-2385	203	26	test	test	NOUN
ajase-2385	203	27	data	datum	NOUN
ajase-2385	203	28	for	for	ADP
ajase-2385	203	29	smlm	smlm	ADJ
ajase-2385	203	30	date	date	NOUN
ajase-2385	203	31	rfr	rfr	PROPN
ajase-2385	203	32	svr	svr	PROPN
ajase-2385	203	33	lasso	lasso	VERB
ajase-2385	203	34	brr	brr	PROPN
ajase-2385	203	35	real	real	PROPN
ajase-2385	203	36	cvk	cvk	PROPN
ajase-2385	203	37	wfv	wfv	PROPN
ajase-2385	203	38	cvk	cvk	PROPN
ajase-2385	203	39	wfv	wfv	PROPN
ajase-2385	203	40	cvk	cvk	PROPN
ajase-2385	203	41	wfv	wfv	PROPN
ajase-2385	203	42	cvk	cvk	PROPN
ajase-2385	203	43	wfv	wfv	PROPN
ajase-2385	203	44	2018	2018	NUM
ajase-2385	203	45	oct	oct	NOUN
ajase-2385	203	46	3.3	3.3	NUM
ajase-2385	203	47	3.98	3.98	NUM
ajase-2385	203	48	3.86	3.86	NUM
ajase-2385	203	49	3.42	3.42	NUM
ajase-2385	203	50	3.61	3.61	NUM
ajase-2385	203	51	4.38	4.38	NUM
ajase-2385	203	52	4.38	4.38	NUM
ajase-2385	203	53	4.23	4.23	NUM
ajase-2385	203	54	4.23	4.23	NUM
ajase-2385	203	55	2018	2018	NUM
ajase-2385	203	56	nov	nov	PROPN
ajase-2385	203	57	3.1	3.1	NUM
ajase-2385	203	58	3.11	3.11	NUM
ajase-2385	203	59	3.10	3.10	NUM
ajase-2385	203	60	3.66	3.66	NUM
ajase-2385	203	61	3.72	3.72	NUM
ajase-2385	203	62	3.52	3.52	NUM
ajase-2385	203	63	3.52	3.52	NUM
ajase-2385	203	64	3.50	3.50	NUM
ajase-2385	203	65	3.50	3.50	NUM
ajase-2385	203	66	2018	2018	NUM
ajase-2385	203	67	dec	dec	PROPN
ajase-2385	203	68	2.8	2.8	NUM
ajase-2385	203	69	3.42	3.42	NUM
ajase-2385	203	70	3.79	3.79	NUM
ajase-2385	203	71	3.55	3.55	NUM
ajase-2385	203	72	3.57	3.57	NUM
ajase-2385	203	73	3.44	3.44	NUM
ajase-2385	203	74	3.44	3.44	NUM
ajase-2385	203	75	3.47	3.47	NUM
ajase-2385	203	76	3.47	3.47	NUM
ajase-2385	203	77	2019	2019	NUM
ajase-2385	203	78	jan	jan	NOUN
ajase-2385	203	79	3.7	3.7	NUM
ajase-2385	203	80	2.82	2.82	NUM
ajase-2385	203	81	2.81	2.81	NUM
ajase-2385	203	82	3.12	3.12	NUM
ajase-2385	203	83	3.11	3.11	NUM
ajase-2385	203	84	3.14	3.14	NUM
ajase-2385	203	85	3.14	3.14	NUM
ajase-2385	203	86	3.12	3.12	NUM
ajase-2385	203	87	3.12	3.12	NUM
ajase-2385	203	88	2019	2019	NUM
ajase-2385	203	89	feb	feb	NOUN
ajase-2385	203	90	4	4	NUM
ajase-2385	203	91	2.74	2.74	NUM
ajase-2385	203	92	2.71	2.71	NUM
ajase-2385	203	93	4.48	4.48	NUM
ajase-2385	203	94	4.49	4.49	NUM
ajase-2385	203	95	4.15	4.15	NUM
ajase-2385	203	96	4.14	4.14	NUM
ajase-2385	203	97	4.20	4.20	NUM
ajase-2385	203	98	4.20	4.20	NUM
ajase-2385	203	99	2019	2019	NUM
ajase-2385	203	100	mar	mar	PROPN
ajase-2385	203	101	4.3	4.3	NUM
ajase-2385	203	102	3.54	3.54	NUM
ajase-2385	203	103	3.55	3.55	NUM
ajase-2385	203	104	4.00	4.00	NUM
ajase-2385	203	105	4.11	4.11	NUM
ajase-2385	203	106	4.35	4.35	NUM
ajase-2385	203	107	4.35	4.35	NUM
ajase-2385	203	108	4.31	4.31	NUM
ajase-2385	203	109	4.31	4.31	NUM
ajase-2385	203	110	2019	2019	NUM
ajase-2385	203	111	apr	apr	NOUN
ajase-2385	203	112	4.5	4.5	NUM
ajase-2385	203	113	4.27	4.27	NUM
ajase-2385	203	114	4.47	4.47	NUM
ajase-2385	203	115	4.54	4.54	NUM
ajase-2385	203	116	4.66	4.66	NUM
ajase-2385	203	117	4.63	4.63	NUM
ajase-2385	203	118	4.63	4.63	NUM
ajase-2385	203	119	4.60	4.60	NUM
ajase-2385	203	120	4.60	4.60	NUM
ajase-2385	203	121	2019	2019	NUM
ajase-2385	203	122	may	may	AUX
ajase-2385	203	123	5	5	NUM
ajase-2385	203	124	4.68	4.68	NUM
ajase-2385	203	125	4.59	4.59	NUM
ajase-2385	203	126	4.60	4.60	NUM
ajase-2385	203	127	4.74	4.74	NUM
ajase-2385	203	128	4.81	4.81	NUM
ajase-2385	203	129	4.81	4.81	NUM
ajase-2385	203	130	4.78	4.78	NUM
ajase-2385	203	131	4.78	4.78	NUM
ajase-2385	203	132	2019	2019	NUM
ajase-2385	203	133	jun	jun	PROPN
ajase-2385	203	134	3.8	3.8	NUM
ajase-2385	203	135	4.94	4.94	NUM
ajase-2385	203	136	4.81	4.81	NUM
ajase-2385	203	137	5.21	5.21	NUM
ajase-2385	203	138	5.38	5.38	NUM
ajase-2385	203	139	5.32	5.32	NUM
ajase-2385	203	140	5.32	5.32	NUM
ajase-2385	203	141	5.32	5.32	NUM
ajase-2385	203	142	5.32	5.32	NUM
ajase-2385	203	143	2019	2019	NUM
ajase-2385	203	144	jul	jul	NOUN
ajase-2385	203	145	3.5	3.5	NUM
ajase-2385	203	146	3.67	3.67	NUM
ajase-2385	203	147	3.74	3.74	NUM
ajase-2385	203	148	3.27	3.27	NUM
ajase-2385	203	149	3.42	3.42	NUM
ajase-2385	203	150	3.96	3.96	NUM
ajase-2385	203	151	3.97	3.97	NUM
ajase-2385	203	152	3.84	3.84	NUM
ajase-2385	203	153	3.84	3.84	NUM
ajase-2385	203	154	2019	2019	NUM
ajase-2385	203	155	aug	aug	PROPN
ajase-2385	203	156	3.4	3.4	NUM
ajase-2385	203	157	3.81	3.81	NUM
ajase-2385	203	158	3.42	3.42	NUM
ajase-2385	203	159	4.00	4.00	NUM
ajase-2385	203	160	4.03	4.03	NUM
ajase-2385	203	161	3.80	3.80	NUM
ajase-2385	203	162	3.80	3.80	NUM
ajase-2385	203	163	3.80	3.80	NUM
ajase-2385	203	164	3.80	3.80	NUM
ajase-2385	203	165	2019	2019	NUM
ajase-2385	203	166	sep	sep	NOUN
ajase-2385	203	167	5	5	NUM
ajase-2385	203	168	3.51	3.51	NUM
ajase-2385	203	169	3.80	3.80	NUM
ajase-2385	203	170	3.66	3.66	NUM
ajase-2385	203	171	3.71	3.71	NUM
ajase-2385	203	172	3.73	3.73	NUM
ajase-2385	203	173	3.73	3.73	NUM
ajase-2385	203	174	3.74	3.74	NUM
ajase-2385	203	175	3.74	3.74	NUM
ajase-2385	203	176	2019	2019	NUM
ajase-2385	203	177	oct	oct	NOUN
ajase-2385	203	178	5.4	5.4	NUM
ajase-2385	203	179	5.77	5.77	NUM
ajase-2385	203	180	5.68	5.68	NUM
ajase-2385	203	181	5.97	5.97	NUM
ajase-2385	203	182	6.08	6.08	NUM
ajase-2385	203	183	5.46	5.46	NUM
ajase-2385	203	184	5.46	5.46	NUM
ajase-2385	203	185	5.55	5.55	NUM
ajase-2385	203	186	5.55	5.55	NUM
ajase-2385	203	187	2019	2019	NUM
ajase-2385	203	188	nov	nov	NOUN
ajase-2385	203	189	4.4	4.4	NUM
ajase-2385	203	190	6.51	6.51	NUM
ajase-2385	203	191	6.40	6.40	NUM
ajase-2385	203	192	5.00	5.00	NUM
ajase-2385	203	193	5.26	5.26	NUM
ajase-2385	203	194	5.68	5.68	NUM
ajase-2385	203	195	5.68	5.68	NUM
ajase-2385	203	196	5.62	5.62	NUM
ajase-2385	203	197	5.62	5.62	NUM
ajase-2385	203	198	2019	2019	NUM
ajase-2385	203	199	dec	dec	PROPN
ajase-2385	203	200	4.8	4.8	NUM
ajase-2385	203	201	4.49	4.49	NUM
ajase-2385	203	202	4.41	4.41	NUM
ajase-2385	203	203	3.83	3.83	NUM
ajase-2385	203	204	4.00	4.00	NUM
ajase-2385	203	205	4.55	4.55	NUM
ajase-2385	203	206	4.56	4.56	NUM
ajase-2385	203	207	4.43	4.43	NUM
ajase-2385	203	208	4.43	4.43	NUM
ajase-2385	203	209	2020	2020	NUM
ajase-2385	203	210	jan	jan	PROPN
ajase-2385	203	211	5.7	5.7	NUM
ajase-2385	203	212	4.78	4.78	NUM
ajase-2385	203	213	4.76	4.76	NUM
ajase-2385	203	214	5.25	5.25	NUM
ajase-2385	203	215	5.38	5.38	NUM
ajase-2385	203	216	5.11	5.11	NUM
ajase-2385	203	217	5.11	5.11	NUM
ajase-2385	203	218	5.16	5.16	NUM
ajase-2385	203	219	5.16	5.16	NUM
ajase-2385	203	220	2020	2020	NUM
ajase-2385	203	221	feb	feb	NOUN
ajase-2385	203	222	6.2	6.2	NUM
ajase-2385	203	223	6.08	6.08	NUM
ajase-2385	203	224	6.04	6.04	NUM
ajase-2385	203	225	5.90	5.90	NUM
ajase-2385	203	226	6.09	6.09	NUM
ajase-2385	203	227	6.03	6.03	NUM
ajase-2385	203	228	6.03	6.03	NUM
ajase-2385	203	229	6.07	6.07	NUM
ajase-2385	203	230	6.07	6.07	NUM
ajase-2385	203	231	2020	2020	NUM
ajase-2385	203	232	mar	mar	PROPN
ajase-2385	203	233	5.4	5.4	NUM
ajase-2385	203	234	6.66	6.66	NUM
ajase-2385	203	235	6.48	6.48	NUM
ajase-2385	203	236	6.02	6.02	NUM
ajase-2385	203	237	6.28	6.28	NUM
ajase-2385	203	238	6.44	6.44	NUM
ajase-2385	203	239	6.44	6.44	NUM
ajase-2385	203	240	6.42	6.42	NUM
ajase-2385	203	241	6.42	6.42	NUM
ajase-2385	203	242	2020	2020	NUM
ajase-2385	203	243	apr	apr	NOUN
ajase-2385	203	244	5.2	5.2	NUM
ajase-2385	203	245	4.97	4.97	NUM
ajase-2385	203	246	5.01	5.01	NUM
ajase-2385	203	247	4.66	4.66	NUM
ajase-2385	203	248	4.89	4.89	NUM
ajase-2385	203	249	5.52	5.52	NUM
ajase-2385	203	250	5.52	5.52	NUM
ajase-2385	203	251	5.42	5.42	NUM
ajase-2385	203	252	5.42	5.42	NUM
ajase-2385	204	1	pa	pa	PROPN
ajase-2385	204	2	ge	ge	PROPN
ajase-2385	204	3	58	58	NUM
ajase-2385	204	4	https://journals.e-palli.com/home/index.php/ajase	https://journals.e-palli.com/home/index.php/ajase	PROPN
ajase-2385	204	5	am	be	AUX
ajase-2385	204	6	.	.	PUNCT
ajase-2385	205	1	j.	j.	PROPN
ajase-2385	205	2	appl	appl	PROPN
ajase-2385	205	3	.	.	PROPN
ajase-2385	206	1	stat	stat	PROPN
ajase-2385	206	2	.	.	PUNCT
ajase-2385	207	1	econ	econ	PROPN
ajase-2385	207	2	.	.	PUNCT
ajase-2385	208	1	3(1	3(1	NUM
ajase-2385	208	2	)	)	PUNCT
ajase-2385	208	3	51	51	NUM
ajase-2385	208	4	-	-	SYM
ajase-2385	208	5	60	60	NUM
ajase-2385	208	6	,	,	PUNCT
ajase-2385	208	7	2024	2024	NUM
ajase-2385	208	8	2020	2020	NUM
ajase-2385	208	9	may	may	AUX
ajase-2385	208	10	4	4	NUM
ajase-2385	208	11	5.06	5.06	NUM
ajase-2385	208	12	5.21	5.21	NUM
ajase-2385	208	13	5.12	5.12	NUM
ajase-2385	208	14	5.29	5.29	NUM
ajase-2385	208	15	5.41	5.41	NUM
ajase-2385	208	16	5.41	5.41	NUM
ajase-2385	208	17	5.41	5.41	NUM
ajase-2385	208	18	5.41	5.41	NUM
ajase-2385	208	19	2020	2020	NUM
ajase-2385	208	20	jun	jun	PROPN
ajase-2385	208	21	3.9	3.9	NUM
ajase-2385	208	22	3.33	3.33	NUM
ajase-2385	208	23	3.04	3.04	NUM
ajase-2385	208	24	3.56	3.56	NUM
ajase-2385	208	25	3.72	3.72	NUM
ajase-2385	208	26	4.15	4.15	NUM
ajase-2385	208	27	4.15	4.15	NUM
ajase-2385	208	28	4.08	4.08	NUM
ajase-2385	208	29	4.08	4.08	NUM
ajase-2385	208	30	2020	2020	NUM
ajase-2385	208	31	jul	jul	PROPN
ajase-2385	208	32	4.2	4.2	NUM
ajase-2385	208	33	3.53	3.53	NUM
ajase-2385	208	34	3.36	3.36	NUM
ajase-2385	208	35	4.29	4.29	NUM
ajase-2385	208	36	4.36	4.36	NUM
ajase-2385	208	37	4.20	4.20	NUM
ajase-2385	208	38	4.20	4.20	NUM
ajase-2385	208	39	4.23	4.23	NUM
ajase-2385	208	40	4.23	4.23	NUM
ajase-2385	208	41	2020	2020	NUM
ajase-2385	208	42	aug	aug	PROPN
ajase-2385	208	43	4.1	4.1	NUM
ajase-2385	208	44	3.85	3.85	NUM
ajase-2385	208	45	3.97	3.97	NUM
ajase-2385	208	46	4.39	4.39	NUM
ajase-2385	208	47	4.49	4.49	NUM
ajase-2385	208	48	4.54	4.54	NUM
ajase-2385	208	49	4.54	4.54	NUM
ajase-2385	208	50	4.56	4.56	NUM
ajase-2385	208	51	4.56	4.56	NUM
ajase-2385	208	52	2020	2020	NUM
ajase-2385	208	53	sep	sep	PROPN
ajase-2385	208	54	4	4	NUM
ajase-2385	208	55	4.24	4.24	NUM
ajase-2385	208	56	4.21	4.21	NUM
ajase-2385	208	57	4.09	4.09	NUM
ajase-2385	208	58	4.21	4.21	NUM
ajase-2385	208	59	4.39	4.39	NUM
ajase-2385	208	60	4.39	4.39	NUM
ajase-2385	208	61	4.35	4.35	NUM
ajase-2385	208	62	4.35	4.35	NUM
ajase-2385	208	63	algorithm	algorithm	NOUN
ajase-2385	208	64	4	4	NUM
ajase-2385	208	65	presents	present	VERB
ajase-2385	208	66	the	the	DET
ajase-2385	208	67	pseudo	pseudo	NOUN
ajase-2385	208	68	code	code	NOUN
ajase-2385	208	69	for	for	ADP
ajase-2385	208	70	rfr	rfr	PROPN
ajase-2385	208	71	.	.	PUNCT
ajase-2385	209	1	rfr	rfr	PROPN
ajase-2385	209	2	is	be	AUX
ajase-2385	209	3	a	a	DET
ajase-2385	209	4	popular	popular	ADJ
ajase-2385	209	5	ensemble	ensemble	ADJ
ajase-2385	209	6	learning	learning	NOUN
ajase-2385	209	7	method	method	NOUN
ajase-2385	209	8	used	use	VERB
ajase-2385	209	9	for	for	ADP
ajase-2385	209	10	both	both	CCONJ
ajase-2385	209	11	classification	classification	NOUN
ajase-2385	209	12	and	and	CCONJ
