id	sid	tid	token	lemma	pos
ap-6763	1	1	acta	acta	PROPN
ap-6763	1	2	polytechnica	polytechnica	PROPN
ap-6763	1	3	https://doi.org/10.14311/ap.2021.61.0364	https://doi.org/10.14311/ap.2021.61.0364	PROPN
ap-6763	1	4	acta	acta	PROPN
ap-6763	1	5	polytechnica	polytechnica	PROPN
ap-6763	1	6	61(2):364–377	61(2):364–377	PROPN
ap-6763	1	7	,	,	PUNCT
ap-6763	1	8	2021	2021	NUM
ap-6763	1	9	©	©	ADP
ap-6763	1	10	2021	2021	NUM
ap-6763	1	11	the	the	DET
ap-6763	1	12	author(s	author(s	NOUN
ap-6763	1	13	)	)	PUNCT
ap-6763	1	14	.	.	PUNCT
ap-6763	2	1	licensed	license	VERB
ap-6763	2	2	under	under	ADP
ap-6763	2	3	a	a	DET
ap-6763	2	4	cc	cc	NOUN
ap-6763	2	5	-	-	PUNCT
ap-6763	2	6	by	by	ADP
ap-6763	2	7	4.0	4.0	NUM
ap-6763	2	8	licence	licence	NOUN
ap-6763	2	9	published	publish	VERB
ap-6763	2	10	by	by	ADP
ap-6763	2	11	the	the	DET
ap-6763	2	12	czech	czech	PROPN
ap-6763	2	13	technical	technical	PROPN
ap-6763	2	14	university	university	PROPN
ap-6763	2	15	in	in	ADP
ap-6763	2	16	prague	prague	PROPN
ap-6763	2	17	modified	modify	VERB
ap-6763	2	18	possibilistic	possibilistic	ADJ
ap-6763	2	19	fuzzy	fuzzy	ADJ
ap-6763	2	20	c	c	NOUN
ap-6763	2	21	-	-	PUNCT
ap-6763	2	22	means	means	NOUN
ap-6763	2	23	algorithm	algorithm	NOUN
ap-6763	2	24	for	for	ADP
ap-6763	2	25	clustering	cluster	VERB
ap-6763	2	26	incomplete	incomplete	ADJ
ap-6763	2	27	data	datum	NOUN
ap-6763	2	28	sets	set	NOUN
ap-6763	2	29	rustama,∗	rustama,∗	NOUN
ap-6763	2	30	,	,	PUNCT
ap-6763	2	31	koredianto	koredianto	PROPN
ap-6763	2	32	usmana	usmana	PROPN
ap-6763	2	33	,	,	PUNCT
ap-6763	2	34	mudyawati	mudyawati	PROPN
ap-6763	2	35	kamaruddinb	kamaruddinb	PROPN
ap-6763	2	36	,	,	PUNCT
ap-6763	2	37	dina	dina	PROPN
ap-6763	2	38	chamidahc	chamidahc	PROPN
ap-6763	2	39	,	,	PUNCT
ap-6763	2	40	nopendrid	nopendrid	VERB
ap-6763	2	41	,	,	PUNCT
ap-6763	2	42	khaerudin	khaerudin	PROPN
ap-6763	2	43	saleha	saleha	NOUN
ap-6763	2	44	,	,	PUNCT
ap-6763	2	45	yulinda	yulinda	PROPN
ap-6763	2	46	eliskara	eliskara	PROPN
ap-6763	2	47	,	,	PUNCT
ap-6763	2	48	ismail	ismail	NOUN
ap-6763	2	49	marzukie	marzukie	AUX
ap-6763	2	50	a	a	DET
ap-6763	2	51	telkom	telkom	NOUN
ap-6763	2	52	university	university	NOUN
ap-6763	2	53	,	,	PUNCT
ap-6763	2	54	school	school	NOUN
ap-6763	2	55	of	of	ADP
ap-6763	2	56	electrical	electrical	ADJ
ap-6763	2	57	engineering	engineering	NOUN
ap-6763	2	58	,	,	PUNCT
ap-6763	2	59	department	department	NOUN
ap-6763	2	60	of	of	ADP
ap-6763	2	61	telecommunication	telecommunication	NOUN
ap-6763	2	62	engineering	engineering	NOUN
ap-6763	2	63	,	,	PUNCT
ap-6763	2	64	jl	jl	PROPN
ap-6763	2	65	.	.	PROPN
ap-6763	2	66	telekomunikasi	telekomunikasi	PROPN
ap-6763	2	67	no.1	no.1	PROPN
ap-6763	2	68	dayeuh	dayeuh	PROPN
ap-6763	2	69	kolot	kolot	NOUN
ap-6763	2	70	,	,	PUNCT
ap-6763	2	71	40257	40257	NUM
ap-6763	2	72	kabupaten	kabupaten	PROPN
ap-6763	2	73	bandung	bandung	PROPN
ap-6763	2	74	,	,	PUNCT
ap-6763	2	75	jawa	jawa	PROPN
ap-6763	2	76	barat	barat	PROPN
ap-6763	2	77	,	,	PUNCT
ap-6763	2	78	indonesia	indonesia	PROPN
ap-6763	2	79	b	b	PROPN
ap-6763	2	80	universitas	universita	NOUN
ap-6763	2	81	muhammadiyah	muhammadiyah	ADP
ap-6763	2	82	semarang	semarang	PROPN
ap-6763	2	83	,	,	PUNCT
ap-6763	2	84	faculty	faculty	NOUN
ap-6763	2	85	of	of	ADP
ap-6763	2	86	health	health	NOUN
ap-6763	2	87	sciences	sciences	PROPN
ap-6763	2	88	,	,	PUNCT
ap-6763	2	89	semarang	semarang	PROPN
ap-6763	2	90	,	,	PUNCT
ap-6763	2	91	jawa	jawa	PROPN
ap-6763	2	92	tengah	tengah	PROPN
ap-6763	2	93	,	,	PUNCT
ap-6763	2	94	indonesia	indonesia	PROPN
ap-6763	2	95	c	c	PROPN
ap-6763	2	96	universitas	universitas	PROPN
ap-6763	2	97	wijaya	wijaya	PROPN
ap-6763	2	98	kusuma	kusuma	PROPN
ap-6763	2	99	surabaya	surabaya	PROPN
ap-6763	2	100	,	,	PUNCT
ap-6763	2	101	faculty	faculty	NOUN
ap-6763	2	102	of	of	ADP
ap-6763	2	103	language	language	NOUN
ap-6763	2	104	and	and	CCONJ
ap-6763	2	105	science	science	NOUN
ap-6763	2	106	,	,	PUNCT
ap-6763	2	107	department	department	NOUN
ap-6763	2	108	of	of	ADP
ap-6763	2	109	biology	biology	NOUN
ap-6763	2	110	education	education	NOUN
ap-6763	2	111	,	,	PUNCT
ap-6763	2	112	surabaya	surabaya	PROPN
ap-6763	2	113	,	,	PUNCT
ap-6763	2	114	jawa	jawa	PROPN
ap-6763	2	115	timur	timur	PROPN
ap-6763	2	116	,	,	PUNCT
ap-6763	2	117	indonesia	indonesia	PROPN
ap-6763	2	118	d	d	PROPN
ap-6763	2	119	telkom	telkom	PROPN
ap-6763	2	120	university	university	NOUN
ap-6763	2	121	,	,	PUNCT
ap-6763	2	122	school	school	NOUN
ap-6763	2	123	of	of	ADP
ap-6763	2	124	industrial	industrial	ADJ
ap-6763	2	125	engineering	engineering	NOUN
ap-6763	2	126	,	,	PUNCT
ap-6763	2	127	department	department	NOUN
ap-6763	2	128	of	of	ADP
ap-6763	2	129	industrial	industrial	ADJ
ap-6763	2	130	engineering	engineering	NOUN
ap-6763	2	131	,	,	PUNCT
ap-6763	2	132	jawa	jawa	PROPN
ap-6763	2	133	barat	barat	PROPN
ap-6763	2	134	,	,	PUNCT
ap-6763	2	135	indonesia	indonesia	PROPN
ap-6763	2	136	e	e	PROPN
ap-6763	2	137	fajar	fajar	PROPN
ap-6763	2	138	university	university	PROPN
ap-6763	2	139	,	,	PUNCT
ap-6763	2	140	department	department	NOUN
ap-6763	2	141	of	of	ADP
ap-6763	2	142	chemical	chemical	PROPN
ap-6763	2	143	engineering	engineering	PROPN
ap-6763	2	144	,	,	PUNCT
ap-6763	2	145	makassar	makassar	PROPN
ap-6763	2	146	,	,	PUNCT
ap-6763	2	147	sulawesi	sulawesi	PROPN
ap-6763	2	148	selatan	selatan	PROPN
ap-6763	2	149	,	,	PUNCT
ap-6763	2	150	indonesia	indonesia	PROPN
ap-6763	2	151	∗	∗	PROPN
ap-6763	2	152	corresponding	correspond	VERB
ap-6763	2	153	author	author	NOUN
ap-6763	2	154	:	:	PUNCT
ap-6763	2	155	rustam@telkomuniversity.ac.id	rustam@telkomuniversity.ac.id	ADJ
ap-6763	2	156	abstract	abstract	NOUN
ap-6763	2	157	.	.	PUNCT
ap-6763	3	1	a	a	DET
ap-6763	3	2	possibilistic	possibilistic	ADJ
ap-6763	3	3	fuzzy	fuzzy	ADJ
ap-6763	3	4	c	c	NOUN
ap-6763	3	5	-	-	PUNCT
ap-6763	3	6	means	means	NOUN
ap-6763	3	7	(	(	PUNCT
ap-6763	3	8	pfcm	pfcm	PROPN
ap-6763	3	9	)	)	PUNCT
ap-6763	3	10	algorithm	algorithm	NOUN
ap-6763	3	11	is	be	AUX
ap-6763	3	12	a	a	DET
ap-6763	3	13	reliable	reliable	ADJ
ap-6763	3	14	algorithm	algorithm	NOUN
ap-6763	3	15	proposed	propose	VERB
ap-6763	3	16	to	to	PART
ap-6763	3	17	deal	deal	VERB
ap-6763	3	18	with	with	ADP
ap-6763	3	19	the	the	DET
ap-6763	3	20	weaknesses	weakness	NOUN
ap-6763	3	21	associated	associate	VERB
ap-6763	3	22	with	with	ADP
ap-6763	3	23	handling	handle	VERB
ap-6763	3	24	noise	noise	NOUN
ap-6763	3	25	sensitivity	sensitivity	NOUN
ap-6763	3	26	and	and	CCONJ
ap-6763	3	27	coincidence	coincidence	NOUN
ap-6763	3	28	clusters	cluster	NOUN
ap-6763	3	29	in	in	ADP
ap-6763	3	30	fuzzy	fuzzy	ADJ
ap-6763	3	31	c	c	NOUN
ap-6763	3	32	-	-	PUNCT
ap-6763	3	33	means	means	NOUN
ap-6763	3	34	(	(	PUNCT
ap-6763	3	35	fcm	fcm	X
ap-6763	3	36	)	)	PUNCT
ap-6763	3	37	and	and	CCONJ
ap-6763	3	38	possibilistic	possibilistic	ADJ
ap-6763	3	39	c	c	NOUN
ap-6763	3	40	-	-	PUNCT
ap-6763	3	41	means	means	NOUN
ap-6763	3	42	(	(	PUNCT
ap-6763	3	43	pcm	pcm	NOUN
ap-6763	3	44	)	)	PUNCT
ap-6763	3	45	.	.	PUNCT
ap-6763	4	1	however	however	ADV
ap-6763	4	2	,	,	PUNCT
ap-6763	4	3	the	the	DET
ap-6763	4	4	pfcm	pfcm	PROPN
ap-6763	4	5	algorithm	algorithm	NOUN
ap-6763	4	6	is	be	AUX
ap-6763	4	7	only	only	ADV
ap-6763	4	8	applicable	applicable	ADJ
ap-6763	4	9	to	to	PART
ap-6763	4	10	complete	complete	VERB
ap-6763	4	11	data	datum	NOUN
ap-6763	4	12	sets	set	NOUN
ap-6763	4	13	.	.	PUNCT
ap-6763	5	1	therefore	therefore	ADV
ap-6763	5	2	,	,	PUNCT
ap-6763	5	3	this	this	DET
ap-6763	5	4	research	research	NOUN
ap-6763	5	5	modified	modify	VERB
ap-6763	5	6	the	the	DET
ap-6763	5	7	pfcm	pfcm	NOUN
ap-6763	5	8	for	for	ADP
ap-6763	5	9	clustering	cluster	VERB
ap-6763	5	10	incomplete	incomplete	ADJ
ap-6763	5	11	data	datum	NOUN
ap-6763	5	12	sets	set	NOUN
ap-6763	5	13	to	to	PART
ap-6763	5	14	ocspfcm	ocspfcm	VERB
ap-6763	5	15	and	and	CCONJ
ap-6763	5	16	npspfcm	npspfcm	ADJ
ap-6763	5	17	with	with	ADP
ap-6763	5	18	the	the	DET
ap-6763	5	19	performance	performance	NOUN
ap-6763	5	20	evaluated	evaluate	VERB
ap-6763	5	21	based	base	VERB
ap-6763	5	22	on	on	ADP
ap-6763	5	23	three	three	NUM
ap-6763	5	24	aspects	aspect	NOUN
ap-6763	5	25	,	,	PUNCT
ap-6763	5	26	1	1	NUM
ap-6763	5	27	)	)	PUNCT
ap-6763	5	28	accuracy	accuracy	NOUN
ap-6763	5	29	percentage	percentage	NOUN
ap-6763	5	30	,	,	PUNCT
ap-6763	5	31	2	2	X
ap-6763	5	32	)	)	PUNCT
ap-6763	5	33	the	the	DET
ap-6763	5	34	number	number	NOUN
ap-6763	5	35	of	of	ADP
ap-6763	5	36	iterations	iteration	NOUN
ap-6763	5	37	,	,	PUNCT
ap-6763	5	38	and	and	CCONJ
ap-6763	5	39	3	3	X
ap-6763	5	40	)	)	PUNCT
ap-6763	5	41	centroid	centroid	NOUN
ap-6763	5	42	errors	error	NOUN
ap-6763	5	43	.	.	PUNCT
ap-6763	6	1	the	the	DET
ap-6763	6	2	results	result	NOUN
ap-6763	6	3	showed	show	VERB
ap-6763	6	4	that	that	SCONJ
ap-6763	6	5	the	the	DET
ap-6763	6	6	npspfcm	npspfcm	NOUN
ap-6763	6	7	outperforms	outperform	VERB
ap-6763	6	8	the	the	DET
ap-6763	6	9	ocspfcm	ocspfcm	NOUN
ap-6763	6	10	with	with	ADP
ap-6763	6	11	missing	miss	VERB
ap-6763	6	12	values	value	NOUN
ap-6763	6	13	ranging	range	VERB
ap-6763	6	14	from	from	ADP
ap-6763	6	15	5	5	NUM
ap-6763	6	16	%	%	NOUN
ap-6763	6	17	−	−	PROPN
ap-6763	6	18	30	30	NUM
ap-6763	6	19	%	%	NOUN
ap-6763	6	20	for	for	ADP
ap-6763	6	21	all	all	DET
ap-6763	6	22	experimental	experimental	ADJ
ap-6763	6	23	data	datum	NOUN
ap-6763	6	24	sets	set	NOUN
ap-6763	6	25	.	.	PUNCT
ap-6763	7	1	furthermore	furthermore	ADV
ap-6763	7	2	,	,	PUNCT
ap-6763	7	3	both	both	DET
ap-6763	7	4	algorithms	algorithm	NOUN
ap-6763	7	5	provide	provide	VERB
ap-6763	7	6	average	average	ADJ
ap-6763	7	7	accuracies	accuracy	NOUN
ap-6763	7	8	between	between	ADP
ap-6763	7	9	97.75	97.75	NUM
ap-6763	7	10	%	%	NOUN
ap-6763	7	11	−78.98	−78.98	NUM
ap-6763	7	12	%	%	NOUN
ap-6763	7	13	and	and	CCONJ
ap-6763	7	14	98.86	98.86	NUM
ap-6763	7	15	%	%	NOUN
ap-6763	7	16	−92.49	−92.49	NUM
ap-6763	7	17	%	%	NOUN
ap-6763	7	18	,	,	PUNCT
ap-6763	7	19	respectively	respectively	ADV
ap-6763	7	20	.	.	PUNCT
ap-6763	8	1	keywords	keyword	NOUN
ap-6763	8	2	:	:	PUNCT
ap-6763	8	3	incomplete	incomplete	ADJ
ap-6763	8	4	data	datum	NOUN
ap-6763	8	5	,	,	PUNCT
ap-6763	8	6	fuzzy	fuzzy	ADJ
ap-6763	8	7	clustering	clustering	NOUN
ap-6763	8	8	,	,	PUNCT
ap-6763	8	9	possibilistic	possibilistic	ADJ
ap-6763	8	10	clustering	clustering	NOUN
ap-6763	8	11	,	,	PUNCT
ap-6763	8	12	missing	miss	VERB
ap-6763	8	13	values	value	NOUN
ap-6763	8	14	imputation	imputation	NOUN
ap-6763	8	15	.	.	PUNCT
ap-6763	9	1	1	1	X
ap-6763	9	2	.	.	X
ap-6763	9	3	introduction	introduction	NOUN
ap-6763	9	4	incomplete	incomplete	ADJ
ap-6763	9	5	data	datum	NOUN
ap-6763	9	6	sets	set	NOUN
ap-6763	9	7	are	be	AUX
ap-6763	9	8	commonly	commonly	ADV
ap-6763	9	9	found	find	VERB
ap-6763	9	10	in	in	ADP
ap-6763	9	11	the	the	DET
ap-6763	9	12	real	real	ADJ
ap-6763	9	13	world	world	NOUN
ap-6763	9	14	due	due	ADP
ap-6763	9	15	to	to	ADP
ap-6763	9	16	failures	failure	NOUN
ap-6763	9	17	during	during	ADP
ap-6763	9	18	the	the	DET
ap-6763	9	19	collection	collection	NOUN
ap-6763	9	20	,	,	PUNCT
ap-6763	9	21	merging	merging	NOUN
ap-6763	9	22	,	,	PUNCT
ap-6763	9	23	cleaning	cleaning	NOUN
ap-6763	9	24	,	,	PUNCT
ap-6763	9	25	and	and	CCONJ
ap-6763	9	26	transfer	transfer	NOUN
ap-6763	9	27	of	of	ADP
ap-6763	9	28	data	datum	NOUN
ap-6763	9	29	from	from	ADP
ap-6763	9	30	one	one	NUM
ap-6763	9	31	source	source	NOUN
ap-6763	9	32	to	to	ADP
ap-6763	9	33	another	another	PRON
ap-6763	9	34	[	[	X
ap-6763	9	35	1	1	NUM
ap-6763	9	36	]	]	PUNCT
ap-6763	9	37	.	.	PUNCT
ap-6763	10	1	the	the	DET
ap-6763	10	2	main	main	ADJ
ap-6763	10	3	problem	problem	NOUN
ap-6763	10	4	faced	face	VERB
ap-6763	10	5	when	when	SCONJ
ap-6763	10	6	trying	try	VERB
ap-6763	10	7	to	to	PART
ap-6763	10	8	cluster	cluster	VERB
ap-6763	10	9	incomplete	incomplete	ADJ
ap-6763	10	10	data	datum	NOUN
ap-6763	10	11	sets	set	NOUN
ap-6763	10	12	is	be	AUX
ap-6763	10	13	the	the	DET
ap-6763	10	14	inability	inability	NOUN
ap-6763	10	15	of	of	ADP
ap-6763	10	16	the	the	DET
ap-6763	10	17	existing	exist	VERB
ap-6763	10	18	algorithm	algorithm	NOUN
ap-6763	10	19	to	to	PART
ap-6763	10	20	carry	carry	VERB
ap-6763	10	21	out	out	ADP
ap-6763	10	22	the	the	DET
ap-6763	10	23	process	process	NOUN
ap-6763	10	24	.	.	PUNCT
ap-6763	11	1	this	this	PRON
ap-6763	11	2	is	be	AUX
ap-6763	11	3	because	because	SCONJ
ap-6763	11	4	popular	popular	ADJ
ap-6763	11	5	clustering	clustering	ADJ
ap-6763	11	6	algorithms	algorithms	NOUN
ap-6763	11	7	comprises	comprise	VERB
ap-6763	11	8	fuzzy	fuzzy	ADJ
ap-6763	11	9	c	c	NOUN
ap-6763	11	10	-	-	PUNCT
ap-6763	11	11	means	means	NOUN
ap-6763	11	12	(	(	PUNCT
ap-6763	11	13	fcm	fcm	X
ap-6763	11	14	)	)	PUNCT
ap-6763	12	1	[	[	X
ap-6763	12	2	2	2	NUM
ap-6763	12	3	]	]	PUNCT
ap-6763	12	4	and	and	CCONJ
ap-6763	12	5	possibilistic	possibilistic	ADJ
ap-6763	12	6	c	c	NOUN
ap-6763	12	7	-	-	PUNCT
ap-6763	12	8	means	means	NOUN
ap-6763	12	9	(	(	PUNCT
ap-6763	12	10	pcm	pcm	NOUN
ap-6763	12	11	)	)	PUNCT
ap-6763	13	1	[	[	X
ap-6763	13	2	3	3	NUM
ap-6763	13	3	]	]	PUNCT
ap-6763	13	4	,	,	PUNCT
ap-6763	13	5	which	which	PRON
ap-6763	13	6	are	be	AUX
ap-6763	13	7	used	use	VERB
ap-6763	13	8	for	for	ADP
ap-6763	13	9	complete	complete	ADJ
ap-6763	13	10	data	datum	NOUN
ap-6763	13	11	sets	set	NOUN
ap-6763	13	12	.	.	PUNCT
ap-6763	14	1	bezdek	bezdek	PROPN
ap-6763	14	2	and	and	CCONJ
ap-6763	14	3	hathaway	hathaway	PROPN
ap-6763	15	1	[	[	X
ap-6763	15	2	4	4	X
ap-6763	15	3	]	]	PUNCT
ap-6763	15	4	developed	develop	VERB
ap-6763	15	5	the	the	DET
ap-6763	15	6	fcm	fcm	PROPN
ap-6763	15	7	algorithm	algorithm	NOUN
ap-6763	15	8	to	to	PART
ap-6763	15	9	deal	deal	VERB
ap-6763	15	10	with	with	ADP
ap-6763	15	11	the	the	DET
ap-6763	15	12	problem	problem	NOUN
ap-6763	15	13	of	of	ADP
ap-6763	15	14	clustering	cluster	VERB
ap-6763	15	15	data	data	NOUN
ap-6763	15	16	sets	set	NOUN
ap-6763	15	17	with	with	ADP
ap-6763	15	18	missing	miss	VERB
ap-6763	15	19	values	value	NOUN
ap-6763	15	20	.	.	PUNCT
ap-6763	16	1	they	they	PRON
ap-6763	16	2	proposed	propose	VERB
ap-6763	16	3	whole	whole	ADJ
ap-6763	16	4	data	datum	NOUN
ap-6763	16	5	strategy	strategy	NOUN
ap-6763	16	6	fuzzy	fuzzy	ADJ
ap-6763	16	7	c	c	NOUN
ap-6763	16	8	-	-	PUNCT
ap-6763	16	9	means	means	NOUN
ap-6763	16	10	(	(	PUNCT
ap-6763	16	11	wdsfcm	wdsfcm	PROPN
ap-6763	16	12	)	)	PUNCT
ap-6763	16	13	to	to	PART
ap-6763	16	14	deal	deal	VERB
ap-6763	16	15	with	with	ADP
ap-6763	16	16	the	the	DET
ap-6763	16	17	problems	problem	NOUN
ap-6763	16	18	associated	associate	VERB
ap-6763	16	19	with	with	ADP
ap-6763	16	20	the	the	DET
ap-6763	16	21	incomplete	incomplete	ADJ
ap-6763	16	22	data	datum	NOUN
ap-6763	16	23	set	set	VERB
ap-6763	16	24	clustering	cluster	VERB
ap-6763	16	25	by	by	ADP
ap-6763	16	26	removing	remove	VERB
ap-6763	16	27	features	feature	NOUN
ap-6763	16	28	that	that	PRON
ap-6763	16	29	contain	contain	VERB
ap-6763	16	30	missing	missing	ADJ
ap-6763	16	31	values	value	NOUN
ap-6763	16	32	and	and	CCONJ
ap-6763	16	33	running	run	VERB
ap-6763	16	34	standard	standard	NOUN
ap-6763	16	35	fcm	fcm	X
ap-6763	16	36	algorithms	algorithm	NOUN
ap-6763	16	37	,	,	PUNCT
ap-6763	16	38	thereby	thereby	ADV
ap-6763	16	39	making	make	VERB
ap-6763	16	40	the	the	DET
ap-6763	16	41	remaining	remain	VERB
ap-6763	16	42	data	datum	NOUN
ap-6763	16	43	complete	complete	ADJ
ap-6763	16	44	.	.	PUNCT
ap-6763	17	1	however	however	ADV
ap-6763	17	2	,	,	PUNCT
ap-6763	17	3	the	the	DET
ap-6763	17	4	wdsfcm	wdsfcm	NOUN
ap-6763	17	5	produces	produce	VERB
ap-6763	17	6	biased	biased	ADJ
ap-6763	17	7	clustering	clustering	NOUN
ap-6763	17	8	results	result	NOUN
ap-6763	17	9	when	when	SCONJ
ap-6763	17	10	the	the	DET
ap-6763	17	11	missing	miss	VERB
ap-6763	17	12	values	value	NOUN
ap-6763	17	13	are	be	AUX
ap-6763	17	14	large	large	ADJ
ap-6763	17	15	.	.	PUNCT
ap-6763	18	1	dixon	dixon	PROPN
ap-6763	19	1	[	[	X
ap-6763	19	2	5	5	NUM
ap-6763	19	3	]	]	PUNCT
ap-6763	19	4	proposed	propose	VERB
ap-6763	19	5	the	the	DET
ap-6763	19	6	partial	partial	ADJ
ap-6763	19	7	distance	distance	NOUN
ap-6763	19	8	strategy	strategy	NOUN
ap-6763	19	9	(	(	PUNCT
ap-6763	19	10	pds	pds	NOUN
ap-6763	19	11	)	)	PUNCT
ap-6763	19	12	algorithm	algorithm	NOUN
ap-6763	19	13	to	to	PART
ap-6763	19	14	deal	deal	VERB
ap-6763	19	15	with	with	ADP
ap-6763	19	16	incomplete	incomplete	ADJ
ap-6763	19	17	clustering	clustering	ADJ
ap-6763	19	18	data	data	NOUN
ap-6763	19	19	sets	set	NOUN
ap-6763	19	20	by	by	ADP
ap-6763	19	21	calculating	calculate	VERB
ap-6763	19	22	a	a	DET
ap-6763	19	23	partial	partial	ADJ
ap-6763	19	24	distance	distance	NOUN
ap-6763	19	25	(	(	PUNCT
ap-6763	19	26	squared	squared	ADJ
ap-6763	19	27	euclidean	euclidean	NOUN
ap-6763	19	28	)	)	PUNCT
ap-6763	19	29	.	.	PUNCT
ap-6763	20	1	the	the	DET
ap-6763	20	2	available	available	ADJ
ap-6763	20	3	data	data	NOUN
ap-6763	20	4	points	point	NOUN
ap-6763	20	5	were	be	AUX
ap-6763	20	6	used	use	VERB
ap-6763	20	7	to	to	PART
ap-6763	20	8	determine	determine	VERB
ap-6763	20	9	the	the	DET
ap-6763	20	10	missing	miss	VERB
ap-6763	20	11	values	value	NOUN
ap-6763	20	12	with	with	ADP
ap-6763	20	13	the	the	DET
ap-6763	20	14	quantity	quantity	NOUN
ap-6763	20	15	scaled	scale	VERB
ap-6763	20	16	using	use	VERB
ap-6763	20	17	the	the	DET
ap-6763	20	18	reciprocal	reciprocal	NOUN
ap-6763	20	19	of	of	ADP
ap-6763	20	20	the	the	DET
ap-6763	20	21	component	component	NOUN
ap-6763	20	22	proportion	proportion	NOUN
ap-6763	20	23	.	.	PUNCT
ap-6763	21	1	bezdek	bezdek	PROPN
ap-6763	21	2	and	and	CCONJ
ap-6763	21	3	hathaway	hathaway	PROPN
ap-6763	22	1	[	[	X
ap-6763	22	2	4	4	X
ap-6763	22	3	]	]	PUNCT
ap-6763	22	4	modified	modify	VERB
ap-6763	22	5	the	the	DET
ap-6763	22	6	fcm	fcm	X
ap-6763	22	7	using	use	VERB
ap-6763	22	8	the	the	DET
ap-6763	22	9	pds	pds	NOUN
ap-6763	22	10	in	in	ADP
ap-6763	22	11	order	order	NOUN
ap-6763	22	12	to	to	PART
ap-6763	22	13	deal	deal	VERB
ap-6763	22	14	with	with	ADP
ap-6763	22	15	the	the	DET
ap-6763	22	16	problems	problem	NOUN
ap-6763	22	17	associated	associate	VERB
ap-6763	22	18	with	with	ADP
ap-6763	22	19	clustering	clustering	ADJ
ap-6763	22	20	incomplete	incomplete	ADJ
ap-6763	22	21	data	datum	NOUN
ap-6763	22	22	sets	set	NOUN
ap-6763	22	23	known	know	VERB
ap-6763	22	24	as	as	ADP
ap-6763	22	25	the	the	DET
ap-6763	22	26	pdsfcm	pdsfcm	PROPN
ap-6763	22	27	algorithm	algorithm	PROPN
ap-6763	22	28	.	.	PUNCT
ap-6763	23	1	the	the	DET
ap-6763	23	2	wdsfcm	wdsfcm	NOUN
ap-6763	23	3	and	and	CCONJ
ap-6763	23	4	pdsfcm	pdsfcm	VERB
ap-6763	23	5	algorithms	algorithm	NOUN
ap-6763	23	6	do	do	AUX
ap-6763	23	7	not	not	PART
ap-6763	23	8	impute	impute	VERB
ap-6763	23	9	missing	missing	ADJ
ap-6763	23	10	values	value	NOUN
ap-6763	23	11	,	,	PUNCT
ap-6763	23	12	therefore	therefore	ADV
ap-6763	23	13	they	they	PRON
ap-6763	23	14	are	be	AUX
ap-6763	23	15	unable	unable	ADJ
ap-6763	23	16	to	to	PART
ap-6763	23	17	ascertain	ascertain	VERB
ap-6763	23	18	the	the	DET
ap-6763	23	19	missing	miss	VERB
ap-6763	23	20	values	value	NOUN
ap-6763	23	21	after	after	ADP
ap-6763	23	22	the	the	DET
ap-6763	23	23	clustering	clustering	ADJ
ap-6763	23	24	process	process	NOUN
ap-6763	23	25	.	.	PUNCT
ap-6763	24	1	the	the	DET
ap-6763	24	2	following	following	ADJ
ap-6763	24	3	algorithms	algorithm	NOUN
ap-6763	24	4	,	,	PUNCT
ap-6763	24	5	proposed	propose	VERB
ap-6763	24	6	by	by	ADP
ap-6763	24	7	bezdek	bezdek	PROPN
ap-6763	24	8	and	and	CCONJ
ap-6763	24	9	hathaway	hathaway	PROPN
ap-6763	24	10	[	[	X
ap-6763	24	11	4	4	NUM
ap-6763	24	12	]	]	PUNCT
ap-6763	24	13	imputed	impute	VERB
ap-6763	24	14	missing	missing	ADJ
ap-6763	24	15	values	value	NOUN
ap-6763	24	16	.	.	PUNCT
ap-6763	25	1	furthermore	furthermore	ADV
ap-6763	25	2	,	,	PUNCT
ap-6763	25	3	they	they	PRON
ap-6763	25	4	modified	modify	VERB
ap-6763	25	5	the	the	DET
ap-6763	25	6	fcm	fcm	PROPN
ap-6763	25	7	algorithm	algorithm	NOUN
ap-6763	25	8	using	use	VERB
ap-6763	25	9	the	the	DET
ap-6763	25	10	optimal	optimal	ADJ
ap-6763	25	11	completion	completion	NOUN
ap-6763	25	12	strategy	strategy	NOUN
ap-6763	25	13	(	(	PUNCT
ap-6763	25	14	ocs	ocs	PROPN
ap-6763	25	15	)	)	PUNCT
ap-6763	25	16	and	and	CCONJ
ap-6763	25	17	the	the	DET
ap-6763	25	18	nearest	near	ADJ
ap-6763	25	19	prototype	prototype	NOUN
ap-6763	25	20	strategy	strategy	NOUN
ap-6763	25	21	(	(	PUNCT
ap-6763	25	22	nps	nps	PROPN
ap-6763	25	23	)	)	PUNCT
ap-6763	25	24	,	,	PUNCT
ap-6763	25	25	each	each	PRON
ap-6763	25	26	of	of	ADP
ap-6763	25	27	which	which	PRON
ap-6763	25	28	is	be	AUX
ap-6763	25	29	referred	refer	VERB
ap-6763	25	30	to	to	ADP
ap-6763	25	31	as	as	ADP
ap-6763	25	32	the	the	DET
ap-6763	25	33	ocsfcm	ocsfcm	NOUN
ap-6763	25	34	and	and	CCONJ
ap-6763	25	35	npsfcm	npsfcm	PROPN
ap-6763	25	36	algorithms	algorithm	NOUN
ap-6763	25	37	.	.	PUNCT
ap-6763	26	1	the	the	DET
ap-6763	26	2	ocsfcm	ocsfcm	PROPN
ap-6763	26	3	algorithm	algorithm	NOUN
ap-6763	26	4	estimates	estimate	VERB
ap-6763	26	5	missing	miss	VERB
ap-6763	26	6	values	value	NOUN
ap-6763	26	7	by	by	ADP
ap-6763	26	8	considering	consider	VERB
ap-6763	26	9	missing	miss	VERB
ap-6763	26	10	values	value	NOUN
ap-6763	26	11	as	as	ADP
ap-6763	26	12	an	an	DET
ap-6763	26	13	additional	additional	ADJ
ap-6763	26	14	variable	variable	NOUN
ap-6763	26	15	and	and	CCONJ
ap-6763	26	16	partitioning	partition	VERB
ap-6763	26	17	the	the	DET
ap-6763	26	18	data	datum	NOUN
ap-6763	26	19	while	while	SCONJ
ap-6763	26	20	optimizing	optimize	VERB
ap-6763	26	21	the	the	DET
ap-6763	26	22	value	value	NOUN
ap-6763	26	23	of	of	ADP
ap-6763	26	24	the	the	DET
ap-6763	26	25	fcm	fcm	X
ap-6763	26	26	objective	objective	ADJ
ap-6763	26	27	function	function	NOUN
ap-6763	26	28	.	.	PUNCT
ap-6763	27	1	the	the	DET
ap-6763	27	2	npsfcm	npsfcm	PROPN
ap-6763	27	3	algorithm	algorithm	NOUN
ap-6763	27	4	estimates	estimate	NOUN
ap-6763	27	5	missing	miss	VERB
ap-6763	27	6	values	value	NOUN
ap-6763	27	7	using	use	VERB
ap-6763	27	8	the	the	DET
ap-6763	27	9	closest	close	ADJ
ap-6763	27	10	prototype	prototype	NOUN
ap-6763	27	11	cluster	cluster	NOUN
ap-6763	27	12	in	in	ADP
ap-6763	27	13	each	each	DET
ap-6763	27	14	iteration	iteration	NOUN
ap-6763	27	15	step	step	NOUN
ap-6763	27	16	.	.	PUNCT
ap-6763	28	1	therefore	therefore	ADV
ap-6763	28	2	,	,	PUNCT
ap-6763	28	3	the	the	DET
ap-6763	28	4	difference	difference	NOUN
ap-6763	28	5	between	between	ADP
ap-6763	28	6	the	the	DET
ap-6763	28	7	ocsfcm	ocsfcm	NOUN