ajase-2385	209	13	regression	regression	NOUN
ajase-2385	209	14	problems	problem	NOUN
ajase-2385	209	15	.	.	PUNCT
ajase-2385	210	1	the	the	DET
ajase-2385	210	2	algorithm	algorithm	NOUN
ajase-2385	210	3	builds	build	VERB
ajase-2385	210	4	a	a	DET
ajase-2385	210	5	specified	specified	ADJ
ajase-2385	210	6	number	number	NOUN
ajase-2385	210	7	of	of	ADP
ajase-2385	210	8	decision	decision	NOUN
ajase-2385	210	9	trees	tree	NOUN
ajase-2385	210	10	using	use	VERB
ajase-2385	210	11	a	a	DET
ajase-2385	210	12	bootstrapped	bootstrapped	ADJ
ajase-2385	210	13	sample	sample	NOUN
ajase-2385	210	14	of	of	ADP
ajase-2385	210	15	the	the	DET
ajase-2385	210	16	training	training	NOUN
ajase-2385	210	17	data	datum	NOUN
ajase-2385	210	18	and	and	CCONJ
ajase-2385	210	19	selects	select	NOUN
ajase-2385	210	20	a	a	DET
ajase-2385	210	21	random	random	ADJ
ajase-2385	210	22	subset	subset	NOUN
ajase-2385	210	23	of	of	ADP
ajase-2385	210	24	features	feature	NOUN
ajase-2385	210	25	at	at	ADP
ajase-2385	210	26	each	each	DET
ajase-2385	210	27	node	node	NOUN
ajase-2385	210	28	to	to	PART
ajase-2385	210	29	split	split	VERB
ajase-2385	210	30	on	on	ADP
ajase-2385	210	31	.	.	PUNCT
ajase-2385	211	1	the	the	DET
ajase-2385	211	2	final	final	ADJ
ajase-2385	211	3	prediction	prediction	NOUN
ajase-2385	211	4	is	be	AUX
ajase-2385	211	5	the	the	DET
ajase-2385	211	6	average	average	NOUN
ajase-2385	211	7	of	of	ADP
ajase-2385	211	8	the	the	DET
ajase-2385	211	9	predictions	prediction	NOUN
ajase-2385	211	10	from	from	ADP
ajase-2385	211	11	all	all	DET
ajase-2385	211	12	the	the	DET
ajase-2385	211	13	trees	tree	NOUN
ajase-2385	211	14	in	in	ADP
ajase-2385	211	15	the	the	DET
ajase-2385	211	16	forest	forest	NOUN
ajase-2385	211	17	.	.	PUNCT
ajase-2385	212	1	the	the	DET
ajase-2385	212	2	rfr	rfr	PROPN
ajase-2385	212	3	algorithm	algorithm	NOUN
ajase-2385	212	4	is	be	AUX
ajase-2385	212	5	known	know	VERB
ajase-2385	212	6	for	for	ADP
ajase-2385	212	7	its	its	PRON
ajase-2385	212	8	ability	ability	NOUN
ajase-2385	212	9	to	to	PART
ajase-2385	212	10	handle	handle	VERB
ajase-2385	212	11	high	high	ADJ
ajase-2385	212	12	dimensional	dimensional	ADJ
ajase-2385	212	13	data	datum	NOUN
ajase-2385	212	14	and	and	CCONJ
ajase-2385	212	15	avoid	avoid	VERB
ajase-2385	212	16	overfitting	overfitte	VERB
ajase-2385	212	17	.	.	PUNCT
ajase-2385	213	1	implementation	implementation	NOUN
ajase-2385	213	2	,	,	PUNCT
ajase-2385	213	3	when	when	SCONJ
ajase-2385	213	4	choosing	choose	VERB
ajase-2385	213	5	a	a	DET
ajase-2385	213	6	model	model	NOUN
ajase-2385	213	7	for	for	ADP
ajase-2385	213	8	practical	practical	ADJ
ajase-2385	213	9	applications	application	NOUN
ajase-2385	213	10	.	.	PUNCT
ajase-2385	214	1	in	in	ADP
ajase-2385	214	2	conclusion	conclusion	NOUN
ajase-2385	214	3	,	,	PUNCT
ajase-2385	214	4	the	the	DET
ajase-2385	214	5	results	result	NOUN
ajase-2385	214	6	suggest	suggest	VERB
ajase-2385	214	7	that	that	SCONJ
ajase-2385	214	8	the	the	DET
ajase-2385	214	9	svr	svr	PROPN
ajase-2385	214	10	model	model	NOUN
ajase-2385	214	11	with	with	ADP
ajase-2385	214	12	wfv	wfv	PROPN
ajase-2385	214	13	may	may	AUX
ajase-2385	214	14	be	be	AUX
ajase-2385	214	15	a	a	DET
ajase-2385	214	16	suitable	suitable	ADJ
ajase-2385	214	17	choice	choice	NOUN
ajase-2385	214	18	for	for	ADP
ajase-2385	214	19	predicting	predict	VERB
ajase-2385	214	20	the	the	DET
ajase-2385	214	21	inflation	inflation	NOUN
ajase-2385	214	22	rate	rate	NOUN
ajase-2385	214	23	in	in	ADP
ajase-2385	214	24	sri	sri	PROPN
ajase-2385	214	25	lanka	lanka	PROPN
ajase-2385	214	26	,	,	PUNCT
ajase-2385	214	27	but	but	CCONJ
ajase-2385	214	28	further	further	ADJ
ajase-2385	214	29	validation	validation	NOUN
ajase-2385	214	30	and	and	CCONJ
ajase-2385	214	31	evaluation	evaluation	NOUN
ajase-2385	214	32	may	may	AUX
ajase-2385	214	33	be	be	AUX
ajase-2385	214	34	required	require	VERB
ajase-2385	214	35	to	to	PART
ajase-2385	214	36	ensure	ensure	VERB
ajase-2385	214	37	the	the	DET
ajase-2385	214	38	reliability	reliability	NOUN
ajase-2385	214	39	of	of	ADP
ajase-2385	214	40	the	the	DET
ajase-2385	214	41	results	result	NOUN
ajase-2385	214	42	.	.	PUNCT
ajase-2385	215	1	table	table	NOUN
ajase-2385	215	2	3	3	NUM
ajase-2385	215	3	:	:	PUNCT
ajase-2385	215	4	mape	mape	NOUN
ajase-2385	215	5	values	value	NOUN
ajase-2385	215	6	in	in	ADP
ajase-2385	215	7	test	test	NOUN
ajase-2385	215	8	data	datum	NOUN
ajase-2385	215	9	of	of	ADP
ajase-2385	215	10	each	each	DET
ajase-2385	215	11	smlm	smlm	ADJ
ajase-2385	215	12	cvk	cvk	PROPN
ajase-2385	215	13	wfv	wfv	PROPN
ajase-2385	215	14	model	model	PROPN
ajase-2385	215	15	mape	mape	PROPN
ajase-2385	215	16	model	model	PROPN
ajase-2385	215	17	mape	mape	PROPN
ajase-2385	215	18	lr	lr	VERB
ajase-2385	215	19	13.42	13.42	NUM
ajase-2385	215	20	lr	lr	PROPN
ajase-2385	215	21	13.43	13.43	NUM
ajase-2385	215	22	brr	brr	NOUN
ajase-2385	215	23	13.04	13.04	NUM
ajase-2385	215	24	brr	brr	PROPN
ajase-2385	215	25	13.40	13.40	NUM
ajase-2385	215	26	svr	svr	PROPN
ajase-2385	215	27	12.79	12.79	NUM
ajase-2385	215	28	svr	svr	PROPN
ajase-2385	215	29	13.34	13.34	NUM
ajase-2385	215	30	rfr	rfr	PROPN
ajase-2385	215	31	15.82	15.82	NUM
ajase-2385	215	32	rfr	rfr	PROPN
ajase-2385	215	33	15.63	15.63	NUM
ajase-2385	215	34	table	table	NOUN
ajase-2385	215	35	3	3	NUM
ajase-2385	215	36	shows	show	VERB
ajase-2385	215	37	the	the	DET
ajase-2385	215	38	mape	mape	NOUN
ajase-2385	215	39	values	value	NOUN
ajase-2385	215	40	for	for	ADP
ajase-2385	215	41	four	four	NUM
ajase-2385	215	42	different	different	ADJ
ajase-2385	215	43	supervised	supervised	ADJ
ajase-2385	215	44	machine	machine	NOUN
ajase-2385	215	45	learning	learning	NOUN
ajase-2385	215	46	models	model	NOUN
ajase-2385	215	47	(	(	PUNCT
ajase-2385	215	48	smlms	smlm	NOUN
ajase-2385	215	49	)	)	PUNCT
ajase-2385	215	50	used	use	VERB
ajase-2385	215	51	to	to	PART
ajase-2385	215	52	predict	predict	VERB
ajase-2385	215	53	the	the	DET
ajase-2385	215	54	inflation	inflation	NOUN
ajase-2385	215	55	rate	rate	NOUN
ajase-2385	215	56	in	in	ADP
ajase-2385	215	57	sri	sri	PROPN
ajase-2385	215	58	lanka	lanka	PROPN
ajase-2385	215	59	.	.	PUNCT
ajase-2385	216	1	the	the	DET
ajase-2385	216	2	table	table	NOUN
ajase-2385	216	3	presents	present	VERB
ajase-2385	216	4	the	the	DET
ajase-2385	216	5	mape	mape	NOUN
ajase-2385	216	6	values	value	NOUN
ajase-2385	216	7	for	for	ADP
ajase-2385	216	8	each	each	DET
ajase-2385	216	9	model	model	NOUN
ajase-2385	216	10	in	in	ADP
ajase-2385	216	11	two	two	NUM
ajase-2385	216	12	columns	column	NOUN
ajase-2385	216	13	for	for	ADP
ajase-2385	216	14	two	two	NUM
ajase-2385	216	15	different	different	ADJ
ajase-2385	216	16	cross	cross	NOUN
ajase-2385	216	17	validation	validation	NOUN
ajase-2385	216	18	methods	method	NOUN
ajase-2385	216	19	cvk	cvk	ADJ
ajase-2385	216	20	and	and	CCONJ
ajase-2385	216	21	wfv	wfv	PROPN
ajase-2385	216	22	.	.	PUNCT
ajase-2385	217	1	upon	upon	SCONJ
ajase-2385	217	2	examining	examine	VERB
ajase-2385	217	3	the	the	DET
ajase-2385	217	4	mape	mape	NOUN
ajase-2385	217	5	values	value	NOUN
ajase-2385	217	6	,	,	PUNCT
ajase-2385	217	7	it	it	PRON
ajase-2385	217	8	can	can	AUX
ajase-2385	217	9	be	be	AUX
ajase-2385	217	10	concluded	conclude	VERB
ajase-2385	217	11	that	that	SCONJ
ajase-2385	217	12	the	the	DET
ajase-2385	217	13	support	support	NOUN
ajase-2385	217	14	vector	vector	NOUN
ajase-2385	217	15	regression	regression	NOUN
ajase-2385	217	16	(	(	PUNCT
ajase-2385	217	17	svr	svr	PROPN
ajase-2385	217	18	)	)	PUNCT
ajase-2385	217	19	model	model	NOUN
ajase-2385	217	20	outperformed	outperform	VERB
ajase-2385	217	21	all	all	DET
ajase-2385	217	22	the	the	DET
ajase-2385	217	23	other	other	ADJ
ajase-2385	217	24	models	model	NOUN
ajase-2385	217	25	for	for	ADP
ajase-2385	217	26	both	both	CCONJ
ajase-2385	217	27	feature	feature	NOUN
ajase-2385	217	28	extraction	extraction	NOUN
ajase-2385	217	29	techniques	technique	NOUN
ajase-2385	217	30	.	.	PUNCT
ajase-2385	218	1	for	for	ADP
ajase-2385	218	2	wfv	wfv	PROPN
ajase-2385	218	3	,	,	PUNCT
ajase-2385	218	4	svr	svr	PROPN
ajase-2385	218	5	had	have	VERB
ajase-2385	218	6	the	the	DET
ajase-2385	218	7	lowest	low	ADJ
ajase-2385	218	8	mape	mape	NOUN
ajase-2385	218	9	of	of	ADP
ajase-2385	218	10	13.34	13.34	NUM
ajase-2385	218	11	%	%	NOUN
ajase-2385	218	12	,	,	PUNCT
ajase-2385	218	13	followed	follow	VERB
ajase-2385	218	14	by	by	ADP
ajase-2385	218	15	bayesian	bayesian	NOUN
ajase-2385	218	16	ridge	ridge	NOUN
ajase-2385	218	17	regression	regression	PROPN
ajase-2385	218	18	(	(	PUNCT
ajase-2385	218	19	brr	brr	NOUN
ajase-2385	218	20	)	)	PUNCT
ajase-2385	218	21	at	at	ADP
ajase-2385	218	22	13.40	13.40	NUM
ajase-2385	218	23	%	%	NOUN
ajase-2385	218	24	,	,	PUNCT
ajase-2385	218	25	lasso	lasso	NOUN
ajase-2385	218	26	regression	regression	NOUN
ajase-2385	218	27	(	(	PUNCT
ajase-2385	218	28	lr	lr	NOUN
ajase-2385	218	29	)	)	PUNCT
ajase-2385	218	30	at	at	ADP
ajase-2385	218	31	13.43	13.43	NUM
ajase-2385	218	32	%	%	NOUN
ajase-2385	218	33	,	,	PUNCT
ajase-2385	218	34	and	and	CCONJ
ajase-2385	218	35	random	random	ADJ
ajase-2385	218	36	forest	forest	NOUN
ajase-2385	218	37	regression	regression	NOUN
ajase-2385	218	38	(	(	PUNCT
ajase-2385	218	39	rfr	rfr	PROPN
ajase-2385	218	40	)	)	PUNCT
ajase-2385	218	41	at	at	ADP
ajase-2385	218	42	15.63	15.63	NUM
ajase-2385	218	43	%	%	NOUN
ajase-2385	218	44	.	.	PUNCT
ajase-2385	219	1	similarly	similarly	ADV
ajase-2385	219	2	,	,	PUNCT
ajase-2385	219	3	for	for	ADP
ajase-2385	219	4	the	the	DET
ajase-2385	219	5	other	other	ADJ
ajase-2385	219	6	feature	feature	NOUN
ajase-2385	219	7	extraction	extraction	NOUN
ajase-2385	219	8	technique	technique	NOUN
ajase-2385	219	9	,	,	PUNCT
ajase-2385	219	10	svr	svr	PROPN
ajase-2385	219	11	had	have	VERB
ajase-2385	219	12	the	the	DET
ajase-2385	219	13	lowest	low	ADJ
ajase-2385	219	14	mape	mape	NOUN
ajase-2385	219	15	of	of	ADP
ajase-2385	219	16	12.79	12.79	NUM
ajase-2385	219	17	%	%	NOUN
ajase-2385	219	18	,	,	PUNCT
ajase-2385	219	19	followed	follow	VERB
ajase-2385	219	20	by	by	ADP
ajase-2385	219	21	brr	brr	NOUN
ajase-2385	219	22	at	at	ADP
ajase-2385	219	23	13.04	13.04	NUM
ajase-2385	219	24	%	%	NOUN
ajase-2385	219	25	,	,	PUNCT
ajase-2385	219	26	lr	lr	X
ajase-2385	219	27	at	at	ADP
ajase-2385	219	28	13.42	13.42	NUM
ajase-2385	219	29	%	%	NOUN
ajase-2385	219	30	,	,	PUNCT
ajase-2385	219	31	and	and	CCONJ
ajase-2385	219	32	rfr	rfr	PROPN
ajase-2385	219	33	at	at	ADP
ajase-2385	219	34	15.82	15.82	NUM
ajase-2385	219	35	%	%	NOUN
ajase-2385	219	36	.	.	PUNCT
ajase-2385	220	1	therefore	therefore	ADV
ajase-2385	220	2	,	,	PUNCT
ajase-2385	220	3	svr	svr	PROPN
ajase-2385	220	4	is	be	AUX
ajase-2385	220	5	the	the	DET
ajase-2385	220	6	most	most	ADV
ajase-2385	220	7	accurate	accurate	ADJ
ajase-2385	220	8	model	model	NOUN
ajase-2385	220	9	for	for	ADP
ajase-2385	220	10	predicting	predict	VERB
ajase-2385	220	11	the	the	DET
ajase-2385	220	12	inflation	inflation	NOUN
ajase-2385	220	13	rate	rate	NOUN
ajase-2385	220	14	in	in	ADP
ajase-2385	220	15	sri	sri	PROPN
ajase-2385	220	16	lanka	lanka	PROPN
ajase-2385	220	17	based	base	VERB
ajase-2385	220	18	on	on	ADP
ajase-2385	220	19	the	the	DET
ajase-2385	220	20	given	give	VERB
ajase-2385	220	21	features	feature	NOUN
ajase-2385	220	22	.	.	PUNCT
ajase-2385	221	1	however	however	ADV
ajase-2385	221	2	,	,	PUNCT
ajase-2385	221	3	it	it	PRON
ajase-2385	221	4	is	be	AUX
ajase-2385	221	5	important	important	ADJ
ajase-2385	221	6	to	to	PART
ajase-2385	221	7	note	note	VERB
ajase-2385	221	8	that	that	SCONJ
ajase-2385	221	9	the	the	DET
ajase-2385	221	10	differences	difference	NOUN
ajase-2385	221	11	in	in	ADP
ajase-2385	221	12	mape	mape	NOUN
ajase-2385	221	13	values	value	NOUN
ajase-2385	221	14	among	among	ADP
ajase-2385	221	15	the	the	DET
ajase-2385	221	16	models	model	NOUN
ajase-2385	221	17	were	be	AUX
ajase-2385	221	18	relatively	relatively	ADV
ajase-2385	221	19	small	small	ADJ
ajase-2385	221	20	,	,	PUNCT
ajase-2385	221	21	with	with	ADP
ajase-2385	221	22	differences	difference	NOUN
ajase-2385	221	23	of	of	ADP
ajase-2385	221	24	only	only	ADV
ajase-2385	221	25	a	a	DET
ajase-2385	221	26	few	few	ADJ
ajase-2385	221	27	percentage	percentage	NOUN
ajase-2385	221	28	points	point	NOUN
ajase-2385	221	29	.	.	PUNCT
ajase-2385	222	1	therefore	therefore	ADV
ajase-2385	222	2	,	,	PUNCT
ajase-2385	222	3	it	it	PRON
ajase-2385	222	4	may	may	AUX
ajase-2385	222	5	be	be	AUX
ajase-2385	222	6	more	more	ADV
ajase-2385	222	7	appropriate	appropriate	ADJ
ajase-2385	222	8	to	to	PART
ajase-2385	222	9	consider	consider	VERB
ajase-2385	222	10	other	other	ADJ
ajase-2385	222	11	factors	factor	NOUN
ajase-2385	222	12	,	,	PUNCT
ajase-2385	222	13	such	such	ADJ
ajase-2385	222	14	as	as	ADP
ajase-2385	222	15	computational	computational	ADJ
ajase-2385	222	16	complexity	complexity	NOUN
ajase-2385	222	17	and	and	CCONJ
ajase-2385	222	18	ease	ease	NOUN
ajase-2385	222	19	of	of	ADP
ajase-2385	222	20	figure	figure	NOUN
ajase-2385	222	21	6	6	NUM
ajase-2385	222	22	:	:	PUNCT
ajase-2385	222	23	forecasted	forecast	VERB
ajase-2385	222	24	valuessvr	valuessvr	ADJ
ajase-2385	222	25	with	with	ADP
ajase-2385	222	26	wfv	wfv	NOUN
ajase-2385	222	27	techniques	technique	NOUN
ajase-2385	222	28	the	the	DET
ajase-2385	222	29	graph	graph	NOUN
ajase-2385	222	30	shows	show	VERB
ajase-2385	222	31	the	the	DET
ajase-2385	222	32	actual	actual	ADJ
ajase-2385	222	33	values	value	NOUN
ajase-2385	222	34	and	and	CCONJ
ajase-2385	222	35	forecast	forecast	NOUN
ajase-2385	222	36	values	value	NOUN
ajase-2385	222	37	of	of	ADP
ajase-2385	222	38	a	a	DET
ajase-2385	222	39	certain	certain	ADJ
ajase-2385	222	40	variable	variable	NOUN
ajase-2385	222	41	over	over	ADP
ajase-2385	222	42	a	a	DET
ajase-2385	222	43	period	period	NOUN
ajase-2385	222	44	.	.	PUNCT
ajase-2385	223	1	the	the	DET
ajase-2385	223	2	variable	variable	NOUN
ajase-2385	223	3	is	be	AUX
ajase-2385	223	4	denoted	denote	VERB
ajase-2385	223	5	by	by	ADP
ajase-2385	223	6	yt	yt	NOUN
ajase-2385	223	7	while	while	SCONJ
ajase-2385	223	8	the	the	DET
ajase-2385	223	9	forecasted	forecast	VERB
ajase-2385	223	10	values	value	NOUN
ajase-2385	223	11	are	be	AUX
ajase-2385	223	12	generated	generate	VERB
ajase-2385	223	13	using	use	VERB
ajase-2385	223	14	a	a	DET
ajase-2385	223	15	machine	machine	NOUN
ajase-2385	223	16	learning	learn	VERB
ajase-2385	223	17	model	model	NOUN
ajase-2385	223	18	,	,	PUNCT
ajase-2385	223	19	namely	namely	ADV
ajase-2385	223	20	support	support	VERB
ajase-2385	223	21	vector	vector	NOUN
ajase-2385	223	22	regression	regression	NOUN
ajase-2385	223	23	(	(	PUNCT
ajase-2385	223	24	svr	svr	PROPN
ajase-2385	223	25	)	)	PUNCT
ajase-2385	223	26	.	.	PUNCT
ajase-2385	224	1	the	the	DET
ajase-2385	224	2	graph	graph	NOUN
ajase-2385	224	3	consists	consist	VERB
ajase-2385	224	4	of	of	ADP
ajase-2385	224	5	two	two	NUM
ajase-2385	224	6	lines	line	NOUN
ajase-2385	224	7	:	:	PUNCT
ajase-2385	224	8	one	one	NUM
ajase-2385	224	9	line	line	NOUN
ajase-2385	224	10	representing	represent	VERB
ajase-2385	224	11	the	the	DET
ajase-2385	224	12	actual	actual	ADJ
ajase-2385	224	13	values	value	NOUN
ajase-2385	224	14	and	and	CCONJ
ajase-2385	224	15	another	another	DET
ajase-2385	224	16	line	line	NOUN
ajase-2385	224	17	representing	represent	VERB
ajase-2385	224	18	the	the	DET
ajase-2385	224	19	forecasted	forecast	VERB
ajase-2385	224	20	values	value	NOUN
ajase-2385	224	21	.	.	PUNCT
ajase-2385	225	1	the	the	DET
ajase-2385	225	2	actual	actual	ADJ
ajase-2385	225	3	values	value	NOUN
ajase-2385	225	4	are	be	AUX
ajase-2385	225	5	plotted	plot	VERB
ajase-2385	225	6	as	as	ADP
ajase-2385	225	7	points	point	NOUN
ajase-2385	225	8	on	on	ADP
ajase-2385	225	9	the	the	DET
ajase-2385	225	10	graph	graph	NOUN
ajase-2385	225	11	,	,	PUNCT
ajase-2385	225	12	while	while	SCONJ
ajase-2385	225	13	the	the	DET
ajase-2385	225	14	forecasted	forecast	VERB
ajase-2385	225	15	values	value	NOUN
ajase-2385	225	16	are	be	AUX
ajase-2385	225	17	connected	connect	VERB
ajase-2385	225	18	by	by	ADP
ajase-2385	225	19	a	a	DET
ajase-2385	225	20	line	line	NOUN
ajase-2385	225	21	.	.	PUNCT
ajase-2385	226	1	the	the	DET
ajase-2385	226	2	graph	graph	NOUN
ajase-2385	226	3	enables	enable	VERB
ajase-2385	226	4	a	a	DET
ajase-2385	226	5	visual	visual	ADJ
ajase-2385	226	6	comparison	comparison	NOUN
ajase-2385	226	7	between	between	ADP
ajase-2385	226	8	the	the	DET
ajase-2385	226	9	actual	actual	ADJ
ajase-2385	226	10	values	value	NOUN
ajase-2385	226	11	and	and	CCONJ
ajase-2385	226	12	the	the	DET
ajase-2385	226	13	forecasted	forecast	VERB
ajase-2385	226	14	values	value	NOUN
ajase-2385	226	15	.	.	PUNCT
ajase-2385	227	1	the	the	DET
ajase-2385	227	2	closeness	closeness	NOUN
ajase-2385	227	3	of	of	ADP
ajase-2385	227	4	the	the	DET
ajase-2385	227	5	forecasted	forecast	VERB
ajase-2385	227	6	values	value	NOUN
ajase-2385	227	7	to	to	ADP
ajase-2385	227	8	the	the	DET
ajase-2385	227	9	actual	actual	ADJ
ajase-2385	227	10	values	value	NOUN
ajase-2385	227	11	can	can	AUX
ajase-2385	227	12	be	be	AUX
ajase-2385	227	13	seen	see	VERB
ajase-2385	227	14	from	from	ADP
ajase-2385	227	15	the	the	DET
ajase-2385	227	16	graph	graph	NOUN
ajase-2385	227	17	.	.	PUNCT
ajase-2385	228	1	looking	look	VERB
ajase-2385	228	2	at	at	ADP
ajase-2385	228	3	the	the	DET
ajase-2385	228	4	graph	graph	NOUN
ajase-2385	228	5	,	,	PUNCT
ajase-2385	228	6	it	it	PRON
ajase-2385	228	7	can	can	AUX
ajase-2385	228	8	be	be	AUX
ajase-2385	228	9	observed	observe	VERB
ajase-2385	228	10	that	that	SCONJ
ajase-2385	228	11	the	the	DET
ajase-2385	228	12	svr	svr	PROPN
ajase-2385	228	13	model	model	NOUN
ajase-2385	228	14	generally	generally	ADV
ajase-2385	228	15	performed	perform	VERB
ajase-2385	228	16	well	well	ADV
ajase-2385	228	17	in	in	ADP
ajase-2385	228	18	forecasting	forecast	VERB
ajase-2385	228	19	the	the	DET
ajase-2385	228	20	variable	variable	NOUN
ajase-2385	228	21	.	.	PUNCT
ajase-2385	229	1	however	however	ADV
ajase-2385	229	2	,	,	PUNCT
ajase-2385	229	3	there	there	PRON
ajase-2385	229	4	are	be	VERB
ajase-2385	229	5	some	some	DET
ajase-2385	229	6	instances	instance	NOUN
ajase-2385	229	7	where	where	SCONJ
ajase-2385	229	8	the	the	DET
ajase-2385	229	9	forecasted	forecast	VERB
ajase-2385	229	10	values	value	NOUN
ajase-2385	229	11	deviate	deviate	VERB
ajase-2385	229	12	from	from	ADP
ajase-2385	229	13	the	the	DET
ajase-2385	229	14	actual	actual	ADJ
ajase-2385	229	15	values	value	NOUN
ajase-2385	229	16	.	.	PUNCT
ajase-2385	230	1	for	for	ADP
ajase-2385	230	2	example	example	NOUN
ajase-2385	230	3	,	,	PUNCT
ajase-2385	230	4	in	in	ADP
ajase-2385	230	5	february	february	PROPN
ajase-2385	230	6	2021	2021	NUM
ajase-2385	230	7	,	,	PUNCT
ajase-2385	230	8	the	the	DET
ajase-2385	230	9	actual	actual	ADJ
ajase-2385	230	10	value	value	NOUN
ajase-2385	230	11	was	be	AUX
ajase-2385	230	12	3.3	3.3	NUM
ajase-2385	230	13	,	,	PUNCT
ajase-2385	230	14	but	but	CCONJ
ajase-2385	230	15	the	the	DET
ajase-2385	230	16	forecasted	forecast	VERB
ajase-2385	230	17	value	value	NOUN
ajase-2385	230	18	was	be	AUX
ajase-2385	230	19	2.992228	2.992228	NUM
ajase-2385	230	20	,	,	PUNCT
ajase-2385	230	21	which	which	PRON
ajase-2385	230	22	is	be	AUX
ajase-2385	230	23	considerably	considerably	ADV
ajase-2385	230	24	lower	low	ADJ
ajase-2385	230	25	.	.	PUNCT
ajase-2385	231	1	similarly	similarly	ADV
ajase-2385	231	2	,	,	PUNCT
ajase-2385	231	3	in	in	ADP
ajase-2385	231	4	may	may	PROPN
ajase-2385	231	5	2021	2021	NUM
ajase-2385	231	6	,	,	PUNCT
ajase-2385	231	7	the	the	DET
ajase-2385	231	8	actual	actual	ADJ
ajase-2385	231	9	value	value	NOUN
ajase-2385	231	10	was	be	AUX
ajase-2385	231	11	4.5	4.5	NUM
ajase-2385	231	12	,	,	PUNCT
ajase-2385	231	13	but	but	CCONJ
ajase-2385	231	14	the	the	DET
ajase-2385	231	15	forecasted	forecast	VERB
ajase-2385	231	16	value	value	NOUN
ajase-2385	231	17	was	be	AUX
ajase-2385	231	18	3.827932	3.827932	NUM
ajase-2385	231	19	,	,	PUNCT
ajase-2385	231	20	which	which	PRON
ajase-2385	231	21	is	be	AUX
ajase-2385	231	22	also	also	ADV
ajase-2385	231	23	lower	low	ADJ
ajase-2385	231	24	.	.	PUNCT
ajase-2385	232	1	on	on	ADP
ajase-2385	232	2	the	the	DET
ajase-2385	232	3	other	other	ADJ
ajase-2385	232	4	hand	hand	NOUN
ajase-2385	232	5	,	,	PUNCT
ajase-2385	232	6	in	in	ADP
ajase-2385	232	7	september	september	PROPN
ajase-2385	232	8	2021	2021	NUM
ajase-2385	232	9	,	,	PUNCT
ajase-2385	232	10	the	the	DET
ajase-2385	232	11	actual	actual	ADJ
ajase-2385	232	12	value	value	NOUN
ajase-2385	232	13	was	be	AUX
ajase-2385	232	14	5.7	5.7	NUM
ajase-2385	232	15	,	,	PUNCT
ajase-2385	232	16	and	and	CCONJ
ajase-2385	232	17	the	the	DET
ajase-2385	232	18	forecasted	forecast	VERB
ajase-2385	232	19	value	value	NOUN
ajase-2385	232	20	was	be	AUX
ajase-2385	232	21	6.004278	6.004278	NUM
ajase-2385	232	22	,	,	PUNCT
ajase-2385	232	23	which	which	PRON
ajase-2385	232	24	is	be	AUX
ajase-2385	232	25	slightly	slightly	ADV
ajase-2385	232	26	higher	high	ADJ
ajase-2385	232	27	.	.	PUNCT
ajase-2385	233	1	the	the	DET
ajase-2385	233	2	closeness	closeness	NOUN
ajase-2385	233	3	of	of	ADP
ajase-2385	233	4	the	the	DET
ajase-2385	233	5	forecasted	forecast	VERB
ajase-2385	233	6	values	value	NOUN
ajase-2385	233	7	to	to	ADP
ajase-2385	233	8	the	the	DET
ajase-2385	233	9	actual	actual	ADJ
ajase-2385	233	10	values	value	NOUN
ajase-2385	233	11	can	can	AUX
ajase-2385	233	12	be	be	AUX
ajase-2385	233	13	seen	see	VERB
ajase-2385	233	14	from	from	ADP
ajase-2385	233	15	the	the	DET
ajase-2385	233	16	trend	trend	NOUN
ajase-2385	233	17	line	line	NOUN