ap-6763	28	8	and	and	CCONJ
ap-6763	28	9	the	the	DET
ap-6763	28	10	npsfcm	npsfcm	NOUN
ap-6763	28	11	algorithms	algorithm	VERB
ap-6763	28	12	lies	lie	VERB
ap-6763	28	13	in	in	ADP
ap-6763	28	14	the	the	DET
ap-6763	28	15	technique	technique	NOUN
ap-6763	28	16	used	use	VERB
ap-6763	28	17	to	to	PART
ap-6763	28	18	update	update	VERB
ap-6763	28	19	the	the	DET
ap-6763	28	20	imputation	imputation	NOUN
ap-6763	28	21	for	for	ADP
ap-6763	28	22	missing	miss	VERB
ap-6763	28	23	values	value	NOUN
ap-6763	28	24	at	at	ADP
ap-6763	28	25	each	each	DET
ap-6763	28	26	iteration	iteration	NOUN
ap-6763	28	27	step	step	NOUN
ap-6763	28	28	.	.	PUNCT
ap-6763	29	1	in	in	ADP
ap-6763	29	2	another	another	DET
ap-6763	29	3	research	research	NOUN
ap-6763	29	4	,	,	PUNCT
ap-6763	29	5	bezdek	bezdek	PROPN
ap-6763	29	6	et	et	PROPN
ap-6763	29	7	al	al	PROPN
ap-6763	29	8	.	.	PUNCT
ap-6763	30	1	[	[	X
ap-6763	30	2	6	6	NUM
ap-6763	30	3	]	]	PUNCT
ap-6763	30	4	introduced	introduce	VERB
ap-6763	30	5	the	the	DET
ap-6763	30	6	possibilistic	possibilistic	ADJ
ap-6763	30	7	fuzzy	fuzzy	ADJ
ap-6763	30	8	c	c	NOUN
ap-6763	30	9	-	-	PUNCT
ap-6763	30	10	means	means	NOUN
ap-6763	30	11	(	(	PUNCT
ap-6763	30	12	pfcm	pfcm	VERB
ap-6763	30	13	)	)	PUNCT
ap-6763	30	14	algorithm	algorithm	NOUN
ap-6763	30	15	,	,	PUNCT
ap-6763	30	16	which	which	PRON
ap-6763	30	17	corrects	correct	VERB
ap-6763	30	18	the	the	DET
ap-6763	30	19	shortcomings	shortcoming	NOUN
ap-6763	30	20	of	of	ADP
ap-6763	30	21	the	the	DET
ap-6763	30	22	fcm	fcm	X
ap-6763	30	23	and	and	CCONJ
ap-6763	30	24	pcm	pcm	NOUN
ap-6763	30	25	by	by	ADP
ap-6763	30	26	overcoming	overcome	VERB
ap-6763	30	27	noise	noise	NOUN
ap-6763	30	28	sensitivity	sensitivity	NOUN
ap-6763	30	29	and	and	CCONJ
ap-6763	30	30	the	the	DET
ap-6763	30	31	occurrence	occurrence	NOUN
ap-6763	30	32	of	of	ADP
ap-6763	30	33	coincidental	coincidental	ADJ
ap-6763	30	34	clusters	cluster	NOUN
ap-6763	30	35	.	.	PUNCT
ap-6763	31	1	however	however	ADV
ap-6763	31	2	,	,	PUNCT
ap-6763	31	3	there	there	PRON
ap-6763	31	4	are	be	VERB
ap-6763	31	5	some	some	DET
ap-6763	31	6	disadvantages	disadvantage	NOUN
ap-6763	31	7	associated	associate	VERB
ap-6763	31	8	with	with	ADP
ap-6763	31	9	the	the	DET
ap-6763	31	10	pfcm	pfcm	PROPN
ap-6763	31	11	algorithm	algorithm	NOUN
ap-6763	31	12	,	,	PUNCT
ap-6763	31	13	it	it	PRON
ap-6763	31	14	can	can	AUX
ap-6763	31	15	be	be	AUX
ap-6763	31	16	used	use	VERB
ap-6763	31	17	only	only	ADV
ap-6763	31	18	for	for	ADP
ap-6763	31	19	clustering	cluster	VERB
ap-6763	31	20	complete	complete	ADJ
ap-6763	31	21	data	datum	NOUN
ap-6763	31	22	sets	set	NOUN
ap-6763	31	23	.	.	PUNCT
ap-6763	32	1	in	in	ADP
ap-6763	32	2	addition	addition	NOUN
ap-6763	32	3	,	,	PUNCT
ap-6763	32	4	some	some	DET
ap-6763	32	5	recent	recent	ADJ
ap-6763	32	6	studies	study	NOUN
ap-6763	32	7	proposed	propose	VERB
ap-6763	32	8	clustering	cluster	VERB
ap-6763	32	9	364	364	NUM
ap-6763	32	10	https://doi.org/10.14311/ap.2021.61.0364	https://doi.org/10.14311/ap.2021.61.0364	NOUN
ap-6763	32	11	https://creativecommons.org/licenses/by/4.0/	https://creativecommons.org/licenses/by/4.0/	PROPN
ap-6763	32	12	https://www.cvut.cz/en	https://www.cvut.cz/en	NUM
ap-6763	32	13	vol	vol	NOUN
ap-6763	32	14	.	.	PROPN
ap-6763	33	1	61	61	NUM
ap-6763	33	2	no	no	NOUN
ap-6763	33	3	.	.	PUNCT
ap-6763	34	1	2/2021	2/2021	NUM
ap-6763	34	2	modified	modify	VERB
ap-6763	34	3	possibilistic	possibilistic	ADJ
ap-6763	34	4	fuzzy	fuzzy	ADJ
ap-6763	34	5	c	c	NOUN
ap-6763	34	6	-	-	PUNCT
ap-6763	34	7	means	mean	VERB
ap-6763	34	8	algorithm	algorithm	NOUN
ap-6763	34	9	algorithms	algorithm	NOUN
ap-6763	34	10	only	only	ADV
ap-6763	34	11	for	for	ADP
ap-6763	34	12	complete	complete	ADJ
ap-6763	34	13	data	data	NOUN
ap-6763	34	14	sets	set	NOUN
ap-6763	34	15	,	,	PUNCT
ap-6763	34	16	including	include	VERB
ap-6763	34	17	[	[	X
ap-6763	34	18	7	7	NUM
ap-6763	34	19	–	–	PUNCT
ap-6763	34	20	12	12	NUM
ap-6763	34	21	]	]	PUNCT
ap-6763	34	22	.	.	PUNCT
ap-6763	35	1	this	this	DET
ap-6763	35	2	research	research	NOUN
ap-6763	35	3	describes	describe	VERB
ap-6763	35	4	the	the	DET
ap-6763	35	5	pfcm	pfcm	PROPN
ap-6763	35	6	algorithm	algorithm	NOUN
ap-6763	35	7	for	for	ADP
ap-6763	35	8	clustering	cluster	VERB
ap-6763	35	9	complete	complete	ADJ
ap-6763	35	10	data	datum	NOUN
ap-6763	35	11	sets	set	NOUN
ap-6763	35	12	in	in	ADP
ap-6763	35	13	section	section	NOUN
ap-6763	35	14	2	2	NUM
ap-6763	35	15	.	.	PUNCT
ap-6763	35	16	section	section	NOUN
ap-6763	35	17	3	3	NUM
ap-6763	35	18	explains	explain	VERB
ap-6763	35	19	the	the	DET
ap-6763	35	20	pfcm	pfcm	PROPN
ap-6763	35	21	algorithm	algorithm	NOUN
ap-6763	35	22	for	for	ADP
ap-6763	35	23	clustering	cluster	VERB
ap-6763	35	24	incomplete	incomplete	ADJ
ap-6763	35	25	data	datum	NOUN
ap-6763	35	26	sets	set	NOUN
ap-6763	35	27	,	,	PUNCT
ap-6763	35	28	while	while	SCONJ
ap-6763	35	29	section	section	NOUN
ap-6763	35	30	4	4	NUM
ap-6763	35	31	describes	describe	VERB
ap-6763	35	32	the	the	DET
ap-6763	35	33	experimental	experimental	ADJ
ap-6763	35	34	setup	setup	NOUN
ap-6763	35	35	.	.	PUNCT
ap-6763	36	1	in	in	ADP
ap-6763	36	2	section	section	NOUN
ap-6763	36	3	5	5	NUM
ap-6763	36	4	,	,	PUNCT
ap-6763	36	5	the	the	DET
ap-6763	36	6	experimental	experimental	ADJ
ap-6763	36	7	results	result	NOUN
ap-6763	36	8	of	of	ADP
ap-6763	36	9	the	the	DET
ap-6763	36	10	real	real	ADJ
ap-6763	36	11	world	world	NOUN
ap-6763	36	12	and	and	CCONJ
ap-6763	36	13	artificial	artificial	ADJ
ap-6763	36	14	data	datum	NOUN
ap-6763	36	15	sets	set	NOUN
ap-6763	36	16	are	be	AUX
ap-6763	36	17	shown	show	VERB
ap-6763	36	18	with	with	ADP
ap-6763	36	19	the	the	DET
ap-6763	36	20	results	result	NOUN
ap-6763	36	21	analysed	analyse	VERB
ap-6763	36	22	.	.	PUNCT
ap-6763	37	1	finally	finally	ADV
ap-6763	37	2	,	,	PUNCT
ap-6763	37	3	section	section	NOUN
ap-6763	37	4	6	6	NUM
ap-6763	37	5	concludes	conclude	VERB
ap-6763	37	6	the	the	DET
ap-6763	37	7	research	research	NOUN
ap-6763	37	8	.	.	PUNCT
ap-6763	38	1	2	2	X
ap-6763	38	2	.	.	X
ap-6763	38	3	possibilistic	possibilistic	ADJ
ap-6763	38	4	fuzzy	fuzzy	ADJ
ap-6763	38	5	c	c	NOUN
ap-6763	38	6	-	-	PUNCT
ap-6763	38	7	means	means	NOUN
ap-6763	38	8	(	(	PUNCT
ap-6763	38	9	pfcm	pfcm	PROPN
ap-6763	38	10	)	)	PUNCT
ap-6763	38	11	algorithm	algorithm	NOUN
ap-6763	38	12	of	of	ADP
ap-6763	38	13	complete	complete	ADJ
ap-6763	38	14	data	datum	NOUN
ap-6763	38	15	sets	set	NOUN
ap-6763	38	16	suppose	suppose	VERB
ap-6763	38	17	unlabeled	unlabeled	ADJ
ap-6763	38	18	data	datum	NOUN
ap-6763	38	19	sets	set	VERB
ap-6763	38	20	x	x	PUNCT
ap-6763	38	21	=	=	SYM
ap-6763	38	22	{	{	PUNCT
ap-6763	38	23	x1,x2	x1,x2	PROPN
ap-6763	38	24	,	,	PUNCT
ap-6763	38	25	·	·	PUNCT
ap-6763	38	26	·	·	PUNCT
ap-6763	38	27	·	·	PUNCT
ap-6763	38	28	,	,	PUNCT
ap-6763	38	29	xn	xn	X
ap-6763	38	30	}	}	PUNCT
ap-6763	38	31	⊂	⊂	PROPN
ap-6763	38	32	rd	rd	PROPN
ap-6763	38	33	clustered	cluster	VERB
ap-6763	38	34	into	into	ADP
ap-6763	38	35	a	a	DET
ap-6763	38	36	fuzzy	fuzzy	ADJ
ap-6763	38	37	subset	subset	NOUN
ap-6763	38	38	of	of	ADP
ap-6763	38	39	c	c	PROPN
ap-6763	38	40	(	(	PUNCT
ap-6763	38	41	1	1	NUM
ap-6763	38	42	<	<	X
ap-6763	38	43	c	c	X
ap-6763	38	44	<	<	X
ap-6763	38	45	n	n	CCONJ
ap-6763	38	46	)	)	PUNCT
ap-6763	38	47	clusters	cluster	NOUN
ap-6763	38	48	.	.	PUNCT
ap-6763	39	1	here	here	ADV
ap-6763	39	2	,	,	PUNCT
ap-6763	39	3	n	n	PROPN
ap-6763	39	4	and	and	CCONJ
ap-6763	39	5	d	d	ADP
ap-6763	39	6	state	state	NOUN
ap-6763	39	7	the	the	DET
ap-6763	39	8	number	number	NOUN
ap-6763	39	9	and	and	CCONJ
ap-6763	39	10	dimension	dimension	NOUN
ap-6763	39	11	of	of	ADP
ap-6763	39	12	each	each	DET
ap-6763	39	13	data	datum	NOUN
ap-6763	39	14	point	point	NOUN
ap-6763	39	15	,	,	PUNCT
ap-6763	39	16	respectively	respectively	ADV
ap-6763	39	17	.	.	PUNCT
ap-6763	40	1	the	the	DET
ap-6763	40	2	x	x	PUNCT
ap-6763	40	3	is	be	AUX
ap-6763	40	4	clustered	cluster	VERB
ap-6763	40	5	into	into	ADP
ap-6763	40	6	c	c	NOUN
ap-6763	40	7	by	by	ADP
ap-6763	40	8	minimizing	minimize	VERB
ap-6763	40	9	the	the	DET
ap-6763	40	10	following	follow	VERB
ap-6763	40	11	objective	objective	ADJ
ap-6763	40	12	function	function	NOUN
ap-6763	40	13	[	[	X
ap-6763	40	14	6	6	NUM
ap-6763	40	15	]	]	PUNCT
ap-6763	40	16	.	.	PUNCT
ap-6763	41	1	jm	jm	PROPN
ap-6763	41	2	,	,	PUNCT
ap-6763	41	3	τ	τ	PROPN
ap-6763	41	4	(	(	PUNCT
ap-6763	41	5	u	u	PROPN
ap-6763	41	6	,	,	PUNCT
ap-6763	41	7	t	t	PROPN
ap-6763	41	8	,	,	PUNCT
ap-6763	41	9	v	v	NOUN
ap-6763	41	10	;	;	PUNCT
ap-6763	41	11	x	x	X
ap-6763	41	12	)	)	PUNCT
ap-6763	41	13	=	=	SYM
ap-6763	42	1	n∑	n∑	NOUN
ap-6763	42	2	k=1	k=1	X
ap-6763	43	1	c∑	c∑	NOUN
ap-6763	43	2	i=1	i=1	PROPN
ap-6763	44	1	(	(	PUNCT
ap-6763	44	2	αumik	αumik	ADJ
ap-6763	44	3	+	+	X
ap-6763	44	4	βtτik)d2	βtτik)d2	NOUN
ap-6763	44	5	ik	ik	PROPN
ap-6763	44	6	+	+	PROPN
ap-6763	45	1	c∑	c∑	X
ap-6763	45	2	i=1	i=1	X
ap-6763	45	3	δi	δi	X
ap-6763	46	1	n∑	n∑	INTJ
ap-6763	46	2	k=1	k=1	X
ap-6763	46	3	(	(	PUNCT
ap-6763	46	4	1−	1−	NUM
ap-6763	46	5	tik)τ	tik)τ	NOUN
ap-6763	46	6	.	.	PUNCT
ap-6763	47	1	(	(	PUNCT
ap-6763	47	2	1	1	X
ap-6763	47	3	)	)	PUNCT
ap-6763	47	4	here	here	ADV
ap-6763	47	5	,	,	PUNCT
ap-6763	47	6	α(α	α(α	PROPN
ap-6763	47	7	>	>	X
ap-6763	47	8	0	0	NUM
ap-6763	47	9	)	)	PUNCT
ap-6763	47	10	denotes	denote	VERB
ap-6763	47	11	the	the	DET
ap-6763	47	12	importance	importance	NOUN
ap-6763	47	13	level	level	NOUN
ap-6763	47	14	of	of	ADP
ap-6763	47	15	fuzzy	fuzzy	ADJ
ap-6763	47	16	membership	membership	NOUN
ap-6763	47	17	degree	degree	NOUN
ap-6763	47	18	(	(	PUNCT
ap-6763	47	19	uik	uik	NOUN
ap-6763	47	20	)	)	PUNCT
ap-6763	47	21	.	.	PUNCT
ap-6763	48	1	equation	equation	NOUN
ap-6763	48	2	(	(	PUNCT
ap-6763	48	3	1	1	X
ap-6763	48	4	)	)	PUNCT
ap-6763	48	5	is	be	AUX
ap-6763	48	6	subject	subject	ADJ
ap-6763	48	7	to	to	ADP
ap-6763	48	8	∑c	∑c	PROPN
ap-6763	48	9	i=1	i=1	PROPN
ap-6763	48	10	uik	uik	NOUN
ap-6763	48	11	=	=	NOUN
ap-6763	48	12	1	1	NUM
ap-6763	48	13	constraints	constraint	NOUN
ap-6763	48	14	.	.	PUNCT
ap-6763	49	1	krishnapuram	krishnapuram	PROPN
ap-6763	49	2	and	and	CCONJ
ap-6763	49	3	keller	keller	PROPN
ap-6763	50	1	[	[	X
ap-6763	50	2	3	3	NUM
ap-6763	50	3	]	]	PUNCT
ap-6763	50	4	relaxed	relax	VERB
ap-6763	50	5	this	this	DET
ap-6763	50	6	constrain	constrain	VERB
ap-6763	50	7	to	to	PART
ap-6763	50	8	become∑c	become∑c	VERB
ap-6763	50	9	i=1	i=1	PROPN
ap-6763	50	10	uik	uik	PROPN
ap-6763	50	11	≥	≥	PROPN
ap-6763	50	12	1	1	NUM
ap-6763	50	13	,	,	PUNCT
ap-6763	50	14	therefore	therefore	ADV
ap-6763	50	15	,	,	PUNCT
ap-6763	50	16	it	it	PRON
ap-6763	50	17	is	be	AUX
ap-6763	50	18	better	well	ADJ
ap-6763	50	19	in	in	ADP
ap-6763	50	20	reflecting	reflect	VERB
ap-6763	50	21	clusters	cluster	NOUN
ap-6763	50	22	xk	xk	PROPN
ap-6763	50	23	to	to	ADP
ap-6763	50	24	the	the	DET
ap-6763	50	25	i	i	PROPN
ap-6763	50	26	-	-	PUNCT
ap-6763	50	27	th	th	PROPN
ap-6763	50	28	.	.	PUNCT
ap-6763	51	1	tik	tik	PROPN
ap-6763	51	2	denotes	denote	NOUN
ap-6763	51	3	a	a	DET
ap-6763	51	4	possibilistic	possibilistic	ADJ
ap-6763	51	5	membership	membership	NOUN
ap-6763	51	6	degree	degree	NOUN
ap-6763	51	7	of	of	ADP
ap-6763	51	8	xk	xk	PROPN
ap-6763	51	9	to	to	ADP
ap-6763	51	10	the	the	DET
ap-6763	51	11	i	i	PROPN
ap-6763	51	12	-	-	PUNCT
ap-6763	51	13	th	th	VERB
ap-6763	51	14	cluster	cluster	NOUN
ap-6763	51	15	and	and	CCONJ
ap-6763	51	16	β(β	β(β	X
ap-6763	51	17	>	>	X
ap-6763	51	18	0	0	X
ap-6763	51	19	)	)	PUNCT
ap-6763	51	20	denotes	denote	VERB
ap-6763	51	21	the	the	DET
ap-6763	51	22	importance	importance	NOUN
ap-6763	51	23	level	level	NOUN
ap-6763	51	24	of	of	ADP
ap-6763	51	25	tik	tik	PROPN
ap-6763	51	26	.	.	PUNCT
ap-6763	52	1	d2	d2	PROPN
ap-6763	52	2	ik	ik	X
ap-6763	52	3	=	=	SYM
ap-6763	52	4	‖xk	‖xk	NUM
ap-6763	52	5	−	−	PROPN
ap-6763	52	6	vi‖2	vi‖2	PROPN
ap-6763	52	7	denotes	denote	VERB
ap-6763	52	8	the	the	DET
ap-6763	52	9	euclidean	euclidean	ADJ
ap-6763	52	10	distance	distance	NOUN
ap-6763	52	11	of	of	ADP
ap-6763	52	12	the	the	DET
ap-6763	52	13	j	j	PROPN
ap-6763	52	14	-	-	PUNCT
ap-6763	52	15	th	th	VERB
ap-6763	52	16	data	datum	NOUN
ap-6763	52	17	point	point	NOUN
ap-6763	52	18	to	to	ADP
ap-6763	52	19	i	i	PRON
ap-6763	52	20	-	-	PUNCT
ap-6763	52	21	th	th	PROPN
ap-6763	52	22	cluster	cluster	NOUN
ap-6763	52	23	centre	centre	NOUN
ap-6763	52	24	.	.	PUNCT
ap-6763	53	1	v	v	X
ap-6763	53	2	=	=	SYM
ap-6763	53	3	{	{	PUNCT
ap-6763	53	4	v1,v2	v1,v2	PROPN
ap-6763	53	5	,	,	PUNCT
ap-6763	53	6	·	·	PUNCT
ap-6763	53	7	·	·	PUNCT
ap-6763	53	8	·	·	PUNCT
ap-6763	53	9	,	,	PUNCT
ap-6763	53	10	vc	vc	PART
ap-6763	53	11	}	}	PUNCT
ap-6763	53	12	denotes	denote	VERB
ap-6763	53	13	the	the	DET
ap-6763	53	14	centre	centre	NOUN
ap-6763	53	15	of	of	ADP
ap-6763	53	16	the	the	DET
ap-6763	53	17	cluster	cluster	NOUN
ap-6763	53	18	set	set	NOUN
ap-6763	53	19	,	,	PUNCT
ap-6763	53	20	where	where	SCONJ
ap-6763	53	21	vi	vi	PROPN
ap-6763	53	22	∈	∈	PROPN
ap-6763	53	23	rd	rd	PROPN
ap-6763	53	24	and	and	CCONJ
ap-6763	53	25	δi	δi	VERB
ap-6763	53	26	>	>	PRON
ap-6763	53	27	0	0	NUM
ap-6763	53	28	is	be	AUX
ap-6763	53	29	the	the	DET
ap-6763	53	30	typical	typical	ADJ
ap-6763	53	31	of	of	ADP
ap-6763	53	32	possibilistic	possibilistic	NOUN
ap-6763	53	33	.	.	PUNCT
ap-6763	54	1	where	where	SCONJ
ap-6763	54	2	m	m	VERB
ap-6763	54	3	>	>	X
ap-6763	54	4	1	1	NUM
ap-6763	54	5	and	and	CCONJ
ap-6763	54	6	τ	τ	PROPN
ap-6763	54	7	>	>	X
ap-6763	54	8	1	1	NUM
ap-6763	54	9	are	be	AUX
ap-6763	54	10	fuzzy	fuzzy	ADJ
ap-6763	54	11	parameter	parameter	NOUN
ap-6763	54	12	and	and	CCONJ
ap-6763	54	13	possibilistic	possibilistic	ADJ
ap-6763	54	14	parameter	parameter	NOUN
ap-6763	54	15	,	,	PUNCT
ap-6763	54	16	respectively	respectively	ADV
ap-6763	54	17	.	.	PUNCT
ap-6763	55	1	basically	basically	ADV
ap-6763	55	2	,	,	PUNCT
ap-6763	55	3	uik	uik	NOUN
ap-6763	55	4	,	,	PUNCT
ap-6763	55	5	tik	tik	PROPN
ap-6763	55	6	,	,	PUNCT
ap-6763	55	7	and	and	CCONJ
ap-6763	55	8	vi	vi	NOUN
ap-6763	55	9	are	be	AUX
ap-6763	55	10	determined	determine	VERB
ap-6763	55	11	simultaneously	simultaneously	ADV
ap-6763	55	12	.	.	PUNCT
ap-6763	56	1	however	however	ADV
ap-6763	56	2	,	,	PUNCT
ap-6763	56	3	in	in	ADP
ap-6763	56	4	this	this	DET
ap-6763	56	5	research	research	NOUN
ap-6763	56	6	,	,	PUNCT
ap-6763	56	7	these	these	DET
ap-6763	56	8	values	value	NOUN
ap-6763	56	9	were	be	AUX
ap-6763	56	10	determined	determine	VERB
ap-6763	56	11	numerically	numerically	ADV
ap-6763	56	12	using	use	VERB
ap-6763	56	13	the	the	DET
ap-6763	56	14	recursive	recursive	ADJ
ap-6763	56	15	method	method	NOUN
ap-6763	56	16	.	.	PUNCT
ap-6763	57	1	therefore	therefore	ADV
ap-6763	57	2	,	,	PUNCT
ap-6763	57	3	the	the	DET
ap-6763	57	4	initially	initially	ADV
ap-6763	57	5	values	value	NOUN
ap-6763	57	6	to	to	PART
ap-6763	57	7	be	be	AUX
ap-6763	57	8	calculated	calculate	VERB
ap-6763	57	9	are	be	AUX
ap-6763	57	10	chosen	choose	VERB
ap-6763	57	11	as	as	SCONJ
ap-6763	57	12	follows	follow	VERB
ap-6763	57	13	:	:	PUNCT
ap-6763	57	14	initiate	initiate	VERB
ap-6763	57	15	vi	vi	PROPN
ap-6763	57	16	to	to	PART
ap-6763	57	17	calculate	calculate	VERB
ap-6763	57	18	uik	uik	NOUN
ap-6763	57	19	and	and	CCONJ
ap-6763	57	20	tik	tik	PROPN
ap-6763	57	21	.	.	PROPN
ap-6763	57	22	2.1	2.1	NUM
ap-6763	57	23	.	.	PUNCT
ap-6763	58	1	possibilistic	possibilistic	ADJ
ap-6763	58	2	fuzzy	fuzzy	ADJ
ap-6763	58	3	c	c	NOUN
ap-6763	58	4	-	-	PUNCT
ap-6763	58	5	means	means	NOUN
ap-6763	58	6	(	(	PUNCT
ap-6763	58	7	pfcm	pfcm	PROPN
ap-6763	58	8	)	)	PUNCT
ap-6763	58	9	algorithm	algorithm	NOUN
ap-6763	58	10	in	in	ADP
ap-6763	58	11	this	this	DET
ap-6763	58	12	section	section	NOUN
ap-6763	58	13	,	,	PUNCT
ap-6763	58	14	the	the	DET
ap-6763	58	15	complete	complete	ADJ
ap-6763	58	16	data	data	NOUN
ap-6763	58	17	sets	set	NOUN
ap-6763	58	18	are	be	AUX
ap-6763	58	19	clustered	cluster	VERB
ap-6763	58	20	using	use	VERB
ap-6763	58	21	the	the	DET
ap-6763	58	22	possibilistic	possibilistic	ADJ
ap-6763	58	23	fuzzy	fuzzy	ADJ
ap-6763	58	24	c	c	NOUN
ap-6763	58	25	-	-	PUNCT
ap-6763	58	26	means	means	NOUN
ap-6763	58	27	(	(	PUNCT
ap-6763	58	28	pfcm	pfcm	PROPN
ap-6763	58	29	)	)	PUNCT
ap-6763	58	30	algorithm	algorithm	NOUN
ap-6763	59	1	[	[	X
ap-6763	59	2	6	6	NUM
ap-6763	59	3	]	]	PUNCT
ap-6763	59	4	.	.	PUNCT
ap-6763	60	1	the	the	DET
ap-6763	60	2	pfcm	pfcm	PROPN
ap-6763	60	3	algorithm	algorithm	NOUN
ap-6763	60	4	is	be	AUX
ap-6763	60	5	described	describe	VERB
ap-6763	60	6	as	as	ADP
ap-6763	60	7	follows	follow	VERB
ap-6763	60	8	.	.	PUNCT
ap-6763	61	1	step	step	NOUN
ap-6763	61	2	i	i	PRON
ap-6763	61	3	:	:	PUNCT
ap-6763	61	4	fix	fix	VERB
ap-6763	61	5	m	m	PRON
ap-6763	61	6	>	>	X
ap-6763	61	7	1	1	NUM
ap-6763	61	8	,	,	PUNCT
ap-6763	61	9	τ	τ	PROPN
ap-6763	61	10	>	>	X
ap-6763	61	11	1	1	NUM
ap-6763	61	12	,	,	PUNCT
ap-6763	61	13	ε	ε	PROPN
ap-6763	61	14	>	>	X
ap-6763	61	15	0	0	PUNCT
ap-6763	62	1	and	and	CCONJ
ap-6763	62	2	1	1	NUM
ap-6763	62	3	<	<	X
ap-6763	62	4	c	c	X
ap-6763	62	5	<	<	X
ap-6763	62	6	n.	n.	PROPN
ap-6763	62	7	pick	pick	PROPN
ap-6763	62	8	v(0	v(0	PROPN
ap-6763	62	9	)	)	PUNCT
ap-6763	62	10	∈	∈	PROPN
ap-6763	62	11	rd	rd	PROPN
ap-6763	62	12	,	,	PUNCT
ap-6763	62	13	v(0	v(0	PROPN
ap-6763	62	14	)	)	PUNCT
ap-6763	62	15	can	can	AUX
ap-6763	62	16	be	be	AUX
ap-6763	62	17	chosen	choose	VERB
ap-6763	62	18	randomly	randomly	ADV
ap-6763	62	19	from	from	ADP
ap-6763	62	20	x	x	X
ap-6763	62	21	=	=	PRON
ap-6763	62	22	{	{	PUNCT
ap-6763	62	23	x1,x2	x1,x2	PROPN
ap-6763	62	24	,	,	PUNCT
ap-6763	62	25	·	·	PUNCT
ap-6763	62	26	·	·	PUNCT
ap-6763	62	27	·	·	PUNCT
ap-6763	62	28	,	,	PUNCT
ap-6763	62	29	xn	xn	X
ap-6763	62	30	}	}	PUNCT
ap-6763	62	31	⊂	⊂	PROPN
ap-6763	62	32	rd	rd	PROPN
ap-6763	62	33	.	.	PUNCT
ap-6763	63	1	then	then	ADV
ap-6763	63	2	at	at	ADP
ap-6763	63	3	step	step	NOUN
ap-6763	63	4	l	l	NOUN
ap-6763	63	5	,	,	PUNCT
ap-6763	63	6	l	l	NOUN
ap-6763	63	7	=	=	SYM
ap-6763	63	8	1	1	NUM
ap-6763	63	9	,	,	PUNCT
ap-6763	63	10	2	2	NUM
ap-6763	63	11	,	,	PUNCT
ap-6763	63	12	·	·	PUNCT
ap-6763	63	13	·	·	PUNCT
ap-6763	63	14	·	·	PUNCT
ap-6763	63	15	step	step	NOUN
ap-6763	63	16	ii	ii	PROPN
ap-6763	63	17	:	:	PUNCT
ap-6763	63	18	calculate	calculate	VERB
ap-6763	63	19	fuzzy	fuzzy	ADJ
ap-6763	63	20	membership	membership	NOUN
ap-6763	63	21	degree	degree	NOUN
ap-6763	63	22	(	(	PUNCT
ap-6763	63	23	uik	uik	NOUN
ap-6763	63	24	)	)	PUNCT
ap-6763	63	25	which	which	PRON
ap-6763	63	26	minimize	minimize	VERB
ap-6763	63	27	the	the	DET
ap-6763	63	28	objective	objective	ADJ
ap-6763	63	29	function	function	NOUN
ap-6763	63	30	jm	jm	PROPN
ap-6763	63	31	,	,	PUNCT
ap-6763	63	32	τ	τ	PROPN
ap-6763	63	33	using	use	VERB
ap-6763	63	34	the	the	DET
ap-6763	63	35	following	follow	VERB
ap-6763	63	36	u	u	PROPN
ap-6763	63	37	(	(	PUNCT
ap-6763	63	38	l	l	NOUN
ap-6763	63	39	)	)	PUNCT
ap-6763	63	40	ik	ik	PROPN
ap-6763	63	41	=	=	SYM
ap-6763	63	42			PROPN
ap-6763	63	43	c∑	c∑	PRON
ap-6763	63	44	j=1	j=1	PROPN
ap-6763	63	45	(	(	PUNCT
ap-6763	63	46	d2	d2	PROPN
ap-6763	63	47	ik	ik	PROPN
ap-6763	63	48	d2	d2	PROPN
ap-6763	63	49	jk	jk	PROPN
ap-6763	63	50	)	)	PUNCT
ap-6763	63	51	1	1	NUM
ap-6763	64	1	m−1	m−1	PROPN
ap-6763	64	2	−1	−1	INTJ
ap-6763	64	3	,	,	PUNCT
ap-6763	64	4	(	(	PUNCT
ap-6763	64	5	2	2	X
ap-6763	64	6	)	)	PUNCT
ap-6763	64	7	where	where	SCONJ
ap-6763	64	8	d2	d2	PROPN
ap-6763	64	9	ik	ik	PROPN
ap-6763	64	10	=	=	SYM
ap-6763	64	11	∥∥∥xk	∥∥∥xk	PROPN
ap-6763	64	12	−	−	NOUN
ap-6763	64	13	v(l−1	v(l−1	NOUN
ap-6763	64	14	)	)	PUNCT
ap-6763	64	15	i	i	PRON
ap-6763	64	16	∥∥∥2	∥∥∥2	VERB
ap-6763	64	17	,	,	PUNCT
ap-6763	64	18	for	for	ADP
ap-6763	64	19	1	1	NUM
ap-6763	64	20	≤	≤	NUM
ap-6763	64	21	i	i	PRON
ap-6763	64	22	≤	≤	NOUN
ap-6763	64	23	c	c	NOUN
ap-6763	64	24	and	and	CCONJ
ap-6763	64	25	1	1	NUM
ap-6763	64	26	≤	≤	NUM
ap-6763	64	27	k	k	PROPN
ap-6763	64	28	≤	≤	PROPN
ap-6763	64	29	n.	n.	NOUN
ap-6763	64	30	step	step	PROPN
ap-6763	64	31	iii	iii	PROPN
ap-6763	64	32	:	:	PUNCT
ap-6763	64	33	calculate	calculate	VERB
ap-6763	64	34	the	the	DET
ap-6763	64	35	possibilistic	possibilistic	ADJ
ap-6763	64	36	typical	typical	ADJ
ap-6763	64	37	(	(	PUNCT
ap-6763	64	38	δi	δi	PROPN
ap-6763	64	39	)	)	PUNCT
ap-6763	64	40	,	,	PUNCT
ap-6763	64	41	which	which	PRON
ap-6763	64	42	minimizes	minimize	VERB
ap-6763	64	43	the	the	DET
ap-6763	64	44	objective	objective	ADJ
ap-6763	64	45	function	function	NOUN
ap-6763	64	46	jm	jm	PROPN
ap-6763	64	47	,	,	PUNCT
ap-6763	64	48	τ	τ	PROPN
ap-6763	64	49	using	use	VERB
ap-6763	64	50	the	the	DET
ap-6763	64	51	following	follow	VERB
ap-6763	64	52	δ	δ	PROPN
ap-6763	64	53	(	(	PUNCT
ap-6763	64	54	l	l	NOUN
ap-6763	64	55	)	)	PUNCT
ap-6763	64	56	i	i	PRON
ap-6763	64	57	=	=	PUNCT
ap-6763	65	1	k	k	X
ap-6763	65	2	∑n	∑n	NOUN
ap-6763	65	3	k=1	k=1	NOUN
ap-6763	66	1	(	(	PUNCT
ap-6763	66	2	u	u	X
ap-6763	66	3	(	(	PUNCT
ap-6763	66	4	l	l	NOUN
ap-6763	66	5	)	)	PUNCT
ap-6763	66	6	ik	ik	PROPN
ap-6763	66	7	)	)	PUNCT
ap-6763	66	8	m	m	PROPN
ap-6763	66	9	d2	d2	PROPN
ap-6763	66	10	ik∑n	ik∑n	NOUN
ap-6763	66	11	k=1	k=1	PROPN
ap-6763	67	1	(	(	PUNCT
ap-6763	67	2	u	u	X
ap-6763	67	3	(	(	PUNCT
ap-6763	67	4	l	l	NOUN
ap-6763	67	5	)	)	PUNCT
ap-6763	67	6	ik	ik	PROPN
ap-6763	67	7	)	)	PUNCT
ap-6763	67	8	m	m	VERB
ap-6763	67	9	,	,	PUNCT
ap-6763	67	10	(	(	PUNCT
ap-6763	67	11	3	3	X
ap-6763	67	12	)	)	PUNCT
ap-6763	67	13	where	where	SCONJ
ap-6763	67	14	d2	d2	PROPN
ap-6763	67	15	ik	ik	PROPN
ap-6763	67	16	=	=	SYM
ap-6763	67	17	∥∥∥xk	∥∥∥xk	PROPN
ap-6763	67	18	−	−	NOUN
ap-6763	67	19	v(l−1	v(l−1	NOUN
ap-6763	67	20	)	)	PUNCT
ap-6763	67	21	i	i	PRON
ap-6763	67	22	∥∥∥2	∥∥∥2	VERB
ap-6763	67	23	.	.	PUNCT
ap-6763	68	1	here	here	ADV
ap-6763	68	2	k	k	X
ap-6763	68	3	,	,	PUNCT
ap-6763	68	4	is	be	AUX
ap-6763	68	5	always	always	ADV
ap-6763	68	6	chosen	choose	VERB
ap-6763	68	7	to	to	PART
ap-6763	68	8	be	be	AUX
ap-6763	68	9	1	1	NUM
ap-6763	68	10	[	[	X
ap-6763	68	11	6	6	NUM
ap-6763	68	12	]	]	PUNCT
ap-6763	68	13	.	.	PUNCT
ap-6763	69	1	step	step	NOUN
ap-6763	69	2	iv	iv	NUM
ap-6763	69	3	:	:	PUNCT
ap-6763	69	4	calculate	calculate	VERB
ap-6763	69	5	the	the	DET
ap-6763	69	6	possibilistic	possibilistic	ADJ
ap-6763	69	7	membership	membership	NOUN
ap-6763	69	8	degree	degree	NOUN
ap-6763	69	9	(	(	PUNCT
ap-6763	69	10	tik	tik	NOUN
ap-6763	69	11	)	)	PUNCT
ap-6763	69	12	,	,	PUNCT
ap-6763	69	13	which	which	PRON
ap-6763	69	14	minimizes	minimize	VERB
ap-6763	69	15	the	the	DET