ajase-2385	233	18	of	of	ADP
ajase-2385	233	19	the	the	DET
ajase-2385	233	20	forecasted	forecast	VERB
ajase-2385	233	21	values	value	NOUN
ajase-2385	233	22	,	,	PUNCT
ajase-2385	233	23	which	which	PRON
ajase-2385	233	24	closely	closely	ADV
ajase-2385	233	25	follows	follow	VERB
ajase-2385	233	26	the	the	DET
ajase-2385	233	27	trend	trend	NOUN
ajase-2385	233	28	line	line	NOUN
ajase-2385	233	29	of	of	ADP
ajase-2385	233	30	the	the	DET
ajase-2385	233	31	actual	actual	ADJ
ajase-2385	233	32	values	value	NOUN
ajase-2385	233	33	.	.	PUNCT
ajase-2385	234	1	overall	overall	ADV
ajase-2385	234	2	,	,	PUNCT
ajase-2385	234	3	the	the	DET
ajase-2385	234	4	graph	graph	NOUN
ajase-2385	234	5	provides	provide	VERB
ajase-2385	234	6	a	a	DET
ajase-2385	234	7	clear	clear	ADJ
ajase-2385	234	8	visualization	visualization	NOUN
ajase-2385	234	9	of	of	ADP
ajase-2385	234	10	the	the	DET
ajase-2385	234	11	performance	performance	NOUN
ajase-2385	234	12	of	of	ADP
ajase-2385	234	13	the	the	DET
ajase-2385	234	14	svr	svr	PROPN
ajase-2385	234	15	model	model	NOUN
ajase-2385	234	16	in	in	ADP
ajase-2385	234	17	forecasting	forecast	VERB
ajase-2385	234	18	the	the	DET
ajase-2385	234	19	variable	variable	NOUN
ajase-2385	234	20	.	.	PUNCT
ajase-2385	235	1	it	it	PRON
ajase-2385	235	2	highlights	highlight	VERB
ajase-2385	235	3	the	the	DET
ajase-2385	235	4	instances	instance	NOUN
ajase-2385	235	5	where	where	SCONJ
ajase-2385	235	6	the	the	DET
ajase-2385	235	7	model	model	NOUN
ajase-2385	235	8	performed	perform	VERB
ajase-2385	235	9	well	well	ADV
ajase-2385	235	10	and	and	CCONJ
ajase-2385	235	11	the	the	DET
ajase-2385	235	12	instances	instance	NOUN
ajase-2385	235	13	where	where	SCONJ
ajase-2385	235	14	it	it	PRON
ajase-2385	235	15	deviated	deviate	VERB
ajase-2385	235	16	from	from	ADP
ajase-2385	235	17	the	the	DET
ajase-2385	235	18	actual	actual	ADJ
ajase-2385	235	19	values	value	NOUN
ajase-2385	235	20	.	.	PUNCT
ajase-2385	236	1	the	the	DET
ajase-2385	236	2	insights	insight	NOUN
ajase-2385	236	3	from	from	ADP
ajase-2385	236	4	the	the	DET
ajase-2385	236	5	graph	graph	NOUN
ajase-2385	236	6	can	can	AUX
ajase-2385	236	7	be	be	AUX
ajase-2385	236	8	used	use	VERB
ajase-2385	236	9	to	to	PART
ajase-2385	236	10	further	far	ADV
ajase-2385	236	11	refine	refine	VERB
ajase-2385	236	12	the	the	DET
ajase-2385	236	13	machine	machine	NOUN
ajase-2385	236	14	learning	learn	VERB
ajase-2385	236	15	model	model	NOUN
ajase-2385	236	16	and	and	CCONJ
ajase-2385	236	17	improve	improve	VERB
ajase-2385	236	18	its	its	PRON
ajase-2385	236	19	forecasting	forecasting	NOUN
ajase-2385	236	20	accuracy	accuracy	NOUN
ajase-2385	236	21	.	.	PUNCT
ajase-2385	237	1	pa	pa	PROPN
ajase-2385	237	2	ge	ge	PROPN
ajase-2385	237	3	59	59	NUM
ajase-2385	237	4	https://journals.e-palli.com/home/index.php/ajase	https://journals.e-palli.com/home/index.php/ajase	PROPN
ajase-2385	237	5	am	be	AUX
ajase-2385	237	6	.	.	PUNCT
ajase-2385	238	1	j.	j.	PROPN
ajase-2385	238	2	appl	appl	PROPN
ajase-2385	238	3	.	.	PROPN
ajase-2385	239	1	stat	stat	PROPN
ajase-2385	239	2	.	.	PUNCT
ajase-2385	240	1	econ	econ	PROPN
ajase-2385	240	2	.	.	PUNCT
ajase-2385	241	1	3(1	3(1	NUM
ajase-2385	241	2	)	)	PUNCT
ajase-2385	241	3	51	51	NUM
ajase-2385	241	4	-	-	SYM
ajase-2385	241	5	60	60	NUM
ajase-2385	241	6	,	,	PUNCT
ajase-2385	241	7	2024	2024	NUM
ajase-2385	241	8	table	table	NOUN
ajase-2385	241	9	4	4	NUM
ajase-2385	241	10	shows	show	VERB
ajase-2385	241	11	the	the	DET
ajase-2385	241	12	forecasted	forecast	VERB
ajase-2385	241	13	values	value	NOUN
ajase-2385	241	14	generated	generate	VERB
ajase-2385	241	15	by	by	ADP
ajase-2385	241	16	a	a	DET
ajase-2385	241	17	support	support	NOUN
ajase-2385	241	18	vector	vector	NOUN
ajase-2385	241	19	regression	regression	NOUN
ajase-2385	241	20	(	(	PUNCT
ajase-2385	241	21	svr	svr	PROPN
ajase-2385	241	22	)	)	PUNCT
ajase-2385	241	23	model	model	NOUN
ajase-2385	241	24	using	use	VERB
ajase-2385	241	25	the	the	DET
ajase-2385	241	26	wavelet	wavelet	NOUN
ajase-2385	241	27	-	-	PUNCT
ajase-2385	241	28	based	base	VERB
ajase-2385	241	29	feature	feature	NOUN
ajase-2385	241	30	vector	vector	NOUN
ajase-2385	241	31	(	(	PUNCT
ajase-2385	241	32	wfv	wfv	NOUN
ajase-2385	241	33	)	)	PUNCT
ajase-2385	241	34	technique	technique	NOUN
ajase-2385	241	35	.	.	PUNCT
ajase-2385	242	1	the	the	DET
ajase-2385	242	2	table	table	NOUN
ajase-2385	242	3	includes	include	VERB
ajase-2385	242	4	the	the	DET
ajase-2385	242	5	date	date	NOUN
ajase-2385	242	6	,	,	PUNCT
ajase-2385	242	7	the	the	DET
ajase-2385	242	8	actual	actual	ADJ
ajase-2385	242	9	values	value	NOUN
ajase-2385	242	10	of	of	ADP
ajase-2385	242	11	the	the	DET
ajase-2385	242	12	variable	variable	NOUN
ajase-2385	242	13	being	be	AUX
ajase-2385	242	14	forecasted	forecast	VERB
ajase-2385	242	15	(	(	PUNCT
ajase-2385	242	16	yt	yt	NOUN
ajase-2385	242	17	)	)	PUNCT
ajase-2385	242	18	,	,	PUNCT
ajase-2385	242	19	and	and	CCONJ
ajase-2385	242	20	the	the	DET
ajase-2385	242	21	forecasted	forecast	VERB
ajase-2385	242	22	values	value	NOUN
ajase-2385	242	23	generated	generate	VERB
ajase-2385	242	24	by	by	ADP
ajase-2385	242	25	the	the	DET
ajase-2385	242	26	model	model	NOUN
ajase-2385	242	27	.	.	PUNCT
ajase-2385	243	1	the	the	DET
ajase-2385	243	2	mape	mape	NOUN
ajase-2385	243	3	value	value	NOUN
ajase-2385	243	4	of	of	ADP
ajase-2385	243	5	10.16	10.16	NUM
ajase-2385	243	6	%	%	NOUN
ajase-2385	243	7	indicates	indicate	VERB
ajase-2385	243	8	that	that	SCONJ
ajase-2385	243	9	the	the	DET
ajase-2385	243	10	average	average	ADJ
ajase-2385	243	11	error	error	NOUN
ajase-2385	243	12	of	of	ADP
ajase-2385	243	13	the	the	DET
ajase-2385	243	14	forecasted	forecast	VERB
ajase-2385	243	15	values	value	NOUN
ajase-2385	243	16	is	be	AUX
ajase-2385	243	17	approximately	approximately	ADV
ajase-2385	243	18	10	10	NUM
ajase-2385	243	19	%	%	NOUN
ajase-2385	243	20	of	of	ADP
ajase-2385	243	21	the	the	DET
ajase-2385	243	22	actual	actual	ADJ
ajase-2385	243	23	values	value	NOUN
ajase-2385	243	24	.	.	PUNCT
ajase-2385	244	1	the	the	DET
ajase-2385	244	2	table	table	NOUN
ajase-2385	244	3	demonstrates	demonstrate	VERB
ajase-2385	244	4	that	that	SCONJ
ajase-2385	244	5	the	the	DET
ajase-2385	244	6	model	model	NOUN
ajase-2385	244	7	was	be	AUX
ajase-2385	244	8	relatively	relatively	ADV
ajase-2385	244	9	accurate	accurate	ADJ
ajase-2385	244	10	in	in	ADP
ajase-2385	244	11	predicting	predict	VERB
ajase-2385	244	12	the	the	DET
ajase-2385	244	13	values	value	NOUN
ajase-2385	244	14	for	for	ADP
ajase-2385	244	15	the	the	DET
ajase-2385	244	16	first	first	ADJ
ajase-2385	244	17	few	few	ADJ
ajase-2385	244	18	months	month	NOUN
ajase-2385	244	19	,	,	PUNCT
ajase-2385	244	20	but	but	CCONJ
ajase-2385	244	21	the	the	DET
ajase-2385	244	22	accuracy	accuracy	NOUN
ajase-2385	244	23	decreased	decrease	VERB
ajase-2385	244	24	in	in	ADP
ajase-2385	244	25	later	later	ADJ
ajase-2385	244	26	months	month	NOUN
ajase-2385	244	27	,	,	PUNCT
ajase-2385	244	28	with	with	ADP
ajase-2385	244	29	the	the	DET
ajase-2385	244	30	largest	large	ADJ
ajase-2385	244	31	discrepancy	discrepancy	NOUN
ajase-2385	244	32	occurring	occur	VERB
ajase-2385	244	33	in	in	ADP
ajase-2385	244	34	may	may	PROPN
ajase-2385	244	35	.	.	PUNCT
ajase-2385	245	1	the	the	DET
ajase-2385	245	2	model	model	NOUN
ajase-2385	245	3	showed	show	VERB
ajase-2385	245	4	improvement	improvement	NOUN
ajase-2385	245	5	in	in	ADP
ajase-2385	245	6	june	june	PROPN
ajase-2385	245	7	and	and	CCONJ
ajase-2385	245	8	july	july	PROPN
ajase-2385	245	9	but	but	CCONJ
ajase-2385	245	10	still	still	ADV
ajase-2385	245	11	underestimated	underestimate	VERB
ajase-2385	245	12	the	the	DET
ajase-2385	245	13	actual	actual	ADJ
ajase-2385	245	14	values	value	NOUN
ajase-2385	245	15	in	in	ADP
ajase-2385	245	16	august	august	PROPN
ajase-2385	245	17	and	and	CCONJ
ajase-2385	245	18	september	september	PROPN
ajase-2385	245	19	.	.	PUNCT
ajase-2385	246	1	overall	overall	ADV
ajase-2385	246	2	,	,	PUNCT
ajase-2385	246	3	the	the	DET
ajase-2385	246	4	table	table	NOUN
ajase-2385	246	5	suggests	suggest	VERB
ajase-2385	246	6	that	that	SCONJ
ajase-2385	246	7	the	the	DET
ajase-2385	246	8	svr	svr	PROPN
ajase-2385	246	9	model	model	NOUN
ajase-2385	246	10	with	with	ADP
ajase-2385	246	11	the	the	DET
ajase-2385	246	12	wfv	wfv	NOUN
ajase-2385	246	13	technique	technique	NOUN
ajase-2385	246	14	may	may	AUX
ajase-2385	246	15	be	be	AUX
ajase-2385	246	16	a	a	DET
ajase-2385	246	17	suitable	suitable	ADJ
ajase-2385	246	18	choice	choice	NOUN
ajase-2385	246	19	for	for	ADP
ajase-2385	246	20	forecasting	forecast	VERB
ajase-2385	246	21	the	the	DET
ajase-2385	246	22	variable	variable	NOUN
ajase-2385	246	23	of	of	ADP
ajase-2385	246	24	interest	interest	NOUN
ajase-2385	246	25	,	,	PUNCT
ajase-2385	246	26	but	but	CCONJ
ajase-2385	246	27	further	further	ADJ
ajase-2385	246	28	analysis	analysis	NOUN
ajase-2385	246	29	and	and	CCONJ
ajase-2385	246	30	model	model	NOUN
ajase-2385	246	31	refinement	refinement	NOUN
ajase-2385	246	32	may	may	AUX
ajase-2385	246	33	be	be	AUX
ajase-2385	246	34	necessary	necessary	ADJ
ajase-2385	246	35	to	to	PART
ajase-2385	246	36	improve	improve	VERB
ajase-2385	246	37	accuracy	accuracy	NOUN
ajase-2385	246	38	.	.	PUNCT
ajase-2385	247	1	conclusions	conclusion	NOUN
ajase-2385	247	2	in	in	ADP
ajase-2385	247	3	conclusion	conclusion	NOUN
ajase-2385	247	4	,	,	PUNCT
ajase-2385	247	5	the	the	DET
ajase-2385	247	6	support	support	NOUN
ajase-2385	247	7	vector	vector	NOUN
ajase-2385	247	8	regression	regression	NOUN
ajase-2385	247	9	(	(	PUNCT
ajase-2385	247	10	svr	svr	PROPN
ajase-2385	247	11	)	)	PUNCT
ajase-2385	247	12	model	model	NOUN
ajase-2385	247	13	with	with	ADP
ajase-2385	247	14	the	the	DET
ajase-2385	247	15	walk	walk	NOUN
ajase-2385	247	16	forward	forward	ADV
ajase-2385	247	17	validation	validation	NOUN
ajase-2385	247	18	(	(	PUNCT
ajase-2385	247	19	wfv	wfv	NOUN
ajase-2385	247	20	)	)	PUNCT
ajase-2385	247	21	technique	technique	NOUN
ajase-2385	247	22	demonstrated	demonstrate	VERB
ajase-2385	247	23	superior	superior	ADJ
ajase-2385	247	24	performance	performance	NOUN
ajase-2385	247	25	in	in	ADP
ajase-2385	247	26	forecasting	forecast	VERB
ajase-2385	247	27	the	the	DET
ajase-2385	247	28	inflation	inflation	NOUN
ajase-2385	247	29	rate	rate	NOUN
ajase-2385	247	30	in	in	ADP
ajase-2385	247	31	sri	sri	PROPN
ajase-2385	247	32	lanka	lanka	PROPN
ajase-2385	247	33	.	.	PUNCT
ajase-2385	248	1	the	the	DET
ajase-2385	248	2	model	model	NOUN
ajase-2385	248	3	’s	’s	PART
ajase-2385	248	4	accuracy	accuracy	NOUN
ajase-2385	248	5	was	be	AUX
ajase-2385	248	6	measured	measure	VERB
ajase-2385	248	7	using	use	VERB
ajase-2385	248	8	the	the	DET
ajase-2385	248	9	mean	mean	ADJ
ajase-2385	248	10	absolute	absolute	ADJ
ajase-2385	248	11	percentage	percentage	NOUN
ajase-2385	248	12	error	error	NOUN
ajase-2385	248	13	(	(	PUNCT
ajase-2385	248	14	mape	mape	NOUN
ajase-2385	248	15	)	)	PUNCT
ajase-2385	248	16	value	value	NOUN
ajase-2385	248	17	,	,	PUNCT
ajase-2385	248	18	which	which	PRON
ajase-2385	248	19	was	be	AUX
ajase-2385	248	20	found	find	VERB
ajase-2385	248	21	to	to	PART
ajase-2385	248	22	be	be	AUX
ajase-2385	248	23	10.16	10.16	NUM
ajase-2385	248	24	%	%	NOUN
ajase-2385	248	25	.	.	PUNCT
ajase-2385	249	1	the	the	DET
ajase-2385	249	2	predicted	predict	VERB
ajase-2385	249	3	values	value	NOUN
ajase-2385	249	4	of	of	ADP
ajase-2385	249	5	the	the	DET
ajase-2385	249	6	svr	svr	PROPN
ajase-2385	249	7	model	model	NOUN
ajase-2385	249	8	with	with	ADP
ajase-2385	249	9	wfv	wfv	NOUN
ajase-2385	249	10	technique	technique	NOUN
ajase-2385	249	11	were	be	AUX
ajase-2385	249	12	compared	compare	VERB
ajase-2385	249	13	to	to	ADP
ajase-2385	249	14	the	the	DET
ajase-2385	249	15	actual	actual	ADJ
ajase-2385	249	16	inflation	inflation	NOUN
ajase-2385	249	17	rates	rate	NOUN
ajase-2385	249	18	,	,	PUNCT
ajase-2385	249	19	and	and	CCONJ
ajase-2385	249	20	it	it	PRON
ajase-2385	249	21	was	be	AUX
ajase-2385	249	22	observed	observe	VERB
ajase-2385	249	23	that	that	SCONJ
ajase-2385	249	24	the	the	DET
ajase-2385	249	25	model	model	NOUN
ajase-2385	249	26	’s	’s	PART
ajase-2385	249	27	forecasts	forecast	NOUN
ajase-2385	249	28	closely	closely	ADV
ajase-2385	249	29	matched	match	VERB
ajase-2385	249	30	the	the	DET
ajase-2385	249	31	actual	actual	ADJ
ajase-2385	249	32	values	value	NOUN
ajase-2385	249	33	.	.	PUNCT
ajase-2385	250	1	however	however	ADV
ajase-2385	250	2	,	,	PUNCT
ajase-2385	250	3	the	the	DET
ajase-2385	250	4	model	model	NOUN
ajase-2385	250	5	’s	’s	PART
ajase-2385	250	6	sensitivity	sensitivity	NOUN
ajase-2385	250	7	to	to	ADP
ajase-2385	250	8	unusual	unusual	ADJ
ajase-2385	250	9	data	datum	NOUN
ajase-2385	250	10	was	be	AUX
ajase-2385	250	11	noted	note	VERB
ajase-2385	250	12	,	,	PUNCT
ajase-2385	250	13	which	which	PRON
ajase-2385	250	14	could	could	AUX
ajase-2385	250	15	be	be	AUX
ajase-2385	250	16	addressed	address	VERB
ajase-2385	250	17	by	by	ADP
ajase-2385	250	18	using	use	VERB
ajase-2385	250	19	a	a	DET
ajase-2385	250	20	more	more	ADV
ajase-2385	250	21	robust	robust	ADJ
ajase-2385	250	22	machine	machine	NOUN
ajase-2385	250	23	learning	learning	NOUN
ajase-2385	250	24	model	model	NOUN
ajase-2385	250	25	.	.	PUNCT
ajase-2385	251	1	overall	overall	ADV
ajase-2385	251	2	,	,	PUNCT
ajase-2385	251	3	the	the	DET
ajase-2385	251	4	findings	finding	NOUN
ajase-2385	251	5	suggest	suggest	VERB
ajase-2385	251	6	that	that	SCONJ
ajase-2385	251	7	the	the	DET
ajase-2385	251	8	svr	svr	PROPN
ajase-2385	251	9	model	model	NOUN
ajase-2385	251	10	with	with	ADP
ajase-2385	251	11	wfv	wfv	NOUN
ajase-2385	251	12	technique	technique	NOUN
ajase-2385	251	13	can	can	AUX
ajase-2385	251	14	be	be	AUX
ajase-2385	251	15	a	a	DET
ajase-2385	251	16	valuable	valuable	ADJ
ajase-2385	251	17	tool	tool	NOUN
ajase-2385	251	18	for	for	ADP
ajase-2385	251	19	forecasting	forecast	VERB
ajase-2385	251	20	inflation	inflation	NOUN
ajase-2385	251	21	rates	rate	NOUN
ajase-2385	251	22	in	in	ADP
ajase-2385	251	23	sri	sri	PROPN
ajase-2385	251	24	lanka	lanka	PROPN
ajase-2385	251	25	.	.	PUNCT
ajase-2385	252	1	as	as	ADP
ajase-2385	252	2	a	a	DET
ajase-2385	252	3	future	future	ADJ
ajase-2385	252	4	direction	direction	NOUN
ajase-2385	252	5	,	,	PUNCT
ajase-2385	252	6	it	it	PRON
ajase-2385	252	7	would	would	AUX
ajase-2385	252	8	be	be	AUX
ajase-2385	252	9	beneficial	beneficial	ADJ
ajase-2385	252	10	to	to	PART
ajase-2385	252	11	consider	consider	VERB
ajase-2385	252	12	the	the	DET
ajase-2385	252	13	presence	presence	NOUN
ajase-2385	252	14	of	of	ADP
ajase-2385	252	15	outliers	outlier	NOUN
ajase-2385	252	16	in	in	ADP
ajase-2385	252	17	the	the	DET
ajase-2385	252	18	data	datum	NOUN
ajase-2385	252	19	and	and	CCONJ
ajase-2385	252	20	explore	explore	VERB
ajase-2385	252	21	robust	robust	ADJ
ajase-2385	252	22	machine	machine	NOUN
ajase-2385	252	23	learning	learning	NOUN
ajase-2385	252	24	models	model	NOUN
ajase-2385	252	25	that	that	PRON
ajase-2385	252	26	can	can	AUX
ajase-2385	252	27	handle	handle	VERB
ajase-2385	252	28	them	they	PRON
ajase-2385	252	29	effectively	effectively	ADV
ajase-2385	252	30	.	.	PUNCT
ajase-2385	253	1	additionally	additionally	ADV
ajase-2385	253	2	,	,	PUNCT
ajase-2385	253	3	incorporating	incorporate	VERB
ajase-2385	253	4	other	other	ADJ
ajase-2385	253	5	relevant	relevant	ADJ
ajase-2385	253	6	economic	economic	ADJ
ajase-2385	253	7	and	and	CCONJ
ajase-2385	253	8	financial	financial	ADJ
ajase-2385	253	9	indicators	indicator	NOUN
ajase-2385	253	10	into	into	ADP
ajase-2385	253	11	the	the	DET
ajase-2385	253	12	model	model	NOUN
ajase-2385	253	13	can	can	AUX
ajase-2385	253	14	potentially	potentially	ADV
ajase-2385	253	15	improve	improve	VERB
ajase-2385	253	16	the	the	DET
ajase-2385	253	17	accuracy	accuracy	NOUN
ajase-2385	253	18	of	of	ADP
ajase-2385	253	19	inflation	inflation	NOUN
ajase-2385	253	20	rate	rate	NOUN
ajase-2385	253	21	forecasts	forecast	NOUN
ajase-2385	253	22	.	.	PUNCT
ajase-2385	254	1	referances	referance	NOUN
ajase-2385	254	2	anagaw	anagaw	PROPN
ajase-2385	254	3	,	,	PUNCT
ajase-2385	254	4	t.	t.	PROPN
ajase-2385	254	5	(	(	PUNCT
ajase-2385	254	6	2023	2023	NUM
ajase-2385	254	7	)	)	PUNCT
ajase-2385	254	8	.	.	PUNCT
ajase-2385	255	1	review	review	VERB
ajase-2385	255	2	on	on	ADP
ajase-2385	255	3	:	:	PUNCT
ajase-2385	255	4	effect	effect	NOUN
ajase-2385	255	5	of	of	ADP
ajase-2385	255	6	inflation	inflation	NOUN
ajase-2385	255	7	on	on	ADP
ajase-2385	255	8	economic	economic	ADJ
ajase-2385	255	9	growth	growth	NOUN
ajase-2385	255	10	in	in	ADP
ajase-2385	255	11	ethiopia	ethiopia	PROPN
ajase-2385	255	12	.	.	PUNCT
ajase-2385	256	1	american	american	PROPN
ajase-2385	256	2	journal	journal	PROPN
ajase-2385	256	3	of	of	ADP
ajase-2385	256	4	applied	apply	VERB
ajase-2385	256	5	statistics	statistic	NOUN
ajase-2385	256	6	and	and	CCONJ
ajase-2385	256	7	economics	economic	NOUN
ajase-2385	256	8	,	,	PUNCT
ajase-2385	256	9	2(1	2(1	NUM
ajase-2385	256	10	)	)	PUNCT
ajase-2385	256	11	,	,	PUNCT
ajase-2385	256	12	7–10	7–10	NOUN
ajase-2385	256	13	.	.	PUNCT
ajase-2385	257	1	https://doi	https://doi	NOUN
ajase-2385	257	2	.	.	PUNCT
ajase-2385	257	3	org/10.54536	org/10.54536	PROPN
ajase-2385	257	4	/	/	SYM
ajase-2385	257	5	ajase.v2i1.1658	ajase.v2i1.1658	NUM
ajase-2385	257	6	armstrong	armstrong	PROPN
ajase-2385	257	7	,	,	PUNCT
ajase-2385	257	8	j.	j.	PROPN
ajase-2385	257	9	s.	s.	PROPN
ajase-2385	257	10	(	(	PUNCT
ajase-2385	257	11	1992	1992	NUM
ajase-2385	257	12	)	)	PUNCT
ajase-2385	257	13	.	.	PUNCT
ajase-2385	258	1	error	error	NOUN
ajase-2385	258	2	measures	measure	NOUN
ajase-2385	258	3	for	for	ADP
ajase-2385	258	4	generalizing	generalize	VERB
ajase-2385	258	5	about	about	ADP
ajase-2385	258	6	forecasting	forecasting	NOUN
ajase-2385	258	7	methods	method	NOUN
ajase-2385	258	8	:	:	PUNCT
ajase-2385	258	9	empirical	empirical	ADJ
ajase-2385	258	10	comparisons	comparison	NOUN
ajase-2385	258	11	.	.	PUNCT
ajase-2385	259	1	international	international	ADJ
ajase-2385	259	2	journal	journal	PROPN
ajase-2385	259	3	of	of	ADP
ajase-2385	259	4	forecasting	forecasting	NOUN
ajase-2385	259	5	,	,	PUNCT
ajase-2385	259	6	8(1	8(1	NOUN
ajase-2385	259	7	)	)	PUNCT
ajase-2385	259	8	,	,	PUNCT
ajase-2385	259	9	69	69	NUM
ajase-2385	259	10	-	-	SYM
ajase-2385	259	11	80	80	NUM
ajase-2385	259	12	.	.	PUNCT
ajase-2385	260	1	atkeson	atkeson	NOUN
ajase-2385	260	2	,	,	PUNCT
ajase-2385	260	3	a.	a.	NOUN
ajase-2385	260	4	o.	o.	PROPN
ajase-2385	260	5	(	(	PUNCT
ajase-2385	260	6	2001	2001	NUM
ajase-2385	260	7	)	)	PUNCT
ajase-2385	260	8	.	.	PUNCT
ajase-2385	261	1	are	be	AUX
ajase-2385	261	2	phillips	phillips	PROPN
ajase-2385	261	3	curves	curve	NOUN
ajase-2385	261	4	useful	useful	ADJ
ajase-2385	261	5	for	for	ADP
ajase-2385	261	6	forecasting	forecast	VERB
ajase-2385	261	7	inflation	inflation	NOUN
ajase-2385	261	8	.	.	PUNCT
ajase-2385	262	1	pp	pp	ADV
ajase-2385	262	2	.	.	PUNCT
ajase-2385	263	1	2–11	2–11	PROPN
ajase-2385	263	2	.	.	PUNCT
ajase-2385	264	1	bandara	bandara	PROPN
ajase-2385	264	2	,	,	PUNCT
ajase-2385	264	3	r.	r.	PROPN
ajase-2385	264	4	(	(	PUNCT
ajase-2385	264	5	2011	2011	NUM
ajase-2385	264	6	)	)	PUNCT
ajase-2385	264	7	.	.	PUNCT
ajase-2385	265	1	the	the	DET
ajase-2385	265	2	determinants	determinant	NOUN
ajase-2385	265	3	of	of	ADP
ajase-2385	265	4	inflation	inflation	NOUN
ajase-2385	265	5	in	in	ADP
ajase-2385	265	6	sri	sri	PROPN
ajase-2385	265	7	lanka	lanka	PROPN
ajase-2385	265	8	:	:	PUNCT
ajase-2385	265	9	an	an	DET
ajase-2385	265	10	application	application	NOUN
ajase-2385	265	11	of	of	ADP
ajase-2385	265	12	the	the	DET
ajase-2385	265	13	vector	vector	NOUN
ajase-2385	265	14	autoregression	autoregression	NOUN
ajase-2385	265	15	model	model	NOUN
ajase-2385	265	16	.	.	PUNCT
ajase-2385	266	1	south	south	PROPN
ajase-2385	266	2	asia	asia	PROPN
ajase-2385	266	3	economic	economic	PROPN
ajase-2385	266	4	journal	journal	PROPN
ajase-2385	266	5	,	,	PUNCT
ajase-2385	266	6	12(2	12(2	NUM
ajase-2385	266	7	)	)	PUNCT
ajase-2385	266	8	,	,	PUNCT
ajase-2385	266	9	271	271	NUM
ajase-2385	266	10	-	-	SYM
ajase-2385	266	11	286	286	NUM
ajase-2385	266	12	.	.	PUNCT
ajase-2385	267	1	https://doi.org/10.1177/139156141101200204	https://doi.org/10.1177/139156141101200204	ADJ
ajase-2385	267	2	bandara	bandara	PROPN
ajase-2385	267	3	,	,	PUNCT
ajase-2385	267	4	w.	w.	PROPN
ajase-2385	267	5	m.	m.	PROPN
ajase-2385	267	6	s	s	PROPN
ajase-2385	267	7	&	&	CCONJ
ajase-2385	267	8	de	de	PROPN
ajase-2385	267	9	mel	mel	PROPN
ajase-2385	267	10	,	,	PUNCT
ajase-2385	267	11	w.	w.	PROPN
ajase-2385	267	12	a.	a.	PROPN
ajase-2385	267	13	r.	r.	PROPN
ajase-2385	267	14	(	(	PUNCT
ajase-2385	267	15	2021	2021	NUM
ajase-2385	267	16	)	)	PUNCT
ajase-2385	267	17	.	.	PUNCT
ajase-2385	268	1	arimaneural	arimaneural	ADJ
ajase-2385	268	2	hybrid	hybrid	ADJ
ajase-2385	268	3	estimates	estimate	NOUN
ajase-2385	268	4	of	of	ADP
ajase-2385	268	5	inflationary	inflationary	ADJ
ajase-2385	268	6	expectations	expectation	NOUN
ajase-2385	268	7	:	:	PUNCT
ajase-2385	268	8	some	some	DET
ajase-2385	268	9	evidence	evidence	NOUN
ajase-2385	268	10	from	from	ADP
ajase-2385	268	11	sri	sri	PROPN
ajase-2385	268	12	lanka	lanka	PROPN
ajase-2385	268	13	.	.	PUNCT
ajase-2385	269	1	20th	20th	ADJ
ajase-2385	269	2	academic	academic	ADJ
ajase-2385	269	3	sessions	session	NOUN
ajase-2385	269	4	univercity	univercity	NOUN
ajase-2385	269	5	of	of	ADP
ajase-2385	269	6	ruhuna	ruhuna	PROPN
ajase-2385	269	7	,	,	PUNCT
ajase-2385	269	8	1(1	1(1	NUM
ajase-2385	269	9	)	)	PUNCT
ajase-2385	269	10	,	,	PUNCT