ap-6763	69	16	objective	objective	ADJ
ap-6763	69	17	function	function	NOUN
ap-6763	69	18	jm	jm	PROPN
ap-6763	69	19	,	,	PUNCT
ap-6763	70	1	τ	τ	PROPN
ap-6763	70	2	using	use	VERB
ap-6763	70	3	the	the	DET
ap-6763	70	4	following	following	ADJ
ap-6763	70	5	t	t	PROPN
ap-6763	70	6	(	(	PUNCT
ap-6763	70	7	l	l	NOUN
ap-6763	70	8	)	)	PUNCT
ap-6763	70	9	ik	ik	PROPN
ap-6763	70	10	=	=	SYM
ap-6763	70	11	1	1	PROPN
ap-6763	71	1	+	+	X
ap-6763	71	2	(	(	PUNCT
ap-6763	71	3	β	β	X
ap-6763	71	4	δ	δ	PROPN
ap-6763	71	5	(	(	PUNCT
ap-6763	71	6	l	l	NOUN
ap-6763	71	7	)	)	PUNCT
ap-6763	71	8	i	i	PRON
ap-6763	71	9	d2	d2	VERB
ap-6763	71	10	ik	ik	X
ap-6763	71	11	)	)	PUNCT
ap-6763	71	12	1	1	NUM
ap-6763	71	13	τ−1	τ−1	PROPN
ap-6763	71	14	−1	−1	PROPN
ap-6763	71	15	,	,	PUNCT
ap-6763	71	16	(	(	PUNCT
ap-6763	71	17	4	4	X
ap-6763	71	18	)	)	PUNCT
ap-6763	71	19	where	where	SCONJ
ap-6763	71	20	d2	d2	PROPN
ap-6763	71	21	ik	ik	PROPN
ap-6763	71	22	=	=	SYM
ap-6763	71	23	∥∥∥xk	∥∥∥xk	PROPN
ap-6763	71	24	−	−	NOUN
ap-6763	71	25	v(l−1	v(l−1	NOUN
ap-6763	71	26	)	)	PUNCT
ap-6763	71	27	i	i	PRON
ap-6763	71	28	∥∥∥2	∥∥∥2	VERB
ap-6763	71	29	,	,	PUNCT
ap-6763	71	30	for	for	ADP
ap-6763	71	31	1	1	NUM
ap-6763	71	32	≤	≤	NUM
ap-6763	71	33	i	i	PRON
ap-6763	71	34	≤	≤	NOUN
ap-6763	71	35	c	c	NOUN
ap-6763	71	36	and	and	CCONJ
ap-6763	71	37	1	1	NUM
ap-6763	71	38	≤	≤	NUM
ap-6763	71	39	k	k	PROPN
ap-6763	71	40	≤	≤	PROPN
ap-6763	71	41	n.	n.	NOUN
ap-6763	71	42	step	step	NOUN
ap-6763	71	43	v	v	NOUN
ap-6763	71	44	:	:	PUNCT
ap-6763	71	45	update	update	VERB
ap-6763	71	46	the	the	DET
ap-6763	71	47	cluster	cluster	NOUN
ap-6763	71	48	centre	centre	NOUN
ap-6763	71	49	(	(	PUNCT
ap-6763	71	50	vi	vi	NOUN
ap-6763	71	51	)	)	PUNCT
ap-6763	71	52	,	,	PUNCT
ap-6763	71	53	which	which	PRON
ap-6763	71	54	minimizes	minimize	VERB
ap-6763	71	55	the	the	DET
ap-6763	71	56	objective	objective	ADJ
ap-6763	71	57	function	function	NOUN
ap-6763	71	58	jm	jm	PROPN
ap-6763	71	59	,	,	PUNCT
ap-6763	71	60	τ	τ	PROPN
ap-6763	71	61	using	use	VERB
ap-6763	71	62	the	the	DET
ap-6763	71	63	following	follow	VERB
ap-6763	71	64	v(l	v(l	NOUN
ap-6763	71	65	)	)	PUNCT
ap-6763	72	1	i	i	PRON
ap-6763	72	2	=	=	PUNCT
ap-6763	73	1	∑n	∑n	NOUN
ap-6763	74	1	k=1	k=1	X
ap-6763	74	2	(	(	PUNCT
ap-6763	74	3	(	(	PUNCT
ap-6763	74	4	αu	αu	X
ap-6763	74	5	(	(	PUNCT
ap-6763	74	6	l	l	NOUN
ap-6763	74	7	)	)	PUNCT
ap-6763	74	8	ik	ik	PROPN
ap-6763	74	9	)	)	PUNCT
ap-6763	74	10	m	m	VERB
ap-6763	74	11	+	+	PUNCT
ap-6763	74	12	(	(	PUNCT
ap-6763	74	13	βt	βt	INTJ
ap-6763	74	14	(	(	PUNCT
ap-6763	74	15	l	l	NOUN
ap-6763	74	16	)	)	PUNCT
ap-6763	74	17	ik	ik	PROPN
ap-6763	74	18	)	)	PUNCT
ap-6763	74	19	τ	τ	PROPN
ap-6763	74	20	)	)	PUNCT
ap-6763	74	21	xk∑n	xk∑n	X
ap-6763	75	1	k=1	k=1	PUNCT
ap-6763	75	2	(	(	PUNCT
ap-6763	75	3	(	(	PUNCT
ap-6763	75	4	αu	αu	X
ap-6763	75	5	(	(	PUNCT
ap-6763	75	6	l	l	NOUN
ap-6763	75	7	)	)	PUNCT
ap-6763	75	8	ik	ik	PROPN
ap-6763	75	9	)	)	PUNCT
ap-6763	75	10	m	m	VERB
ap-6763	75	11	+	+	PUNCT
ap-6763	75	12	(	(	PUNCT
ap-6763	75	13	βt	βt	INTJ
ap-6763	75	14	(	(	PUNCT
ap-6763	75	15	l	l	NOUN
ap-6763	75	16	)	)	PUNCT
ap-6763	75	17	ik	ik	PROPN
ap-6763	75	18	)	)	PUNCT
ap-6763	75	19	τ	τ	PROPN
ap-6763	75	20	)	)	PUNCT
ap-6763	75	21	,	,	PUNCT
ap-6763	75	22	(	(	PUNCT
ap-6763	75	23	5	5	X
ap-6763	75	24	)	)	PUNCT
ap-6763	75	25	for	for	ADP
ap-6763	75	26	1	1	NUM
ap-6763	75	27	≤	≤	NUM
ap-6763	75	28	i	i	PRON
ap-6763	75	29	≤	≤	ADJ
ap-6763	75	30	c.	c.	NOUN
ap-6763	75	31	step	step	NOUN
ap-6763	75	32	vi	vi	PROPN
ap-6763	75	33	:	:	PUNCT
ap-6763	75	34	compare	compare	PROPN
ap-6763	75	35	v(l	v(l	NOUN
ap-6763	75	36	)	)	PUNCT
ap-6763	76	1	i	i	PRON
ap-6763	76	2	to	to	ADP
ap-6763	76	3	v(l−1	v(l−1	NOUN
ap-6763	76	4	)	)	PUNCT
ap-6763	76	5	i	i	PRON
ap-6763	76	6	using∥∥∥v(l	using∥∥∥v(l	VERB
ap-6763	76	7	)	)	PUNCT
ap-6763	77	1	i	i	PRON
ap-6763	77	2	−	−	VERB
ap-6763	77	3	v(l−1	v(l−1	NOUN
ap-6763	77	4	)	)	PUNCT
ap-6763	77	5	i	i	PRON
ap-6763	77	6	∥∥∥	∥∥∥	PROPN
ap-6763	77	7	<	<	X
ap-6763	77	8	ε	ε	PROPN
ap-6763	77	9	.	.	PUNCT
ap-6763	78	1	if	if	SCONJ
ap-6763	78	2	true	true	ADJ
ap-6763	78	3	,	,	PUNCT
ap-6763	78	4	then	then	ADV
ap-6763	78	5	stop	stop	VERB
ap-6763	78	6	.	.	PUNCT
ap-6763	79	1	otherwise	otherwise	ADV
ap-6763	79	2	,	,	PUNCT
ap-6763	79	3	set	set	VERB
ap-6763	79	4	l	l	NOUN
ap-6763	79	5	=	=	PUNCT
ap-6763	80	1	l	l	NOUN
ap-6763	80	2	+	+	CCONJ
ap-6763	80	3	1	1	NUM
ap-6763	80	4	and	and	CCONJ
ap-6763	80	5	return	return	VERB
ap-6763	80	6	to	to	ADP
ap-6763	80	7	step	step	NOUN
ap-6763	80	8	ii	ii	PROPN
ap-6763	80	9	.	.	PUNCT
ap-6763	81	1	the	the	DET
ap-6763	81	2	clustering	clustering	ADJ
ap-6763	81	3	result	result	NOUN
ap-6763	81	4	of	of	ADP
ap-6763	81	5	the	the	DET
ap-6763	81	6	complete	complete	ADJ
ap-6763	81	7	data	data	NOUN
ap-6763	81	8	sets	set	NOUN
ap-6763	81	9	will	will	AUX
ap-6763	81	10	be	be	AUX
ap-6763	81	11	a	a	DET
ap-6763	81	12	base	base	NOUN
ap-6763	81	13	for	for	ADP
ap-6763	81	14	evaluating	evaluate	VERB
ap-6763	81	15	the	the	DET
ap-6763	81	16	performance	performance	NOUN
ap-6763	81	17	of	of	ADP
ap-6763	81	18	the	the	DET
ap-6763	81	19	ocspfcm	ocspfcm	NOUN
ap-6763	81	20	and	and	CCONJ
ap-6763	81	21	npspfcm	npspfcm	PROPN
ap-6763	81	22	(	(	PUNCT
ap-6763	81	23	see	see	VERB
ap-6763	81	24	section	section	NOUN
ap-6763	81	25	4	4	NUM
ap-6763	81	26	)	)	PUNCT
ap-6763	81	27	.	.	PUNCT
ap-6763	82	1	3	3	X
ap-6763	82	2	.	.	X
ap-6763	82	3	possibilistic	possibilistic	ADJ
ap-6763	82	4	fuzzy	fuzzy	ADJ
ap-6763	82	5	c	c	NOUN
ap-6763	82	6	-	-	PUNCT
ap-6763	82	7	means	means	NOUN
ap-6763	82	8	(	(	PUNCT
ap-6763	82	9	pfcm	pfcm	PROPN
ap-6763	82	10	)	)	PUNCT
ap-6763	82	11	algorithm	algorithm	NOUN
ap-6763	82	12	of	of	ADP
ap-6763	82	13	incomplete	incomplete	ADJ
ap-6763	82	14	data	datum	NOUN
ap-6763	82	15	sets	set	NOUN
ap-6763	82	16	given	give	VERB
ap-6763	82	17	incomplete	incomplete	ADJ
ap-6763	82	18	data	datum	NOUN
ap-6763	82	19	sets	set	VERB
ap-6763	82	20	y	y	PROPN
ap-6763	82	21	=	=	SYM
ap-6763	82	22	{	{	PUNCT
ap-6763	82	23	y1,y2	y1,y2	PROPN
ap-6763	82	24	,	,	PUNCT
ap-6763	82	25	·	·	PUNCT
ap-6763	82	26	·	·	PUNCT
ap-6763	82	27	·	·	PUNCT
ap-6763	82	28	,	,	PUNCT
ap-6763	82	29	yn	yn	PROPN
ap-6763	82	30	}	}	PUNCT
ap-6763	82	31	⊂	⊂	PROPN
ap-6763	82	32	rd	rd	PROPN
ap-6763	82	33	and	and	CCONJ
ap-6763	82	34	y2	y2	PROPN
ap-6763	82	35	=	=	SYM
ap-6763	82	36	(	(	PUNCT
ap-6763	82	37	2.35	2.35	NUM
ap-6763	82	38	,	,	PUNCT
ap-6763	82	39	?	?	PUNCT
ap-6763	82	40	,	,	PUNCT
ap-6763	82	41	1.32	1.32	NUM
ap-6763	82	42	,	,	PUNCT
ap-6763	82	43	?	?	PUNCT
ap-6763	82	44	,	,	PUNCT
ap-6763	82	45	3.44)t	3.44)t	PROPN
ap-6763	82	46	∈	∈	PROPN
ap-6763	82	47	r5	r5	PROPN
ap-6763	82	48	.	.	PUNCT
ap-6763	83	1	y22	y22	PROPN
ap-6763	83	2	and	and	CCONJ
ap-6763	83	3	y24	y24	NOUN
ap-6763	83	4	are	be	AUX
ap-6763	83	5	missing	miss	VERB
ap-6763	83	6	values	value	NOUN
ap-6763	83	7	.	.	PUNCT
ap-6763	84	1	the	the	DET
ap-6763	84	2	question	question	NOUN
ap-6763	84	3	is	be	AUX
ap-6763	84	4	how	how	SCONJ
ap-6763	84	5	to	to	PART
ap-6763	84	6	cluster	cluster	VERB
ap-6763	84	7	y	y	PROPN
ap-6763	84	8	?	?	PUNCT
ap-6763	84	9	to	to	PART
ap-6763	84	10	answer	answer	VERB
ap-6763	84	11	this	this	DET
ap-6763	84	12	question	question	NOUN
ap-6763	84	13	,	,	PUNCT
ap-6763	84	14	we	we	PRON
ap-6763	84	15	propose	propose	VERB
ap-6763	84	16	the	the	DET
ap-6763	84	17	ocspfcm	ocspfcm	NOUN
ap-6763	84	18	and	and	CCONJ
ap-6763	84	19	npspfcm	npspfcm	ADJ
ap-6763	84	20	for	for	ADP
ap-6763	84	21	clustering	cluster	VERB
ap-6763	84	22	incomplete	incomplete	ADJ
ap-6763	84	23	data	datum	NOUN
ap-6763	84	24	sets	set	NOUN
ap-6763	84	25	such	such	ADJ
ap-6763	84	26	as	as	ADP
ap-6763	84	27	y.	y.	NOUN
ap-6763	84	28	the	the	DET
ap-6763	84	29	notation	notation	NOUN
ap-6763	84	30	used	use	VERB
ap-6763	84	31	throughout	throughout	ADP
ap-6763	84	32	this	this	DET
ap-6763	84	33	article	article	NOUN
ap-6763	84	34	is	be	AUX
ap-6763	84	35	as	as	SCONJ
ap-6763	84	36	follows	follow	VERB
ap-6763	84	37	.	.	PUNCT
ap-6763	85	1	let	let	VERB
ap-6763	85	2	365	365	NUM
ap-6763	85	3	rustam	rustam	PROPN
ap-6763	85	4	,	,	PUNCT
ap-6763	85	5	k.	k.	PROPN
ap-6763	85	6	usman	usman	PROPN
ap-6763	85	7	,	,	PUNCT
ap-6763	85	8	m.	m.	NOUN
ap-6763	85	9	kamaruddin	kamaruddin	PROPN
ap-6763	85	10	et	et	PROPN
ap-6763	85	11	al	al	PROPN
ap-6763	85	12	.	.	PROPN
ap-6763	85	13	acta	acta	PROPN
ap-6763	85	14	polytechnica	polytechnica	PROPN
ap-6763	86	1	yk	yk	PROPN
ap-6763	87	1	=	=	PROPN
ap-6763	87	2	kth	kth	PROPN
ap-6763	87	3	d	d	X
ap-6763	87	4	-	-	ADJ
ap-6763	87	5	dimensional	dimensional	ADJ
ap-6763	87	6	datapoint	datapoint	NOUN
ap-6763	87	7	(	(	PUNCT
ap-6763	87	8	data	data	NOUN
ap-6763	87	9	vector	vector	PROPN
ap-6763	87	10	)	)	PUNCT
ap-6763	87	11	,	,	PUNCT
ap-6763	87	12	for	for	ADP
ap-6763	87	13	1	1	NUM
ap-6763	87	14	≤	≤	NUM
ap-6763	87	15	k	k	NOUN
ap-6763	87	16	≤	≤	PROPN
ap-6763	87	17	n	n	CCONJ
ap-6763	87	18	;	;	PUNCT
ap-6763	87	19	ykj	ykj	PROPN
ap-6763	87	20	=	=	PUNCT
ap-6763	87	21	jth	jth	PROPN
ap-6763	87	22	feature	feature	NOUN
ap-6763	87	23	value	value	NOUN
ap-6763	87	24	of	of	ADP
ap-6763	87	25	the	the	DET
ap-6763	87	26	kthdata	kthdata	NOUN
ap-6763	87	27	point	point	NOUN
ap-6763	87	28	,	,	PUNCT
ap-6763	87	29	for	for	ADP
ap-6763	87	30	1	1	NUM
ap-6763	87	31	≤	≤	NUM
ap-6763	87	32	j	j	PROPN
ap-6763	87	33	≤	≤	PROPN
ap-6763	87	34	d	d	PROPN
ap-6763	87	35	,	,	PUNCT
ap-6763	87	36	1	1	NUM
ap-6763	87	37	≤	≤	NUM
ap-6763	87	38	k	k	NOUN
ap-6763	87	39	≤	≤	PROPN
ap-6763	87	40	n	n	CCONJ
ap-6763	87	41	;	;	PUNCT
ap-6763	87	42	y	y	PROPN
ap-6763	87	43	=	=	SYM
ap-6763	87	44	{	{	PUNCT
ap-6763	87	45	y1,y2	y1,y2	PROPN
ap-6763	87	46	,	,	PUNCT
ap-6763	87	47	·	·	PUNCT
ap-6763	87	48	·	·	PUNCT
ap-6763	87	49	·	·	PUNCT
ap-6763	87	50	,	,	PUNCT
ap-6763	87	51	yn	yn	PROPN
ap-6763	87	52	}	}	PUNCT
ap-6763	87	53	⊂	⊂	PROPN
ap-6763	87	54	rd	rd	PROPN
ap-6763	87	55	;	;	PUNCT
ap-6763	87	56	yc	yc	PROPN
ap-6763	87	57	=	=	PRON
ap-6763	87	58	{	{	PUNCT
ap-6763	87	59	yk	yk	PROPN
ap-6763	87	60	∈	∈	PROPN
ap-6763	87	61	y|	y|	NOUN
ap-6763	87	62	yk	yk	PROPN
ap-6763	87	63	is	be	AUX
ap-6763	87	64	a	a	DET
ap-6763	87	65	complete	complete	ADJ
ap-6763	87	66	data	data	NOUN
ap-6763	87	67	point	point	NOUN
ap-6763	87	68	}	}	PUNCT
ap-6763	87	69	;	;	PUNCT
ap-6763	87	70	yp	yp	PROPN
ap-6763	87	71	=	=	PRON
ap-6763	87	72	{	{	PUNCT
ap-6763	87	73	ykj	ykj	NOUN
ap-6763	87	74	for	for	ADP
ap-6763	87	75	1	1	NUM
ap-6763	87	76	≤	≤	NUM
ap-6763	87	77	j	j	PROPN
ap-6763	87	78	≤	≤	PROPN
ap-6763	87	79	d	d	PROPN
ap-6763	87	80	,	,	PUNCT
ap-6763	87	81	1	1	NUM
ap-6763	87	82	≤	≤	NUM
ap-6763	87	83	k	k	X
ap-6763	87	84	≤	≤	ADJ
ap-6763	87	85	n|	n|	NOUN
ap-6763	87	86	the	the	DET
ap-6763	87	87	value	value	NOUN
ap-6763	87	88	for	for	ADP
ap-6763	87	89	ykj	ykj	NOUN
ap-6763	87	90	is	be	AUX
ap-6763	87	91	present	present	ADJ
ap-6763	87	92	in	in	ADP
ap-6763	87	93	y	y	PROPN
ap-6763	87	94	}	}	PUNCT
ap-6763	87	95	;	;	PUNCT
ap-6763	88	1	ym	ym	PRON
ap-6763	88	2	=	=	NOUN
ap-6763	88	3	{	{	PUNCT
ap-6763	88	4	ykj	ykj	NOUN
ap-6763	88	5	=	=	PUNCT
ap-6763	88	6	?	?	PUNCT
ap-6763	89	1	for	for	ADP
ap-6763	89	2	1	1	NUM
ap-6763	89	3	≤	≤	NUM
ap-6763	89	4	j	j	PROPN
ap-6763	89	5	≤	≤	PROPN
ap-6763	89	6	d	d	PROPN
ap-6763	89	7	,	,	PUNCT
ap-6763	89	8	1	1	NUM
ap-6763	89	9	≤	≤	NUM
ap-6763	89	10	k	k	X
ap-6763	89	11	≤	≤	ADJ
ap-6763	89	12	n|	n|	NOUN
ap-6763	89	13	the	the	DET
ap-6763	89	14	value	value	NOUN
ap-6763	89	15	for	for	ADP
ap-6763	89	16	ykj	ykj	NOUN
ap-6763	89	17	is	be	AUX
ap-6763	89	18	missing	miss	VERB
ap-6763	89	19	in	in	ADP
ap-6763	89	20	y	y	PROPN
ap-6763	89	21	}	}	PUNCT
ap-6763	89	22	.	.	PUNCT
ap-6763	90	1	3.1	3.1	NUM
ap-6763	90	2	.	.	PUNCT
ap-6763	91	1	optimal	optimal	ADJ
ap-6763	91	2	completion	completion	NOUN
ap-6763	91	3	strategy	strategy	NOUN
ap-6763	91	4	possibilistic	possibilistic	ADJ
ap-6763	91	5	fuzzy	fuzzy	ADJ
ap-6763	91	6	c	c	NOUN
ap-6763	91	7	-	-	PUNCT
ap-6763	91	8	means	means	NOUN
ap-6763	91	9	(	(	PUNCT
ap-6763	91	10	ocspfcm	ocspfcm	PROPN
ap-6763	91	11	)	)	PUNCT
ap-6763	91	12	algorithm	algorithm	NOUN
ap-6763	91	13	the	the	DET
ap-6763	91	14	explanation	explanation	NOUN
ap-6763	91	15	of	of	ADP
ap-6763	91	16	the	the	DET
ap-6763	91	17	ocspfcm	ocspfcm	PROPN
ap-6763	91	18	algorithm	algorithm	NOUN
ap-6763	91	19	is	be	AUX
ap-6763	91	20	as	as	SCONJ
ap-6763	91	21	follows	follow	VERB
ap-6763	91	22	.	.	PUNCT
ap-6763	92	1	step	step	NOUN
ap-6763	92	2	i	i	PRON
ap-6763	92	3	:	:	PUNCT
ap-6763	92	4	fix	fix	VERB
ap-6763	92	5	m	m	PRON
ap-6763	92	6	>	>	X
ap-6763	92	7	1	1	NUM
ap-6763	92	8	,	,	PUNCT
ap-6763	92	9	τ	τ	PROPN
ap-6763	92	10	>	>	X
ap-6763	92	11	1	1	NUM
ap-6763	92	12	,	,	PUNCT
ap-6763	92	13	ε	ε	PROPN
ap-6763	92	14	>	>	X
ap-6763	92	15	0	0	PUNCT
ap-6763	93	1	and	and	CCONJ
ap-6763	93	2	1	1	NUM
ap-6763	93	3	<	<	X
ap-6763	93	4	c	c	X
ap-6763	93	5	<	<	X
ap-6763	93	6	n.	n.	PROPN
ap-6763	93	7	initiate	initiate	VERB
ap-6763	93	8	y(0	y(0	PROPN
ap-6763	93	9	)	)	PUNCT
ap-6763	93	10	m	m	PROPN
ap-6763	93	11	,	,	PUNCT
ap-6763	93	12	for	for	ADP
ap-6763	93	13	each	each	DET
ap-6763	93	14	ykj	ykj	NOUN
ap-6763	93	15	∈	∈	PROPN
ap-6763	93	16	ym	ym	INTJ
ap-6763	93	17	,	,	PUNCT
ap-6763	93	18	with	with	ADP
ap-6763	93	19	picking	pick	VERB
ap-6763	93	20	a	a	DET
ap-6763	93	21	random	random	ADJ
ap-6763	93	22	available	available	ADJ
ap-6763	93	23	value	value	NOUN
ap-6763	93	24	in	in	ADP
ap-6763	93	25	yp	yp	PROPN
ap-6763	93	26	.	.	PUNCT
ap-6763	94	1	then	then	ADV
ap-6763	94	2	pick	pick	VERB
ap-6763	94	3	v(0	v(0	PROPN
ap-6763	94	4	)	)	PUNCT
ap-6763	94	5	∈	∈	PROPN
ap-6763	94	6	rd	rd	PROPN
ap-6763	94	7	,	,	PUNCT
ap-6763	94	8	v(0	v(0	PROPN
ap-6763	94	9	)	)	PUNCT
ap-6763	94	10	can	can	AUX
ap-6763	94	11	be	be	AUX
ap-6763	94	12	chosen	choose	VERB
ap-6763	94	13	randomly	randomly	ADV
ap-6763	94	14	from	from	ADP
ap-6763	94	15	the	the	DET
ap-6763	94	16	y	y	PROPN
ap-6763	94	17	=	=	PUNCT
ap-6763	94	18	{	{	PUNCT
ap-6763	94	19	y1,y2	y1,y2	PROPN
ap-6763	94	20	,	,	PUNCT
ap-6763	94	21	·	·	PUNCT
ap-6763	94	22	·	·	PUNCT
ap-6763	94	23	·	·	PUNCT
ap-6763	94	24	,	,	PUNCT
ap-6763	94	25	yn	yn	PROPN
ap-6763	94	26	}	}	PUNCT
ap-6763	94	27	⊂	⊂	PROPN
ap-6763	94	28	rd	rd	PROPN
ap-6763	94	29	.	.	PUNCT
ap-6763	95	1	then	then	ADV
ap-6763	95	2	at	at	ADP
ap-6763	95	3	step	step	NOUN
ap-6763	95	4	l	l	NOUN
ap-6763	95	5	,	,	PUNCT
ap-6763	95	6	l	l	NOUN
ap-6763	95	7	=	=	SYM
ap-6763	95	8	1	1	NUM
ap-6763	95	9	,	,	PUNCT
ap-6763	95	10	2	2	NUM
ap-6763	95	11	,	,	PUNCT
ap-6763	95	12	·	·	PUNCT
ap-6763	95	13	·	·	PUNCT
ap-6763	95	14	·	·	PUNCT
ap-6763	95	15	step	step	NOUN
ap-6763	95	16	ii	ii	PROPN
ap-6763	95	17	:	:	PUNCT
ap-6763	95	18	calculate	calculate	VERB
ap-6763	95	19	the	the	DET
ap-6763	95	20	fuzzy	fuzzy	ADJ
ap-6763	95	21	membership	membership	NOUN
ap-6763	95	22	degree	degree	NOUN
ap-6763	95	23	(	(	PUNCT
ap-6763	95	24	uik	uik	NOUN
ap-6763	95	25	)	)	PUNCT
ap-6763	95	26	,	,	PUNCT
ap-6763	95	27	which	which	PRON
ap-6763	95	28	minimizes	minimize	VERB
ap-6763	95	29	the	the	DET
ap-6763	95	30	objective	objective	ADJ
ap-6763	95	31	function	function	NOUN
ap-6763	95	32	jm	jm	PROPN
ap-6763	95	33	,	,	PUNCT
ap-6763	95	34	τ	τ	PROPN
ap-6763	95	35	using	use	VERB
ap-6763	95	36	the	the	DET
ap-6763	95	37	following	follow	VERB
ap-6763	95	38	u	u	PROPN
ap-6763	95	39	(	(	PUNCT
ap-6763	95	40	l	l	NOUN
ap-6763	95	41	)	)	PUNCT
ap-6763	95	42	ik	ik	PROPN
ap-6763	95	43	=	=	SYM
ap-6763	95	44			PROPN
ap-6763	96	1	c∑	c∑	PRON
ap-6763	96	2	j=1	j=1	PROPN
ap-6763	96	3	(	(	PUNCT
ap-6763	96	4	d2	d2	PROPN
ap-6763	96	5	ik	ik	PROPN
ap-6763	96	6	d2	d2	PROPN
ap-6763	96	7	jk	jk	PROPN
ap-6763	96	8	)	)	PUNCT
ap-6763	96	9	1	1	NUM
ap-6763	96	10	m−1	m−1	PROPN
ap-6763	96	11	−1	−1	INTJ
ap-6763	96	12	,	,	PUNCT
ap-6763	96	13	(	(	PUNCT
ap-6763	96	14	6	6	NUM
ap-6763	96	15	)	)	PUNCT
ap-6763	96	16	where	where	SCONJ
ap-6763	96	17	d2	d2	PROPN
ap-6763	96	18	ik	ik	PROPN
ap-6763	96	19	=	=	SYM
ap-6763	96	20	∥∥∥xk	∥∥∥xk	PROPN
ap-6763	96	21	−	−	NOUN
ap-6763	96	22	v(l−1	v(l−1	NOUN
ap-6763	96	23	)	)	PUNCT
ap-6763	96	24	i	i	PRON
ap-6763	96	25	∥∥∥2	∥∥∥2	VERB
ap-6763	96	26	,	,	PUNCT
ap-6763	96	27	for	for	ADP
ap-6763	96	28	1	1	NUM
ap-6763	96	29	≤	≤	NUM
ap-6763	96	30	i	i	PRON
ap-6763	96	31	≤	≤	NOUN
ap-6763	96	32	c	c	NOUN
ap-6763	96	33	and	and	CCONJ
ap-6763	96	34	1	1	NUM
ap-6763	96	35	≤	≤	NUM
ap-6763	96	36	k	k	PROPN
ap-6763	96	37	≤	≤	PROPN
ap-6763	96	38	n.	n.	NOUN
ap-6763	96	39	step	step	PROPN
ap-6763	96	40	iii	iii	PROPN
ap-6763	96	41	:	:	PUNCT
ap-6763	96	42	calculate	calculate	VERB
ap-6763	96	43	the	the	DET
ap-6763	96	44	possibilistic	possibilistic	ADJ
ap-6763	96	45	typical	typical	ADJ
ap-6763	96	46	(	(	PUNCT
ap-6763	96	47	δi	δi	PROPN
ap-6763	96	48	)	)	PUNCT
ap-6763	96	49	,	,	PUNCT
ap-6763	96	50	which	which	PRON
ap-6763	96	51	minimizes	minimize	VERB
ap-6763	96	52	the	the	DET
ap-6763	96	53	objective	objective	ADJ
ap-6763	96	54	function	function	NOUN
ap-6763	96	55	jm	jm	PROPN
ap-6763	96	56	,	,	PUNCT
ap-6763	96	57	τ	τ	PROPN
ap-6763	96	58	using	use	VERB
ap-6763	96	59	the	the	DET
ap-6763	96	60	following	follow	VERB
ap-6763	96	61	δ	δ	PROPN
ap-6763	96	62	(	(	PUNCT
ap-6763	96	63	l	l	NOUN
ap-6763	96	64	)	)	PUNCT
ap-6763	96	65	i	i	PRON
ap-6763	96	66	=	=	PUNCT
ap-6763	97	1	∑n	∑n	NOUN
ap-6763	98	1	k=1	k=1	NOUN
ap-6763	98	2	(	(	PUNCT
ap-6763	98	3	u	u	X
ap-6763	98	4	(	(	PUNCT
ap-6763	98	5	l	l	NOUN
ap-6763	98	6	)	)	PUNCT
ap-6763	98	7	ik	ik	PROPN
ap-6763	98	8	)	)	PUNCT
ap-6763	98	9	m	m	PROPN
ap-6763	98	10	d2	d2	PROPN
ap-6763	98	11	ik∑n	ik∑n	NOUN
ap-6763	98	12	k=1	k=1	PROPN
ap-6763	98	13	(	(	PUNCT
ap-6763	98	14	u	u	X
ap-6763	98	15	(	(	PUNCT
ap-6763	98	16	l	l	NOUN
ap-6763	98	17	)	)	PUNCT
ap-6763	98	18	ik	ik	PROPN
ap-6763	98	19	)	)	PUNCT
ap-6763	98	20	m	m	VERB
ap-6763	98	21	,	,	PUNCT
ap-6763	98	22	(	(	PUNCT
ap-6763	98	23	7	7	X
ap-6763	98	24	)	)	PUNCT
ap-6763	98	25	where	where	SCONJ
ap-6763	98	26	d2	d2	PROPN
ap-6763	98	27	ik	ik	PROPN
ap-6763	98	28	=	=	SYM
ap-6763	98	29	∥∥∥xk	∥∥∥xk	PROPN
ap-6763	98	30	−	−	NOUN
ap-6763	98	31	v(l−1	v(l−1	NOUN
ap-6763	98	32	)	)	PUNCT
ap-6763	98	33	i	i	PRON
ap-6763	98	34	∥∥∥2	∥∥∥2	VERB
ap-6763	98	35	.	.	PUNCT
ap-6763	99	1	step	step	VERB
ap-6763	99	2	iv	iv	NUM
ap-6763	99	3	:	:	PUNCT
ap-6763	99	4	calculate	calculate	VERB
ap-6763	99	5	the	the	DET
ap-6763	99	6	possibilistic	possibilistic	ADJ
ap-6763	99	7	membership	membership	NOUN
ap-6763	99	8	degree	degree	NOUN
ap-6763	99	9	(	(	PUNCT
ap-6763	99	10	tik	tik	NOUN
ap-6763	99	11	)	)	PUNCT
ap-6763	99	12	,	,	PUNCT
ap-6763	99	13	which	which	PRON
ap-6763	99	14	minimizes	minimize	VERB
ap-6763	99	15	the	the	DET
ap-6763	99	16	objective	objective	ADJ
ap-6763	99	17	function	function	NOUN
ap-6763	99	18	jm	jm	PROPN
ap-6763	99	19	,	,	PUNCT
ap-6763	100	1	τ	τ	PROPN
ap-6763	100	2	using	use	VERB
ap-6763	100	3	the	the	DET
ap-6763	100	4	following	following	ADJ
ap-6763	100	5	t	t	PROPN
ap-6763	100	6	(	(	PUNCT
ap-6763	100	7	l	l	NOUN
ap-6763	100	8	)	)	PUNCT
ap-6763	100	9	ik	ik	PROPN
ap-6763	100	10	=	=	SYM
ap-6763	100	11	1	1	PROPN
ap-6763	101	1	+	+	X
ap-6763	101	2	(	(	PUNCT
ap-6763	101	3	β	β	X
ap-6763	101	4	δ	δ	PROPN
ap-6763	101	5	(	(	PUNCT
ap-6763	101	6	l	l	NOUN
ap-6763	101	7	)	)	PUNCT
ap-6763	101	8	i	i	PRON
ap-6763	101	9	d2	d2	VERB
ap-6763	101	10	ik	ik	X
ap-6763	101	11	)	)	PUNCT
ap-6763	101	12	1	1	NUM
ap-6763	101	13	τ−1	τ−1	PROPN
ap-6763	101	14	−1	−1	PROPN
ap-6763	101	15	,	,	PUNCT
ap-6763	101	16	(	(	PUNCT
ap-6763	101	17	8)	8)	NUM
ap-6763	101	18	where	where	SCONJ
ap-6763	101	19	d2	d2	PROPN
ap-6763	101	20	ik	ik	PROPN
ap-6763	101	21	=	=	SYM
ap-6763	101	22	∥∥∥xk	∥∥∥xk	PROPN
ap-6763	101	23	−	−	NOUN
ap-6763	101	24	v(l−1	v(l−1	NOUN
ap-6763	101	25	)	)	PUNCT
ap-6763	101	26	i	i	PRON
ap-6763	101	27	∥∥∥2	∥∥∥2	VERB
ap-6763	101	28	,	,	PUNCT
ap-6763	101	29	for	for	ADP
ap-6763	101	30	1	1	NUM
ap-6763	101	31	≤	≤	NUM
ap-6763	101	32	i	i	PRON
ap-6763	101	33	≤	≤	NOUN
ap-6763	101	34	c	c	NOUN
ap-6763	101	35	and	and	CCONJ
ap-6763	101	36	1	1	NUM
ap-6763	101	37	≤	≤	NUM
ap-6763	101	38	k	k	PROPN
ap-6763	101	39	≤	≤	PROPN
ap-6763	101	40	n.	n.	NOUN
ap-6763	101	41	step	step	NOUN
ap-6763	101	42	v	v	NOUN
ap-6763	101	43	:	:	PUNCT
ap-6763	101	44	update	update	VERB
ap-6763	101	45	the	the	DET
ap-6763	101	46	cluster	cluster	NOUN
ap-6763	101	47	centre	centre	NOUN
ap-6763	101	48	(	(	PUNCT
ap-6763	101	49	vi	vi	NOUN
ap-6763	101	50	)	)	PUNCT
ap-6763	101	51	,	,	PUNCT
ap-6763	101	52	which	which	PRON
ap-6763	101	53	minimizes	minimize	VERB
ap-6763	101	54	the	the	DET
ap-6763	101	55	objective	objective	ADJ
ap-6763	101	56	function	function	NOUN
ap-6763	101	57	jm	jm	PROPN
ap-6763	101	58	,	,	PUNCT
ap-6763	101	59	τ	τ	PROPN
ap-6763	101	60	using	use	VERB
ap-6763	101	61	the	the	DET
ap-6763	101	62	following	follow	VERB
ap-6763	101	63	v(l	v(l	NOUN
ap-6763	101	64	)	)	PUNCT
ap-6763	102	1	i	i	PRON
ap-6763	102	2	=	=	PUNCT
ap-6763	103	1	∑n	∑n	NOUN
ap-6763	104	1	k=1	k=1	X
ap-6763	104	2	(	(	PUNCT
ap-6763	104	3	(	(	PUNCT
ap-6763	104	4	αu	αu	X
ap-6763	104	5	(	(	PUNCT
ap-6763	104	6	l	l	NOUN
ap-6763	104	7	)	)	PUNCT
ap-6763	104	8	ik	ik	PROPN
ap-6763	104	9	)	)	PUNCT
ap-6763	104	10	m	m	VERB
ap-6763	104	11	+	+	PUNCT
ap-6763	104	12	(	(	PUNCT
ap-6763	104	13	βt	βt	INTJ
ap-6763	104	14	(	(	PUNCT
ap-6763	104	15	l	l	NOUN
ap-6763	104	16	)	)	PUNCT
ap-6763	104	17	ik	ik	PROPN
ap-6763	104	18	)	)	PUNCT
ap-6763	104	19	τ	τ	PROPN
ap-6763	104	20	)	)	PUNCT
ap-6763	104	21	yk∑n	yk∑n	X
ap-6763	105	1	k=1	k=1	X
ap-6763	105	2	(	(	PUNCT
ap-6763	105	3	(	(	PUNCT
ap-6763	105	4	αu	αu	X
ap-6763	105	5	(	(	PUNCT
ap-6763	105	6	l	l	NOUN
ap-6763	105	7	)	)	PUNCT
ap-6763	105	8	ik	ik	PROPN
ap-6763	105	9	)	)	PUNCT
ap-6763	105	10	m	m	VERB
ap-6763	105	11	+	+	PUNCT
ap-6763	105	12	(	(	PUNCT
ap-6763	105	13	βt	βt	INTJ
ap-6763	105	14	(	(	PUNCT
ap-6763	105	15	l	l	NOUN
ap-6763	105	16	)	)	PUNCT
ap-6763	105	17	ik	ik	PROPN
ap-6763	105	18	)	)	PUNCT
ap-6763	105	19	τ	τ	PROPN
ap-6763	105	20	)	)	PUNCT
ap-6763	105	21	,	,	PUNCT
ap-6763	105	22	(	(	PUNCT
ap-6763	105	23	9	9	X
ap-6763	105	24	)	)	PUNCT
ap-6763	105	25	for	for	ADP
ap-6763	105	26	1	1	NUM
ap-6763	105	27	≤	≤	NUM
ap-6763	105	28	i	i	PRON
ap-6763	105	29	≤	≤	ADJ
ap-6763	105	30	c.	c.	NOUN
ap-6763	105	31	step	step	NOUN
ap-6763	105	32	vi	vi	PROPN
ap-6763	105	33	:	:	PUNCT
ap-6763	105	34	compare	compare	PROPN
ap-6763	105	35	v(l	v(l	NOUN
ap-6763	105	36	)	)	PUNCT
ap-6763	106	1	i	i	PRON
ap-6763	106	2	to	to	ADP
ap-6763	106	3	v(l−1	v(l−1	NOUN