ajase-2385	269	11	1	1	X
ajase-2385	269	12	.	.	PUNCT
ajase-2385	269	13	retrieved	retrieve	VERB
ajase-2385	269	14	from	from	ADP
ajase-2385	269	15	http://	http://	PROPN
ajase-2385	269	16	ir.lib.ruh.ac.lk/handle/iruor/13401	ir.lib.ruh.ac.lk/handle/iruor/13401	PROPN
ajase-2385	269	17	bergmeir	bergmeir	PROPN
ajase-2385	269	18	,	,	PUNCT
ajase-2385	269	19	c.	c.	PROPN
ajase-2385	269	20	,	,	PUNCT
ajase-2385	269	21	&	&	CCONJ
ajase-2385	269	22	benítez	benítez	PROPN
ajase-2385	269	23	,	,	PUNCT
ajase-2385	269	24	j.	j.	PROPN
ajase-2385	269	25	(	(	PUNCT
ajase-2385	269	26	2012	2012	NUM
ajase-2385	269	27	)	)	PUNCT
ajase-2385	269	28	.	.	PUNCT
ajase-2385	270	1	on	on	ADP
ajase-2385	270	2	the	the	DET
ajase-2385	270	3	use	use	NOUN
ajase-2385	270	4	of	of	ADP
ajase-2385	270	5	crossvalidation	crossvalidation	NOUN
ajase-2385	270	6	for	for	ADP
ajase-2385	270	7	time	time	NOUN
ajase-2385	270	8	series	series	PROPN
ajase-2385	270	9	predictor	predictor	PROPN
ajase-2385	270	10	evaluation	evaluation	NOUN
ajase-2385	270	11	.	.	PUNCT
ajase-2385	271	1	information	information	NOUN
ajase-2385	271	2	sciences	sciences	PROPN
ajase-2385	271	3	,	,	PUNCT
ajase-2385	271	4	191	191	NUM
ajase-2385	271	5	,	,	PUNCT
ajase-2385	271	6	192	192	NUM
ajase-2385	271	7	-	-	SYM
ajase-2385	271	8	213	213	NUM
ajase-2385	271	9	.	.	PUNCT
ajase-2385	271	10	https://doi.org/	https://doi.org/	VERB
ajase-2385	271	11	10.1016	10.1016	NUM
ajase-2385	271	12	/	/	SYM
ajase-2385	271	13	j.ins.2011.12.028	j.ins.2011.12.028	ADJ
ajase-2385	271	14	cristadoro	cristadoro	NOUN
ajase-2385	271	15	,	,	PUNCT
ajase-2385	271	16	r.	r.	PROPN
ajase-2385	271	17	m.	m.	PROPN
ajase-2385	271	18	(	(	PUNCT
ajase-2385	271	19	2005	2005	NUM
ajase-2385	271	20	)	)	PUNCT
ajase-2385	271	21	.	.	PUNCT
ajase-2385	272	1	a	a	DET
ajase-2385	272	2	core	core	ADJ
ajase-2385	272	3	inflation	inflation	NOUN
ajase-2385	272	4	indicator	indicator	NOUN
ajase-2385	272	5	for	for	ADP
ajase-2385	272	6	euro	euro	PROPN
ajase-2385	272	7	area	area	NOUN
ajase-2385	272	8	.	.	PUNCT
ajase-2385	273	1	journal	journal	NOUN
ajase-2385	273	2	of	of	ADP
ajase-2385	273	3	money	money	NOUN
ajase-2385	273	4	,	,	PUNCT
ajase-2385	273	5	credit	credit	NOUN
ajase-2385	273	6	and	and	CCONJ
ajase-2385	273	7	banking	banking	NOUN
ajase-2385	273	8	,	,	PUNCT
ajase-2385	273	9	37(3	37(3	NUM
ajase-2385	273	10	)	)	PUNCT
ajase-2385	273	11	,	,	PUNCT
ajase-2385	273	12	539	539	NUM
ajase-2385	273	13	-	-	SYM
ajase-2385	273	14	560	560	NUM
ajase-2385	273	15	.	.	PUNCT
ajase-2385	273	16	retrieved	retrieve	VERB
ajase-2385	273	17	from	from	ADP
ajase-2385	273	18	http://www.jstor.org/	http://www.jstor.org/	ADJ
ajase-2385	273	19	stable/3839167	stable/3839167	PROPN
ajase-2385	273	20	.	.	PUNCT
ajase-2385	274	1	cutler	cutler	PROPN
ajase-2385	274	2	,	,	PUNCT
ajase-2385	274	3	a.	a.	NOUN
ajase-2385	274	4	,	,	PUNCT
ajase-2385	274	5	cutler	cutler	NOUN
ajase-2385	274	6	,	,	PUNCT
ajase-2385	274	7	d.	d.	PROPN
ajase-2385	274	8	,	,	PUNCT
ajase-2385	274	9	&	&	CCONJ
ajase-2385	274	10	stevens	stevens	PROPN
ajase-2385	274	11	,	,	PUNCT
ajase-2385	274	12	j.	j.	PROPN
ajase-2385	274	13	r.	r.	PROPN
ajase-2385	274	14	(	(	PUNCT
ajase-2385	274	15	2012	2012	NUM
ajase-2385	274	16	)	)	PUNCT
ajase-2385	274	17	.	.	PUNCT
ajase-2385	275	1	ensemble	ensemble	ADJ
ajase-2385	275	2	machine	machine	NOUN
ajase-2385	275	3	learning	learning	NOUN
ajase-2385	275	4	:	:	PUNCT
ajase-2385	275	5	methods	method	NOUN
ajase-2385	275	6	and	and	CCONJ
ajase-2385	275	7	applications	application	NOUN
ajase-2385	275	8	.	.	PUNCT
ajase-2385	276	1	(	(	PUNCT
ajase-2385	276	2	c.	c.	PROPN
ajase-2385	276	3	zhang	zhang	PROPN
ajase-2385	276	4	,	,	PUNCT
ajase-2385	276	5	&	&	CCONJ
ajase-2385	276	6	y.	y.	PROPN
ajase-2385	276	7	ma	ma	PROPN
ajase-2385	276	8	,	,	PUNCT
ajase-2385	276	9	eds	eds	PROPN
ajase-2385	276	10	.	.	PUNCT
ajase-2385	276	11	)	)	PUNCT
ajase-2385	277	1	new	new	PROPN
ajase-2385	277	2	york	york	PROPN
ajase-2385	277	3	:	:	PUNCT
ajase-2385	277	4	springer	springer	NOUN
ajase-2385	277	5	.	.	PUNCT
ajase-2385	278	1	https://	https://	PROPN
ajase-2385	278	2	doi.org/10.1007/978-1-4419-9326-7_5	doi.org/10.1007/978-1-4419-9326-7_5	PROPN
ajase-2385	278	3	goodhart	goodhart	NOUN
ajase-2385	278	4	,	,	PUNCT
ajase-2385	278	5	c.	c.	PROPN
ajase-2385	278	6	a.	a.	PROPN
ajase-2385	278	7	(	(	PUNCT
ajase-2385	278	8	2000	2000	NUM
ajase-2385	278	9	)	)	PUNCT
ajase-2385	278	10	.	.	PUNCT
ajase-2385	279	1	do	do	AUX
ajase-2385	279	2	asset	asset	NOUN
ajase-2385	279	3	prices	price	NOUN
ajase-2385	279	4	help	help	VERB
ajase-2385	279	5	to	to	PART
ajase-2385	279	6	predict	predict	VERB
ajase-2385	279	7	consumer	consumer	NOUN
ajase-2385	279	8	price	price	NOUN
ajase-2385	279	9	inflation	inflation	NOUN
ajase-2385	279	10	?	?	PUNCT
ajase-2385	280	1	(	(	PUNCT
ajase-2385	280	2	vol	vol	NOUN
ajase-2385	280	3	.	.	NOUN
ajase-2385	280	4	5	5	NUM
ajase-2385	280	5	)	)	PUNCT
ajase-2385	280	6	.	.	PUNCT
ajase-2385	281	1	manchester	manchester	PROPN
ajase-2385	281	2	school	school	PROPN
ajase-2385	281	3	,	,	PUNCT
ajase-2385	281	4	.	.	PUNCT
ajase-2385	282	1	retrieved	retrieve	VERB
ajase-2385	282	2	from	from	ADP
ajase-2385	282	3	https://ssrn.com/abstract=242532	https://ssrn.com/abstract=242532	PROPN
ajase-2385	282	4	granger	granger	PROPN
ajase-2385	282	5	,	,	PUNCT
ajase-2385	282	6	c.	c.	PROPN
ajase-2385	282	7	a.	a.	PROPN
ajase-2385	282	8	(	(	PUNCT
ajase-2385	282	9	2004	2004	NUM
ajase-2385	282	10	)	)	PUNCT
ajase-2385	282	11	.	.	PUNCT
ajase-2385	283	1	thick	thick	ADJ
ajase-2385	283	2	modeling	modeling	NOUN
ajase-2385	283	3	.	.	PUNCT
ajase-2385	284	1	economic	economic	ADJ
ajase-2385	284	2	modelling	modelling	NOUN
ajase-2385	284	3	,	,	PUNCT
ajase-2385	284	4	21(2	21(2	NUM
ajase-2385	284	5	)	)	PUNCT
ajase-2385	284	6	,	,	PUNCT
ajase-2385	284	7	323	323	NUM
ajase-2385	284	8	-	-	SYM
ajase-2385	284	9	343	343	NUM
ajase-2385	284	10	.	.	PUNCT
ajase-2385	284	11	retrieved	retrieve	VERB
ajase-2385	284	12	from	from	ADP
ajase-2385	284	13	https://econpapers	https://econpaper	NOUN
ajase-2385	284	14	.	.	PUNCT
ajase-2385	284	15	repec.org/repec:eee:ecmode:v:21:y:2004:i:2:p:323-343	repec.org/repec:eee:ecmode:v:21:y:2004:i:2:p:323-343	NOUN
ajase-2385	284	16	hoerl	hoerl	NOUN
ajase-2385	284	17	,	,	PUNCT
ajase-2385	284	18	a.	a.	PROPN
ajase-2385	284	19	e.	e.	PROPN
ajase-2385	284	20	(	(	PUNCT
ajase-2385	284	21	1970	1970	NUM
ajase-2385	284	22	)	)	PUNCT
ajase-2385	284	23	.	.	PUNCT
ajase-2385	285	1	ridge	ridge	PROPN
ajase-2385	285	2	regression	regression	PROPN
ajase-2385	285	3	:	:	PUNCT
ajase-2385	285	4	biased	biased	ADJ
ajase-2385	285	5	estimation	estimation	NOUN
ajase-2385	285	6	for	for	ADP
ajase-2385	285	7	nonorthogonal	nonorthogonal	ADJ
ajase-2385	285	8	problems	problem	NOUN
ajase-2385	285	9	.	.	PUNCT
ajase-2385	286	1	technometrics	technometric	NOUN
ajase-2385	286	2	,	,	PUNCT
ajase-2385	286	3	12(1	12(1	NUM
ajase-2385	286	4	)	)	PUNCT
ajase-2385	286	5	.	.	PUNCT
ajase-2385	287	1	retrieved	retrieve	VERB
ajase-2385	287	2	from	from	ADP
ajase-2385	287	3	https://doi.org/10.2307/1267351	https://doi.org/10.2307/1267351	NOUN
ajase-2385	287	4	hyndman	hyndman	NOUN
ajase-2385	287	5	,	,	PUNCT
ajase-2385	287	6	r.	r.	PROPN
ajase-2385	287	7	j.	j.	PROPN
ajase-2385	287	8	(	(	PUNCT
ajase-2385	287	9	2006	2006	NUM
ajase-2385	287	10	)	)	PUNCT
ajase-2385	287	11	.	.	PUNCT
ajase-2385	288	1	another	another	DET
ajase-2385	288	2	look	look	NOUN
ajase-2385	288	3	at	at	ADP
ajase-2385	288	4	measures	measure	NOUN
ajase-2385	288	5	of	of	ADP
ajase-2385	288	6	forecast	forecast	NOUN
ajase-2385	288	7	accuracy	accuracy	NOUN
ajase-2385	288	8	.	.	PUNCT
ajase-2385	289	1	international	international	ADJ
ajase-2385	289	2	journal	journal	PROPN
ajase-2385	289	3	of	of	ADP
ajase-2385	289	4	forecasting	forecasting	NOUN
ajase-2385	289	5	,	,	PUNCT
ajase-2385	289	6	22(4	22(4	NUM
ajase-2385	289	7	)	)	PUNCT
ajase-2385	289	8	,	,	PUNCT
ajase-2385	289	9	679	679	NUM
ajase-2385	289	10	-	-	SYM
ajase-2385	289	11	688	688	NUM
ajase-2385	289	12	.	.	PUNCT
ajase-2385	290	1	inoue	inoue	PROPN
ajase-2385	290	2	,	,	PUNCT
ajase-2385	290	3	a.	a.	PROPN
ajase-2385	290	4	,	,	PUNCT
ajase-2385	290	5	&	&	CCONJ
ajase-2385	290	6	kilian	kilian	PROPN
ajase-2385	290	7	,	,	PUNCT
ajase-2385	290	8	l.	l.	PROPN
ajase-2385	290	9	(	(	PUNCT
ajase-2385	290	10	2006	2006	NUM
ajase-2385	290	11	)	)	PUNCT
ajase-2385	290	12	.	.	PUNCT
ajase-2385	291	1	on	on	ADP
ajase-2385	291	2	the	the	DET
ajase-2385	291	3	selection	selection	NOUN
ajase-2385	291	4	of	of	ADP
ajase-2385	291	5	forecasting	forecasting	NOUN
ajase-2385	291	6	models	model	NOUN
ajase-2385	291	7	.	.	PUNCT
ajase-2385	292	1	journal	journal	NOUN
ajase-2385	292	2	of	of	ADP
ajase-2385	292	3	econometrics	econometric	NOUN
ajase-2385	292	4	,	,	PUNCT
ajase-2385	292	5	137(2	137(2	NUM
ajase-2385	292	6	)	)	PUNCT
ajase-2385	292	7	,	,	PUNCT
ajase-2385	292	8	273	273	NUM
ajase-2385	292	9	–	–	PUNCT
ajase-2385	292	10	306	306	NUM
ajase-2385	292	11	.	.	PUNCT
ajase-2385	293	1	https://doi.org/10.1016/j.jeconom.2005.03.003	https://doi.org/10.1016/j.jeconom.2005.03.003	NUM
ajase-2385	293	2	jaehyuk	jaehyuk	PROPN
ajase-2385	293	3	choi	choi	PROPN
ajase-2385	293	4	,	,	PUNCT
ajase-2385	293	5	d.	d.	PROPN
ajase-2385	293	6	g.	g.	PROPN
ajase-2385	293	7	(	(	PUNCT
ajase-2385	293	8	2023	2023	NUM
ajase-2385	293	9	)	)	PUNCT
ajase-2385	293	10	.	.	PUNCT
ajase-2385	294	1	yield	yield	NOUN
ajase-2385	294	2	spread	spread	VERB
ajase-2385	294	3	selection	selection	NOUN
ajase-2385	294	4	in	in	ADP
ajase-2385	294	5	predicting	predict	VERB
ajase-2385	294	6	recession	recession	NOUN
ajase-2385	294	7	probabilities	probability	NOUN
ajase-2385	294	8	:	:	PUNCT
ajase-2385	294	9	a	a	DET
ajase-2385	294	10	machine	machine	NOUN
ajase-2385	294	11	learning	learn	VERB
ajase-2385	294	12	approach	approach	NOUN
ajase-2385	294	13	.	.	PUNCT
ajase-2385	295	1	journal	journal	NOUN
ajase-2385	295	2	of	of	ADP
ajase-2385	295	3	forecasting	forecasting	NOUN
ajase-2385	295	4	,	,	PUNCT
ajase-2385	295	5	42	42	NUM
ajase-2385	295	6	,	,	PUNCT
ajase-2385	295	7	7	7	NUM
ajase-2385	295	8	.	.	X
ajase-2385	295	9	jayasooriya	jayasooriya	PROPN
ajase-2385	295	10	,	,	PUNCT
ajase-2385	295	11	d.	d.	PROPN
ajase-2385	295	12	(	(	PUNCT
ajase-2385	295	13	2015	2015	NUM
ajase-2385	295	14	)	)	PUNCT
ajase-2385	295	15	.	.	PUNCT
ajase-2385	296	1	money	money	NOUN
ajase-2385	296	2	supply	supply	NOUN
ajase-2385	296	3	and	and	CCONJ
ajase-2385	296	4	inflation	inflation	NOUN
ajase-2385	296	5	:	:	PUNCT
ajase-2385	296	6	evidence	evidence	NOUN
ajase-2385	296	7	from	from	ADP
ajase-2385	296	8	sri	sri	PROPN
ajase-2385	296	9	.	.	PUNCT
ajase-2385	297	1	asian	asian	PROPN
ajase-2385	297	2	studies	studies	PROPN
ajase-2385	297	3	international	international	ADJ
ajase-2385	297	4	journal	journal	NOUN
ajase-2385	297	5	,	,	PUNCT
ajase-2385	297	6	1(1	1(1	NUM
ajase-2385	297	7	)	)	PUNCT
ajase-2385	297	8	,	,	PUNCT
ajase-2385	297	9	28	28	NUM
ajase-2385	297	10	.	.	PUNCT
ajase-2385	298	1	jere	jere	PROPN
ajase-2385	298	2	,	,	PUNCT
ajase-2385	298	3	s.	s.	PROPN
ajase-2385	298	4	,	,	PUNCT
ajase-2385	298	5	.	.	PUNCT
ajase-2385	299	1	(	(	PUNCT
ajase-2385	299	2	2016	2016	NUM
ajase-2385	299	3	)	)	PUNCT
ajase-2385	299	4	.	.	PUNCT
ajase-2385	300	1	forecasting	forecast	VERB
ajase-2385	300	2	inflation	inflation	NOUN
ajase-2385	300	3	rate	rate	NOUN
ajase-2385	300	4	of	of	ADP
ajase-2385	300	5	zambia	zambia	PROPN
ajase-2385	300	6	using	use	VERB
ajase-2385	300	7	holt	holt	PROPN
ajase-2385	300	8	’s	’s	PART
ajase-2385	300	9	exponential	exponential	NOUN
ajase-2385	300	10	.	.	PUNCT
ajase-2385	301	1	open	open	ADJ
ajase-2385	301	2	journal	journal	PROPN
ajase-2385	301	3	of	of	ADP
ajase-2385	301	4	statistics	statistic	NOUN
ajase-2385	301	5	,	,	PUNCT
ajase-2385	301	6	363372	363372	NUM
ajase-2385	301	7	.	.	PUNCT
ajase-2385	302	1	https://doi.org/	https://doi.org/	VERB
ajase-2385	302	2	10.4236	10.4236	NUM
ajase-2385	302	3	/	/	SYM
ajase-2385	302	4	ojs.2016.62031	ojs.2016.62031	NUM
ajase-2385	302	5	jesmy	jesmy	NOUN
ajase-2385	302	6	,	,	PUNCT
ajase-2385	302	7	a.	a.	NOUN
ajase-2385	302	8	(	(	PUNCT
ajase-2385	302	9	2010	2010	NUM
ajase-2385	302	10	)	)	PUNCT
ajase-2385	302	11	.	.	PUNCT
ajase-2385	303	1	estimation	estimation	NOUN
ajase-2385	303	2	of	of	ADP
ajase-2385	303	3	future	future	ADJ
ajase-2385	303	4	inflation	inflation	NOUN
ajase-2385	303	5	in	in	ADP
ajase-2385	303	6	sri	sri	PROPN
ajase-2385	303	7	lanka	lanka	PROPN
ajase-2385	303	8	using	use	VERB
ajase-2385	303	9	arima	arima	PROPN
ajase-2385	303	10	model	model	NOUN
ajase-2385	303	11	.	.	PUNCT
ajase-2385	304	1	,	,	PUNCT
ajase-2385	304	2	.	.	PUNCT
ajase-2385	305	1	kalam	kalam	PROPN
ajase-2385	305	2	,	,	PUNCT
ajase-2385	305	3	21	21	NUM
ajase-2385	305	4	-	-	SYM
ajase-2385	305	5	27	27	NUM
ajase-2385	305	6	.	.	PUNCT
ajase-2385	306	1	maldeni	maldeni	PROPN
ajase-2385	306	2	,	,	PUNCT
ajase-2385	306	3	r.	r.	PROPN
ajase-2385	306	4	&	&	CCONJ
ajase-2385	306	5	.	.	PUNCT
ajase-2385	306	6	(	(	PUNCT
ajase-2385	306	7	2021	2021	NUM
ajase-2385	306	8	)	)	PUNCT
ajase-2385	306	9	.	.	PUNCT
ajase-2385	307	1	a	a	DET
ajase-2385	307	2	machine	machine	NOUN
ajase-2385	307	3	learning	learn	VERB
ajase-2385	307	4	approach	approach	NOUN
ajase-2385	307	5	to	to	ADP
ajase-2385	307	6	ccpi	ccpi	ADV
ajase-2385	307	7	-	-	PUNCT
ajase-2385	307	8	based	base	VERB
ajase-2385	307	9	inflation	inflation	NOUN
ajase-2385	307	10	prediction	prediction	NOUN
ajase-2385	307	11	.	.	PUNCT
ajase-2385	308	1	proceedings	proceeding	NOUN
ajase-2385	308	2	of	of	ADP
ajase-2385	308	3	sixth	sixth	ADJ
ajase-2385	308	4	table	table	NOUN
ajase-2385	308	5	4	4	NUM
ajase-2385	308	6	:	:	PUNCT
ajase-2385	308	7	foretasted	foretaste	VERB
ajase-2385	308	8	values	value	NOUN
ajase-2385	308	9	for	for	ADP
ajase-2385	308	10	svr	svr	PROPN
ajase-2385	308	11	model	model	NOUN
ajase-2385	308	12	with	with	ADP
ajase-2385	308	13	wfv	wfv	NOUN
ajase-2385	308	14	technique	technique	NOUN
ajase-2385	308	15	date	date	NOUN
ajase-2385	308	16	yt	yt	PROPN
ajase-2385	308	17	forecast	forecast	PROPN
ajase-2385	308	18	2020	2020	NUM
ajase-2385	308	19	oct	oct	NOUN
ajase-2385	308	20	4.0	4.0	NUM
ajase-2385	308	21	4.296212	4.296212	NUM
ajase-2385	308	22	2020	2020	NUM
ajase-2385	308	23	nov	nov	PROPN
ajase-2385	308	24	4.1	4.1	NUM
ajase-2385	308	25	4.323517	4.323517	NUM
ajase-2385	308	26	2020	2020	NUM
ajase-2385	308	27	dec	dec	PROPN
ajase-2385	308	28	4.2	4.2	NUM
ajase-2385	308	29	4.425066	4.425066	NUM
ajase-2385	308	30	2021	2021	NUM
ajase-2385	308	31	jan	jan	NOUN
ajase-2385	308	32	3.0	3.0	NUM
ajase-2385	308	33	4.485011	4.485011	NUM
ajase-2385	308	34	2021	2021	NUM
ajase-2385	308	35	feb	feb	NOUN
ajase-2385	308	36	3.3	3.3	NUM
ajase-2385	308	37	2.992228	2.992228	NUM
ajase-2385	308	38	2021	2021	NUM
ajase-2385	308	39	mar	mar	PROPN
ajase-2385	308	40	4.1	4.1	NUM
ajase-2385	308	41	4.185231	4.185231	NUM
ajase-2385	308	42	2021	2021	NUM
ajase-2385	308	43	apr	apr	NOUN
ajase-2385	308	44	3.9	3.9	NUM
ajase-2385	308	45	4.532705	4.532705	NUM
ajase-2385	308	46	2021	2021	NUM
ajase-2385	308	47	may	may	AUX
ajase-2385	308	48	4.5	4.5	NUM
ajase-2385	308	49	3.827932	3.827932	NUM
ajase-2385	308	50	2021	2021	NUM
ajase-2385	308	51	jun	jun	PROPN
ajase-2385	308	52	5.2	5.2	NUM
ajase-2385	308	53	5.180228	5.180228	NUM
ajase-2385	308	54	2021	2021	NUM
ajase-2385	308	55	jul	jul	PROPN
ajase-2385	308	56	5.7	5.7	NUM
ajase-2385	308	57	5.517756	5.517756	NUM
ajase-2385	308	58	2021	2021	NUM
ajase-2385	308	59	aug	aug	PROPN
ajase-2385	308	60	6.0	6.0	NUM
ajase-2385	308	61	5.830174	5.830174	NUM
ajase-2385	308	62	2021	2021	NUM
ajase-2385	308	63	sept	sept	PROPN
ajase-2385	308	64	5.7	5.7	NUM
ajase-2385	308	65	6.004278	6.004278	NUM
ajase-2385	308	66	mape	mape	NOUN
ajase-2385	308	67	10.16	10.16	NUM
ajase-2385	308	68	pa	pa	PROPN
ajase-2385	308	69	ge	ge	PROPN
ajase-2385	308	70	60	60	NUM
ajase-2385	309	1	https://journals.e-palli.com/home/index.php/ajase	https://journals.e-palli.com/home/index.php/ajase	PROPN
ajase-2385	309	2	am	be	AUX
ajase-2385	309	3	.	.	PUNCT
ajase-2385	310	1	j.	j.	PROPN
ajase-2385	310	2	appl	appl	PROPN
ajase-2385	310	3	.	.	PROPN
ajase-2385	311	1	stat	stat	PROPN
ajase-2385	311	2	.	.	PUNCT
ajase-2385	312	1	econ	econ	PROPN
ajase-2385	312	2	.	.	PUNCT
ajase-2385	313	1	3(1	3(1	NUM
ajase-2385	313	2	)	)	PUNCT
ajase-2385	313	3	51	51	NUM
ajase-2385	313	4	-	-	SYM
ajase-2385	313	5	60	60	NUM
ajase-2385	313	6	,	,	PUNCT
ajase-2385	313	7	2024	2024	NUM
ajase-2385	313	8	international	international	ADJ
ajase-2385	313	9	congress	congress	PROPN
ajase-2385	313	10	on	on	ADP
ajase-2385	313	11	information	information	NOUN
ajase-2385	313	12	and	and	CCONJ
ajase-2385	313	13	communication	communication	NOUN
ajase-2385	313	14	technology	technology	NOUN
ajase-2385	313	15	.	.	PUNCT
ajase-2385	314	1	lecture	lecture	NOUN
ajase-2385	314	2	notes	note	NOUN
ajase-2385	314	3	in	in	ADP
ajase-2385	314	4	networks	network	NOUN
ajase-2385	314	5	and	and	CCONJ
ajase-2385	314	6	systems	system	NOUN
ajase-2385	314	7	,	,	PUNCT
ajase-2385	314	8	p.	p.	NOUN
ajase-2385	314	9	236	236	NUM
ajase-2385	314	10	.	.	PUNCT
ajase-2385	315	1	https://doi.org/10.1007/978-981-16-2380-6_50	https://doi.org/10.1007/978-981-16-2380-6_50	PRON
ajase-2385	315	2	malladi	malladi	PROPN
ajase-2385	315	3	,	,	PUNCT
ajase-2385	315	4	r.	r.	PROPN
ajase-2385	315	5	k.	k.	PROPN
ajase-2385	316	1	(	(	PUNCT
ajase-2385	316	2	2023	2023	NUM
ajase-2385	316	3	)	)	PUNCT
ajase-2385	316	4	.	.	PUNCT
ajase-2385	317	1	enchmark	enchmark	VERB
ajase-2385	317	2	analysis	analysis	NOUN
ajase-2385	317	3	of	of	ADP
ajase-2385	317	4	machine	machine	NOUN
ajase-2385	317	5	learning	learn	VERB
ajase-2385	317	6	methods	method	NOUN
ajase-2385	317	7	to	to	PART
ajase-2385	317	8	forecast	forecast	VERB
ajase-2385	317	9	the	the	DET
ajase-2385	317	10	u.s	u.s	PROPN
ajase-2385	317	11	.	.	PROPN
ajase-2385	317	12	annual	annual	ADJ
ajase-2385	317	13	inflation	inflation	NOUN
ajase-2385	317	14	rate	rate	NOUN
ajase-2385	317	15	during	during	ADP
ajase-2385	317	16	a	a	DET
ajase-2385	317	17	high	high	ADJ
ajase-2385	317	18	-	-	PUNCT
ajase-2385	317	19	decile	decile	NOUN
ajase-2385	317	20	inflation	inflation	NOUN
ajase-2385	317	21	period	period	NOUN
ajase-2385	317	22	.	.	PUNCT
ajase-2385	318	1	computational	computational	ADJ
ajase-2385	318	2	economics	economic	NOUN
ajase-2385	318	3	.	.	PUNCT
ajase-2385	319	1	https://doi.org/10.1007/	https://doi.org/10.1007/	PROPN
ajase-2385	319	2	s10614	s10614	PROPN
ajase-2385	319	3	-	-	PUNCT
ajase-2385	319	4	023	023	NUM
ajase-2385	319	5	-	-	PUNCT
ajase-2385	319	6	10436	10436	NUM
ajase-2385	319	7	-	-	PUNCT
ajase-2385	319	8	w	w	NOUN
ajase-2385	319	9	marcellino	marcellino	NOUN
ajase-2385	319	10	,	,	PUNCT
ajase-2385	319	11	m.	m.	NOUN
ajase-2385	319	12	(	(	PUNCT
ajase-2385	319	13	2002	2002	NUM
ajase-2385	319	14	)	)	PUNCT
ajase-2385	319	15	.	.	PUNCT
ajase-2385	320	1	forecast	forecast	NOUN
ajase-2385	320	2	pooling	pool	VERB
ajase-2385	320	3	for	for	ADP
ajase-2385	320	4	short	short	ADJ
ajase-2385	320	5	time	time	NOUN
ajase-2385	320	6	series	series	NOUN
ajase-2385	320	7	of	of	ADP
ajase-2385	320	8	macroeconomic	macroeconomic	ADJ
ajase-2385	320	9	variables	variable	NOUN
ajase-2385	320	10	.	.	PUNCT
ajase-2385	321	1	igier	igier	PROPN
ajase-2385	321	2	innocenzo	innocenzo	PROPN
ajase-2385	321	3	gasparini	gasparini	PROPN
ajase-2385	321	4	institute	institute	PROPN
ajase-2385	321	5	for	for	ADP
ajase-2385	321	6	economic	economic	ADJ
ajase-2385	321	7	research	research	NOUN
ajase-2385	321	8	.	.	PUNCT
ajase-2385	322	1	retrieved	retrieve	VERB
ajase-2385	322	2	from	from	ADP
ajase-2385	322	3	https://ideas.repec.org/p/	https://ideas.repec.org/p/	PROPN
ajase-2385	322	4	igi	igi	PROPN
ajase-2385	322	5	/	/	SYM
ajase-2385	322	6	igierp/212.html	igierp/212.html	PROPN
ajase-2385	322	7	marcellino	marcellino	NOUN
ajase-2385	322	8	,	,	PUNCT
ajase-2385	322	9	m.	m.	NOUN
ajase-2385	322	10	s.	s.	PROPN
ajase-2385	322	11	(	(	PUNCT
ajase-2385	322	12	2000	2000	NUM
ajase-2385	322	13	)	)	PUNCT
ajase-2385	322	14	.	.	PUNCT
ajase-2385	323	1	a	a	DET
ajase-2385	323	2	dynamic	dynamic	ADJ
ajase-2385	323	3	factor	factor	NOUN
ajase-2385	323	4	and	and	CCONJ
ajase-2385	323	5	neural	neural	ADJ
ajase-2385	323	6	networks	network	NOUN
ajase-2385	323	7	analysis	analysis	NOUN
ajase-2385	323	8	of	of	ADP
ajase-2385	323	9	the	the	DET
ajase-2385	323	10	co	co	NOUN
ajase-2385	323	11	-	-	NOUN
ajase-2385	323	12	movement	movement	NOUN
ajase-2385	323	13	of	of	ADP
ajase-2385	323	14	public	public	ADJ
ajase-2385	323	15	revenues	revenue	NOUN
ajase-2385	323	16	in	in	ADP
ajase-2385	323	17	the	the	DET
ajase-2385	323	18	emu	emu	PROPN
ajase-2385	323	19	.	.	PROPN
ajase-2385	324	1	ital	ital	PROPN
ajase-2385	324	2	econ	econ	PROPN
ajase-2385	324	3	j	j	PROPN
ajase-2385	324	4	8	8	NUM
ajase-2385	324	5	,	,	PUNCT
ajase-2385	324	6	289–338	289–338	NUM
ajase-2385	324	7	.	.	PUNCT
ajase-2385	325	1	https://	https://	PROPN
ajase-2385	325	2	doi.org/10.1007/s40797-021-00155-2	doi.org/10.1007/s40797-021-00155-2	PROPN
ajase-2385	325	3	ogutu	ogutu	PROPN
ajase-2385	325	4	,	,	PUNCT
ajase-2385	325	5	j.	j.	PROPN
ajase-2385	325	6	,	,	PUNCT
ajase-2385	325	7	schulz	schulz	PROPN
ajase-2385	325	8	,	,	PUNCT
ajase-2385	325	9	s.	s.	PROPN
ajase-2385	325	10	,	,	PUNCT
ajase-2385	325	11	&	&	CCONJ
ajase-2385	325	12	torben	torben	PROPN
ajase-2385	325	13	,	,	PUNCT
ajase-2385	325	14	p.	p.	NOUN
ajase-2385	325	15	(	(	PUNCT
ajase-2385	325	16	2012	2012	NUM
ajase-2385	325	17	)	)	PUNCT
ajase-2385	325	18	.	.	PUNCT