ap-6763	106	4	)	)	PUNCT
ap-6763	106	5	i	i	PRON
ap-6763	106	6	using∥∥∥v(l	using∥∥∥v(l	VERB
ap-6763	106	7	)	)	PUNCT
ap-6763	107	1	i	i	PRON
ap-6763	107	2	−	−	VERB
ap-6763	107	3	v(l−1	v(l−1	NOUN
ap-6763	107	4	)	)	PUNCT
ap-6763	107	5	i	i	PRON
ap-6763	107	6	∥∥∥	∥∥∥	PROPN
ap-6763	107	7	<	<	X
ap-6763	107	8	ε	ε	PROPN
ap-6763	107	9	.	.	PUNCT
ap-6763	108	1	if	if	SCONJ
ap-6763	108	2	true	true	ADJ
ap-6763	108	3	,	,	PUNCT
ap-6763	108	4	then	then	ADV
ap-6763	108	5	stop	stop	VERB
ap-6763	108	6	.	.	PUNCT
ap-6763	109	1	otherwise	otherwise	ADV
ap-6763	109	2	,	,	PUNCT
ap-6763	109	3	go	go	VERB
ap-6763	109	4	to	to	PART
ap-6763	109	5	step	step	VERB
ap-6763	109	6	vii	vii	PROPN
ap-6763	109	7	.	.	PUNCT
ap-6763	110	1	step	step	PROPN
ap-6763	110	2	vii	vii	PROPN
ap-6763	110	3	:	:	PUNCT
ap-6763	110	4	calculate	calculate	NOUN
ap-6763	110	5	ym	ym	INTJ
ap-6763	110	6	,	,	PUNCT
ap-6763	110	7	which	which	PRON
ap-6763	110	8	minimizes	minimize	VERB
ap-6763	110	9	the	the	DET
ap-6763	110	10	objective	objective	ADJ
ap-6763	110	11	function	function	NOUN
ap-6763	110	12	jm	jm	PROPN
ap-6763	110	13	,	,	PUNCT
ap-6763	110	14	τ	τ	PROPN
ap-6763	110	15	,	,	PUNCT
ap-6763	110	16	for	for	ADP
ap-6763	110	17	all	all	DET
ap-6763	110	18	ykj	ykj	NOUN
ap-6763	110	19	∈	∈	PROPN
ap-6763	111	1	ym	ym	NOUN
ap-6763	111	2	using	use	VERB
ap-6763	111	3	the	the	DET
ap-6763	111	4	following	follow	VERB
ap-6763	111	5	y(l	y(l	PROPN
ap-6763	111	6	)	)	PUNCT
ap-6763	112	1	kj	kj	NOUN
ap-6763	112	2	=	=	PUNCT
ap-6763	112	3	∑n	∑n	PROPN
ap-6763	113	1	k=1	k=1	X
ap-6763	113	2	(	(	PUNCT
ap-6763	113	3	(	(	PUNCT
ap-6763	113	4	αu	αu	X
ap-6763	113	5	(	(	PUNCT
ap-6763	113	6	l	l	NOUN
ap-6763	113	7	)	)	PUNCT
ap-6763	113	8	ik	ik	PROPN
ap-6763	113	9	)	)	PUNCT
ap-6763	113	10	m	m	VERB
ap-6763	113	11	+	+	PUNCT
ap-6763	113	12	(	(	PUNCT
ap-6763	113	13	βt	βt	INTJ
ap-6763	113	14	(	(	PUNCT
ap-6763	113	15	l	l	NOUN
ap-6763	113	16	)	)	PUNCT
ap-6763	113	17	ik	ik	PROPN
ap-6763	113	18	)	)	PUNCT
ap-6763	113	19	τ	τ	PROPN
ap-6763	113	20	)	)	PUNCT
ap-6763	113	21	v(l	v(l	PROPN
ap-6763	113	22	)	)	PUNCT
ap-6763	113	23	ij∑n	ij∑n	VERB
ap-6763	113	24	k=1	k=1	X
ap-6763	114	1	(	(	PUNCT
ap-6763	114	2	(	(	PUNCT
ap-6763	114	3	αu	αu	X
ap-6763	114	4	(	(	PUNCT
ap-6763	114	5	l	l	NOUN
ap-6763	114	6	)	)	PUNCT
ap-6763	114	7	ik	ik	PROPN
ap-6763	114	8	)	)	PUNCT
ap-6763	114	9	m	m	VERB
ap-6763	114	10	+	+	PUNCT
ap-6763	114	11	(	(	PUNCT
ap-6763	114	12	βt	βt	INTJ
ap-6763	114	13	(	(	PUNCT
ap-6763	114	14	l	l	NOUN
ap-6763	114	15	)	)	PUNCT
ap-6763	114	16	ik	ik	PROPN
ap-6763	114	17	)	)	PUNCT
ap-6763	114	18	τ	τ	PROPN
ap-6763	114	19	)	)	PUNCT
ap-6763	114	20	.	.	PUNCT
ap-6763	115	1	(	(	PUNCT
ap-6763	115	2	10	10	NUM
ap-6763	115	3	)	)	PUNCT
ap-6763	115	4	now	now	ADV
ap-6763	115	5	,	,	PUNCT
ap-6763	115	6	set	set	VERB
ap-6763	115	7	l	l	NOUN
ap-6763	115	8	=	=	PUNCT
ap-6763	116	1	l	l	NOUN
ap-6763	116	2	+	+	CCONJ
ap-6763	116	3	1	1	NUM
ap-6763	116	4	and	and	CCONJ
ap-6763	116	5	return	return	VERB
ap-6763	116	6	to	to	ADP
ap-6763	116	7	step	step	NOUN
ap-6763	116	8	ii	ii	PROPN
ap-6763	116	9	.	.	PUNCT
ap-6763	117	1	we	we	PRON
ap-6763	117	2	update	update	VERB
ap-6763	117	3	the	the	DET
ap-6763	117	4	missing	miss	VERB
ap-6763	117	5	values	value	NOUN
ap-6763	117	6	imputation	imputation	NOUN
ap-6763	117	7	on	on	ADP
ap-6763	117	8	step	step	NOUN
ap-6763	117	9	vii	vii	PROPN
ap-6763	117	10	using	use	VERB
ap-6763	117	11	the	the	DET
ap-6763	117	12	sum	sum	NOUN
ap-6763	117	13	of	of	ADP
ap-6763	117	14	fuzzy	fuzzy	ADJ
ap-6763	117	15	with	with	ADP
ap-6763	117	16	possibilistic	possibilistic	ADJ
ap-6763	117	17	membership	membership	NOUN
ap-6763	117	18	degress	degress	PROPN
ap-6763	117	19	multiplied	multiply	VERB
ap-6763	117	20	by	by	ADP
ap-6763	117	21	the	the	DET
ap-6763	117	22	values	value	NOUN
ap-6763	117	23	existing	exist	VERB
ap-6763	117	24	on	on	ADP
ap-6763	117	25	the	the	DET
ap-6763	117	26	cluster	cluster	NOUN
ap-6763	117	27	centre	centre	NOUN
ap-6763	117	28	as	as	SCONJ
ap-6763	117	29	shown	show	VERB
ap-6763	117	30	in	in	ADP
ap-6763	117	31	equation	equation	NOUN
ap-6763	117	32	10	10	NUM
ap-6763	117	33	.	.	PUNCT
ap-6763	117	34	3.2	3.2	NUM
ap-6763	117	35	.	.	PUNCT
ap-6763	118	1	nearest	near	ADJ
ap-6763	118	2	prototype	prototype	NOUN
ap-6763	118	3	strategy	strategy	NOUN
ap-6763	118	4	possibilistic	possibilistic	ADJ
ap-6763	118	5	fuzzy	fuzzy	ADJ
ap-6763	118	6	c	c	NOUN
ap-6763	118	7	-	-	PUNCT
ap-6763	118	8	means	means	NOUN
ap-6763	118	9	(	(	PUNCT
ap-6763	118	10	npspfcm	npspfcm	NOUN
ap-6763	118	11	)	)	PUNCT
ap-6763	118	12	algorithm	algorithm	NOUN
ap-6763	118	13	the	the	DET
ap-6763	118	14	difference	difference	NOUN
ap-6763	118	15	between	between	ADP
ap-6763	118	16	the	the	DET
ap-6763	118	17	ocspfcm	ocspfcm	NOUN
ap-6763	118	18	and	and	CCONJ
ap-6763	118	19	the	the	DET
ap-6763	118	20	npspfcm	npspfcm	NOUN
ap-6763	118	21	lies	lie	VERB
ap-6763	118	22	in	in	ADP
ap-6763	118	23	step	step	NOUN
ap-6763	118	24	vii	vii	PROPN
ap-6763	118	25	.	.	PUNCT
ap-6763	119	1	the	the	DET
ap-6763	119	2	imputation	imputation	NOUN
ap-6763	119	3	of	of	ADP
ap-6763	119	4	the	the	DET
ap-6763	119	5	missing	miss	VERB
ap-6763	119	6	values	value	NOUN
ap-6763	119	7	was	be	AUX
ap-6763	119	8	updated	update	VERB
ap-6763	119	9	by	by	ADP
ap-6763	119	10	the	the	DET
ap-6763	119	11	value	value	NOUN
ap-6763	119	12	available	available	ADJ
ap-6763	119	13	in	in	ADP
ap-6763	119	14	the	the	DET
ap-6763	119	15	nearest	near	ADJ
ap-6763	119	16	cluster	cluster	NOUN
ap-6763	119	17	center	center	NOUN
ap-6763	119	18	.	.	PUNCT
ap-6763	120	1	step	step	NOUN
ap-6763	120	2	vii	vii	PROPN
ap-6763	120	3	of	of	ADP
ap-6763	120	4	the	the	DET
ap-6763	120	5	npspfcm	npspfcm	ADJ
ap-6763	120	6	algorithm	algorithm	NOUN
ap-6763	120	7	is	be	AUX
ap-6763	120	8	defined	define	VERB
ap-6763	120	9	as	as	ADP
ap-6763	120	10	follows	follow	VERB
ap-6763	120	11	.	.	PUNCT
ap-6763	121	1	step	step	NOUN
ap-6763	121	2	vii	vii	PROPN
ap-6763	121	3	:	:	PUNCT
ap-6763	121	4	calculate	calculate	NOUN
ap-6763	121	5	y(l	y(l	PROPN
ap-6763	121	6	)	)	PUNCT
ap-6763	121	7	m	m	PROPN
ap-6763	121	8	,	,	PUNCT
ap-6763	121	9	which	which	PRON
ap-6763	121	10	minimizes	minimize	VERB
ap-6763	121	11	the	the	DET
ap-6763	121	12	objective	objective	ADJ
ap-6763	121	13	function	function	NOUN
ap-6763	121	14	jm	jm	PROPN
ap-6763	121	15	,	,	PUNCT
ap-6763	121	16	τ	τ	PROPN
ap-6763	121	17	,	,	PUNCT
ap-6763	121	18	for	for	ADP
ap-6763	121	19	all	all	DET
ap-6763	121	20	ykj	ykj	NOUN
ap-6763	121	21	∈	∈	PROPN
ap-6763	122	1	ym	ym	INTJ
ap-6763	122	2	using	use	VERB
ap-6763	122	3	the	the	DET
ap-6763	122	4	following	follow	VERB
ap-6763	122	5	y	y	PROPN
ap-6763	122	6	(	(	PUNCT
ap-6763	122	7	l	l	NOUN
ap-6763	122	8	)	)	PUNCT
ap-6763	122	9	kj	kj	NOUN
ap-6763	122	10	=	=	PUNCT
ap-6763	122	11	v	v	PROPN
ap-6763	122	12	(	(	PUNCT
ap-6763	122	13	l	l	NOUN
ap-6763	122	14	)	)	PUNCT
ap-6763	122	15	ij	ij	NOUN
ap-6763	122	16	,	,	PUNCT
ap-6763	122	17	(	(	PUNCT
ap-6763	122	18	11	11	NUM
ap-6763	122	19	)	)	PUNCT
ap-6763	122	20	where	where	SCONJ
ap-6763	122	21	d2	d2	PROPN
ap-6763	122	22	ik	ik	PROPN
ap-6763	122	23	=	=	SYM
ap-6763	122	24	min	min	PROPN
ap-6763	122	25	{	{	PUNCT
ap-6763	122	26	d2	d2	PROPN
ap-6763	122	27	1k	1k	NOUN
ap-6763	122	28	,	,	PUNCT
ap-6763	122	29	d	d	NOUN
ap-6763	122	30	2	2	NUM
ap-6763	122	31	2k	2k	NUM
ap-6763	122	32	,	,	PUNCT
ap-6763	122	33	...	...	PUNCT
ap-6763	122	34	,	,	PUNCT
ap-6763	123	1	d	d	PROPN
ap-6763	123	2	2	2	NUM
ap-6763	123	3	ck	ck	NOUN
ap-6763	123	4	}	}	PUNCT
ap-6763	123	5	and	and	CCONJ
ap-6763	123	6	d2	d2	VERB
ap-6763	123	7	ck	ck	NOUN
ap-6763	123	8	=	=	SYM
ap-6763	123	9	‖xk	‖xk	NUM
ap-6763	123	10	−	−	NOUN
ap-6763	123	11	vc‖2	vc‖2	NOUN
ap-6763	123	12	.	.	PUNCT
ap-6763	124	1	now	now	ADV
ap-6763	124	2	,	,	PUNCT
ap-6763	124	3	set	set	VERB
ap-6763	124	4	l	l	NOUN
ap-6763	124	5	=	=	PUNCT
ap-6763	124	6	l+	l+	X
ap-6763	124	7	1	1	NUM
ap-6763	124	8	and	and	CCONJ
ap-6763	124	9	return	return	VERB
ap-6763	124	10	to	to	ADP
ap-6763	124	11	step	step	NOUN
ap-6763	124	12	ii	ii	PROPN
ap-6763	124	13	.	.	PUNCT
ap-6763	125	1	literature	literature	PROPN
ap-6763	125	2	[	[	X
ap-6763	125	3	13	13	NUM
ap-6763	125	4	]	]	PUNCT
ap-6763	125	5	presents	present	VERB
ap-6763	125	6	the	the	DET
ap-6763	125	7	time	time	NOUN
ap-6763	125	8	complexity	complexity	NOUN
ap-6763	125	9	of	of	ADP
ap-6763	125	10	the	the	DET
ap-6763	125	11	ocs	ocs	PROPN
ap-6763	125	12	and	and	CCONJ
ap-6763	125	13	nps	nps	PROPN
ap-6763	125	14	.	.	PUNCT
ap-6763	126	1	the	the	DET
ap-6763	126	2	time	time	NOUN
ap-6763	126	3	complexity	complexity	NOUN
ap-6763	126	4	for	for	ADP
ap-6763	126	5	the	the	DET
ap-6763	126	6	ocs	ocs	PROPN
ap-6763	126	7	and	and	CCONJ
ap-6763	126	8	nps	nps	PROPN
ap-6763	126	9	is	be	AUX
ap-6763	126	10	o(nc2d	o(nc2d	NOUN
ap-6763	126	11	)	)	PUNCT
ap-6763	126	12	,	,	PUNCT
ap-6763	126	13	respectively	respectively	ADV
ap-6763	126	14	,	,	PUNCT
ap-6763	126	15	where	where	SCONJ
ap-6763	126	16	n	n	PRON
ap-6763	126	17	is	be	AUX
ap-6763	126	18	the	the	DET
ap-6763	126	19	number	number	NOUN
ap-6763	126	20	of	of	ADP
ap-6763	126	21	data	datum	NOUN
ap-6763	126	22	ponts	pont	NOUN
ap-6763	126	23	,	,	PUNCT
ap-6763	126	24	c	c	PROPN
ap-6763	126	25	is	be	AUX
ap-6763	126	26	the	the	DET
ap-6763	126	27	number	number	NOUN
ap-6763	126	28	of	of	ADP
ap-6763	126	29	clusters	cluster	NOUN
ap-6763	126	30	,	,	PUNCT
ap-6763	126	31	and	and	CCONJ
ap-6763	126	32	d	d	NOUN
ap-6763	126	33	is	be	AUX
ap-6763	126	34	the	the	DET
ap-6763	126	35	dimension	dimension	NOUN
ap-6763	126	36	of	of	ADP
ap-6763	126	37	data	datum	NOUN
ap-6763	126	38	points	point	NOUN
ap-6763	126	39	.	.	PUNCT
ap-6763	127	1	the	the	DET
ap-6763	127	2	ocspfcm	ocspfcm	NOUN
ap-6763	127	3	and	and	CCONJ
ap-6763	127	4	npspfcm	npspfcm	ADJ
ap-6763	127	5	algorithms	algorithm	NOUN
ap-6763	127	6	proposed	propose	VERB
ap-6763	127	7	in	in	ADP
ap-6763	127	8	this	this	DET
ap-6763	127	9	research	research	NOUN
ap-6763	127	10	were	be	AUX
ap-6763	127	11	adapted	adapt	VERB
ap-6763	127	12	from	from	ADP
ap-6763	127	13	the	the	DET
ap-6763	127	14	ocs	ocs	PROPN
ap-6763	127	15	and	and	CCONJ
ap-6763	127	16	nps	nps	PROPN
ap-6763	127	17	with	with	ADP
ap-6763	127	18	the	the	DET
ap-6763	127	19	same	same	ADJ
ap-6763	127	20	time	time	NOUN
ap-6763	127	21	complexity	complexity	NOUN
ap-6763	127	22	,	,	PUNCT
ap-6763	127	23	namely	namely	ADV
ap-6763	127	24	o(nc2d	o(nc2d	NOUN
ap-6763	127	25	)	)	PUNCT
ap-6763	127	26	.	.	PUNCT
ap-6763	128	1	4	4	X
ap-6763	128	2	.	.	X
ap-6763	128	3	experimental	experimental	ADJ
ap-6763	128	4	setup	setup	NOUN
ap-6763	128	5	this	this	DET
ap-6763	128	6	study	study	NOUN
ap-6763	128	7	evaluated	evaluate	VERB
ap-6763	128	8	and	and	CCONJ
ap-6763	128	9	demonstrated	demonstrate	VERB
ap-6763	128	10	the	the	DET
ap-6763	128	11	potential	potential	NOUN
ap-6763	128	12	of	of	ADP
ap-6763	128	13	the	the	DET
ap-6763	128	14	ocspfcm	ocspfcm	NOUN
ap-6763	128	15	and	and	CCONJ
ap-6763	128	16	npspfcm	npspfcm	ADJ
ap-6763	128	17	for	for	ADP
ap-6763	128	18	clustering	cluster	VERB
ap-6763	128	19	incomplete	incomplete	ADJ
ap-6763	128	20	data	datum	NOUN
ap-6763	128	21	sets	set	NOUN
ap-6763	128	22	.	.	PUNCT
ap-6763	129	1	the	the	DET
ap-6763	129	2	experiments	experiment	NOUN
ap-6763	129	3	were	be	AUX
ap-6763	129	4	carried	carry	VERB
ap-6763	129	5	out	out	ADP
ap-6763	129	6	in	in	ADP
ap-6763	129	7	the	the	DET
ap-6763	129	8	following	follow	VERB
ap-6763	129	9	stages	stage	NOUN
ap-6763	129	10	.	.	PUNCT
ap-6763	130	1	firstly	firstly	ADV
ap-6763	130	2	,	,	PUNCT
ap-6763	130	3	the	the	DET
ap-6763	130	4	complete	complete	ADJ
ap-6763	130	5	data	data	NOUN
ap-6763	130	6	sets	set	NOUN
ap-6763	130	7	were	be	AUX
ap-6763	130	8	clustered	cluster	VERB
ap-6763	130	9	using	use	VERB
ap-6763	130	10	the	the	DET
ap-6763	130	11	pfcm	pfcm	ADJ
ap-6763	130	12	algorithm	algorithm	NOUN
ap-6763	130	13	to	to	PART
ap-6763	130	14	obtain	obtain	VERB
ap-6763	130	15	the	the	DET
ap-6763	130	16	distribution	distribution	NOUN
ap-6763	130	17	of	of	ADP
ap-6763	130	18	data	datum	NOUN
ap-6763	130	19	points	point	NOUN
ap-6763	130	20	in	in	ADP
ap-6763	130	21	the	the	DET
ap-6763	130	22	actual	actual	ADJ
ap-6763	130	23	cluster	cluster	NOUN
ap-6763	130	24	.	.	PUNCT
ap-6763	131	1	the	the	DET
ap-6763	131	2	result	result	NOUN
ap-6763	131	3	of	of	ADP
ap-6763	131	4	this	this	DET
ap-6763	131	5	stage	stage	NOUN
ap-6763	131	6	is	be	AUX
ap-6763	131	7	used	use	VERB
ap-6763	131	8	as	as	ADP
ap-6763	131	9	a	a	DET
ap-6763	131	10	base	base	NOUN
ap-6763	131	11	in	in	ADP
ap-6763	131	12	evaluating	evaluate	VERB
ap-6763	131	13	the	the	DET
ap-6763	131	14	performance	performance	NOUN
ap-6763	131	15	of	of	ADP
ap-6763	131	16	the	the	DET
ap-6763	131	17	ocspfcm	ocspfcm	NOUN
ap-6763	131	18	and	and	CCONJ
ap-6763	131	19	npspfcm	npspfcm	VERB
ap-6763	131	20	366	366	NUM
ap-6763	131	21	vol	vol	NOUN
ap-6763	131	22	.	.	PUNCT
ap-6763	132	1	61	61	NUM
ap-6763	132	2	no	no	NOUN
ap-6763	132	3	.	.	PUNCT
ap-6763	133	1	2/2021	2/2021	NUM
ap-6763	133	2	modified	modify	VERB
ap-6763	133	3	possibilistic	possibilistic	ADJ
ap-6763	133	4	fuzzy	fuzzy	ADJ
ap-6763	133	5	c	c	NOUN
ap-6763	133	6	-	-	PUNCT
ap-6763	133	7	means	mean	VERB
ap-6763	133	8	algorithm	algorithm	NOUN
ap-6763	133	9	algorithms	algorithm	NOUN
ap-6763	133	10	.	.	PUNCT
ap-6763	134	1	in	in	ADP
ap-6763	134	2	addition	addition	NOUN
ap-6763	134	3	,	,	PUNCT
ap-6763	134	4	the	the	DET
ap-6763	134	5	cluster	cluster	NOUN
ap-6763	134	6	validity	validity	NOUN
ap-6763	134	7	index	index	NOUN
ap-6763	134	8	was	be	AUX
ap-6763	134	9	used	use	VERB
ap-6763	134	10	to	to	PART
ap-6763	134	11	obtain	obtain	VERB
ap-6763	134	12	the	the	DET
ap-6763	134	13	optimal	optimal	ADJ
ap-6763	134	14	number	number	NOUN
ap-6763	134	15	of	of	ADP
ap-6763	134	16	clusters	cluster	NOUN
ap-6763	134	17	in	in	ADP
ap-6763	134	18	complete	complete	ADJ
ap-6763	134	19	data	datum	NOUN
ap-6763	134	20	sets	set	NOUN
ap-6763	134	21	.	.	PUNCT
ap-6763	135	1	the	the	DET
ap-6763	135	2	cluster	cluster	NOUN
ap-6763	135	3	validity	validity	NOUN
ap-6763	135	4	index	index	NOUN
ap-6763	135	5	used	use	VERB
ap-6763	135	6	is	be	AUX
ap-6763	135	7	the	the	DET
ap-6763	135	8	xie	xie	PROPN
ap-6763	135	9	-	-	PUNCT
ap-6763	135	10	beni	beni	PROPN
ap-6763	135	11	index	index	NOUN
ap-6763	135	12	shown	show	VERB
ap-6763	135	13	in	in	ADP
ap-6763	135	14	equation	equation	NOUN
ap-6763	135	15	(	(	PUNCT
ap-6763	135	16	12	12	NUM
ap-6763	135	17	)	)	PUNCT
ap-6763	135	18	,	,	PUNCT
ap-6763	135	19	with	with	ADP
ap-6763	135	20	a	a	DET
ap-6763	135	21	validity	validity	NOUN
ap-6763	135	22	index	index	NOUN
ap-6763	135	23	used	use	VERB
ap-6763	135	24	to	to	PART
ap-6763	135	25	measure	measure	VERB
ap-6763	135	26	and	and	CCONJ
ap-6763	135	27	determine	determine	VERB
ap-6763	135	28	the	the	DET
ap-6763	135	29	optimal	optimal	ADJ
ap-6763	135	30	number	number	NOUN
ap-6763	135	31	of	of	ADP
ap-6763	135	32	clusters	cluster	NOUN
ap-6763	135	33	.	.	PUNCT
ap-6763	136	1	furthermore	furthermore	ADV
ap-6763	136	2	,	,	PUNCT
ap-6763	136	3	the	the	DET
ap-6763	136	4	xiebeni	xiebeni	ADJ
ap-6763	136	5	index	index	NOUN
ap-6763	136	6	was	be	AUX
ap-6763	136	7	used	use	VERB
ap-6763	136	8	because	because	SCONJ
ap-6763	136	9	the	the	DET
ap-6763	136	10	partition	partition	NOUN
ap-6763	136	11	coefficient	coefficient	NOUN
ap-6763	136	12	(	(	PUNCT
ap-6763	136	13	pc	pc	NOUN
ap-6763	136	14	)	)	PUNCT
ap-6763	136	15	and	and	CCONJ
ap-6763	136	16	classification	classification	NOUN
ap-6763	136	17	entropy	entropy	NOUN
ap-6763	136	18	(	(	PUNCT
ap-6763	136	19	ce	ce	NOUN
ap-6763	136	20	)	)	PUNCT
ap-6763	136	21	indexes	index	NOUN
ap-6763	136	22	eliminate	eliminate	VERB
ap-6763	136	23	the	the	DET
ap-6763	136	24	cluster	cluster	NOUN
ap-6763	136	25	centre	centre	NOUN
ap-6763	136	26	and	and	CCONJ
ap-6763	136	27	data	datum	NOUN
ap-6763	136	28	in	in	ADP
ap-6763	136	29	the	the	DET
ap-6763	136	30	index	index	NOUN
ap-6763	136	31	calculation	calculation	NOUN
ap-6763	136	32	.	.	PUNCT
ap-6763	137	1	meanwhile	meanwhile	ADV
ap-6763	137	2	,	,	PUNCT
ap-6763	137	3	the	the	DET
ap-6763	137	4	cluster	cluster	NOUN
ap-6763	137	5	centre	centre	NOUN
ap-6763	137	6	and	and	CCONJ
ap-6763	137	7	data	datum	NOUN
ap-6763	137	8	are	be	AUX
ap-6763	137	9	two	two	NUM
ap-6763	137	10	basic	basic	ADJ
ap-6763	137	11	attributes	attribute	NOUN
ap-6763	137	12	involved	involve	VERB
ap-6763	137	13	in	in	ADP
ap-6763	137	14	a	a	DET
ap-6763	137	15	data	datum	NOUN
ap-6763	137	16	clustering	clustering	NOUN
ap-6763	137	17	process	process	NOUN
ap-6763	137	18	based	base	VERB
ap-6763	137	19	on	on	ADP
ap-6763	137	20	the	the	DET
ap-6763	137	21	fuzzy	fuzzy	ADJ
ap-6763	137	22	rule	rule	NOUN
ap-6763	137	23	[	[	X
ap-6763	137	24	14	14	NUM
ap-6763	137	25	]	]	PUNCT
ap-6763	137	26	.	.	PUNCT
ap-6763	138	1	the	the	DET
ap-6763	138	2	optimal	optimal	ADJ
ap-6763	138	3	number	number	NOUN
ap-6763	138	4	of	of	ADP
ap-6763	138	5	clusters	cluster	NOUN
ap-6763	138	6	is	be	AUX
ap-6763	138	7	indicated	indicate	VERB
ap-6763	138	8	by	by	ADP
ap-6763	138	9	the	the	DET
ap-6763	138	10	smallest	small	ADJ
ap-6763	138	11	xie	xie	PROPN
ap-6763	138	12	-	-	PUNCT
ap-6763	138	13	beni	beni	ADJ
ap-6763	138	14	index	index	NOUN
ap-6763	138	15	value	value	NOUN
ap-6763	138	16	.	.	PUNCT
ap-6763	139	1	xie	xie	PROPN
ap-6763	139	2	and	and	CCONJ
ap-6763	139	3	beni	beni	PROPN
ap-6763	139	4	[	[	X
ap-6763	139	5	15	15	NUM
ap-6763	139	6	]	]	PUNCT
ap-6763	139	7	proposed	propose	VERB
ap-6763	139	8	the	the	DET
ap-6763	139	9	cluster	cluster	NOUN
ap-6763	139	10	validity	validity	NOUN
ap-6763	139	11	index	index	NOUN
ap-6763	139	12	as	as	SCONJ
ap-6763	139	13	follows	follow	VERB
ap-6763	139	14	.	.	PUNCT
ap-6763	140	1	xb(u	xb(u	PROPN
ap-6763	140	2	,	,	PUNCT
ap-6763	140	3	v	v	INTJ
ap-6763	140	4	;	;	PUNCT
ap-6763	140	5	x	x	X
ap-6763	140	6	)	)	PUNCT
ap-6763	141	1	=	=	SYM
ap-6763	142	1	∑c	∑c	PROPN
ap-6763	142	2	i=1	i=1	PROPN
ap-6763	142	3	∑n	∑n	PROPN
ap-6763	142	4	k=1(uik)2	k=1(uik)2	PROPN
ap-6763	142	5	‖xk	‖xk	NUM
ap-6763	142	6	−	−	PROPN
ap-6763	142	7	vi‖2	vi‖2	PROPN
ap-6763	142	8	n	n	PROPN
ap-6763	142	9	·	·	SYM
ap-6763	142	10	min	min	NOUN
ap-6763	142	11	i	i	NOUN
ap-6763	142	12	6	6	NUM
ap-6763	142	13	=	=	SYM
ap-6763	142	14	j	j	PROPN
ap-6763	142	15	‖vi	‖vi	PROPN
ap-6763	142	16	−	−	PROPN
ap-6763	142	17	vj‖2	vj‖2	PROPN
ap-6763	142	18	.	.	PUNCT
ap-6763	143	1	(	(	PUNCT
ap-6763	143	2	12	12	NUM
ap-6763	143	3	)	)	PUNCT
ap-6763	143	4	the	the	DET
ap-6763	143	5	performance	performance	NOUN
ap-6763	143	6	of	of	ADP
ap-6763	143	7	the	the	DET
ap-6763	143	8	ocspfcm	ocspfcm	NOUN
ap-6763	143	9	and	and	CCONJ
ap-6763	143	10	npspfcm	npspfcm	ADJ
ap-6763	143	11	algorithms	algorithm	NOUN
ap-6763	143	12	is	be	AUX
ap-6763	143	13	evaluated	evaluate	VERB
ap-6763	143	14	on	on	ADP
ap-6763	143	15	the	the	DET
ap-6763	143	16	real	real	ADJ
ap-6763	143	17	-	-	PUNCT
ap-6763	143	18	world	world	NOUN
ap-6763	143	19	and	and	CCONJ
ap-6763	143	20	artificial	artificial	ADJ
ap-6763	143	21	data	data	NOUN
ap-6763	143	22	sets	set	NOUN
ap-6763	143	23	.	.	PUNCT
ap-6763	144	1	the	the	DET
ap-6763	144	2	real	real	ADJ
ap-6763	144	3	-	-	PUNCT
ap-6763	144	4	world	world	NOUN
ap-6763	144	5	data	datum	NOUN
ap-6763	144	6	sets	set	NOUN
ap-6763	144	7	are	be	AUX
ap-6763	144	8	iris	iris	NOUN
ap-6763	144	9	[	[	X
ap-6763	144	10	16	16	NUM
ap-6763	144	11	]	]	PUNCT
ap-6763	144	12	and	and	CCONJ
ap-6763	144	13	wine	wine	NOUN
ap-6763	144	14	[	[	X
ap-6763	144	15	17	17	NUM
ap-6763	144	16	]	]	PUNCT
ap-6763	144	17	downloaded	download	VERB
ap-6763	144	18	from	from	ADP
ap-6763	144	19	http://archive.ics	http://archive.ics	PRON
ap-6763	144	20	.	.	PUNCT
ap-6763	144	21	uci.edu/ml	uci.edu/ml	PUNCT
ap-6763	145	1	[	[	X
ap-6763	145	2	18	18	NUM
ap-6763	145	3	]	]	PUNCT
ap-6763	145	4	.	.	PUNCT
ap-6763	146	1	iris	iris	NOUN
ap-6763	146	2	data	datum	NOUN
ap-6763	146	3	sets	set	NOUN
ap-6763	146	4	consist	consist	VERB
ap-6763	146	5	of	of	ADP
ap-6763	146	6	150	150	NUM
ap-6763	146	7	data	data	NOUN
ap-6763	146	8	points	point	NOUN
ap-6763	146	9	with	with	ADP
ap-6763	146	10	4	4	NUM
ap-6763	146	11	features	feature	NOUN
ap-6763	146	12	,	,	PUNCT
ap-6763	146	13	with	with	ADP
ap-6763	146	14	a	a	DET
ap-6763	146	15	data	data	NOUN
ap-6763	146	16	size	size	NOUN
ap-6763	146	17	of	of	ADP
ap-6763	146	18	[	[	X
ap-6763	146	19	150×4	150×4	NUM
ap-6763	146	20	]	]	X
ap-6763	146	21	in	in	ADP
ap-6763	146	22	the	the	DET
ap-6763	146	23	matrix	matrix	NOUN
ap-6763	146	24	form	form	NOUN
ap-6763	146	25	.	.	PUNCT
ap-6763	147	1	wine	wine	NOUN
ap-6763	147	2	data	datum	NOUN
ap-6763	147	3	sets	set	NOUN
ap-6763	147	4	consist	consist	VERB
ap-6763	147	5	of	of	ADP
ap-6763	147	6	178	178	NUM
ap-6763	147	7	data	datum	NOUN
ap-6763	147	8	points	point	NOUN
ap-6763	147	9	with	with	ADP
ap-6763	147	10	13	13	NUM
ap-6763	147	11	features	feature	NOUN
ap-6763	147	12	,	,	PUNCT
ap-6763	147	13	with	with	ADP
ap-6763	147	14	a	a	DET
ap-6763	147	15	data	data	NOUN
ap-6763	147	16	size	size	NOUN
ap-6763	147	17	of	of	ADP
ap-6763	147	18	[	[	X
ap-6763	147	19	178×13	178×13	X
ap-6763	147	20	]	]	X
ap-6763	147	21	.	.	PUNCT
ap-6763	148	1	the	the	DET
ap-6763	148	2	artificial	artificial	ADJ
ap-6763	148	3	data	data	NOUN
ap-6763	148	4	sets	set	VERB
ap-6763	148	5	i	i	PRON
ap-6763	148	6	and	and	CCONJ
ap-6763	148	7	ii	ii	PROPN
ap-6763	148	8	used	use	VERB
ap-6763	148	9	were	be	AUX
ap-6763	148	10	generated	generate	VERB
ap-6763	148	11	from	from	ADP
ap-6763	148	12	the	the	DET
ap-6763	148	13	gaussian	gaussian	ADJ
ap-6763	148	14	mixture	mixture	NOUN
ap-6763	148	15	distribution	distribution	NOUN
ap-6763	148	16	rule	rule	NOUN
ap-6763	148	17	with	with	ADP
ap-6763	148	18	two	two	NUM
ap-6763	148	19	clusters	cluster	NOUN
ap-6763	148	20	.	.	PUNCT
ap-6763	149	1	the	the	DET
ap-6763	149	2	artificial	artificial	ADJ
ap-6763	149	3	data	datum	NOUN
ap-6763	149	4	set	set	VERB
ap-6763	149	5	i	i	PRON
ap-6763	149	6	consist	consist	VERB
ap-6763	149	7	of	of	ADP
ap-6763	149	8	1000	1000	NUM
ap-6763	149	9	data	data	NOUN
ap-6763	149	10	points	point	NOUN
ap-6763	149	11	with	with	ADP
ap-6763	149	12	2	2	NUM
ap-6763	149	13	features	feature	NOUN
ap-6763	149	14	and	and	CCONJ
ap-6763	149	15	a	a	DET
ap-6763	149	16	size	size	NOUN
ap-6763	149	17	of	of	ADP
ap-6763	149	18	[	[	X
ap-6763	149	19	1000×2	1000×2	NUM
ap-6763	149	20	]	]	PUNCT
ap-6763	149	21	.	.	PUNCT
ap-6763	150	1	a	a	DET
ap-6763	150	2	scatter	scatter	NOUN
ap-6763	150	3	plot	plot	NOUN
ap-6763	150	4	of	of	ADP
ap-6763	150	5	the	the	DET
ap-6763	150	6	artificial	artificial	ADJ
ap-6763	150	7	data	datum	NOUN
ap-6763	150	8	set	set	VERB
ap-6763	150	9	i	i	PRON
ap-6763	150	10	is	be	AUX
ap-6763	150	11	shown	show	VERB
ap-6763	150	12	in	in	ADP
ap-6763	150	13	figure	figure	NOUN
ap-6763	150	14	1	1	NUM
ap-6763	150	15	.	.	PUNCT
ap-6763	151	1	the	the	DET
ap-6763	151	2	artificial	artificial	ADJ
ap-6763	151	3	data	datum	NOUN
ap-6763	151	4	set	set	VERB
ap-6763	151	5	ii	ii	NUM
ap-6763	151	6	consist	consist	NOUN
ap-6763	151	7	of	of	ADP
ap-6763	151	8	1000	1000	NUM
ap-6763	151	9	data	data	NOUN
ap-6763	151	10	points	point	NOUN
ap-6763	151	11	with	with	ADP
ap-6763	151	12	14	14	NUM
ap-6763	151	13	features	feature	NOUN
ap-6763	151	14	with	with	ADP
ap-6763	151	15	a	a	DET
ap-6763	151	16	size	size	NOUN
ap-6763	151	17	of	of	ADP
ap-6763	151	18	[	[	X
ap-6763	151	19	1000×14	1000×14	NUM
ap-6763	151	20	]	]	PUNCT
ap-6763	151	21	.	.	PUNCT
ap-6763	152	1	the	the	DET
ap-6763	152	2	authors	author	NOUN
ap-6763	152	3	also	also	ADV
ap-6763	152	4	evaluated	evaluate	VERB
ap-6763	152	5	the	the	DET
ap-6763	152	6	performance	performance	NOUN
ap-6763	152	7	of	of	ADP
ap-6763	152	8	the	the	DET
ap-6763	152	9	ocspfcm	ocspfcm	NOUN
ap-6763	152	10	and	and	CCONJ
ap-6763	152	11	npspfcm	npspfcm	ADJ
ap-6763	152	12	on	on	ADP
ap-6763	152	13	larger	large	ADJ
ap-6763	152	14	data	datum	NOUN
ap-6763	152	15	sets	set	NOUN
ap-6763	152	16	,	,	PUNCT
ap-6763	152	17	namely	namely	ADV
ap-6763	152	18	the	the	DET
ap-6763	152	19	artificial	artificial	ADJ
ap-6763	152	20	data	datum	NOUN
ap-6763	152	21	set	set	VERB
ap-6763	152	22	iii	iii	NOUN
ap-6763	152	23	,	,	PUNCT
ap-6763	152	24	which	which	PRON
ap-6763	152	25	consist	consist	VERB
ap-6763	152	26	of	of	ADP
ap-6763	152	27	5000	5000	NUM
ap-6763	152	28	data	datum	NOUN
ap-6763	152	29	points	point	NOUN
ap-6763	152	30	with	with	ADP
ap-6763	152	31	7	7	NUM
ap-6763	152	32	features	feature	NOUN
ap-6763	152	33	with	with	ADP
ap-6763	152	34	a	a	DET
ap-6763	152	35	size	size	NOUN
ap-6763	152	36	of	of	ADP
ap-6763	152	37	[	[	X
ap-6763	152	38	5000×7	5000×7	NOUN
ap-6763	152	39	]	]	X
ap-6763	152	40	.	.	PUNCT
ap-6763	153	1	the	the	DET
ap-6763	153	2	artificial	artificial	ADJ
ap-6763	153	3	data	datum	NOUN
ap-6763	153	4	set	set	VERB
ap-6763	153	5	iii	iii	NUM
ap-6763	153	6	consists	consist	NOUN
ap-6763	153	7	of	of	ADP
ap-6763	153	8	five	five	NUM
ap-6763	153	9	clusters	cluster	NOUN
ap-6763	153	10	.	.	PUNCT
ap-6763	154	1	the	the	DET
ap-6763	154	2	row	row	NOUN
ap-6763	154	3	and	and	CCONJ
ap-6763	154	4	column	column	NOUN
ap-6763	154	5	of	of	ADP
ap-6763	154	6	the	the	DET
ap-6763	154	7	matrix	matrix	NOUN
ap-6763	154	8	represent	represent	VERB
ap-6763	154	9	the	the	DET
ap-6763	154	10	number	number	NOUN
ap-6763	154	11	of	of	ADP
ap-6763	154	12	data	datum	NOUN
ap-6763	154	13	points	point	NOUN
ap-6763	154	14	and	and	CCONJ
ap-6763	154	15	features	feature	NOUN
ap-6763	154	16	,	,	PUNCT
ap-6763	154	17	respectively	respectively	ADV
ap-6763	154	18	.	.	PUNCT
ap-6763	155	1	after	after	ADP
ap-6763	155	2	the	the	DET
ap-6763	155	3	clustering	clustering	NOUN
ap-6763	155	4	,	,	PUNCT
ap-6763	155	5	the	the	DET
ap-6763	155	6	complete	complete	ADJ
ap-6763	155	7	data	data	NOUN
ap-6763	155	8	sets	set	NOUN
ap-6763	155	9	were	be	AUX
ap-6763	155	10	made	make	VERB
ap-6763	155	11	into	into	ADP
ap-6763	155	12	incomplete	incomplete	ADJ
ap-6763	155	13	data	datum	NOUN
ap-6763	155	14	sets	set	NOUN
ap-6763	155	15	or	or	CCONJ
ap-6763	155	16	,	,	PUNCT
ap-6763	155	17	in	in	ADP
ap-6763	155	18	other	other	ADJ
ap-6763	155	19	words	word	NOUN
ap-6763	155	20	,	,	PUNCT
ap-6763	155	21	data	datum	NOUN
ap-6763	155	22	sets	set	NOUN
ap-6763	155	23	contain	contain	VERB
ap-6763	155	24	missing	missing	ADJ
ap-6763	155	25	values	value	NOUN
ap-6763	155	26	.	.	PUNCT
ap-6763	156	1	each	each	DET
ap-6763	156	2	data	datum	NOUN
ap-6763	156	3	set	set	VERB
ap-6763	156	4	consists	consist	VERB
ap-6763	156	5	of	of	ADP
ap-6763	156	6	missing	miss	VERB
ap-6763	156	7	values	value	NOUN
ap-6763	156	8	with	with	ADP
ap-6763	156	9	predetermined	predetermine	VERB
ap-6763	156	10	percentages	percentage	NOUN
ap-6763	156	11	of	of	ADP
ap-6763	156	12	5	5	NUM
ap-6763	156	13	%	%	NOUN
ap-6763	156	14	,	,	PUNCT
ap-6763	156	15	10	10	NUM
ap-6763	156	16	%	%	NOUN
ap-6763	156	17	,	,	PUNCT
ap-6763	156	18	15	15	NUM
ap-6763	156	19	%	%	NOUN
ap-6763	156	20	,	,	PUNCT
ap-6763	156	21	20	20	NUM
ap-6763	156	22	%	%	NOUN
ap-6763	156	23	,	,	PUNCT
ap-6763	156	24	25	25	NUM
ap-6763	156	25	%	%	NOUN
ap-6763	156	26	,	,	PUNCT
ap-6763	156	27	and	and	CCONJ
ap-6763	156	28	30	30	NUM
ap-6763	156	29	%	%	NOUN
ap-6763	156	30	.	.	PUNCT
ap-6763	157	1	furthermore	furthermore	ADV
ap-6763	157	2	,	,	PUNCT
ap-6763	157	3	the	the	DET
ap-6763	157	4	missing	miss	VERB
ap-6763	157	5	values	value	NOUN
ap-6763	157	6	were	be	AUX
ap-6763	157	7	randomly	randomly	ADV
ap-6763	157	8	determined	determine	VERB
ap-6763	157	9	in	in	ADP
ap-6763	157	10	the	the	DET
ap-6763	157	11	matrix	matrix	NOUN
ap-6763	157	12	column	column	NOUN
ap-6763	157	13	direction	direction	NOUN
ap-6763	157	14	of	of	ADP
ap-6763	157	15	the	the	DET
ap-6763	157	16	complete	complete	ADJ
ap-6763	157	17	the	the	DET
ap-6763	157	18	data	data	NOUN
ap-6763	157	19	sets	set	NOUN
ap-6763	157	20	.	.	PUNCT
ap-6763	158	1	the	the	DET
ap-6763	158	2	third	third	ADJ
ap-6763	158	3	stage	stage	NOUN
ap-6763	158	4	examined	examine	VERB
ap-6763	158	5	the	the	DET
ap-6763	158	6	performance	performance	NOUN
ap-6763	158	7	of	of	ADP
ap-6763	158	8	the	the	DET
ap-6763	158	9	ocspfcm	ocspfcm	NOUN
ap-6763	158	10	and	and	CCONJ
ap-6763	158	11	npspfcm	npspfcm	ADJ
ap-6763	158	12	algorithms	algorithm	NOUN
ap-6763	158	13	for	for	ADP
ap-6763	158	14	clustering	cluster	VERB
ap-6763	158	15	incomplete	incomplete	ADJ
ap-6763	158	16	data	datum	NOUN
ap-6763	158	17	sets	set	NOUN
ap-6763	158	18	.	.	PUNCT
ap-6763	159	1	the	the	DET
ap-6763	159	2	evaluation	evaluation	NOUN
ap-6763	159	3	is	be	AUX
ap-6763	159	4	based	base	VERB
ap-6763	159	5	on	on	ADP
ap-6763	159	6	three	three	NUM
ap-6763	159	7	aspects	aspect	NOUN
ap-6763	159	8	,	,	PUNCT
ap-6763	159	9	the	the	DET
ap-6763	159	10	percentage	percentage	NOUN
ap-6763	159	11	accuracy	accuracy	NOUN
ap-6763	159	12	,	,	PUNCT
ap-6763	159	13	the	the	DET
ap-6763	159	14	number	number	NOUN
ap-6763	159	15	of	of	ADP
ap-6763	159	16	iterations	iteration	NOUN
ap-6763	159	17	,	,	PUNCT
ap-6763	159	18	and	and	CCONJ
ap-6763	159	19	centroid	centroid	NOUN
ap-6763	159	20	errors	error	NOUN
ap-6763	159	21	.	.	PUNCT
ap-6763	160	1	the	the	DET
ap-6763	160	2	formula	formula	NOUN
ap-6763	160	3	used	use	VERB
ap-6763	160	4	to	to	PART
ap-6763	160	5	calculate	calculate	VERB
ap-6763	160	6	the	the	DET
ap-6763	160	7	percentage	percentage	NOUN
ap-6763	160	8	accuracy	accuracy	NOUN
ap-6763	160	9	is	be	AUX
ap-6763	160	10	as	as	SCONJ
ap-6763	160	11	follows	follow	VERB
ap-6763	160	12	[	[	X
ap-6763	160	13	19	19	NUM
ap-6763	160	14	]	]	PUNCT
ap-6763	160	15	.	.	PUNCT
ap-6763	161	1	%	%	NOUN
ap-6763	161	2	accuracy	accuracy	NOUN
ap-6763	162	1	=	=	PRON
ap-6763	162	2	a	a	PRON
ap-6763	162	3	n	n	NUM
ap-6763	162	4	100	100	NUM
ap-6763	162	5	%	%	NOUN
ap-6763	162	6	(	(	PUNCT
ap-6763	162	7	13	13	NUM
ap-6763	162	8	)	)	PUNCT
ap-6763	162	9	where	where	SCONJ
ap-6763	162	10	a	a	PRON
ap-6763	162	11	is	be	AUX
ap-6763	162	12	the	the	DET
ap-6763	162	13	number	number	NOUN
ap-6763	162	14	of	of	ADP
ap-6763	162	15	data	datum	NOUN
ap-6763	162	16	points	point	NOUN
ap-6763	162	17	clustered	cluster	VERB
ap-6763	162	18	correctly	correctly	ADV
ap-6763	162	19	and	and	CCONJ
ap-6763	162	20	n	n	PRON
ap-6763	162	21	is	be	AUX
ap-6763	162	22	the	the	DET
ap-6763	162	23	total	total	ADJ
ap-6763	162	24	number	number	NOUN
ap-6763	162	25	of	of	ADP
ap-6763	162	26	data	datum	NOUN
ap-6763	162	27	points	point	NOUN
ap-6763	162	28	.	.	PUNCT
ap-6763	163	1	in	in	ADP
ap-6763	163	2	this	this	DET
ap-6763	163	3	figure	figure	NOUN
ap-6763	163	4	1	1	NUM
ap-6763	163	5	.	.	PUNCT
ap-6763	163	6	artificial	artificial	ADJ
ap-6763	163	7	data	datum	NOUN
ap-6763	163	8	set	set	VERB
ap-6763	163	9	i	i	PRON
ap-6763	163	10	study	study	VERB
ap-6763	163	11	,	,	PUNCT
ap-6763	163	12	centroid	centroid	PROPN
ap-6763	163	13	errors	error	NOUN
ap-6763	163	14	are	be	AUX
ap-6763	163	15	the	the	DET
ap-6763	163	16	magnitude	magnitude	NOUN
ap-6763	163	17	of	of	ADP
ap-6763	163	18	the	the	DET
ap-6763	163	19	cluster	cluster	NOUN
ap-6763	163	20	centre	centre	NOUN
ap-6763	163	21	error	error	NOUN
ap-6763	163	22	for	for	ADP
ap-6763	163	23	an	an	DET
ap-6763	163	24	incomplete	incomplete	ADJ
ap-6763	163	25	data	datum	NOUN
ap-6763	163	26	set	set	VERB
ap-6763	163	27	clustered	clustered	ADJ
ap-6763	163	28	using	use	VERB
ap-6763	163	29	the	the	DET
ap-6763	163	30	ocspfcm	ocspfcm	NOUN
ap-6763	163	31	and	and	CCONJ
ap-6763	163	32	npspfcm	npspfcm	ADJ
ap-6763	163	33	algorithms	algorithm	NOUN
ap-6763	163	34	when	when	SCONJ
ap-6763	163	35	compared	compare	VERB
ap-6763	163	36	to	to	ADP
ap-6763	163	37	the	the	DET
ap-6763	163	38	cluster	cluster	NOUN
ap-6763	163	39	centre	centre	NOUN
ap-6763	163	40	of	of	ADP
ap-6763	163	41	a	a	DET
ap-6763	163	42	complete	complete	ADJ
ap-6763	163	43	data	datum	NOUN
ap-6763	163	44	set	set	VERB
ap-6763	163	45	clustered	clustered	ADJ
ap-6763	163	46	using	use	VERB
ap-6763	163	47	the	the	DET
ap-6763	163	48	pfcm	pfcm	ADJ
ap-6763	163	49	.	.	PUNCT
ap-6763	164	1	in	in	ADP
ap-6763	164	2	some	some	DET
ap-6763	164	3	applications	application	NOUN
ap-6763	164	4	,	,	PUNCT
ap-6763	164	5	knowing	know	VERB
ap-6763	164	6	the	the	DET
ap-6763	164	7	cluster	cluster	NOUN
ap-6763	164	8	centres	centre	NOUN
ap-6763	164	9	is	be	AUX
ap-6763	164	10	important	important	ADJ
ap-6763	164	11	to	to	PART
ap-6763	164	12	determine	determine	VERB
ap-6763	164	13	the	the	DET
ap-6763	164	14	partitioning	partitioning	NOUN
ap-6763	164	15	of	of	ADP
ap-6763	164	16	data	datum	NOUN
ap-6763	164	17	points	point	NOUN
ap-6763	164	18	[	[	X
ap-6763	164	19	1	1	NUM
ap-6763	164	20	]	]	PUNCT
ap-6763	164	21	.	.	PUNCT
ap-6763	165	1	therefore	therefore	ADV
ap-6763	165	2	,	,	PUNCT
ap-6763	165	3	this	this	DET
ap-6763	165	4	research	research	NOUN
ap-6763	165	5	evaluates	evaluate	VERB
ap-6763	165	6	the	the	DET
ap-6763	165	7	two	two	NUM
ap-6763	165	8	algorithms	algorithm	NOUN
ap-6763	165	9	by	by	ADP
ap-6763	165	10	calculating	calculate	VERB
ap-6763	165	11	the	the	DET
ap-6763	165	12	centroid	centroid	NOUN
ap-6763	165	13	errors	error	NOUN
ap-6763	165	14	at	at	ADP
ap-6763	165	15	each	each	DET
ap-6763	165	16	level	level	NOUN
ap-6763	165	17	of	of	ADP
ap-6763	165	18	the	the	DET
ap-6763	165	19	missing	miss	VERB
ap-6763	165	20	values	value	NOUN
ap-6763	165	21	.	.	PUNCT
ap-6763	166	1	the	the	DET
ap-6763	166	2	euclidean	euclidean	ADJ
ap-6763	166	3	distance	distance	NOUN
ap-6763	166	4	formula	formula	NOUN
ap-6763	166	5	is	be	AUX
ap-6763	166	6	used	use	VERB
ap-6763	166	7	to	to	PART
ap-6763	166	8	calculate	calculate	VERB
ap-6763	166	9	the	the	DET
ap-6763	166	10	centroid	centroid	NOUN
ap-6763	166	11	errors	error	NOUN
ap-6763	166	12	with	with	ADP
ap-6763	166	13	the	the	DET
ap-6763	166	14	centroid	centroid	NOUN
ap-6763	166	15	errors	error	NOUN
ap-6763	166	16	(	(	PUNCT
ap-6763	166	17	e	e	NOUN
ap-6763	166	18	)	)	PUNCT
ap-6763	166	19	averaged	average	VERB
ap-6763	166	20	using	use	VERB
ap-6763	166	21	the	the	DET
ap-6763	166	22	following	follow	VERB
ap-6763	166	23	formula	formula	NOUN
ap-6763	166	24	e	e	X
ap-6763	166	25	=	=	SYM
ap-6763	166	26	∑c	∑c	PROPN
ap-6763	166	27	i=1	i=1	X
ap-6763	166	28	ei	ei	NOUN
ap-6763	166	29	c	c	NOUN
ap-6763	166	30	.	.	PUNCT
ap-6763	167	1	(	(	PUNCT
ap-6763	167	2	14	14	NUM
ap-6763	167	3	)	)	PUNCT
ap-6763	167	4	where	where	SCONJ
ap-6763	167	5	ei	ei	NOUN
ap-6763	167	6	is	be	AUX
ap-6763	167	7	the	the	DET
ap-6763	167	8	i	i	PROPN
ap-6763	167	9	-	-	PUNCT
ap-6763	167	10	th	th	X
ap-6763	167	11	centroid	centroid	NOUN
ap-6763	167	12	error	error	NOUN
ap-6763	167	13	and	and	CCONJ
ap-6763	167	14	c	c	NOUN
ap-6763	167	15	is	be	AUX
ap-6763	167	16	the	the	DET
ap-6763	167	17	number	number	NOUN
ap-6763	167	18	of	of	ADP
ap-6763	167	19	clusters	cluster	NOUN
ap-6763	167	20	.	.	PUNCT
ap-6763	168	1	5	5	X
ap-6763	168	2	.	.	X
ap-6763	168	3	experimental	experimental	ADJ
ap-6763	168	4	results	result	NOUN
ap-6763	168	5	and	and	CCONJ
ap-6763	168	6	discussions	discussion	NOUN
ap-6763	168	7	when	when	SCONJ
ap-6763	168	8	carrying	carry	VERB
ap-6763	168	9	out	out	ADP
ap-6763	168	10	the	the	DET
ap-6763	168	11	experiment	experiment	NOUN
ap-6763	168	12	,	,	PUNCT
ap-6763	168	13	the	the	DET
ap-6763	168	14	first	first	ADJ
ap-6763	168	15	thing	thing	NOUN
ap-6763	168	16	to	to	PART
ap-6763	168	17	do	do	VERB
ap-6763	168	18	is	be	AUX
ap-6763	168	19	to	to	PART
ap-6763	168	20	cluster	cluster	VERB
ap-6763	168	21	the	the	DET
ap-6763	168	22	complete	complete	ADJ
ap-6763	168	23	data	data	NOUN
ap-6763	168	24	sets	set	NOUN
ap-6763	168	25	using	use	VERB
ap-6763	168	26	the	the	DET
ap-6763	168	27	pfcm	pfcm	ADJ
ap-6763	168	28	algorithm	algorithm	NOUN
ap-6763	168	29	with	with	ADP
ap-6763	168	30	the	the	DET
ap-6763	168	31	xie	xie	PROPN
ap-6763	168	32	-	-	PUNCT
ap-6763	168	33	beni	beni	PROPN
ap-6763	168	34	index	index	NOUN
ap-6763	168	35	as	as	ADP
ap-6763	168	36	the	the	DET
ap-6763	168	37	validity	validity	NOUN
ap-6763	168	38	index	index	NOUN
ap-6763	168	39	.	.	PUNCT
ap-6763	169	1	the	the	DET
ap-6763	169	2	result	result	NOUN
ap-6763	169	3	showed	show	VERB
ap-6763	169	4	that	that	SCONJ
ap-6763	169	5	the	the	DET
ap-6763	169	6	smallest	small	ADJ
ap-6763	169	7	xie	xie	PROPN
ap-6763	169	8	-	-	PUNCT
ap-6763	169	9	beni	beni	ADJ
ap-6763	169	10	index	index	NOUN
ap-6763	169	11	value	value	NOUN
ap-6763	169	12	for	for	ADP
ap-6763	169	13	iris	iris	NOUN
ap-6763	169	14	,	,	PUNCT
ap-6763	169	15	wine	wine	NOUN
ap-6763	169	16	,	,	PUNCT
ap-6763	169	17	artificial	artificial	ADJ
ap-6763	169	18	data	datum	NOUN
ap-6763	169	19	sets	set	VERB
ap-6763	169	20	i	i	PRON
ap-6763	169	21	,	,	PUNCT
ap-6763	169	22	and	and	CCONJ
ap-6763	169	23	ii	ii	NOUN
ap-6763	169	24	is	be	AUX
ap-6763	169	25	in	in	ADP
ap-6763	169	26	two	two	NUM
ap-6763	169	27	clusters	cluster	NOUN
ap-6763	169	28	.	.	PUNCT
ap-6763	170	1	this	this	PRON
ap-6763	170	2	is	be	AUX
ap-6763	170	3	in	in	ADP
ap-6763	170	4	line	line	NOUN
ap-6763	170	5	with	with	ADP
ap-6763	170	6	pakhira	pakhira	PROPN
ap-6763	170	7	et	et	PROPN
ap-6763	170	8	al	al	PROPN
ap-6763	170	9	.	.	PUNCT
ap-6763	171	1	[	[	X
ap-6763	171	2	20	20	NUM
ap-6763	171	3	]	]	PUNCT
ap-6763	171	4	using	use	VERB
ap-6763	171	5	the	the	DET
ap-6763	171	6	davies	davy	NOUN
ap-6763	171	7	-	-	PUNCT
ap-6763	171	8	bouldin	bouldin	NOUN
ap-6763	171	9	(	(	PUNCT
ap-6763	171	10	db	db	PROPN
ap-6763	171	11	)	)	PUNCT
ap-6763	171	12	and	and	CCONJ
ap-6763	171	13	the	the	DET
ap-6763	171	14	dunns	dunns	NOUN
ap-6763	171	15	indexes	index	NOUN
ap-6763	171	16	[	[	X
ap-6763	171	17	21	21	NUM
ap-6763	171	18	]	]	PUNCT
ap-6763	171	19	as	as	ADP
ap-6763	171	20	the	the	DET
ap-6763	171	21	cluster	cluster	NOUN
ap-6763	171	22	validity	validity	NOUN
ap-6763	171	23	index	index	NOUN
ap-6763	171	24	.	.	PUNCT
ap-6763	172	1	for	for	ADP
ap-6763	172	2	the	the	DET
ap-6763	172	3	complete	complete	ADJ
ap-6763	172	4	wine	wine	NOUN
ap-6763	172	5	data	data	NOUN
ap-6763	172	6	sets	set	NOUN
ap-6763	172	7	,	,	PUNCT
ap-6763	172	8	the	the	DET
ap-6763	172	9	optimal	optimal	ADJ
ap-6763	172	10	number	number	NOUN
ap-6763	172	11	of	of	ADP
ap-6763	172	12	clusters	cluster	NOUN
ap-6763	172	13	was	be	AUX
ap-6763	172	14	obtained	obtain	VERB
ap-6763	172	15	with	with	ADP
ap-6763	172	16	two	two	NUM
ap-6763	172	17	clusters	cluster	NOUN
ap-6763	172	18	.	.	PUNCT
ap-6763	173	1	this	this	PRON
ap-6763	173	2	is	be	AUX
ap-6763	173	3	in	in	ADP
ap-6763	173	4	line	line	NOUN
ap-6763	173	5	with	with	ADP
ap-6763	173	6	zhang	zhang	PROPN
ap-6763	173	7	et	et	PROPN
ap-6763	173	8	al	al	PROPN
ap-6763	173	9	.	.	PUNCT
ap-6763	174	1	[	[	X
ap-6763	174	2	22	22	NUM
ap-6763	174	3	]	]	PUNCT
ap-6763	174	4	using	use	VERB
ap-6763	174	5	the	the	DET
ap-6763	174	6	mpc	mpc	NOUN
ap-6763	174	7	and	and	CCONJ
ap-6763	174	8	mpa	mpa	PROPN
ap-6763	174	9	indexes	index	NOUN
ap-6763	174	10	[	[	X
ap-6763	174	11	23	23	NUM
ap-6763	174	12	]	]	PUNCT
ap-6763	174	13	as	as	ADP
ap-6763	174	14	the	the	DET
ap-6763	174	15	cluster	cluster	NOUN
ap-6763	174	16	validity	validity	NOUN
ap-6763	174	17	index	index	NOUN
ap-6763	174	18	.	.	PUNCT
ap-6763	175	1	for	for	ADP
ap-6763	175	2	artificial	artificial	ADJ
ap-6763	175	3	data	datum	NOUN
ap-6763	175	4	sets	set	VERB
ap-6763	175	5	i	i	PRON
ap-6763	175	6	and	and	CCONJ
ap-6763	175	7	ii	ii	PROPN
ap-6763	175	8	,	,	PUNCT
ap-6763	175	9	the	the	DET
ap-6763	175	10	optimal	optimal	ADJ
ap-6763	175	11	number	number	NOUN
ap-6763	175	12	of	of	ADP
ap-6763	175	13	clusters	cluster	NOUN
ap-6763	175	14	obtained	obtain	VERB
ap-6763	175	15	is	be	AUX
ap-6763	175	16	also	also	ADV
ap-6763	175	17	two	two	NUM
ap-6763	175	18	clusters	cluster	NOUN
ap-6763	175	19	.	.	PUNCT
ap-6763	176	1	meanwhile	meanwhile	ADV
ap-6763	176	2	,	,	PUNCT
ap-6763	176	3	for	for	ADP
ap-6763	176	4	the	the	DET
ap-6763	176	5	artificial	artificial	ADJ
ap-6763	176	6	dataset	dataset	NOUN
ap-6763	176	7	iii	iii	NOUN
ap-6763	176	8	,	,	PUNCT
ap-6763	176	9	the	the	DET
ap-6763	176	10	optimal	optimal	ADJ
ap-6763	176	11	number	number	NOUN
ap-6763	176	12	of	of	ADP
ap-6763	176	13	clusters	cluster	NOUN
ap-6763	176	14	obtained	obtain	VERB
ap-6763	176	15	is	be	AUX
ap-6763	176	16	five	five	NUM
ap-6763	176	17	clusters	cluster	NOUN
ap-6763	176	18	.	.	PUNCT
ap-6763	177	1	for	for	ADP
ap-6763	177	2	iris	iris	NOUN
ap-6763	177	3	data	datum	NOUN
ap-6763	177	4	sets	set	NOUN
ap-6763	177	5	,	,	PUNCT
ap-6763	177	6	the	the	DET
ap-6763	177	7	first	first	ADJ
ap-6763	177	8	and	and	CCONJ
ap-6763	177	9	second	second	ADJ
ap-6763	177	10	clusters	cluster	NOUN
ap-6763	177	11	consist	consist	VERB
ap-6763	177	12	of	of	ADP
ap-6763	177	13	50	50	NUM
ap-6763	177	14	and	and	CCONJ
ap-6763	177	15	100	100	NUM
ap-6763	177	16	data	datum	NOUN
ap-6763	177	17	points	point	NOUN
ap-6763	177	18	.	.	PUNCT
ap-6763	178	1	for	for	ADP
ap-6763	178	2	wine	wine	NOUN
ap-6763	178	3	data	data	NOUN
ap-6763	178	4	sets	set	NOUN
ap-6763	178	5	,	,	PUNCT
ap-6763	178	6	the	the	DET
ap-6763	178	7	first	first	ADJ
ap-6763	178	8	and	and	CCONJ
ap-6763	178	9	second	second	ADJ
ap-6763	178	10	clusters	cluster	NOUN
ap-6763	178	11	consist	consist	VERB
ap-6763	178	12	of	of	ADP
ap-6763	178	13	78	78	NUM
ap-6763	178	14	and	and	CCONJ
ap-6763	178	15	100	100	NUM
ap-6763	178	16	data	datum	NOUN
ap-6763	178	17	point	point	NOUN
ap-6763	178	18	members	member	NOUN
ap-6763	178	19	.	.	PUNCT
ap-6763	179	1	for	for	ADP
ap-6763	179	2	artificial	artificial	ADJ
ap-6763	179	3	data	datum	NOUN
ap-6763	179	4	sets	set	VERB
ap-6763	179	5	i	i	PRON
ap-6763	179	6	,	,	PUNCT
ap-6763	179	7	the	the	DET
ap-6763	179	8	first	first	ADJ
ap-6763	179	9	and	and	CCONJ
ap-6763	179	10	second	second	ADJ
ap-6763	179	11	clusters	cluster	NOUN
ap-6763	179	12	comprise	comprise	VERB
ap-6763	179	13	494	494	NUM
ap-6763	179	14	and	and	CCONJ
ap-6763	179	15	506	506	NUM
ap-6763	179	16	data	datum	NOUN
ap-6763	179	17	points	point	NOUN
ap-6763	179	18	members	member	NOUN
ap-6763	179	19	,	,	PUNCT
ap-6763	179	20	respectively	respectively	ADV
ap-6763	179	21	.	.	PUNCT
ap-6763	180	1	while	while	SCONJ
ap-6763	180	2	,	,	PUNCT
ap-6763	180	3	for	for	ADP
ap-6763	180	4	artificial	artificial	ADJ
ap-6763	180	5	data	datum	NOUN
ap-6763	180	6	sets	set	VERB
ap-6763	180	7	ii	ii	PROPN
ap-6763	180	8	,	,	PUNCT
ap-6763	180	9	the	the	DET
ap-6763	180	10	first	first	ADJ
ap-6763	180	11	and	and	CCONJ
ap-6763	180	12	second	second	ADJ
ap-6763	180	13	clusters	cluster	NOUN
ap-6763	180	14	consists	consist	VERB
ap-6763	180	15	of	of	ADP
ap-6763	180	16	510	510	NUM
ap-6763	180	17	and	and	CCONJ
ap-6763	180	18	490	490	NUM
ap-6763	180	19	data	datum	NOUN
ap-6763	180	20	points	point	NOUN
ap-6763	180	21	.	.	PUNCT
ap-6763	181	1	for	for	ADP
ap-6763	181	2	artificial	artificial	ADJ
ap-6763	181	3	dataset	dataset	NOUN
ap-6763	181	4	iii	iii	NOUN
ap-6763	181	5	,	,	PUNCT
ap-6763	181	6	972	972	NUM
ap-6763	181	7	,	,	PUNCT
ap-6763	181	8	367	367	NUM
ap-6763	181	9	http://archive.ics.uci.edu/ml	http://archive.ics.uci.edu/ml	NUM
ap-6763	181	10	http://archive.ics.uci.edu/ml	http://archive.ics.uci.edu/ml	ADJ
ap-6763	181	11	rustam	rustam	NOUN
ap-6763	181	12	,	,	PUNCT
ap-6763	181	13	k.	k.	PROPN
ap-6763	181	14	usman	usman	PROPN
ap-6763	181	15	,	,	PUNCT
ap-6763	181	16	m.	m.	NOUN
ap-6763	181	17	kamaruddin	kamaruddin	PROPN
ap-6763	181	18	et	et	PROPN
ap-6763	181	19	al	al	PROPN
ap-6763	181	20	.	.	PROPN
ap-6763	181	21	acta	acta	PROPN
ap-6763	181	22	polytechnica	polytechnica	PROPN
ap-6763	181	23	1081	1081	NUM
ap-6763	181	24	,	,	PUNCT
ap-6763	181	25	1016	1016	NUM
ap-6763	181	26	,	,	PUNCT
ap-6763	181	27	962	962	NUM
ap-6763	181	28	,	,	PUNCT
ap-6763	181	29	and	and	CCONJ
ap-6763	181	30	969	969	NUM
ap-6763	181	31	data	datum	NOUN
ap-6763	181	32	points	point	NOUN
ap-6763	181	33	were	be	AUX
ap-6763	181	34	members	member	NOUN
ap-6763	181	35	of	of	ADP
ap-6763	181	36	the	the	DET
ap-6763	181	37	first	first	ADJ
ap-6763	181	38	,	,	PUNCT
ap-6763	181	39	second	second	ADJ
ap-6763	181	40	,	,	PUNCT
ap-6763	181	41	third	third	ADJ
ap-6763	181	42	,	,	PUNCT
ap-6763	181	43	fourth	fourth	ADJ
ap-6763	181	44	,	,	PUNCT
ap-6763	181	45	and	and	CCONJ
ap-6763	181	46	fifth	fifth	ADJ
ap-6763	181	47	clusters	cluster	NOUN
ap-6763	181	48	,	,	PUNCT
ap-6763	181	49	respectively	respectively	ADV
ap-6763	181	50	.	.	PUNCT
ap-6763	182	1	these	these	DET
ap-6763	182	2	results	result	NOUN
ap-6763	182	3	are	be	AUX
ap-6763	182	4	a	a	DET
ap-6763	182	5	base	base	NOUN
ap-6763	182	6	to	to	ADP
ap-6763	182	7	the	the	DET
ap-6763	182	8	evaluation	evaluation	NOUN
ap-6763	182	9	of	of	ADP
ap-6763	182	10	the	the	DET
ap-6763	182	11	performance	performance	NOUN
ap-6763	182	12	of	of	ADP
ap-6763	182	13	the	the	DET
ap-6763	182	14	proposed	propose	VERB
ap-6763	182	15	ocspfcm	ocspfcm	NOUN
ap-6763	182	16	and	and	CCONJ
ap-6763	182	17	npspfcm	npspfcm	ADJ
ap-6763	182	18	.	.	PUNCT