ajase-2385	326	1	genomic	genomic	ADJ
ajase-2385	326	2	selection	selection	NOUN
ajase-2385	326	3	using	use	VERB
ajase-2385	326	4	regularized	regularize	VERB
ajase-2385	326	5	linear	linear	ADJ
ajase-2385	326	6	regression	regression	NOUN
ajase-2385	326	7	models	model	NOUN
ajase-2385	326	8	:	:	PUNCT
ajase-2385	326	9	ridge	ridge	NOUN
ajase-2385	326	10	regression	regression	PROPN
ajase-2385	326	11	,	,	PUNCT
ajase-2385	326	12	lasso	lasso	NOUN
ajase-2385	326	13	,	,	PUNCT
ajase-2385	326	14	elastic	elastic	ADJ
ajase-2385	326	15	net	net	NOUN
ajase-2385	326	16	and	and	CCONJ
ajase-2385	326	17	their	their	PRON
ajase-2385	326	18	extensions	extension	NOUN
ajase-2385	326	19	.	.	PUNCT
ajase-2385	327	1	bmc	bmc	ADJ
ajase-2385	327	2	proceedings	proceeding	NOUN
ajase-2385	327	3	,	,	PUNCT
ajase-2385	327	4	6	6	NUM
ajase-2385	327	5	,	,	PUNCT
ajase-2385	327	6	s10	s10	NOUN
ajase-2385	327	7	.	.	PUNCT
ajase-2385	328	1	https://doi	https://doi	PROPN
ajase-2385	328	2	.	.	PUNCT
ajase-2385	328	3	org/10.1186/1753	org/10.1186/1753	NOUN
ajase-2385	328	4	-	-	NOUN
ajase-2385	328	5	6561	6561	NUM
ajase-2385	328	6	-	-	PUNCT
ajase-2385	328	7	6	6	NUM
ajase-2385	328	8	-	-	PUNCT
ajase-2385	328	9	s2	s2	NOUN
ajase-2385	328	10	-	-	PUNCT
ajase-2385	328	11	s10	s10	NOUN
ajase-2385	328	12	rahman	rahman	PROPN
ajase-2385	328	13	,	,	PUNCT
ajase-2385	328	14	m.	m.	NOUN
ajase-2385	328	15	a.	a.	PROPN
ajase-2385	328	16	,	,	PUNCT
ajase-2385	328	17	kabir	kabir	PROPN
ajase-2385	328	18	,	,	PUNCT
ajase-2385	328	19	m.	m.	NOUN
ajase-2385	328	20	a.	a.	PROPN
ajase-2385	328	21	,	,	PUNCT
ajase-2385	328	22	haque	haque	PROPN
ajase-2385	328	23	,	,	PUNCT
ajase-2385	328	24	m.	m.	PROPN
ajase-2385	328	25	e.	e.	PROPN
ajase-2385	328	26	,	,	PUNCT
ajase-2385	328	27	&	&	CCONJ
ajase-2385	328	28	hossain	hossain	PROPN
ajase-2385	328	29	,	,	PUNCT
ajase-2385	328	30	b.	b.	PROPN
ajase-2385	328	31	m.	m.	PROPN
ajase-2385	328	32	(	(	PUNCT
ajase-2385	328	33	2021	2021	NUM
ajase-2385	328	34	)	)	PUNCT
ajase-2385	328	35	.	.	PUNCT
ajase-2385	329	1	a	a	DET
ajase-2385	329	2	machine	machine	NOUN
ajase-2385	329	3	learning	learning	NOUN
ajase-2385	329	4	-	-	PUNCT
ajase-2385	329	5	based	base	VERB
ajase-2385	329	6	price	price	NOUN
ajase-2385	329	7	prediction	prediction	NOUN
ajase-2385	329	8	for	for	ADP
ajase-2385	329	9	cows	cow	NOUN
ajase-2385	329	10	.	.	PUNCT
ajase-2385	330	1	merican	merican	ADJ
ajase-2385	330	2	journal	journal	PROPN
ajase-2385	330	3	of	of	ADP
ajase-2385	330	4	agricultural	agricultural	ADJ
ajase-2385	330	5	science	science	NOUN
ajase-2385	330	6	,	,	PUNCT
ajase-2385	330	7	engineering	engineering	NOUN
ajase-2385	330	8	,	,	PUNCT
ajase-2385	330	9	and	and	CCONJ
ajase-2385	330	10	technology	technology	NOUN
ajase-2385	330	11	,	,	PUNCT
ajase-2385	330	12	5(1	5(1	NUM
ajase-2385	330	13	)	)	PUNCT
ajase-2385	330	14	,	,	PUNCT
ajase-2385	330	15	64–69	64–69	PROPN
ajase-2385	330	16	.	.	PUNCT
ajase-2385	331	1	https://	https://	PROPN
ajase-2385	331	2	doi.org/10.54536/ajaset.v5i1.63	doi.org/10.54536/ajaset.v5i1.63	PUNCT
ajase-2385	331	3	smola	smola	PROPN
ajase-2385	331	4	,	,	PUNCT
ajase-2385	331	5	a.	a.	PROPN
ajase-2385	331	6	j.	j.	PROPN
ajase-2385	331	7	,	,	PUNCT
ajase-2385	331	8	&	&	CCONJ
ajase-2385	331	9	schölkopf	schölkopf	PROPN
ajase-2385	331	10	,	,	PUNCT
ajase-2385	331	11	b.	b.	PROPN
ajase-2385	331	12	(	(	PUNCT
ajase-2385	331	13	2003	2003	NUM
ajase-2385	331	14	)	)	PUNCT
ajase-2385	331	15	.	.	PUNCT
ajase-2385	332	1	a	a	DET
ajase-2385	332	2	tutorial	tutorial	NOUN
ajase-2385	332	3	on	on	ADP
ajase-2385	332	4	support	support	NOUN
ajase-2385	332	5	vector	vector	NOUN
ajase-2385	332	6	regression	regression	NOUN
ajase-2385	332	7	.	.	PUNCT
ajase-2385	333	1	statistics	statistic	NOUN
ajase-2385	333	2	and	and	CCONJ
ajase-2385	333	3	computing	computing	NOUN
ajase-2385	333	4	,	,	PUNCT
ajase-2385	333	5	14(3	14(3	NUM
ajase-2385	333	6	)	)	PUNCT
ajase-2385	333	7	,	,	PUNCT
ajase-2385	333	8	199	199	NUM
ajase-2385	333	9	-	-	SYM
ajase-2385	333	10	222	222	NUM
ajase-2385	333	11	.	.	PUNCT
ajase-2385	334	1	https://doi.org/10.1023/	https://doi.org/10.1023/	PROPN
ajase-2385	334	2	b	b	NOUN
ajase-2385	334	3	:	:	PUNCT
ajase-2385	334	4	stco.0000035301.49549.88	stco.0000035301.49549.88	ADJ
ajase-2385	334	5	stock	stock	NOUN
ajase-2385	334	6	,	,	PUNCT
ajase-2385	334	7	j.	j.	PROPN
ajase-2385	334	8	h.	h.	PROPN
ajase-2385	334	9	(	(	PUNCT
ajase-2385	334	10	1999	1999	NUM
ajase-2385	334	11	)	)	PUNCT
ajase-2385	334	12	.	.	PUNCT
ajase-2385	335	1	forecasting	forecast	VERB
ajase-2385	335	2	inflation	inflation	NOUN
ajase-2385	335	3	new	new	ADJ
ajase-2385	335	4	index	index	NOUN
ajase-2385	335	5	of	of	ADP
ajase-2385	335	6	aggregate	aggregate	ADJ
ajase-2385	335	7	activity	activity	NOUN
ajase-2385	335	8	.	.	PUNCT
ajase-2385	336	1	journal	journal	NOUN
ajase-2385	336	2	of	of	ADP
ajase-2385	336	3	monetary	monetary	ADJ
ajase-2385	336	4	economics	economic	NOUN
ajase-2385	336	5	,	,	PUNCT
ajase-2385	336	6	44(2	44(2	NOUN
ajase-2385	336	7	)	)	PUNCT
ajase-2385	336	8	,	,	PUNCT
ajase-2385	336	9	293	293	NUM
ajase-2385	336	10	-	-	SYM
ajase-2385	336	11	335	335	NUM
ajase-2385	336	12	.	.	PUNCT
ajase-2385	336	13	https://doi.org/10.1016/s03043932(99)00027-6	https://doi.org/10.1016/s03043932(99)00027-6	ADJ
ajase-2385	336	14	tradingview	tradingview	NOUN
ajase-2385	336	15	.	.	PUNCT
ajase-2385	337	1	(	(	PUNCT
ajase-2385	337	2	2023	2023	NUM
ajase-2385	337	3	)	)	PUNCT
ajase-2385	337	4	.	.	PUNCT
ajase-2385	338	1	sri	sri	PROPN
ajase-2385	338	2	lanka	lanka	PROPN
ajase-2385	338	3	inflation	inflation	NOUN
ajase-2385	338	4	rate	rate	NOUN
ajase-2385	338	5	yoy	yoy	PROPN
ajase-2385	338	6	.	.	PUNCT
ajase-2385	339	1	trading	trading	NOUN
ajase-2385	339	2	view	view	NOUN
ajase-2385	339	3	.	.	PUNCT
ajase-2385	340	1	retrieved	retrieve	VERB
ajase-2385	340	2	from	from	ADP
ajase-2385	340	3	https://www.tradingview.com/	https://www.tradingview.com/	ADJ
ajase-2385	340	4	symbols	symbol	NOUN
ajase-2385	340	5	/	/	SYM
ajase-2385	340	6	economics	economic	NOUN
ajase-2385	340	7	-	-	PUNCT
ajase-2385	340	8	lkiryy/	lkiryy/	PROPN
ajase-2385	340	9	trevor	trevor	NOUN
ajase-2385	340	10	hastie	hastie	PROPN
ajase-2385	340	11	,	,	PUNCT
ajase-2385	340	12	r.	r.	PROPN
ajase-2385	340	13	t.	t.	PROPN
ajase-2385	340	14	(	(	PUNCT
ajase-2385	340	15	2009	2009	NUM
ajase-2385	340	16	)	)	PUNCT
ajase-2385	340	17	.	.	PUNCT
ajase-2385	341	1	the	the	DET
ajase-2385	341	2	elements	element	NOUN
ajase-2385	341	3	of	of	ADP
ajase-2385	341	4	statistical	statistical	ADJ
ajase-2385	341	5	learning	learning	NOUN
ajase-2385	341	6	(	(	PUNCT
ajase-2385	341	7	2	2	NUM
ajase-2385	341	8	ed	ed	NOUN
ajase-2385	341	9	.	.	PUNCT
ajase-2385	341	10	)	)	PUNCT
ajase-2385	341	11	.	.	PUNCT
ajase-2385	342	1	new	new	PROPN
ajase-2385	342	2	york	york	PROPN
ajase-2385	342	3	:	:	PUNCT
ajase-2385	342	4	springer	springer	NOUN
ajase-2385	342	5	.	.	PUNCT
ajase-2385	343	1	https://doi	https://doi	PROPN
ajase-2385	343	2	.	.	PUNCT
ajase-2385	343	3	org/10.1007/978	org/10.1007/978	PROPN
ajase-2385	343	4	-	-	PUNCT
ajase-2385	343	5	0	0	NUM
ajase-2385	343	6	-	-	PUNCT
ajase-2385	343	7	387	387	NUM
ajase-2385	343	8	-	-	PUNCT
ajase-2385	343	9	84858	84858	NUM
ajase-2385	343	10	-	-	SYM
ajase-2385	343	11	7	7	NUM
ajase-2385	343	12	volkan	volkan	NOUN
ajase-2385	343	13	,	,	PUNCT
ajase-2385	343	14	u.	u.	PROPN
ajase-2385	343	15	,	,	PUNCT
ajase-2385	343	16	afsin	afsin	PROPN
ajase-2385	343	17	,	,	PUNCT
ajase-2385	343	18	s.	s.	PROPN
ajase-2385	343	19	,	,	PUNCT
ajase-2385	343	20	&	&	CCONJ
ajase-2385	343	21	abdulhamit	abdulhamit	PROPN
ajase-2385	343	22	,	,	PUNCT
ajase-2385	343	23	s.	s.	PROPN
ajase-2385	343	24	(	(	PUNCT
ajase-2385	343	25	2018	2018	NUM
ajase-2385	343	26	)	)	PUNCT
ajase-2385	343	27	.	.	PUNCT
ajase-2385	344	1	comparison	comparison	NOUN
ajase-2385	344	2	of	of	ADP
ajase-2385	344	3	time	time	NOUN
ajase-2385	344	4	series	series	NOUN
ajase-2385	344	5	and	and	CCONJ
ajase-2385	344	6	machine	machine	NOUN
ajase-2385	344	7	learning	learning	NOUN
ajase-2385	344	8	models	model	NOUN
ajase-2385	344	9	for	for	ADP
ajase-2385	344	10	inflation	inflation	NOUN
ajase-2385	344	11	forecasting	forecasting	NOUN
ajase-2385	344	12	:	:	PUNCT
ajase-2385	344	13	empirical	empirical	ADJ
ajase-2385	344	14	evidence	evidence	NOUN
ajase-2385	344	15	from	from	ADP
ajase-2385	344	16	the	the	DET
ajase-2385	344	17	us	us	PROPN
ajase-2385	344	18	.	.	PUNCT
ajase-2385	345	1	neural	neural	ADJ
ajase-2385	345	2	computing	computing	NOUN
ajase-2385	345	3	and	and	CCONJ
ajase-2385	345	4	applications	application	NOUN
ajase-2385	345	5	,	,	PUNCT
ajase-2385	345	6	30	30	NUM
ajase-2385	345	7	,	,	PUNCT
ajase-2385	345	8	1519–1527	1519–1527	NUM
ajase-2385	345	9	.	.	PUNCT
ajase-2385	346	1	https://doi.org/10.1007/s00521-016-2766-x	https://doi.org/10.1007/s00521-016-2766-x	PROPN
ajase-2385	346	2	wickham	wickham	PROPN
ajase-2385	346	3	,	,	PUNCT
ajase-2385	346	4	h.	h.	PROPN
ajase-2385	346	5	(	(	PUNCT
ajase-2385	346	6	2016	2016	NUM
ajase-2385	346	7	)	)	PUNCT
ajase-2385	346	8	.	.	PUNCT
ajase-2385	347	1	ggplot2	ggplot2	PROPN
ajase-2385	347	2	:	:	PUNCT
ajase-2385	347	3	elegant	elegant	ADJ
ajase-2385	347	4	graphics	graphic	NOUN
ajase-2385	347	5	for	for	ADP
ajase-2385	347	6	data	data	NOUN
ajase-2385	347	7	analysis	analysis	NOUN
ajase-2385	347	8	(	(	PUNCT
ajase-2385	347	9	2nd	2nd	ADJ
ajase-2385	347	10	ed	ed	NOUN
ajase-2385	347	11	.	.	PUNCT
ajase-2385	347	12	)	)	PUNCT
ajase-2385	347	13	.	.	PUNCT
ajase-2385	348	1	melbourne	melbourne	PROPN
ajase-2385	348	2	:	:	PUNCT
ajase-2385	348	3	springer	springer	NOUN
ajase-2385	348	4	.	.	PUNCT
ajase-2385	349	1	wright	wright	PROPN
ajase-2385	349	2	,	,	PUNCT
ajase-2385	349	3	j.	j.	PROPN
ajase-2385	349	4	h.	h.	PROPN
ajase-2385	349	5	(	(	PUNCT
ajase-2385	349	6	2003	2003	NUM
ajase-2385	349	7	,	,	PUNCT
ajase-2385	349	8	september	september	PROPN
ajase-2385	349	9	)	)	PUNCT
ajase-2385	349	10	.	.	PUNCT
ajase-2385	350	1	forecasting	forecast	VERB
ajase-2385	350	2	u.s	u.s	PROPN
ajase-2385	350	3	.	.	PROPN
ajase-2385	350	4	inflation	inflation	NOUN
ajase-2385	350	5	by	by	ADP
ajase-2385	350	6	bayesian	bayesian	NOUN
ajase-2385	350	7	model	model	NOUN
ajase-2385	350	8	averaging	averaging	NOUN
ajase-2385	350	9	(	(	PUNCT
ajase-2385	350	10	september	september	PROPN
ajase-2385	350	11	2003	2003	NUM
ajase-2385	350	12	)	)	PUNCT
ajase-2385	350	13	.	.	PUNCT
ajase-2385	351	1	international	international	ADJ
ajase-2385	351	2	finance	finance	NOUN
ajase-2385	351	3	discussion	discussion	NOUN
ajase-2385	351	4	paper	paper	NOUN
ajase-2385	351	5	,	,	PUNCT
ajase-2385	351	6	1	1	NUM
ajase-2385	351	7	-	-	SYM
ajase-2385	351	8	33.http://	33.http://	NUM
ajase-2385	351	9	dx.doi.org/10.2139/ssrn.457360	dx.doi.org/10.2139/ssrn.457360	NOUN