ap-6763	183	1	due	due	ADP
ap-6763	183	2	to	to	ADP
ap-6763	183	3	fluctuating	fluctuate	VERB
ap-6763	183	4	results	result	NOUN
ap-6763	183	5	of	of	ADP
ap-6763	183	6	percentage	percentage	NOUN
ap-6763	183	7	accuracy	accuracy	NOUN
ap-6763	183	8	,	,	PUNCT
ap-6763	183	9	the	the	DET
ap-6763	183	10	number	number	NOUN
ap-6763	183	11	of	of	ADP
ap-6763	183	12	iterations	iteration	NOUN
ap-6763	183	13	and	and	CCONJ
ap-6763	183	14	centroid	centroid	NOUN
ap-6763	183	15	errors	error	NOUN
ap-6763	183	16	in	in	ADP
ap-6763	183	17	each	each	DET
ap-6763	183	18	experiment	experiment	NOUN
ap-6763	183	19	,	,	PUNCT
ap-6763	183	20	this	this	DET
ap-6763	183	21	deficiency	deficiency	NOUN
ap-6763	183	22	was	be	AUX
ap-6763	183	23	addressed	address	VERB
ap-6763	183	24	by	by	ADP
ap-6763	183	25	conducting	conduct	VERB
ap-6763	183	26	30	30	NUM
ap-6763	183	27	experiments	experiment	NOUN
ap-6763	183	28	with	with	ADP
ap-6763	183	29	each	each	DET
ap-6763	183	30	data	datum	NOUN
ap-6763	183	31	set	set	VERB
ap-6763	183	32	.	.	PUNCT
ap-6763	184	1	the	the	DET
ap-6763	184	2	mean	mean	NOUN
ap-6763	184	3	of	of	ADP
ap-6763	184	4	the	the	DET
ap-6763	184	5	30	30	NUM
ap-6763	184	6	values	value	NOUN
ap-6763	184	7	is	be	AUX
ap-6763	184	8	used	use	VERB
ap-6763	184	9	for	for	ADP
ap-6763	184	10	percentage	percentage	NOUN
ap-6763	184	11	accuracy	accuracy	NOUN
ap-6763	184	12	,	,	PUNCT
ap-6763	184	13	the	the	DET
ap-6763	184	14	number	number	NOUN
ap-6763	184	15	of	of	ADP
ap-6763	184	16	iterations	iteration	NOUN
ap-6763	184	17	,	,	PUNCT
ap-6763	184	18	and	and	CCONJ
ap-6763	184	19	centroid	centroid	NOUN
ap-6763	184	20	errors	error	NOUN
ap-6763	184	21	.	.	PUNCT
ap-6763	185	1	this	this	DET
ap-6763	185	2	study	study	NOUN
ap-6763	185	3	also	also	ADV
ap-6763	185	4	compared	compare	VERB
ap-6763	185	5	the	the	DET
ap-6763	185	6	performance	performance	NOUN
ap-6763	185	7	of	of	ADP
ap-6763	185	8	the	the	DET
ap-6763	185	9	ocspfcm	ocspfcm	NOUN
ap-6763	185	10	and	and	CCONJ
ap-6763	185	11	npspfcm	npspfcm	ADJ
ap-6763	185	12	with	with	ADP
ap-6763	185	13	three	three	NUM
ap-6763	185	14	clustering	clustering	ADJ
ap-6763	185	15	algorithms	algorithm	NOUN
ap-6763	185	16	for	for	ADP
ap-6763	185	17	the	the	DET
ap-6763	185	18	incomplete	incomplete	ADJ
ap-6763	185	19	data	data	NOUN
ap-6763	185	20	sets	set	NOUN
ap-6763	185	21	,	,	PUNCT
ap-6763	185	22	namely	namely	ADV
ap-6763	185	23	the	the	DET
ap-6763	185	24	ocsfcm	ocsfcm	NOUN
ap-6763	185	25	,	,	PUNCT
ap-6763	185	26	npsfcm	npsfcm	NOUN
ap-6763	185	27	[	[	X
ap-6763	185	28	4	4	NUM
ap-6763	185	29	]	]	PUNCT
ap-6763	185	30	,	,	PUNCT
ap-6763	185	31	and	and	CCONJ
ap-6763	185	32	kfcm	kfcm	PRON
ap-6763	186	1	[	[	X
ap-6763	186	2	24	24	NUM
ap-6763	186	3	]	]	PUNCT
ap-6763	186	4	.	.	PUNCT
ap-6763	187	1	our	our	PRON
ap-6763	187	2	comparison	comparison	NOUN
ap-6763	187	3	with	with	ADP
ap-6763	187	4	the	the	DET
ap-6763	187	5	kfcm	kfcm	PROPN
ap-6763	187	6	algorithm	algorithm	NOUN
ap-6763	187	7	uses	use	VERB
ap-6763	187	8	the	the	DET
ap-6763	187	9	gaussian	gaussian	ADJ
ap-6763	187	10	kernel	kernel	NOUN
ap-6763	187	11	function	function	VERB
ap-6763	187	12	with	with	ADP
ap-6763	187	13	σ	σ	PROPN
ap-6763	187	14	=	=	SYM
ap-6763	187	15	1	1	X
ap-6763	187	16	.	.	PUNCT
ap-6763	188	1	the	the	DET
ap-6763	188	2	sigma	sigma	PROPN
ap-6763	188	3	value	value	NOUN
ap-6763	188	4	(	(	PUNCT
ap-6763	188	5	σ	σ	NOUN
ap-6763	188	6	=	=	SYM
ap-6763	188	7	1	1	X
ap-6763	188	8	)	)	PUNCT
ap-6763	188	9	used	use	VERB
ap-6763	188	10	is	be	AUX
ap-6763	188	11	in	in	ADP
ap-6763	188	12	line	line	NOUN
ap-6763	188	13	with	with	ADP
ap-6763	188	14	zhang	zhang	PROPN
ap-6763	188	15	and	and	CCONJ
ap-6763	188	16	chen	chen	PROPN
ap-6763	188	17	as	as	ADP
ap-6763	188	18	initiators	initiator	NOUN
ap-6763	188	19	of	of	ADP
ap-6763	188	20	the	the	DET
ap-6763	188	21	kfcm	kfcm	PROPN
ap-6763	188	22	algorithm	algorithm	NOUN
ap-6763	188	23	[	[	X
ap-6763	188	24	24	24	NUM
ap-6763	188	25	]	]	PUNCT
ap-6763	188	26	.	.	PUNCT
ap-6763	189	1	here	here	ADV
ap-6763	189	2	,	,	PUNCT
ap-6763	189	3	we	we	PRON
ap-6763	189	4	use	use	VERB
ap-6763	189	5	the	the	DET
ap-6763	189	6	computational	computational	ADJ
ap-6763	189	7	condition	condition	NOUN
ap-6763	189	8	:	:	PUNCT
ap-6763	189	9	ε	ε	PROPN
ap-6763	189	10	=	=	SYM
ap-6763	189	11	0.00001	0.00001	NUM
ap-6763	189	12	,	,	PUNCT
ap-6763	189	13	maximum	maximum	ADJ
ap-6763	189	14	number	number	NOUN
ap-6763	189	15	of	of	ADP
ap-6763	189	16	iterations	iteration	NOUN
ap-6763	189	17	=	=	SYM
ap-6763	189	18	100	100	NUM
ap-6763	189	19	,	,	PUNCT
ap-6763	189	20	α	α	NOUN
ap-6763	189	21	=	=	SYM
ap-6763	189	22	1	1	NUM
ap-6763	189	23	,	,	PUNCT
ap-6763	189	24	β	β	X
ap-6763	189	25	=	=	SYM
ap-6763	189	26	1	1	NUM
ap-6763	189	27	,	,	PUNCT
ap-6763	189	28	m	m	VERB
ap-6763	189	29	=	=	NOUN
ap-6763	189	30	2	2	NUM
ap-6763	189	31	,	,	PUNCT
ap-6763	189	32	and	and	CCONJ
ap-6763	189	33	τ	τ	PROPN
ap-6763	189	34	=	=	SYM
ap-6763	189	35	2	2	NUM
ap-6763	189	36	.	.	NUM
ap-6763	189	37	5.1	5.1	NUM
ap-6763	189	38	.	.	PUNCT
ap-6763	190	1	experiment	experiment	NOUN
ap-6763	190	2	on	on	ADP
ap-6763	190	3	iris	iris	NOUN
ap-6763	190	4	data	datum	NOUN
ap-6763	190	5	sets	set	VERB
ap-6763	190	6	the	the	DET
ap-6763	190	7	results	result	NOUN
ap-6763	190	8	of	of	ADP
ap-6763	190	9	the	the	DET
ap-6763	190	10	complete	complete	ADJ
ap-6763	190	11	iris	iris	NOUN
ap-6763	190	12	data	datum	NOUN
ap-6763	190	13	set	set	VERB
ap-6763	190	14	clusters	cluster	NOUN
ap-6763	190	15	by	by	ADP
ap-6763	190	16	the	the	DET
ap-6763	190	17	pfcm	pfcm	PROPN
ap-6763	190	18	algorithm	algorithm	NOUN
ap-6763	190	19	are	be	AUX
ap-6763	190	20	used	use	VERB
ap-6763	190	21	as	as	ADP
ap-6763	190	22	a	a	DET
ap-6763	190	23	base	base	NOUN
ap-6763	190	24	to	to	PART
ap-6763	190	25	evaluate	evaluate	VERB
ap-6763	190	26	the	the	DET
ap-6763	190	27	performance	performance	NOUN
ap-6763	190	28	of	of	ADP
ap-6763	190	29	the	the	DET
ap-6763	190	30	ocspfcm	ocspfcm	NOUN
ap-6763	190	31	and	and	CCONJ
ap-6763	190	32	npspfcm	npspfcm	ADJ
ap-6763	190	33	on	on	ADP
ap-6763	190	34	incomplete	incomplete	ADJ
ap-6763	190	35	iris	iris	NOUN
ap-6763	190	36	data	datum	NOUN
ap-6763	190	37	sets	set	NOUN
ap-6763	190	38	.	.	PUNCT
ap-6763	191	1	table	table	NOUN
ap-6763	191	2	1	1	NUM
ap-6763	191	3	shows	show	VERB
ap-6763	191	4	the	the	DET
ap-6763	191	5	average	average	ADJ
ap-6763	191	6	accuracy	accuracy	NOUN
ap-6763	191	7	percentage	percentage	NOUN
ap-6763	191	8	for	for	ADP
ap-6763	191	9	iris	iris	NOUN
ap-6763	191	10	data	datum	NOUN
ap-6763	191	11	sets	set	NOUN
ap-6763	191	12	using	use	VERB
ap-6763	191	13	the	the	DET
ap-6763	191	14	ocspfcm	ocspfcm	ADJ
ap-6763	191	15	and	and	CCONJ
ap-6763	191	16	npspfcm	npspfcm	ADJ
ap-6763	191	17	algorithms	algorithm	NOUN
ap-6763	191	18	.	.	PUNCT
ap-6763	192	1	for	for	ADP
ap-6763	192	2	missing	miss	VERB
ap-6763	192	3	values	value	NOUN
ap-6763	192	4	below	below	ADP
ap-6763	192	5	15	15	NUM
ap-6763	192	6	%	%	NOUN
ap-6763	192	7	,	,	PUNCT
ap-6763	192	8	the	the	DET
ap-6763	192	9	ocspfcm	ocspfcm	PROPN
ap-6763	192	10	algorithm	algorithm	NOUN
ap-6763	192	11	had	have	VERB
ap-6763	192	12	the	the	DET
ap-6763	192	13	accuracy	accuracy	NOUN
ap-6763	192	14	percentage	percentage	NOUN
ap-6763	192	15	above	above	ADP
ap-6763	192	16	90	90	NUM
ap-6763	192	17	%	%	NOUN
ap-6763	192	18	.	.	PUNCT
ap-6763	193	1	however	however	ADV
ap-6763	193	2	,	,	PUNCT
ap-6763	193	3	for	for	ADP
ap-6763	193	4	missing	miss	VERB
ap-6763	193	5	values	value	NOUN
ap-6763	193	6	between	between	ADP
ap-6763	193	7	20	20	NUM
ap-6763	193	8	%	%	NOUN
ap-6763	193	9	to	to	PART
ap-6763	193	10	30	30	NUM
ap-6763	193	11	%	%	NOUN
ap-6763	193	12	,	,	PUNCT
ap-6763	193	13	the	the	DET
ap-6763	193	14	ocspfcm	ocspfcm	PROPN
ap-6763	193	15	algorithm	algorithm	NOUN
ap-6763	193	16	had	have	VERB
ap-6763	193	17	an	an	DET
ap-6763	193	18	accuracy	accuracy	NOUN
ap-6763	193	19	percentage	percentage	NOUN
ap-6763	193	20	above	above	ADP
ap-6763	193	21	80	80	NUM
ap-6763	193	22	%	%	NOUN
ap-6763	193	23	with	with	ADP
ap-6763	193	24	a	a	DET
ap-6763	193	25	maximum	maximum	NOUN
ap-6763	193	26	of	of	ADP
ap-6763	193	27	86	86	NUM
ap-6763	193	28	%	%	NOUN
ap-6763	193	29	.	.	PUNCT
ap-6763	194	1	the	the	DET
ap-6763	194	2	npspfcm	npspfcm	ADJ
ap-6763	194	3	algorithm	algorithm	NOUN
ap-6763	194	4	has	have	VERB
ap-6763	194	5	an	an	DET
ap-6763	194	6	accuracy	accuracy	NOUN
ap-6763	194	7	percentage	percentage	NOUN
ap-6763	194	8	above	above	ADP
ap-6763	194	9	90	90	NUM
ap-6763	194	10	%	%	NOUN
ap-6763	194	11	for	for	ADP
ap-6763	194	12	all	all	DET
ap-6763	194	13	tested	test	VERB
ap-6763	194	14	missing	missing	ADJ
ap-6763	194	15	values	value	NOUN
ap-6763	194	16	except	except	SCONJ
ap-6763	194	17	for	for	ADP
ap-6763	194	18	30	30	NUM
ap-6763	194	19	%	%	NOUN
ap-6763	194	20	,	,	PUNCT
ap-6763	194	21	with	with	ADP
ap-6763	194	22	an	an	DET
ap-6763	194	23	accuracy	accuracy	NOUN
ap-6763	194	24	of	of	ADP
ap-6763	194	25	89.13	89.13	NUM
ap-6763	194	26	%	%	NOUN
ap-6763	194	27	.	.	PUNCT
ap-6763	195	1	the	the	DET
ap-6763	195	2	percentage	percentage	NOUN
ap-6763	195	3	of	of	ADP
ap-6763	195	4	accuracy	accuracy	NOUN
ap-6763	195	5	shows	show	VERB
ap-6763	195	6	a	a	DET
ap-6763	195	7	significant	significant	ADJ
ap-6763	195	8	difference	difference	NOUN
ap-6763	195	9	above	above	ADP
ap-6763	195	10	20	20	NUM
ap-6763	195	11	%	%	NOUN
ap-6763	195	12	of	of	ADP
ap-6763	195	13	the	the	DET
ap-6763	195	14	total	total	ADJ
ap-6763	195	15	missing	miss	VERB
ap-6763	195	16	values	value	NOUN
ap-6763	195	17	.	.	PUNCT
ap-6763	196	1	table	table	NOUN
ap-6763	196	2	1	1	NUM
ap-6763	196	3	also	also	ADV
ap-6763	196	4	shows	show	VERB
ap-6763	196	5	that	that	SCONJ
ap-6763	196	6	the	the	PRON
ap-6763	196	7	greater	great	ADJ
ap-6763	196	8	the	the	DET
ap-6763	196	9	number	number	NOUN
ap-6763	196	10	of	of	ADP
ap-6763	196	11	missing	miss	VERB
ap-6763	196	12	values	value	NOUN
ap-6763	196	13	,	,	PUNCT
ap-6763	196	14	the	the	PRON
ap-6763	196	15	lower	low	ADJ
ap-6763	196	16	the	the	DET
ap-6763	196	17	accuracy	accuracy	NOUN
ap-6763	196	18	percentage	percentage	NOUN
ap-6763	196	19	.	.	PUNCT
ap-6763	197	1	furthermore	furthermore	ADV
ap-6763	197	2	,	,	PUNCT
ap-6763	197	3	the	the	DET
ap-6763	197	4	decrease	decrease	NOUN
ap-6763	197	5	in	in	ADP
ap-6763	197	6	the	the	DET
ap-6763	197	7	accuracy	accuracy	NOUN
ap-6763	197	8	percentage	percentage	NOUN
ap-6763	197	9	is	be	AUX
ap-6763	197	10	due	due	ADJ
ap-6763	197	11	to	to	ADP
ap-6763	197	12	the	the	DET
ap-6763	197	13	updated	update	VERB
ap-6763	197	14	missing	miss	VERB
ap-6763	197	15	values	value	NOUN
ap-6763	197	16	imputation	imputation	NOUN
ap-6763	197	17	,	,	PUNCT
ap-6763	197	18	which	which	PRON
ap-6763	197	19	falls	fall	VERB
ap-6763	197	20	far	far	ADV
ap-6763	197	21	from	from	ADP
ap-6763	197	22	the	the	DET
ap-6763	197	23	actual	actual	ADJ
ap-6763	197	24	value	value	NOUN
ap-6763	197	25	.	.	PUNCT
ap-6763	198	1	therefore	therefore	ADV
ap-6763	198	2	,	,	PUNCT
ap-6763	198	3	the	the	DET
ap-6763	198	4	data	data	NOUN
ap-6763	198	5	points	point	NOUN
ap-6763	198	6	that	that	PRON
ap-6763	198	7	contain	contain	VERB
ap-6763	198	8	the	the	DET
ap-6763	198	9	missing	miss	VERB
ap-6763	198	10	values	value	NOUN
ap-6763	198	11	become	become	VERB
ap-6763	198	12	members	member	NOUN
ap-6763	198	13	of	of	ADP
ap-6763	198	14	the	the	DET
ap-6763	198	15	inappropriate	inappropriate	ADJ
ap-6763	198	16	cluster	cluster	NOUN
ap-6763	198	17	.	.	PUNCT
ap-6763	199	1	an	an	DET
ap-6763	199	2	accuracy	accuracy	NOUN
ap-6763	199	3	percentage	percentage	NOUN
ap-6763	199	4	of	of	ADP
ap-6763	199	5	80	80	NUM
ap-6763	199	6	%	%	NOUN
ap-6763	199	7	in	in	ADP
ap-6763	199	8	the	the	DET
ap-6763	199	9	case	case	NOUN
ap-6763	199	10	of	of	ADP
ap-6763	199	11	the	the	DET
ap-6763	199	12	ocspfcm	ocspfcm	PROPN
ap-6763	199	13	algorithm	algorithm	NOUN
ap-6763	199	14	means	mean	VERB
ap-6763	199	15	that	that	SCONJ
ap-6763	199	16	there	there	PRON
ap-6763	199	17	are	be	VERB
ap-6763	199	18	130	130	NUM
ap-6763	199	19	data	datum	NOUN
ap-6763	199	20	points	point	NOUN
ap-6763	199	21	out	out	ADP
ap-6763	199	22	of	of	ADP
ap-6763	199	23	a	a	DET
ap-6763	199	24	total	total	NOUN
ap-6763	199	25	of	of	ADP
ap-6763	199	26	150	150	NUM
ap-6763	199	27	members	member	NOUN
ap-6763	199	28	of	of	ADP
ap-6763	199	29	the	the	DET
ap-6763	199	30	appropriate	appropriate	ADJ
ap-6763	199	31	cluster	cluster	NOUN
ap-6763	199	32	with	with	ADP
ap-6763	199	33	a	a	DET
ap-6763	199	34	30	30	NUM
ap-6763	199	35	%	%	NOUN
ap-6763	199	36	missing	miss	VERB
ap-6763	199	37	values	value	NOUN
ap-6763	199	38	.	.	PUNCT
ap-6763	200	1	in	in	ADP
ap-6763	200	2	addition	addition	NOUN
ap-6763	200	3	,	,	PUNCT
ap-6763	200	4	there	there	PRON
ap-6763	200	5	are	be	VERB
ap-6763	200	6	20	20	NUM
ap-6763	200	7	data	datum	NOUN
ap-6763	200	8	points	point	NOUN
ap-6763	200	9	that	that	PRON
ap-6763	200	10	are	be	AUX
ap-6763	200	11	members	member	NOUN
ap-6763	200	12	of	of	ADP
ap-6763	200	13	the	the	DET
ap-6763	200	14	inappropriate	inappropriate	ADJ
ap-6763	200	15	cluster	cluster	NOUN
ap-6763	200	16	.	.	PUNCT
ap-6763	201	1	while	while	SCONJ
ap-6763	201	2	89.13	89.13	NUM
ap-6763	201	3	%	%	NOUN
ap-6763	201	4	of	of	ADP
ap-6763	201	5	accuracy	accuracy	NOUN
ap-6763	201	6	percentage	percentage	NOUN
ap-6763	201	7	on	on	ADP
ap-6763	201	8	the	the	DET
ap-6763	201	9	npspfcm	npspfcm	ADJ
ap-6763	201	10	algorithm	algorithm	NOUN
ap-6763	201	11	means	mean	VERB
ap-6763	201	12	134	134	NUM
ap-6763	201	13	data	datum	NOUN
ap-6763	201	14	points	point	NOUN
ap-6763	201	15	are	be	AUX
ap-6763	201	16	members	member	NOUN
ap-6763	201	17	of	of	ADP
ap-6763	201	18	the	the	DET
ap-6763	201	19	appropriate	appropriate	ADJ
ap-6763	201	20	cluster	cluster	NOUN
ap-6763	201	21	.	.	PUNCT
ap-6763	202	1	in	in	ADP
ap-6763	202	2	contrast	contrast	NOUN
ap-6763	202	3	,	,	PUNCT
ap-6763	202	4	there	there	PRON
ap-6763	202	5	are	be	VERB
ap-6763	202	6	16	16	NUM
ap-6763	202	7	data	datum	NOUN
ap-6763	202	8	points	point	NOUN
ap-6763	202	9	that	that	PRON
ap-6763	202	10	are	be	AUX
ap-6763	202	11	members	member	NOUN
ap-6763	202	12	of	of	ADP
ap-6763	202	13	the	the	DET
ap-6763	202	14	inappropriate	inappropriate	ADJ
ap-6763	202	15	cluster	cluster	NOUN
ap-6763	202	16	.	.	PUNCT
ap-6763	203	1	from	from	ADP
ap-6763	203	2	table	table	NOUN
ap-6763	203	3	1	1	NUM
ap-6763	203	4	,	,	PUNCT
ap-6763	203	5	it	it	PRON
ap-6763	203	6	can	can	AUX
ap-6763	203	7	be	be	AUX
ap-6763	203	8	seen	see	VERB
ap-6763	203	9	that	that	SCONJ
ap-6763	203	10	the	the	DET
ap-6763	203	11	ocsfcm	ocsfcm	PROPN
ap-6763	203	12	has	have	VERB
ap-6763	203	13	the	the	DET
ap-6763	203	14	best	good	ADJ
ap-6763	203	15	performance	performance	NOUN
ap-6763	203	16	.	.	PUNCT
ap-6763	204	1	our	our	PRON
ap-6763	204	2	ocspfcm	ocspfcm	PROPN
ap-6763	204	3	outperforms	outperform	VERB
ap-6763	204	4	the	the	DET
ap-6763	204	5	npsfcm	npsfcm	NOUN
ap-6763	204	6	and	and	CCONJ
ap-6763	204	7	our	our	PRON
ap-6763	204	8	npspfcm	npspfcm	NOUN
ap-6763	204	9	has	have	VERB
ap-6763	204	10	almost	almost	ADV
ap-6763	204	11	the	the	DET
ap-6763	204	12	same	same	ADJ
ap-6763	204	13	performance	performance	NOUN
ap-6763	204	14	as	as	ADP
ap-6763	204	15	the	the	DET
ap-6763	204	16	npsfcm	npsfcm	NOUN
ap-6763	204	17	and	and	CCONJ
ap-6763	204	18	better	well	ADJ
ap-6763	204	19	than	than	ADP
ap-6763	204	20	kfcm	kfcm	PROPN
ap-6763	204	21	.	.	PUNCT
ap-6763	205	1	table	table	NOUN
ap-6763	205	2	2	2	NUM
ap-6763	205	3	shows	show	VERB
ap-6763	205	4	the	the	DET
ap-6763	205	5	behaviour	behaviour	NOUN
ap-6763	205	6	of	of	ADP
ap-6763	205	7	the	the	DET
ap-6763	205	8	ocspfcm	ocspfcm	NOUN
ap-6763	205	9	and	and	CCONJ
ap-6763	205	10	npspfcm	npspfcm	NOUN
ap-6763	205	11	that	that	PRON
ap-6763	205	12	is	be	AUX
ap-6763	205	13	inversely	inversely	ADV
ap-6763	205	14	proportional	proportional	ADJ
ap-6763	205	15	to	to	ADP
ap-6763	205	16	the	the	DET
ap-6763	205	17	accuracy	accuracy	NOUN
ap-6763	205	18	percentage	percentage	NOUN
ap-6763	205	19	and	and	CCONJ
ap-6763	205	20	the	the	DET
ap-6763	205	21	number	number	NOUN
ap-6763	205	22	of	of	ADP
ap-6763	205	23	iterations	iteration	NOUN
ap-6763	205	24	.	.	PUNCT
ap-6763	206	1	furthermore	furthermore	ADV
ap-6763	206	2	,	,	PUNCT
ap-6763	206	3	the	the	DET
ap-6763	206	4	percentage	percentage	NOUN
ap-6763	206	5	of	of	ADP
ap-6763	206	6	accuracy	accuracy	NOUN
ap-6763	206	7	inversely	inversely	ADV
ap-6763	206	8	decreases	decrease	VERB
ap-6763	206	9	with	with	ADP
ap-6763	206	10	an	an	DET
ap-6763	206	11	increase	increase	NOUN
ap-6763	206	12	in	in	ADP
ap-6763	206	13	the	the	DET
ap-6763	206	14	number	number	NOUN
ap-6763	206	15	of	of	ADP
ap-6763	206	16	iterations	iteration	NOUN
ap-6763	206	17	needed	need	VERB
ap-6763	206	18	.	.	PUNCT
ap-6763	207	1	an	an	DET
ap-6763	207	2	increase	increase	NOUN
ap-6763	207	3	in	in	ADP
ap-6763	207	4	the	the	DET
ap-6763	207	5	number	number	NOUN
ap-6763	207	6	of	of	ADP
ap-6763	207	7	missing	miss	VERB
ap-6763	207	8	values	value	NOUN
ap-6763	207	9	led	lead	VERB
ap-6763	207	10	to	to	ADP
ap-6763	207	11	a	a	DET
ap-6763	207	12	rise	rise	NOUN
ap-6763	207	13	in	in	ADP
ap-6763	207	14	the	the	DET
ap-6763	207	15	number	number	NOUN
ap-6763	207	16	of	of	ADP
ap-6763	207	17	iterations	iteration	NOUN
ap-6763	207	18	.	.	PUNCT
ap-6763	208	1	in	in	ADP
ap-6763	208	2	other	other	ADJ
ap-6763	208	3	words	word	NOUN
ap-6763	208	4	,	,	PUNCT
ap-6763	208	5	the	the	PRON
ap-6763	208	6	greater	great	ADJ
ap-6763	208	7	the	the	DET
ap-6763	208	8	number	number	NOUN
ap-6763	208	9	of	of	ADP
ap-6763	208	10	missing	miss	VERB
ap-6763	208	11	values	value	NOUN
ap-6763	208	12	,	,	PUNCT
ap-6763	208	13	the	the	DET
ap-6763	208	14	more	more	ADJ
ap-6763	208	15	iterations	iteration	NOUN
ap-6763	208	16	needed	need	VERB
ap-6763	208	17	for	for	ADP
ap-6763	208	18	the	the	DET
ap-6763	208	19	termination	termination	NOUN
ap-6763	208	20	.	.	PUNCT
ap-6763	209	1	the	the	DET
ap-6763	209	2	ocspfcm	ocspfcm	NOUN
ap-6763	209	3	requires	require	VERB
ap-6763	209	4	more	more	ADJ
ap-6763	209	5	iterations	iteration	NOUN
ap-6763	209	6	than	than	ADP
ap-6763	209	7	the	the	DET
ap-6763	209	8	npspfcm	npspfcm	NOUN
ap-6763	209	9	.	.	PUNCT
ap-6763	210	1	meanwhile	meanwhile	ADV
ap-6763	210	2	,	,	PUNCT
ap-6763	210	3	the	the	DET
ap-6763	210	4	ocsfcm	ocsfcm	PROPN
ap-6763	210	5	and	and	CCONJ
ap-6763	210	6	npspfcm	npspfcm	PROPN
ap-6763	210	7	provide	provide	VERB
ap-6763	210	8	almost	almost	ADV
ap-6763	210	9	the	the	DET
ap-6763	210	10	same	same	ADJ
ap-6763	210	11	and	and	CCONJ
ap-6763	210	12	better	well	ADJ
ap-6763	210	13	iteration	iteration	NOUN
ap-6763	210	14	performance	performance	NOUN
ap-6763	210	15	than	than	ADP
ap-6763	210	16	others.the	others.the	DET
ap-6763	210	17	npspfcm	npspfcm	PROPN
ap-6763	210	18	has	have	VERB
ap-6763	210	19	a	a	DET
ap-6763	210	20	better	well	ADJ
ap-6763	210	21	iteration	iteration	NOUN
ap-6763	210	22	performance	performance	NOUN
ap-6763	210	23	than	than	ADP
ap-6763	210	24	the	the	DET
ap-6763	210	25	ocspfcm	ocspfcm	NOUN
ap-6763	210	26	and	and	CCONJ
ap-6763	210	27	kfcm	kfcm	PROPN
ap-6763	210	28	.	.	PUNCT
ap-6763	211	1	table	table	NOUN
ap-6763	211	2	3	3	NUM
ap-6763	211	3	shows	show	VERB
ap-6763	211	4	the	the	DET
ap-6763	211	5	difference	difference	NOUN
ap-6763	211	6	in	in	ADP
ap-6763	211	7	centroid	centroid	NOUN
ap-6763	211	8	errors	error	NOUN
ap-6763	211	9	between	between	ADP
ap-6763	211	10	the	the	DET
ap-6763	211	11	ocspfcm	ocspfcm	NOUN
ap-6763	211	12	and	and	CCONJ
ap-6763	211	13	the	the	DET
ap-6763	211	14	npspfcm	npspfcm	NOUN
ap-6763	211	15	,	,	PUNCT
ap-6763	211	16	which	which	PRON
ap-6763	211	17	starts	start	VERB
ap-6763	211	18	to	to	PART
ap-6763	211	19	be	be	AUX
ap-6763	211	20	significant	significant	ADJ
ap-6763	211	21	at	at	ADP
ap-6763	211	22	20	20	NUM
ap-6763	211	23	%	%	NOUN
ap-6763	211	24	missing	miss	VERB
ap-6763	211	25	values	value	NOUN
ap-6763	211	26	.	.	PUNCT
ap-6763	212	1	the	the	DET
ap-6763	212	2	shift	shift	NOUN
ap-6763	212	3	of	of	ADP
ap-6763	212	4	the	the	DET
ap-6763	212	5	cluster	cluster	NOUN
ap-6763	212	6	center	center	NOUN
ap-6763	212	7	is	be	AUX
ap-6763	212	8	closely	closely	ADV
ap-6763	212	9	related	relate	VERB
ap-6763	212	10	to	to	ADP
ap-6763	212	11	the	the	DET
ap-6763	212	12	process	process	NOUN
ap-6763	212	13	of	of	ADP
ap-6763	212	14	updating	update	VERB
ap-6763	212	15	the	the	DET
ap-6763	212	16	missing	miss	VERB
ap-6763	212	17	values	value	NOUN
ap-6763	212	18	.	.	PUNCT
ap-6763	213	1	the	the	DET
ap-6763	213	2	shift	shift	NOUN
ap-6763	213	3	of	of	ADP
ap-6763	213	4	the	the	DET
ap-6763	213	5	clustre	clustre	NOUN
ap-6763	213	6	centre	centre	NOUN
ap-6763	213	7	is	be	AUX
ap-6763	213	8	closely	closely	ADV
ap-6763	213	9	related	relate	VERB
ap-6763	213	10	to	to	ADP
ap-6763	213	11	the	the	DET
ap-6763	213	12	process	process	NOUN
ap-6763	213	13	of	of	ADP
ap-6763	213	14	updating	update	VERB
ap-6763	213	15	the	the	DET
ap-6763	213	16	missing	miss	VERB
ap-6763	213	17	values	value	NOUN
ap-6763	213	18	.	.	PUNCT
ap-6763	214	1	the	the	DET
ap-6763	214	2	algorithm	algorithm	NOUN
ap-6763	214	3	-	-	PUNCT
ap-6763	214	4	updated	update	VERB
ap-6763	214	5	missing	miss	VERB
ap-6763	214	6	values	value	NOUN
ap-6763	214	7	imputation	imputation	NOUN
ap-6763	214	8	falls	fall	VERB
ap-6763	214	9	far	far	ADV
ap-6763	214	10	from	from	ADP
ap-6763	214	11	the	the	DET
ap-6763	214	12	actual	actual	ADJ
ap-6763	214	13	value	value	NOUN
ap-6763	214	14	and	and	CCONJ
ap-6763	214	15	a	a	DET
ap-6763	214	16	cluster	cluster	NOUN
ap-6763	214	17	centre	centre	NOUN
ap-6763	214	18	error	error	NOUN
ap-6763	214	19	occurs	occur	VERB
ap-6763	214	20	.	.	PUNCT
ap-6763	215	1	table	table	NOUN
ap-6763	215	2	3	3	NUM
ap-6763	215	3	also	also	ADV
ap-6763	215	4	shows	show	VERB
ap-6763	215	5	the	the	DET
ap-6763	215	6	process	process	NOUN
ap-6763	215	7	of	of	ADP
ap-6763	215	8	updating	update	VERB
ap-6763	215	9	the	the	DET
ap-6763	215	10	missing	miss	VERB
ap-6763	215	11	values	value	NOUN
ap-6763	215	12	imputation	imputation	NOUN
ap-6763	215	13	by	by	ADP
ap-6763	215	14	the	the	DET
ap-6763	215	15	npspfcm	npspfcm	ADJ
ap-6763	215	16	algorithm	algorithm	NOUN
ap-6763	215	17	comprising	comprising	NOUN
ap-6763	215	18	of	of	ADP
ap-6763	215	19	smaller	small	ADJ
ap-6763	215	20	cluster	cluster	NOUN
ap-6763	215	21	centre	centre	NOUN
ap-6763	215	22	(	(	PUNCT
ap-6763	215	23	centroid	centroid	NOUN
ap-6763	215	24	)	)	PUNCT
ap-6763	215	25	errors	error	NOUN
ap-6763	215	26	compared	compare	VERB
ap-6763	215	27	to	to	ADP
ap-6763	215	28	the	the	DET
ap-6763	215	29	ocspfcm	ocspfcm	PROPN
ap-6763	215	30	algorithm	algorithm	NOUN
ap-6763	215	31	,	,	PUNCT
ap-6763	215	32	and	and	CCONJ
ap-6763	215	33	it	it	PRON
ap-6763	215	34	outperforms	outperform	VERB
ap-6763	215	35	the	the	DET
ap-6763	215	36	kfcm	kfcm	NOUN
ap-6763	215	37	.	.	PUNCT
ap-6763	216	1	conversely	conversely	ADV
ap-6763	216	2	,	,	PUNCT
ap-6763	216	3	the	the	DET
ap-6763	216	4	ocsfcm	ocsfcm	NOUN
ap-6763	216	5	has	have	VERB
ap-6763	216	6	smaller	small	ADJ
ap-6763	216	7	centroid	centroid	NOUN
ap-6763	216	8	errors	error	NOUN
ap-6763	216	9	than	than	ADP
ap-6763	216	10	the	the	DET
ap-6763	216	11	npspfcm	npspfcm	NOUN
ap-6763	216	12	and	and	CCONJ
ap-6763	216	13	is	be	AUX
ap-6763	216	14	better	well	ADJ
ap-6763	216	15	than	than	ADP
ap-6763	216	16	other	other	ADJ
ap-6763	216	17	algorithms	algorithm	NOUN
ap-6763	216	18	.	.	PUNCT
ap-6763	217	1	from	from	ADP
ap-6763	217	2	table	table	NOUN
ap-6763	217	3	1	1	NUM
ap-6763	217	4	,	,	PUNCT
ap-6763	217	5	2	2	NUM
ap-6763	217	6	,	,	PUNCT
ap-6763	217	7	and	and	CCONJ
ap-6763	217	8	3	3	NUM
ap-6763	217	9	,	,	PUNCT
ap-6763	217	10	it	it	PRON
ap-6763	217	11	is	be	AUX
ap-6763	217	12	found	find	VERB
ap-6763	217	13	that	that	SCONJ
ap-6763	217	14	the	the	DET
ap-6763	217	15	npspfcm	npspfcm	NOUN
ap-6763	217	16	’s	’s	PART
ap-6763	217	17	performance	performance	NOUN
ap-6763	217	18	is	be	AUX
ap-6763	217	19	always	always	ADV
ap-6763	217	20	better	well	ADJ
ap-6763	217	21	than	than	ADP
ap-6763	217	22	that	that	PRON
ap-6763	217	23	of	of	ADP
ap-6763	217	24	the	the	DET
ap-6763	217	25	ocspfcm	ocspfcm	NOUN
ap-6763	217	26	and	and	CCONJ
ap-6763	217	27	kfcm	kfcm	NUM
ap-6763	217	28	,	,	PUNCT
ap-6763	217	29	but	but	CCONJ
ap-6763	217	30	not	not	PART
ap-6763	217	31	ocsfcm	ocsfcm	NOUN
ap-6763	217	32	.	.	PUNCT
ap-6763	218	1	5.2	5.2	NUM
ap-6763	218	2	.	.	PUNCT
ap-6763	218	3	experiment	experiment	NOUN
ap-6763	218	4	on	on	ADP
ap-6763	218	5	wine	wine	NOUN
ap-6763	218	6	data	data	NOUN
ap-6763	218	7	sets	set	NOUN
ap-6763	218	8	in	in	ADP
ap-6763	218	9	the	the	DET
ap-6763	218	10	wine	wine	NOUN
ap-6763	218	11	data	data	NOUN
ap-6763	218	12	sets	set	NOUN
ap-6763	218	13	,	,	PUNCT
ap-6763	218	14	evaluations	evaluation	NOUN
ap-6763	218	15	related	relate	VERB
ap-6763	218	16	to	to	ADP
ap-6763	218	17	the	the	DET
ap-6763	218	18	percentage	percentage	NOUN
ap-6763	218	19	accuracy	accuracy	NOUN
ap-6763	218	20	,	,	PUNCT
ap-6763	218	21	number	number	NOUN
ap-6763	218	22	of	of	ADP
ap-6763	218	23	iterations	iteration	NOUN
ap-6763	218	24	,	,	PUNCT
ap-6763	218	25	and	and	CCONJ
ap-6763	218	26	centroid	centroid	PROPN
ap-6763	218	27	errors	error	NOUN
ap-6763	218	28	are	be	AUX
ap-6763	218	29	,	,	PUNCT
ap-6763	218	30	respectively	respectively	ADV
ap-6763	218	31	,	,	PUNCT
ap-6763	218	32	shown	show	VERB
ap-6763	218	33	in	in	ADP
ap-6763	218	34	tables	table	NOUN
ap-6763	218	35	4	4	NUM
ap-6763	218	36	,	,	PUNCT
ap-6763	218	37	5	5	NUM
ap-6763	218	38	,	,	PUNCT
ap-6763	218	39	and	and	CCONJ
ap-6763	218	40	6	6	NUM
ap-6763	218	41	.	.	NOUN
ap-6763	218	42	table	table	NOUN
ap-6763	218	43	4	4	NUM
ap-6763	218	44	shows	show	VERB
ap-6763	218	45	the	the	DET
ap-6763	218	46	accuracy	accuracy	NOUN
ap-6763	218	47	percentage	percentage	NOUN
ap-6763	218	48	of	of	ADP
ap-6763	218	49	the	the	DET
ap-6763	218	50	ocspfcm	ocspfcm	NOUN
ap-6763	218	51	,	,	PUNCT
ap-6763	218	52	above	above	ADP
ap-6763	218	53	90	90	NUM
ap-6763	218	54	%	%	NOUN
ap-6763	218	55	(	(	PUNCT
ap-6763	218	56	5	5	NUM
ap-6763	218	57	%	%	NOUN
ap-6763	218	58	and	and	CCONJ
ap-6763	218	59	10	10	NUM
ap-6763	218	60	%	%	NOUN
ap-6763	218	61	missing	miss	VERB
ap-6763	218	62	values	value	NOUN
ap-6763	218	63	)	)	PUNCT
ap-6763	218	64	,	,	PUNCT
ap-6763	218	65	above	above	ADP
ap-6763	218	66	80	80	NUM
ap-6763	218	67	%	%	NOUN
ap-6763	218	68	(	(	PUNCT
ap-6763	218	69	15	15	NUM
ap-6763	218	70	%	%	NOUN
ap-6763	218	71	,	,	PUNCT
ap-6763	218	72	20	20	NUM
ap-6763	218	73	%	%	NOUN
ap-6763	218	74	,	,	PUNCT
ap-6763	218	75	and	and	CCONJ
ap-6763	218	76	25	25	NUM
ap-6763	218	77	%	%	NOUN
ap-6763	218	78	missing	miss	VERB
ap-6763	218	79	values	value	NOUN
ap-6763	218	80	)	)	PUNCT
ap-6763	218	81	,	,	PUNCT
ap-6763	218	82	and	and	CCONJ
ap-6763	218	83	74.72	74.72	NUM
ap-6763	218	84	%	%	NOUN
ap-6763	218	85	(	(	PUNCT
ap-6763	218	86	30	30	NUM
ap-6763	218	87	%	%	NOUN
ap-6763	218	88	missing	miss	VERB
ap-6763	218	89	values	value	NOUN
ap-6763	218	90	)	)	PUNCT
ap-6763	218	91	.	.	PUNCT
ap-6763	219	1	meanwhile	meanwhile	ADV
ap-6763	219	2	,	,	PUNCT
ap-6763	219	3	the	the	DET
ap-6763	219	4	npspfcm	npspfcm	ADJ
ap-6763	219	5	algorithm	algorithm	NOUN
ap-6763	219	6	as	as	ADP
ap-6763	219	7	an	an	DET
ap-6763	219	8	accuracy	accuracy	NOUN
ap-6763	219	9	percentage	percentage	NOUN
ap-6763	219	10	above	above	ADP
ap-6763	219	11	90	90	NUM
ap-6763	219	12	%	%	NOUN
ap-6763	219	13	for	for	ADP
ap-6763	219	14	all	all	DET
ap-6763	219	15	levels	level	NOUN
ap-6763	219	16	of	of	ADP
ap-6763	219	17	missing	miss	VERB
ap-6763	219	18	values	value	NOUN
ap-6763	219	19	,	,	PUNCT
ap-6763	219	20	except	except	SCONJ
ap-6763	219	21	for	for	ADP
ap-6763	219	22	the	the	DET
ap-6763	219	23	30	30	NUM
ap-6763	219	24	%	%	NOUN
ap-6763	219	25	with	with	ADP
ap-6763	219	26	an	an	DET
ap-6763	219	27	accuracy	accuracy	NOUN
ap-6763	219	28	of	of	ADP
ap-6763	219	29	89.89	89.89	NUM
ap-6763	219	30	%	%	NOUN
ap-6763	219	31	.	.	PUNCT
ap-6763	220	1	these	these	DET
ap-6763	220	2	algorithms	algorithm	NOUN
ap-6763	220	3	produced	produce	VERB
ap-6763	220	4	a	a	DET
ap-6763	220	5	percentage	percentage	NOUN
ap-6763	220	6	of	of	ADP
ap-6763	220	7	accuracy	accuracy	NOUN
ap-6763	220	8	that	that	PRON
ap-6763	220	9	decreases	decrease	VERB
ap-6763	220	10	with	with	ADP
ap-6763	220	11	the	the	DET
ap-6763	220	12	missing	miss	VERB
ap-6763	220	13	value	value	NOUN
ap-6763	220	14	.	.	PUNCT
ap-6763	221	1	for	for	ADP
ap-6763	221	2	the	the	DET
ap-6763	221	3	ocspfcm	ocspfcm	PROPN
ap-6763	221	4	algorithm	algorithm	NOUN
ap-6763	221	5	,	,	PUNCT
ap-6763	221	6	the	the	DET
ap-6763	221	7	percentage	percentage	NOUN
ap-6763	221	8	of	of	ADP
ap-6763	221	9	accuracy	accuracy	NOUN
ap-6763	221	10	is	be	AUX
ap-6763	221	11	74.72	74.72	NUM
ap-6763	221	12	%	%	NOUN
ap-6763	221	13	,	,	PUNCT
ap-6763	221	14	which	which	PRON
ap-6763	221	15	means	mean	VERB
ap-6763	221	16	that	that	SCONJ
ap-6763	221	17	with	with	ADP
ap-6763	221	18	30	30	NUM
ap-6763	221	19	%	%	NOUN
ap-6763	221	20	missing	miss	VERB
ap-6763	221	21	values	value	NOUN
ap-6763	221	22	,	,	PUNCT
ap-6763	221	23	there	there	PRON
ap-6763	221	24	are	be	VERB
ap-6763	221	25	133	133	NUM
ap-6763	221	26	data	datum	NOUN
ap-6763	221	27	points	point	NOUN
ap-6763	221	28	out	out	ADP
ap-6763	221	29	of	of	ADP
ap-6763	221	30	a	a	DET
ap-6763	221	31	total	total	NOUN
ap-6763	221	32	of	of	ADP
ap-6763	221	33	178	178	NUM
ap-6763	221	34	in	in	ADP
ap-6763	221	35	the	the	DET
ap-6763	221	36	appropriate	appropriate	ADJ
ap-6763	221	37	cluster	cluster	NOUN
ap-6763	221	38	.	.	PUNCT
ap-6763	222	1	conversely	conversely	ADV
ap-6763	222	2	,	,	PUNCT
ap-6763	222	3	there	there	PRON
ap-6763	222	4	are	be	VERB
ap-6763	222	5	45	45	NUM
ap-6763	222	6	data	datum	NOUN
ap-6763	222	7	points	point	NOUN
ap-6763	222	8	that	that	PRON
ap-6763	222	9	are	be	AUX
ap-6763	222	10	members	member	NOUN
ap-6763	222	11	of	of	ADP
ap-6763	222	12	an	an	DET
ap-6763	222	13	inappropriate	inappropriate	ADJ
ap-6763	222	14	cluster	cluster	NOUN
ap-6763	222	15	.	.	PUNCT
ap-6763	223	1	for	for	ADP
ap-6763	223	2	the	the	DET
ap-6763	223	3	npspfcm	npspfcm	ADJ
ap-6763	223	4	algorithm	algorithm	NOUN
ap-6763	223	5	,	,	PUNCT
ap-6763	223	6	the	the	DET
ap-6763	223	7	percentage	percentage	NOUN
ap-6763	223	8	of	of	ADP
ap-6763	223	9	accuracy	accuracy	NOUN
ap-6763	223	10	is	be	AUX
ap-6763	223	11	89.89	89.89	NUM
ap-6763	223	12	%	%	NOUN
ap-6763	223	13	,	,	PUNCT
ap-6763	223	14	which	which	PRON
ap-6763	223	15	means	mean	VERB
ap-6763	223	16	that	that	SCONJ
ap-6763	223	17	there	there	PRON
ap-6763	223	18	are	be	VERB
ap-6763	223	19	160	160	NUM
ap-6763	223	20	data	datum	NOUN
ap-6763	223	21	points	point	NOUN
ap-6763	223	22	out	out	ADP
ap-6763	223	23	of	of	ADP
ap-6763	223	24	a	a	DET
ap-6763	223	25	total	total	NOUN
ap-6763	223	26	of	of	ADP
ap-6763	223	27	178	178	NUM
ap-6763	223	28	members	member	NOUN
ap-6763	223	29	of	of	ADP
ap-6763	223	30	the	the	DET
ap-6763	223	31	appropriate	appropriate	ADJ
ap-6763	223	32	cluster	cluster	NOUN
ap-6763	223	33	at	at	ADP
ap-6763	223	34	the	the	DET
ap-6763	223	35	30	30	NUM
ap-6763	223	36	%	%	NOUN
ap-6763	223	37	missing	miss	VERB
ap-6763	223	38	values	value	NOUN
ap-6763	223	39	level	level	NOUN
ap-6763	223	40	.	.	PUNCT
ap-6763	224	1	conversely	conversely	ADV
ap-6763	224	2	,	,	PUNCT
ap-6763	224	3	18	18	NUM
ap-6763	224	4	data	datum	NOUN
ap-6763	224	5	points	point	NOUN
ap-6763	224	6	are	be	AUX
ap-6763	224	7	members	member	NOUN
ap-6763	224	8	of	of	ADP
ap-6763	224	9	an	an	DET
ap-6763	224	10	inappropriate	inappropriate	ADJ
ap-6763	224	11	cluster	cluster	NOUN
ap-6763	224	12	.	.	PUNCT
ap-6763	225	1	in	in	ADP
ap-6763	225	2	the	the	DET
ap-6763	225	3	wine	wine	NOUN
ap-6763	225	4	data	data	NOUN
ap-6763	225	5	sets	set	VERB
ap-6763	225	6	experiment	experiment	NOUN
ap-6763	225	7	,	,	PUNCT
ap-6763	225	8	the	the	DET
ap-6763	225	9	npspfcm	npspfcm	ADJ
ap-6763	225	10	accuracy	accuracy	NOUN
ap-6763	225	11	percentage	percentage	NOUN
ap-6763	225	12	outperforms	outperform	VERB
ap-6763	225	13	other	other	ADJ
ap-6763	225	14	algorithms	algorithm	NOUN
ap-6763	225	15	.	.	PUNCT
ap-6763	226	1	368	368	NUM
ap-6763	226	2	vol	vol	NOUN
ap-6763	226	3	.	.	PUNCT
ap-6763	226	4	61	61	NUM
ap-6763	226	5	no	no	NOUN
ap-6763	226	6	.	.	PUNCT
ap-6763	227	1	2/2021	2/2021	NUM
ap-6763	227	2	modified	modify	VERB
ap-6763	227	3	possibilistic	possibilistic	ADJ
ap-6763	227	4	fuzzy	fuzzy	ADJ
ap-6763	227	5	c	c	NOUN
ap-6763	227	6	-	-	PUNCT
ap-6763	227	7	means	means	NOUN
ap-6763	227	8	algorithm	algorithm	NOUN
ap-6763	227	9	missing	miss	VERB
ap-6763	227	10	values	value	NOUN
ap-6763	227	11	oscpfcm	oscpfcm	VERB
ap-6763	227	12	npspfcm	npspfcm	ADJ
ap-6763	227	13	ocsfcm	ocsfcm	PROPN
ap-6763	227	14	npsfcm	npsfcm	PROPN
ap-6763	227	15	kfcm	kfcm	PROPN
ap-6763	228	1	(	(	PUNCT
ap-6763	228	2	%	%	NOUN
ap-6763	228	3	)	)	PUNCT
ap-6763	228	4	(	(	PUNCT
ap-6763	228	5	%	%	INTJ
ap-6763	228	6	)	)	PUNCT
ap-6763	228	7	(	(	PUNCT
ap-6763	228	8	%	%	INTJ
ap-6763	228	9	)	)	PUNCT
ap-6763	228	10	(	(	PUNCT
ap-6763	228	11	%	%	INTJ
ap-6763	228	12	)	)	PUNCT
ap-6763	228	13	(	(	PUNCT
ap-6763	228	14	%	%	INTJ
ap-6763	228	15	)	)	PUNCT
ap-6763	228	16	(	(	PUNCT
ap-6763	228	17	%	%	INTJ
ap-6763	228	18	)	)	PUNCT
ap-6763	228	19	5	5	NUM
ap-6763	228	20	96.00	96.00	NUM
ap-6763	228	21	98.27	98.27	NUM
ap-6763	229	1	99.2	99.2	NUM
ap-6763	229	2	98.73	98.73	NUM
ap-6763	229	3	96.33	96.33	NUM
ap-6763	229	4	10	10	NUM
ap-6763	229	5	93.33	93.33	NUM
ap-6763	229	6	96.44	96.44	NUM
ap-6763	229	7	98.8	98.8	NUM
ap-6763	229	8	96.87	96.87	NUM
ap-6763	229	9	93.00	93.00	NUM
ap-6763	229	10	15	15	NUM
ap-6763	229	11	90.00	90.00	NUM
ap-6763	229	12	93.96	93.96	NUM
ap-6763	229	13	95.87	95.87	NUM
ap-6763	229	14	94.44	94.44	NUM
ap-6763	229	15	91.33	91.33	NUM
ap-6763	229	16	20	20	NUM
ap-6763	229	17	86.00	86.00	NUM
ap-6763	229	18	92.44	92.44	NUM
ap-6763	229	19	94.33	94.33	NUM
ap-6763	229	20	94.27	94.27	NUM
ap-6763	229	21	89.12	89.12	NUM
ap-6763	229	22	25	25	NUM
ap-6763	229	23	82.00	82.00	NUM
ap-6763	229	24	90.76	90.76	NUM
ap-6763	229	25	93.80	93.80	NUM
ap-6763	229	26	91.47	91.47	NUM
ap-6763	229	27	86.42	86.42	NUM
ap-6763	229	28	30	30	NUM
ap-6763	229	29	80.00	80.00	NUM
ap-6763	229	30	89.13	89.13	NUM
ap-6763	229	31	92.27	92.27	NUM
ap-6763	229	32	90.80	90.80	NUM
ap-6763	229	33	81.00	81.00	NUM
ap-6763	229	34	table	table	NOUN
ap-6763	229	35	1	1	NUM
ap-6763	229	36	.	.	PUNCT
ap-6763	230	1	the	the	DET
ap-6763	230	2	average	average	ADJ
ap-6763	230	3	accuracy	accuracy	NOUN
ap-6763	230	4	percentage	percentage	NOUN
ap-6763	230	5	for	for	ADP
ap-6763	230	6	iris	iris	NOUN
ap-6763	230	7	data	datum	NOUN
ap-6763	230	8	sets	set	NOUN
ap-6763	230	9	missing	miss	VERB
ap-6763	230	10	values	value	NOUN
ap-6763	230	11	oscpfcm	oscpfcm	VERB
ap-6763	230	12	npspfcm	npspfcm	ADJ
ap-6763	230	13	ocsfcm	ocsfcm	PROPN
ap-6763	230	14	npsfcm	npsfcm	PROPN
ap-6763	230	15	kfcm	kfcm	PROPN
ap-6763	230	16	(	(	PUNCT
ap-6763	230	17	%	%	NOUN
ap-6763	230	18	)	)	PUNCT
ap-6763	230	19	(	(	PUNCT
ap-6763	230	20	%	%	INTJ
ap-6763	230	21	)	)	PUNCT
ap-6763	230	22	(	(	PUNCT
ap-6763	230	23	%	%	INTJ
ap-6763	230	24	)	)	PUNCT
ap-6763	230	25	(	(	PUNCT
ap-6763	230	26	%	%	INTJ
ap-6763	230	27	)	)	PUNCT
ap-6763	230	28	(	(	PUNCT
ap-6763	230	29	%	%	INTJ
ap-6763	230	30	)	)	PUNCT
ap-6763	230	31	(	(	PUNCT
ap-6763	230	32	%	%	INTJ
ap-6763	230	33	)	)	PUNCT
ap-6763	230	34	5	5	NUM
ap-6763	230	35	14.03	14.03	NUM
ap-6763	230	36	13.90	13.90	NUM
ap-6763	230	37	12.90	12.90	NUM
ap-6763	230	38	11.30	11.30	NUM
ap-6763	230	39	28.50	28.50	NUM
ap-6763	230	40	10	10	NUM
ap-6763	230	41	17.03	17.03	NUM
ap-6763	230	42	16.50	16.50	NUM
ap-6763	230	43	14.40	14.40	NUM
ap-6763	230	44	12.20	12.20	NUM
ap-6763	230	45	33.10	33.10	NUM
ap-6763	230	46	15	15	NUM
ap-6763	230	47	20.63	20.63	NUM
ap-6763	230	48	19.03	19.03	NUM
ap-6763	230	49	17.40	17.40	NUM
ap-6763	230	50	13.22	13.22	NUM
ap-6763	230	51	45.00	45.00	NUM
ap-6763	230	52	20	20	NUM
ap-6763	230	53	23.40	23.40	NUM
ap-6763	230	54	20.77	20.77	NUM
ap-6763	230	55	16.70	16.70	NUM
ap-6763	230	56	14.00	14.00	NUM
ap-6763	230	57	70.20	70.20	NUM
ap-6763	230	58	25	25	NUM
ap-6763	230	59	30.33	30.33	NUM
ap-6763	230	60	25.80	25.80	NUM
ap-6763	230	61	18.30	18.30	NUM
ap-6763	230	62	16.90	16.90	NUM
ap-6763	230	63	82.00	82.00	NUM
ap-6763	230	64	30	30	NUM
ap-6763	230	65	35.07	35.07	NUM
ap-6763	230	66	29.77	29.77	NUM
ap-6763	230	67	20.90	20.90	NUM
ap-6763	230	68	19.20	19.20	NUM
ap-6763	230	69	83.00	83.00	NUM
ap-6763	230	70	table	table	NOUN
ap-6763	230	71	2	2	NUM
ap-6763	230	72	.	.	PUNCT
ap-6763	231	1	the	the	DET
ap-6763	231	2	average	average	ADJ
ap-6763	231	3	iterations	iteration	NOUN
ap-6763	231	4	for	for	ADP
ap-6763	231	5	iris	iris	NOUN
ap-6763	231	6	data	datum	NOUN
ap-6763	231	7	sets	set	NOUN
ap-6763	231	8	missing	miss	VERB
ap-6763	231	9	values	value	NOUN
ap-6763	231	10	oscpfcm	oscpfcm	VERB
ap-6763	231	11	npspfcm	npspfcm	ADJ
ap-6763	231	12	ocsfcm	ocsfcm	PROPN
ap-6763	231	13	npsfcm	npsfcm	PROPN
ap-6763	231	14	kfcm	kfcm	PROPN
ap-6763	231	15	(	(	PUNCT
ap-6763	231	16	%	%	NOUN
ap-6763	231	17	)	)	PUNCT
ap-6763	231	18	(	(	PUNCT
ap-6763	231	19	%	%	INTJ
ap-6763	231	20	)	)	PUNCT
ap-6763	231	21	(	(	PUNCT
ap-6763	231	22	%	%	INTJ
ap-6763	231	23	)	)	PUNCT
ap-6763	231	24	(	(	PUNCT
ap-6763	231	25	%	%	INTJ
ap-6763	231	26	)	)	PUNCT
ap-6763	231	27	(	(	PUNCT
ap-6763	231	28	%	%	INTJ
ap-6763	231	29	)	)	PUNCT
ap-6763	231	30	(	(	PUNCT
ap-6763	231	31	%	%	INTJ
ap-6763	231	32	)	)	PUNCT
ap-6763	231	33	5	5	NUM
ap-6763	231	34	0.014	0.014	NUM
ap-6763	231	35	0.002	0.002	NUM
ap-6763	231	36	0.002	0.002	NUM
ap-6763	231	37	0.002	0.002	NUM
ap-6763	231	38	0.0556	0.0556	NUM
ap-6763	231	39	10	10	NUM
ap-6763	231	40	0.029	0.029	NUM
ap-6763	231	41	0.005	0.005	NUM
ap-6763	231	42	0.002	0.002	NUM
ap-6763	231	43	0.006	0.006	NUM
ap-6763	231	44	0.2201	0.2201	NUM
ap-6763	231	45	15	15	NUM
ap-6763	231	46	0.060	0.060	NUM
ap-6763	231	47	0.015	0.015	NUM
ap-6763	231	48	0.016	0.016	NUM
ap-6763	231	49	0.019	0.019	NUM
ap-6763	231	50	0.5428	0.5428	NUM
ap-6763	231	51	20	20	NUM
ap-6763	231	52	0.106	0.106	NUM
ap-6763	231	53	0.023	0.023	NUM
ap-6763	231	54	0.024	0.024	NUM
ap-6763	231	55	0.018	0.018	NUM
ap-6763	231	56	1.0256	1.0256	NUM
ap-6763	231	57	25	25	NUM
ap-6763	231	58	0.185	0.185	NUM
ap-6763	231	59	0.031	0.031	NUM
ap-6763	231	60	0.023	0.023	NUM
ap-6763	231	61	0.040	0.040	NUM
ap-6763	231	62	6.9662	6.9662	NUM
ap-6763	231	63	30	30	NUM
ap-6763	231	64	0.228	0.228	NUM
ap-6763	231	65	0.043	0.043	NUM
ap-6763	231	66	0.034	0.034	NUM
ap-6763	231	67	0.070	0.070	NUM
ap-6763	231	68	15.5065	15.5065	NUM
ap-6763	231	69	table	table	NOUN
ap-6763	231	70	3	3	NUM
ap-6763	231	71	.	.	PUNCT
ap-6763	232	1	the	the	DET
ap-6763	232	2	average	average	ADJ
ap-6763	232	3	centroid	centroid	NOUN
ap-6763	232	4	errors	error	NOUN
ap-6763	232	5	for	for	ADP
ap-6763	232	6	iris	iris	NOUN
ap-6763	232	7	data	datum	NOUN
ap-6763	232	8	sets	set	NOUN
ap-6763	232	9	missing	miss	VERB
ap-6763	232	10	values	value	NOUN
ap-6763	232	11	oscpfcm	oscpfcm	VERB
ap-6763	232	12	npspfcm	npspfcm	ADJ
ap-6763	232	13	ocsfcm	ocsfcm	PROPN
ap-6763	232	14	npsfcm	npsfcm	PROPN
ap-6763	232	15	kfcm	kfcm	PROPN
ap-6763	232	16	(	(	PUNCT
ap-6763	232	17	%	%	NOUN
ap-6763	232	18	)	)	PUNCT
ap-6763	232	19	(	(	PUNCT
ap-6763	232	20	%	%	INTJ
ap-6763	232	21	)	)	PUNCT
ap-6763	232	22	(	(	PUNCT
ap-6763	232	23	%	%	INTJ
ap-6763	232	24	)	)	PUNCT
ap-6763	232	25	(	(	PUNCT
ap-6763	232	26	%	%	INTJ
ap-6763	232	27	)	)	PUNCT
ap-6763	232	28	(	(	PUNCT
ap-6763	232	29	%	%	INTJ
ap-6763	232	30	)	)	PUNCT
ap-6763	232	31	(	(	PUNCT
ap-6763	232	32	%	%	INTJ
ap-6763	232	33	)	)	PUNCT
ap-6763	232	34	5	5	NUM
ap-6763	232	35	98.31	98.31	NUM
ap-6763	232	36	97.38	97.38	NUM
ap-6763	232	37	97.53	97.53	NUM
ap-6763	232	38	97.36	97.36	NUM
ap-6763	232	39	96.62	96.62	NUM
ap-6763	232	40	10	10	NUM
ap-6763	232	41	93.26	93.26	NUM
ap-6763	232	42	96.63	96.63	NUM
ap-6763	232	43	95.89	95.89	NUM
ap-6763	232	44	95.38	95.38	NUM
ap-6763	232	45	93.82	93.82	NUM
ap-6763	232	46	15	15	NUM
ap-6763	232	47	89.36	89.36	NUM
ap-6763	232	48	94.38	94.38	NUM
ap-6763	232	49	89.32	89.32	NUM
ap-6763	232	50	89.32	89.32	NUM
ap-6763	232	51	88.76	88.76	NUM
ap-6763	232	52	20	20	NUM
ap-6763	232	53	84.27	84.27	NUM
ap-6763	232	54	92.88	92.88	NUM
ap-6763	232	55	85.17	85.17	NUM
ap-6763	232	56	84.27	84.27	NUM
ap-6763	232	57	85.95	85.95	NUM
ap-6763	232	58	25	25	NUM
ap-6763	232	59	80.82	80.82	NUM
ap-6763	232	60	90.64	90.64	NUM
ap-6763	232	61	79.27	79.27	NUM
ap-6763	232	62	78.09	78.09	NUM
ap-6763	232	63	84.26	84.26	NUM
ap-6763	232	64	30	30	NUM
ap-6763	232	65	74.72	74.72	NUM
ap-6763	232	66	89.89	89.89	NUM
ap-6763	232	67	74.72	74.72	NUM
ap-6763	232	68	74.71	74.71	NUM
ap-6763	232	69	78.08	78.08	NUM
ap-6763	232	70	table	table	NOUN
ap-6763	232	71	4	4	NUM
ap-6763	232	72	.	.	PUNCT
ap-6763	233	1	the	the	DET
ap-6763	233	2	average	average	ADJ
ap-6763	233	3	accuracy	accuracy	NOUN
ap-6763	233	4	percentage	percentage	NOUN
ap-6763	233	5	for	for	ADP
ap-6763	233	6	wine	wine	NOUN
ap-6763	233	7	data	datum	NOUN
ap-6763	233	8	sets	set	VERB
ap-6763	233	9	369	369	NUM
ap-6763	233	10	rustam	rustam	NOUN
ap-6763	233	11	,	,	PUNCT
ap-6763	233	12	k.	k.	PROPN
ap-6763	233	13	usman	usman	PROPN
ap-6763	233	14	,	,	PUNCT
ap-6763	233	15	m.	m.	NOUN
ap-6763	233	16	kamaruddin	kamaruddin	PROPN
ap-6763	233	17	et	et	PROPN
ap-6763	233	18	al	al	PROPN
ap-6763	233	19	.	.	PROPN
ap-6763	233	20	acta	acta	PROPN
ap-6763	233	21	polytechnica	polytechnica	PROPN
ap-6763	233	22	table	table	NOUN
ap-6763	233	23	5	5	NUM
ap-6763	233	24	shows	show	VERB
ap-6763	233	25	that	that	SCONJ
ap-6763	233	26	the	the	DET
ap-6763	233	27	npspfcm	npspfcm	ADJ
ap-6763	233	28	algorithm	algorithm	NOUN
ap-6763	233	29	provided	provide	VERB
ap-6763	233	30	a	a	DET
ap-6763	233	31	number	number	NOUN
ap-6763	233	32	of	of	ADP
ap-6763	233	33	more	more	ADV
ap-6763	233	34	efficient	efficient	ADJ
ap-6763	233	35	iterations	iteration	NOUN
ap-6763	233	36	than	than	ADP
ap-6763	233	37	the	the	DET
ap-6763	233	38	ocspfcm	ocspfcm	NOUN
ap-6763	233	39	and	and	CCONJ
ap-6763	233	40	kfcm	kfcm	PRON
ap-6763	233	41	.	.	PUNCT
ap-6763	234	1	however	however	ADV
ap-6763	234	2	,	,	PUNCT
ap-6763	234	3	the	the	DET
ap-6763	234	4	ocspfcm	ocspfcm	NOUN
ap-6763	234	5	and	and	CCONJ
ap-6763	234	6	npspfcm	npspfcm	ADJ
ap-6763	234	7	are	be	AUX
ap-6763	234	8	no	no	PRON
ap-6763	234	9	more	more	ADV
ap-6763	234	10	efficient	efficient	ADJ
ap-6763	234	11	compared	compare	VERB
ap-6763	234	12	to	to	ADP
ap-6763	234	13	the	the	DET
ap-6763	234	14	ocsfcm	ocsfcm	NOUN
ap-6763	234	15	and	and	CCONJ
ap-6763	234	16	npsfcm	npsfcm	NOUN
ap-6763	234	17	.	.	PROPN
ap-6763	234	18	table	table	NOUN
ap-6763	234	19	6	6	NUM
ap-6763	234	20	shows	show	VERB
ap-6763	234	21	the	the	DET
ap-6763	234	22	average	average	ADJ
ap-6763	234	23	centroid	centroid	NOUN
ap-6763	234	24	errors	error	NOUN
ap-6763	234	25	in	in	ADP
ap-6763	234	26	wine	wine	NOUN
ap-6763	234	27	data	data	NOUN
ap-6763	234	28	sets	set	NOUN
ap-6763	234	29	using	use	VERB
ap-6763	234	30	the	the	DET
ap-6763	234	31	ocspfcm	ocspfcm	ADJ
ap-6763	234	32	and	and	CCONJ
ap-6763	234	33	npspfcm	npspfcm	ADJ
ap-6763	234	34	algorithms	algorithm	NOUN
ap-6763	234	35	.	.	PUNCT
ap-6763	235	1	furthermore	furthermore	ADV
ap-6763	235	2	,	,	PUNCT
ap-6763	235	3	there	there	PRON
ap-6763	235	4	is	be	VERB
ap-6763	235	5	a	a	DET
ap-6763	235	6	larger	large	ADJ
ap-6763	235	7	centroid	centroid	NOUN
ap-6763	235	8	error	error	NOUN
ap-6763	235	9	in	in	ADP
ap-6763	235	10	the	the	DET
ap-6763	235	11	case	case	NOUN
ap-6763	235	12	of	of	ADP
ap-6763	235	13	the	the	DET
ap-6763	235	14	ocspfcm	ocspfcm	ADJ
ap-6763	235	15	algorithm	algorithm	NOUN
ap-6763	235	16	than	than	ADP
ap-6763	235	17	in	in	ADP
ap-6763	235	18	the	the	DET
ap-6763	235	19	case	case	NOUN
ap-6763	235	20	of	of	ADP
ap-6763	235	21	the	the	DET
ap-6763	235	22	npspfcm	npspfcm	NOUN
ap-6763	235	23	at	at	ADP
ap-6763	235	24	all	all	DET
ap-6763	235	25	levels	level	NOUN
ap-6763	235	26	of	of	ADP
ap-6763	235	27	the	the	DET
ap-6763	235	28	total	total	ADJ
ap-6763	235	29	missing	miss	VERB
ap-6763	235	30	values	value	NOUN
ap-6763	235	31	,	,	PUNCT
ap-6763	235	32	except	except	SCONJ
ap-6763	235	33	at	at	ADP
ap-6763	235	34	15	15	NUM
ap-6763	235	35	%	%	NOUN
ap-6763	235	36	,	,	PUNCT
ap-6763	235	37	where	where	SCONJ
ap-6763	235	38	the	the	DET
ap-6763	235	39	npspfcm	npspfcm	NOUN
ap-6763	235	40	gives	give	VERB
ap-6763	235	41	larger	large	ADJ
ap-6763	235	42	centroid	centroid	NOUN
ap-6763	235	43	errors	error	NOUN
ap-6763	235	44	.	.	PUNCT
ap-6763	236	1	the	the	DET
ap-6763	236	2	npspfcm	npspfcm	PROPN
ap-6763	236	3	has	have	VERB
ap-6763	236	4	smaller	small	ADJ
ap-6763	236	5	centroid	centroid	NOUN
ap-6763	236	6	errors	error	NOUN
ap-6763	236	7	than	than	ADP
ap-6763	236	8	the	the	DET
ap-6763	236	9	ocspfcm	ocspfcm	NOUN
ap-6763	236	10	and	and	CCONJ
ap-6763	236	11	kfm	kfm	PROPN
ap-6763	236	12	.	.	PUNCT
ap-6763	237	1	meanwhile	meanwhile	ADV
ap-6763	237	2	,	,	PUNCT
ap-6763	237	3	the	the	DET
ap-6763	237	4	ocsfcm	ocsfcm	PROPN
ap-6763	237	5	and	and	CCONJ
ap-6763	237	6	npsfcm	npsfcm	PROPN
ap-6763	237	7	have	have	VERB
ap-6763	237	8	smaller	small	ADJ
ap-6763	237	9	centroid	centroid	NOUN
ap-6763	237	10	errors	error	NOUN
ap-6763	237	11	than	than	ADP
ap-6763	237	12	the	the	DET
ap-6763	237	13	other	other	ADJ
ap-6763	237	14	three	three	NUM
ap-6763	237	15	algorithms	algorithm	NOUN
ap-6763	237	16	.	.	PUNCT
ap-6763	238	1	5.3	5.3	NUM
ap-6763	238	2	.	.	PUNCT
ap-6763	238	3	experiment	experiment	NOUN
ap-6763	238	4	on	on	ADP
ap-6763	238	5	artificial	artificial	ADJ
ap-6763	238	6	data	datum	NOUN
ap-6763	238	7	sets	set	VERB
ap-6763	238	8	i	i	PRON
ap-6763	238	9	in	in	ADP
ap-6763	238	10	the	the	DET
ap-6763	238	11	artificial	artificial	ADJ
ap-6763	238	12	data	datum	NOUN
ap-6763	238	13	set	set	VERB
ap-6763	238	14	i	i	PRON
ap-6763	238	15	,	,	PUNCT
ap-6763	238	16	evaluations	evaluation	NOUN
ap-6763	238	17	related	relate	VERB
ap-6763	238	18	to	to	ADP
ap-6763	238	19	the	the	DET
ap-6763	238	20	percentage	percentage	NOUN
ap-6763	238	21	of	of	ADP
ap-6763	238	22	accuracy	accuracy	NOUN
ap-6763	238	23	,	,	PUNCT
ap-6763	238	24	number	number	NOUN
ap-6763	238	25	of	of	ADP
ap-6763	238	26	iterations	iteration	NOUN
ap-6763	238	27	,	,	PUNCT
ap-6763	238	28	and	and	CCONJ
ap-6763	238	29	centroid	centroid	PROPN
ap-6763	238	30	errors	error	NOUN
ap-6763	238	31	are	be	AUX
ap-6763	238	32	,	,	PUNCT
ap-6763	238	33	respectively	respectively	ADV
ap-6763	238	34	,	,	PUNCT
ap-6763	238	35	shown	show	VERB
ap-6763	238	36	in	in	ADP
ap-6763	238	37	tables	table	NOUN
ap-6763	238	38	7	7	NUM
ap-6763	238	39	,	,	PUNCT
ap-6763	238	40	8	8	NUM
ap-6763	238	41	,	,	PUNCT
ap-6763	238	42	and	and	CCONJ
ap-6763	238	43	9	9	NUM
ap-6763	238	44	.	.	NOUN
ap-6763	238	45	table	table	NOUN
ap-6763	238	46	7	7	NUM
ap-6763	238	47	shows	show	VERB
ap-6763	238	48	that	that	SCONJ
ap-6763	238	49	the	the	DET
ap-6763	238	50	ocspfcm	ocspfcm	NOUN
ap-6763	238	51	below	below	ADP
ap-6763	238	52	20	20	NUM
ap-6763	238	53	%	%	NOUN
ap-6763	238	54	of	of	ADP
ap-6763	238	55	the	the	DET
ap-6763	238	56	missing	miss	VERB
ap-6763	238	57	values	value	NOUN
ap-6763	238	58	gives	give	VERB
ap-6763	238	59	an	an	DET
ap-6763	238	60	accuracy	accuracy	NOUN
ap-6763	238	61	percentage	percentage	NOUN
ap-6763	238	62	above	above	ADP
ap-6763	238	63	90	90	NUM
ap-6763	238	64	%	%	NOUN
ap-6763	238	65	.	.	PUNCT
ap-6763	239	1	the	the	DET
ap-6763	239	2	npspfcm	npspfcm	ADJ
ap-6763	239	3	algorithm	algorithm	NOUN
ap-6763	239	4	comprises	comprise	NOUN
ap-6763	239	5	of	of	ADP
ap-6763	239	6	an	an	DET
ap-6763	239	7	accuracy	accuracy	NOUN
ap-6763	239	8	performance	performance	NOUN
ap-6763	239	9	above	above	ADP
ap-6763	239	10	90	90	NUM
ap-6763	239	11	%	%	NOUN
ap-6763	239	12	,	,	PUNCT
ap-6763	239	13	with	with	ADP
ap-6763	239	14	30	30	NUM
ap-6763	239	15	%	%	NOUN
ap-6763	239	16	missing	miss	VERB
ap-6763	239	17	values	value	NOUN
ap-6763	239	18	.	.	PUNCT
ap-6763	240	1	the	the	DET
ap-6763	240	2	npspfcm	npspfcm	ADJ
ap-6763	240	3	algorithm	algorithm	NOUN
ap-6763	240	4	produces	produce	VERB
ap-6763	240	5	an	an	DET
ap-6763	240	6	accuracy	accuracy	NOUN
ap-6763	240	7	percentage	percentage	NOUN
ap-6763	240	8	above	above	ADP
ap-6763	240	9	90	90	NUM
ap-6763	240	10	%	%	NOUN
ap-6763	240	11	,	,	PUNCT
ap-6763	240	12	except	except	SCONJ
ap-6763	240	13	for	for	ADP
ap-6763	240	14	30	30	NUM
ap-6763	240	15	%	%	NOUN
ap-6763	240	16	missing	miss	VERB
ap-6763	240	17	values	value	NOUN
ap-6763	240	18	,	,	PUNCT
ap-6763	240	19	which	which	PRON
ap-6763	240	20	has	have	VERB
ap-6763	240	21	88.86	88.86	NUM
ap-6763	240	22	%	%	NOUN
ap-6763	240	23	.	.	PUNCT
ap-6763	241	1	this	this	PRON
ap-6763	241	2	means	mean	VERB
ap-6763	241	3	that	that	SCONJ
ap-6763	241	4	with	with	ADP
ap-6763	241	5	30	30	NUM
ap-6763	241	6	%	%	NOUN
ap-6763	241	7	missing	miss	VERB
ap-6763	241	8	values	value	NOUN
ap-6763	241	9	,	,	PUNCT
ap-6763	241	10	there	there	PRON
ap-6763	241	11	are	be	VERB
ap-6763	241	12	886	886	NUM
ap-6763	241	13	data	datum	NOUN
ap-6763	241	14	points	point	NOUN
ap-6763	241	15	out	out	ADP
ap-6763	241	16	of	of	ADP
ap-6763	241	17	a	a	DET
ap-6763	241	18	total	total	NOUN
ap-6763	241	19	of	of	ADP
ap-6763	241	20	1000	1000	NUM
ap-6763	241	21	members	member	NOUN
ap-6763	241	22	of	of	ADP
ap-6763	241	23	the	the	DET
ap-6763	241	24	appropriate	appropriate	ADJ
ap-6763	241	25	cluster	cluster	NOUN
ap-6763	241	26	and	and	CCONJ
ap-6763	241	27	114	114	NUM
ap-6763	241	28	data	datum	NOUN
ap-6763	241	29	points	point	NOUN
ap-6763	241	30	in	in	ADP
ap-6763	241	31	the	the	DET
ap-6763	241	32	inappropriate	inappropriate	ADJ
ap-6763	241	33	cluster	cluster	NOUN
ap-6763	241	34	.	.	PUNCT
ap-6763	242	1	while	while	SCONJ
ap-6763	242	2	in	in	ADP
ap-6763	242	3	the	the	DET
ap-6763	242	4	case	case	NOUN
ap-6763	242	5	of	of	ADP
ap-6763	242	6	the	the	DET
ap-6763	242	7	ocspfcm	ocspfcm	PROPN
ap-6763	242	8	algorithm	algorithm	NOUN
ap-6763	242	9	,	,	PUNCT
ap-6763	242	10	84.90	84.90	NUM
ap-6763	242	11	%	%	NOUN
ap-6763	242	12	means	mean	VERB
ap-6763	242	13	that	that	SCONJ
ap-6763	242	14	there	there	PRON
ap-6763	242	15	are	be	VERB
ap-6763	242	16	849	849	NUM
ap-6763	242	17	data	datum	NOUN
ap-6763	242	18	points	point	NOUN
ap-6763	242	19	out	out	ADP
ap-6763	242	20	of	of	ADP
ap-6763	242	21	a	a	DET
ap-6763	242	22	total	total	NOUN
ap-6763	242	23	of	of	ADP
ap-6763	242	24	1000	1000	NUM
ap-6763	242	25	members	member	NOUN
ap-6763	242	26	of	of	ADP
ap-6763	242	27	an	an	DET
ap-6763	242	28	appropriate	appropriate	ADJ
ap-6763	242	29	cluster	cluster	NOUN
ap-6763	242	30	with	with	ADP
ap-6763	242	31	151	151	NUM
ap-6763	242	32	in	in	ADP
ap-6763	242	33	an	an	DET
ap-6763	242	34	inappropriate	inappropriate	ADJ
ap-6763	242	35	cluster	cluster	NOUN
ap-6763	242	36	.	.	PUNCT
ap-6763	243	1	table	table	NOUN
ap-6763	243	2	7	7	NUM
ap-6763	243	3	shows	show	VERB
ap-6763	243	4	that	that	SCONJ
ap-6763	243	5	the	the	DET
ap-6763	243	6	ocsfcm	ocsfcm	PROPN
ap-6763	243	7	has	have	VERB
ap-6763	243	8	a	a	DET
ap-6763	243	9	better	well	ADJ
ap-6763	243	10	algorithm	algorithm	NOUN
ap-6763	243	11	performance	performance	NOUN
ap-6763	243	12	than	than	ADP
ap-6763	243	13	others	other	NOUN
ap-6763	243	14	and	and	CCONJ
ap-6763	243	15	the	the	DET
ap-6763	243	16	npspfcm	npspfcm	PROPN
ap-6763	243	17	has	have	VERB
ap-6763	243	18	a	a	DET
ap-6763	243	19	better	well	ADJ
ap-6763	243	20	accuracy	accuracy	NOUN
ap-6763	243	21	percentage	percentage	NOUN
ap-6763	243	22	than	than	ADP
ap-6763	243	23	the	the	DET
ap-6763	243	24	ocspfcm	ocspfcm	NOUN
ap-6763	243	25	and	and	CCONJ
ap-6763	243	26	kfcm	kfcm	NUM
ap-6763	243	27	,	,	PUNCT
ap-6763	243	28	and	and	CCONJ
ap-6763	243	29	has	have	VERB
ap-6763	243	30	almost	almost	ADV
ap-6763	243	31	the	the	DET
ap-6763	243	32	same	same	ADJ
ap-6763	243	33	performance	performance	NOUN
ap-6763	243	34	as	as	ADP
ap-6763	243	35	the	the	DET
ap-6763	243	36	npsfcm	npsfcm	NOUN
ap-6763	243	37	.	.	PUNCT
ap-6763	244	1	table	table	NOUN
ap-6763	244	2	8	8	NUM
ap-6763	244	3	shows	show	VERB
ap-6763	244	4	the	the	DET
ap-6763	244	5	average	average	ADJ
ap-6763	244	6	number	number	NOUN
ap-6763	244	7	of	of	ADP
ap-6763	244	8	iterations	iteration	NOUN
ap-6763	244	9	needed	need	VERB
ap-6763	244	10	for	for	ADP
ap-6763	244	11	the	the	DET
ap-6763	244	12	termination	termination	NOUN
ap-6763	244	13	.	.	PUNCT
ap-6763	245	1	in	in	ADP
ap-6763	245	2	general	general	ADJ
ap-6763	245	3	,	,	PUNCT
ap-6763	245	4	the	the	DET
ap-6763	245	5	number	number	NOUN
ap-6763	245	6	of	of	ADP
ap-6763	245	7	iterations	iteration	NOUN
ap-6763	245	8	required	require	VERB
ap-6763	245	9	by	by	ADP
ap-6763	245	10	the	the	DET
ap-6763	245	11	ocspfcm	ocspfcm	NOUN
ap-6763	245	12	and	and	CCONJ
ap-6763	245	13	npspfcm	npspfcm	ADJ
ap-6763	245	14	are	be	AUX
ap-6763	245	15	relatively	relatively	ADV
ap-6763	245	16	similar	similar	ADJ
ap-6763	245	17	at	at	ADP
ap-6763	245	18	each	each	DET
ap-6763	245	19	level	level	NOUN
ap-6763	245	20	of	of	ADP
ap-6763	245	21	the	the	DET
ap-6763	245	22	missing	miss	VERB
ap-6763	245	23	values	value	NOUN
ap-6763	245	24	.	.	PUNCT
ap-6763	246	1	table	table	NOUN
ap-6763	246	2	8	8	NUM
ap-6763	246	3	also	also	ADV
ap-6763	246	4	shows	show	VERB
ap-6763	246	5	that	that	SCONJ
ap-6763	246	6	the	the	DET
ap-6763	246	7	npsfcm	npsfcm	NOUN
ap-6763	246	8	has	have	VERB
ap-6763	246	9	the	the	DET
ap-6763	246	10	most	most	ADV
ap-6763	246	11	efficient	efficient	ADJ
ap-6763	246	12	iteration	iteration	NOUN
ap-6763	246	13	,	,	PUNCT
ap-6763	246	14	while	while	SCONJ
ap-6763	246	15	the	the	DET
ap-6763	246	16	ocspfcm	ocspfcm	NOUN
ap-6763	246	17	and	and	CCONJ
ap-6763	246	18	npspfcm	npspfcm	ADJ
ap-6763	246	19	are	be	AUX
ap-6763	246	20	more	more	ADV
ap-6763	246	21	efficient	efficient	ADJ
ap-6763	246	22	than	than	ADP
ap-6763	246	23	the	the	DET
ap-6763	246	24	ocsfcm	ocsfcm	NOUN
ap-6763	246	25	and	and	CCONJ
ap-6763	246	26	kfcm	kfcm	PROPN
ap-6763	246	27	.	.	PUNCT
ap-6763	247	1	table	table	NOUN
ap-6763	247	2	9	9	NUM
ap-6763	247	3	shows	show	VERB
ap-6763	247	4	the	the	DET
ap-6763	247	5	average	average	ADJ
ap-6763	247	6	centroid	centroid	NOUN
ap-6763	247	7	errors	error	NOUN
ap-6763	247	8	for	for	ADP
ap-6763	247	9	artificial	artificial	ADJ
ap-6763	247	10	data	datum	NOUN
ap-6763	247	11	set	set	VERB
ap-6763	247	12	i	i	PRON
ap-6763	247	13	with	with	ADP
ap-6763	247	14	the	the	DET
ap-6763	247	15	npspfcm	npspfcm	PROPN
ap-6763	247	16	having	have	VERB
ap-6763	247	17	smaller	small	ADJ
ap-6763	247	18	centroid	centroid	NOUN
ap-6763	247	19	errors	error	NOUN
ap-6763	247	20	than	than	ADP
ap-6763	247	21	the	the	DET
ap-6763	247	22	ocspfcm	ocspfcm	NOUN
ap-6763	247	23	.	.	PUNCT
ap-6763	248	1	this	this	PRON
ap-6763	248	2	is	be	AUX
ap-6763	248	3	the	the	DET
ap-6763	248	4	implication	implication	NOUN
ap-6763	248	5	of	of	ADP
ap-6763	248	6	the	the	DET
ap-6763	248	7	process	process	NOUN
ap-6763	248	8	of	of	ADP
ap-6763	248	9	updating	update	VERB
ap-6763	248	10	the	the	DET
ap-6763	248	11	imputation	imputation	NOUN
ap-6763	248	12	of	of	ADP
ap-6763	248	13	missing	miss	VERB
ap-6763	248	14	values	value	NOUN
ap-6763	248	15	by	by	ADP
ap-6763	248	16	the	the	DET
ap-6763	248	17	npspfcm	npspfcm	NOUN
ap-6763	248	18	.	.	PUNCT
ap-6763	249	1	in	in	ADP
ap-6763	249	2	other	other	ADJ
ap-6763	249	3	words	word	NOUN
ap-6763	249	4	,	,	PUNCT
ap-6763	249	5	the	the	DET
ap-6763	249	6	cluster	cluster	NOUN
ap-6763	249	7	centre	centre	NOUN
ap-6763	249	8	generated	generate	VERB
ap-6763	249	9	by	by	ADP
ap-6763	249	10	the	the	DET
ap-6763	249	11	npspfcm	npspfcm	ADJ
ap-6763	249	12	algorithm	algorithm	NOUN
ap-6763	249	13	is	be	AUX
ap-6763	249	14	closer	close	ADJ
ap-6763	249	15	to	to	ADP
ap-6763	249	16	the	the	DET
ap-6763	249	17	centre	centre	NOUN
ap-6763	249	18	base	base	NOUN
ap-6763	249	19	used	use	VERB
ap-6763	249	20	in	in	ADP
ap-6763	249	21	the	the	DET
ap-6763	249	22	complete	complete	ADJ
ap-6763	249	23	artificial	artificial	ADJ
ap-6763	249	24	data	datum	NOUN
ap-6763	249	25	set	set	VERB
ap-6763	249	26	i.	i.	NOUN
ap-6763	249	27	table	table	NOUN
ap-6763	249	28	9	9	NUM
ap-6763	249	29	also	also	ADV
ap-6763	249	30	shows	show	VERB
ap-6763	249	31	the	the	DET
ap-6763	249	32	ocsfcm	ocsfcm	NOUN
ap-6763	249	33	,	,	PUNCT
ap-6763	249	34	which	which	PRON
ap-6763	249	35	has	have	VERB
ap-6763	249	36	the	the	DET
ap-6763	249	37	smallest	small	ADJ
ap-6763	249	38	centroid	centroid	NOUN
ap-6763	249	39	errors	error	NOUN
ap-6763	249	40	compared	compare	VERB
ap-6763	249	41	to	to	ADP
ap-6763	249	42	others	other	NOUN
ap-6763	249	43	,	,	PUNCT
ap-6763	249	44	and	and	CCONJ
ap-6763	249	45	our	our	PRON
ap-6763	249	46	npspfcm	npspfcm	NOUN
ap-6763	249	47	having	have	VERB
ap-6763	249	48	centroid	centroid	NOUN
ap-6763	249	49	errors	error	NOUN
ap-6763	249	50	smaller	small	ADJ
ap-6763	249	51	than	than	ADP
ap-6763	249	52	the	the	DET
ap-6763	249	53	npsfcm	npsfcm	NOUN
ap-6763	249	54	and	and	CCONJ
ap-6763	249	55	kfcm	kfcm	PROPN
ap-6763	249	56	.	.	PUNCT
ap-6763	250	1	5.4	5.4	NUM
ap-6763	250	2	.	.	PUNCT
ap-6763	250	3	experiment	experiment	NOUN
ap-6763	250	4	on	on	ADP
ap-6763	250	5	artificial	artificial	ADJ
ap-6763	250	6	data	datum	NOUN
ap-6763	250	7	set	set	VERB
ap-6763	250	8	ii	ii	PROPN
ap-6763	250	9	for	for	ADP
ap-6763	250	10	the	the	DET
ap-6763	250	11	artificial	artificial	ADJ
ap-6763	250	12	data	datum	NOUN
ap-6763	250	13	set	set	PROPN
ap-6763	250	14	ii	ii	PROPN
ap-6763	250	15	,	,	PUNCT
ap-6763	250	16	evaluations	evaluation	NOUN
ap-6763	250	17	related	relate	VERB
ap-6763	250	18	to	to	ADP
ap-6763	250	19	the	the	DET
ap-6763	250	20	percentage	percentage	NOUN
ap-6763	250	21	of	of	ADP
ap-6763	250	22	accuracy	accuracy	NOUN
ap-6763	250	23	,	,	PUNCT
ap-6763	250	24	the	the	DET
ap-6763	250	25	number	number	NOUN
ap-6763	250	26	of	of	ADP
ap-6763	250	27	iterations	iteration	NOUN
ap-6763	250	28	,	,	PUNCT
ap-6763	250	29	and	and	CCONJ
ap-6763	250	30	the	the	DET
ap-6763	250	31	centroid	centroid	PROPN
ap-6763	250	32	errors	error	NOUN
ap-6763	250	33	are	be	AUX
ap-6763	250	34	,	,	PUNCT
ap-6763	250	35	respectively	respectively	ADV
ap-6763	250	36	,	,	PUNCT
ap-6763	250	37	shown	show	VERB
ap-6763	250	38	in	in	ADP
ap-6763	250	39	tables	table	NOUN
ap-6763	250	40	10	10	NUM
ap-6763	250	41	,	,	PUNCT
ap-6763	250	42	11	11	NUM
ap-6763	250	43	,	,	PUNCT
ap-6763	250	44	and	and	CCONJ
ap-6763	250	45	12	12	NUM
ap-6763	250	46	.	.	PUNCT
ap-6763	250	47	table	table	NOUN
ap-6763	250	48	10	10	NUM
ap-6763	250	49	shows	show	VERB
ap-6763	250	50	the	the	DET
ap-6763	250	51	average	average	ADJ
ap-6763	250	52	accuracy	accuracy	NOUN
ap-6763	250	53	percentage	percentage	NOUN
ap-6763	250	54	for	for	ADP
ap-6763	250	55	the	the	DET
ap-6763	250	56	artificial	artificial	ADJ
ap-6763	250	57	data	datum	NOUN
ap-6763	250	58	set	set	PROPN
ap-6763	250	59	ii	ii	PROPN
ap-6763	250	60	.	.	PUNCT
ap-6763	251	1	the	the	DET
ap-6763	251	2	ocspfcm	ocspfcm	NOUN
ap-6763	251	3	and	and	CCONJ
ap-6763	251	4	npspfcm	npspfcm	ADJ
ap-6763	251	5	provide	provide	VERB
ap-6763	251	6	accuracy	accuracy	NOUN
ap-6763	251	7	percentages	percentage	NOUN
ap-6763	251	8	above	above	ADP
ap-6763	251	9	95	95	NUM
ap-6763	251	10	%	%	NOUN
ap-6763	251	11	for	for	ADP
ap-6763	251	12	all	all	DET
ap-6763	251	13	missing	miss	VERB
ap-6763	251	14	values	value	NOUN
ap-6763	251	15	percentage	percentage	NOUN
ap-6763	251	16	levels	level	NOUN
ap-6763	251	17	.	.	PUNCT
ap-6763	252	1	for	for	ADP
ap-6763	252	2	the	the	DET
ap-6763	252	3	30	30	NUM
ap-6763	252	4	%	%	NOUN
ap-6763	252	5	missing	miss	VERB
ap-6763	252	6	values	value	NOUN
ap-6763	252	7	,	,	PUNCT
ap-6763	252	8	the	the	DET
ap-6763	252	9	ocspfcm	ocspfcm	NOUN
ap-6763	252	10	and	and	CCONJ
ap-6763	252	11	npspfcm	npspfcm	ADJ
ap-6763	252	12	give	give	VERB
ap-6763	252	13	an	an	DET
ap-6763	252	14	accuracy	accuracy	NOUN
ap-6763	252	15	percentage	percentage	NOUN
ap-6763	252	16	of	of	ADP
ap-6763	252	17	95.30	95.30	NUM
ap-6763	252	18	%	%	NOUN
ap-6763	252	19	and	and	CCONJ
ap-6763	252	20	97.57	97.57	NUM
ap-6763	252	21	%	%	NOUN
ap-6763	252	22	,	,	PUNCT
ap-6763	252	23	respectively	respectively	ADV
ap-6763	252	24	.	.	PUNCT
ap-6763	253	1	this	this	PRON
ap-6763	253	2	means	mean	VERB
ap-6763	253	3	that	that	SCONJ
ap-6763	253	4	in	in	ADP
ap-6763	253	5	the	the	DET
ap-6763	253	6	case	case	NOUN
ap-6763	253	7	of	of	ADP
ap-6763	253	8	the	the	DET
ap-6763	253	9	ocspfcm	ocspfcm	NOUN
ap-6763	253	10	,	,	PUNCT
ap-6763	253	11	there	there	PRON
ap-6763	253	12	are	be	VERB
ap-6763	253	13	953	953	NUM
ap-6763	253	14	data	datum	NOUN
ap-6763	253	15	points	point	NOUN
ap-6763	253	16	out	out	ADP
ap-6763	253	17	of	of	ADP
ap-6763	253	18	a	a	DET
ap-6763	253	19	total	total	NOUN
ap-6763	253	20	of	of	ADP
ap-6763	253	21	1000	1000	NUM
ap-6763	253	22	members	member	NOUN
ap-6763	253	23	in	in	ADP
ap-6763	253	24	the	the	DET
ap-6763	253	25	appropriate	appropriate	ADJ
ap-6763	253	26	cluster	cluster	NOUN
ap-6763	253	27	,	,	PUNCT
ap-6763	253	28	with	with	ADP
ap-6763	253	29	47	47	NUM
ap-6763	253	30	in	in	ADP
ap-6763	253	31	an	an	DET
ap-6763	253	32	inappropriate	inappropriate	ADJ
ap-6763	253	33	cluster	cluster	NOUN
ap-6763	253	34	.	.	PUNCT
ap-6763	254	1	meanwhile	meanwhile	ADV
ap-6763	254	2	,	,	PUNCT
ap-6763	254	3	the	the	DET
ap-6763	254	4	case	case	NOUN
ap-6763	254	5	of	of	ADP
ap-6763	254	6	in	in	ADP
ap-6763	254	7	the	the	DET
ap-6763	254	8	npspfcm	npspfcm	ADJ
ap-6763	254	9	algorithm	algorithm	NOUN
ap-6763	254	10	,	,	PUNCT
ap-6763	254	11	there	there	PRON
ap-6763	254	12	are	be	VERB
ap-6763	254	13	975	975	NUM
ap-6763	254	14	data	datum	NOUN
ap-6763	254	15	points	point	NOUN
ap-6763	254	16	in	in	ADP
ap-6763	254	17	the	the	DET
ap-6763	254	18	appropriate	appropriate	ADJ
ap-6763	254	19	cluster	cluster	NOUN
ap-6763	254	20	and	and	CCONJ
ap-6763	254	21	25	25	NUM
ap-6763	254	22	in	in	ADP
ap-6763	254	23	an	an	DET
ap-6763	254	24	inappropriate	inappropriate	ADJ
ap-6763	254	25	cluster	cluster	NOUN
ap-6763	254	26	.	.	PUNCT
ap-6763	255	1	table	table	NOUN
ap-6763	255	2	10	10	NUM
ap-6763	255	3	also	also	ADV
ap-6763	255	4	shows	show	VERB
ap-6763	255	5	the	the	DET
ap-6763	255	6	advantages	advantage	NOUN
ap-6763	255	7	of	of	ADP
ap-6763	255	8	the	the	DET
ap-6763	255	9	ocsfcm	ocsfcm	NOUN
ap-6763	255	10	and	and	CCONJ
ap-6763	255	11	the	the	DET
ap-6763	255	12	performance	performance	NOUN
ap-6763	255	13	of	of	ADP
ap-6763	255	14	the	the	DET
ap-6763	255	15	npspfcm	npspfcm	NOUN
ap-6763	255	16	and	and	CCONJ
ap-6763	255	17	npsfcm	npsfcm	NOUN
ap-6763	255	18	,	,	PUNCT
ap-6763	255	19	which	which	PRON
ap-6763	255	20	is	be	AUX
ap-6763	255	21	almost	almost	ADV
ap-6763	255	22	the	the	DET
ap-6763	255	23	same	same	ADJ
ap-6763	255	24	but	but	CCONJ
ap-6763	255	25	better	well	ADJ
ap-6763	255	26	than	than	ADP
ap-6763	255	27	that	that	PRON
ap-6763	255	28	of	of	ADP
ap-6763	255	29	the	the	DET
ap-6763	255	30	ocspfcm	ocspfcm	NOUN
ap-6763	255	31	and	and	CCONJ
ap-6763	255	32	kfcm	kfcm	PROPN
ap-6763	255	33	.	.	PUNCT
ap-6763	256	1	table	table	NOUN
ap-6763	256	2	11	11	NUM
ap-6763	256	3	shows	show	VERB
ap-6763	256	4	that	that	SCONJ
ap-6763	256	5	the	the	DET
ap-6763	256	6	npspfcm	npspfcm	NOUN
ap-6763	256	7	and	and	CCONJ
ap-6763	256	8	ocsfcm	ocsfcm	PROPN
ap-6763	256	9	have	have	VERB
ap-6763	256	10	a	a	DET
ap-6763	256	11	similar	similar	ADJ
ap-6763	256	12	number	number	NOUN
ap-6763	256	13	of	of	ADP
ap-6763	256	14	iteration	iteration	NOUN
ap-6763	256	15	and	and	CCONJ
ap-6763	256	16	are	be	AUX
ap-6763	256	17	more	more	ADV
ap-6763	256	18	efficient	efficient	ADJ
ap-6763	256	19	than	than	ADP
ap-6763	256	20	the	the	DET
ap-6763	256	21	ocspfcm	ocspfcm	NOUN
ap-6763	256	22	and	and	CCONJ
ap-6763	256	23	kfcm	kfcm	PROPN
ap-6763	256	24	.	.	PUNCT
ap-6763	257	1	the	the	DET
ap-6763	257	2	npspfcm	npspfcm	PROPN
ap-6763	257	3	also	also	ADV
ap-6763	257	4	provides	provide	VERB
ap-6763	257	5	a	a	DET
ap-6763	257	6	higher	high	ADJ
ap-6763	257	7	accuracy	accuracy	NOUN
ap-6763	257	8	percentage	percentage	NOUN
ap-6763	257	9	as	as	SCONJ
ap-6763	257	10	shown	show	VERB
ap-6763	257	11	in	in	ADP
ap-6763	257	12	table	table	NOUN
ap-6763	257	13	10	10	NUM
ap-6763	257	14	.	.	PUNCT
ap-6763	258	1	furthermore	furthermore	ADV
ap-6763	258	2	,	,	PUNCT
ap-6763	258	3	table	table	NOUN
ap-6763	258	4	12	12	NUM
ap-6763	258	5	shows	show	VERB
ap-6763	258	6	the	the	DET
ap-6763	258	7	smallest	small	ADJ
ap-6763	258	8	centroid	centroid	NOUN
ap-6763	258	9	errors	error	NOUN
ap-6763	258	10	given	give	VERB
ap-6763	258	11	by	by	ADP
ap-6763	258	12	our	our	PRON
ap-6763	258	13	npspfcm	npspfcm	NOUN
ap-6763	258	14	and	and	CCONJ
ap-6763	258	15	it	it	PRON
ap-6763	258	16	outperforms	outperform	VERB
ap-6763	258	17	all	all	DET
ap-6763	258	18	others	other	NOUN
ap-6763	258	19	.	.	PUNCT
ap-6763	259	1	5.5	5.5	NUM
ap-6763	259	2	.	.	PUNCT
ap-6763	259	3	experiment	experiment	NOUN
ap-6763	259	4	on	on	ADP
ap-6763	259	5	artificial	artificial	ADJ
ap-6763	259	6	data	datum	NOUN
ap-6763	259	7	set	set	VERB
ap-6763	259	8	iii	iii	NUM
ap-6763	259	9	experiment	experiment	NOUN
ap-6763	259	10	results	result	NOUN
ap-6763	259	11	on	on	ADP
ap-6763	259	12	artificial	artificial	ADJ
ap-6763	259	13	data	datum	NOUN
ap-6763	259	14	set	set	VERB
ap-6763	259	15	iii	iii	NOUN
ap-6763	259	16	are	be	AUX
ap-6763	259	17	shown	show	VERB
ap-6763	259	18	in	in	ADP
ap-6763	259	19	tables	table	NOUN
ap-6763	259	20	13	13	NUM
ap-6763	259	21	,	,	PUNCT
ap-6763	259	22	14	14	NUM
ap-6763	259	23	,	,	PUNCT
ap-6763	259	24	and	and	CCONJ
ap-6763	259	25	15	15	NUM
ap-6763	259	26	,	,	PUNCT
ap-6763	259	27	respectively	respectively	ADV
ap-6763	259	28	.	.	PUNCT
ap-6763	259	29	table	table	NOUN
ap-6763	259	30	13	13	NUM
ap-6763	259	31	shows	show	VERB
ap-6763	259	32	the	the	DET
ap-6763	259	33	inaccuracy	inaccuracy	NOUN
ap-6763	259	34	of	of	ADP
ap-6763	259	35	the	the	DET
ap-6763	259	36	ocspfcm	ocspfcm	NOUN
ap-6763	259	37	,	,	PUNCT
ap-6763	259	38	which	which	PRON
ap-6763	259	39	is	be	AUX
ap-6763	259	40	still	still	ADV
ap-6763	259	41	superior	superior	ADJ
ap-6763	259	42	to	to	ADP
ap-6763	259	43	the	the	DET
ap-6763	259	44	kfcm	kfcm	PROPN
ap-6763	259	45	.	.	PUNCT
ap-6763	260	1	the	the	DET
ap-6763	260	2	accuracy	accuracy	NOUN
ap-6763	260	3	percentage	percentage	NOUN
ap-6763	260	4	of	of	ADP
ap-6763	260	5	the	the	DET
ap-6763	260	6	ocspfcm	ocspfcm	NOUN
ap-6763	260	7	decreased	decrease	VERB
ap-6763	260	8	dramatically	dramatically	ADV
ap-6763	260	9	at	at	ADP
ap-6763	260	10	20	20	NUM
ap-6763	260	11	%	%	NOUN
ap-6763	260	12	missing	miss	VERB
ap-6763	260	13	values	value	NOUN
ap-6763	260	14	and	and	CCONJ
ap-6763	260	15	above	above	ADV
ap-6763	260	16	.	.	PUNCT
ap-6763	261	1	however	however	ADV
ap-6763	261	2	,	,	PUNCT
ap-6763	261	3	the	the	DET
ap-6763	261	4	shortcomings	shortcoming	NOUN
ap-6763	261	5	of	of	ADP
ap-6763	261	6	the	the	DET
ap-6763	261	7	ocspfcm	ocspfcm	NOUN
ap-6763	261	8	are	be	AUX
ap-6763	261	9	covered	cover	VERB
ap-6763	261	10	by	by	ADP
ap-6763	261	11	the	the	DET
ap-6763	261	12	npspfcm	npspfcm	NOUN
ap-6763	261	13	,	,	PUNCT
ap-6763	261	14	which	which	PRON
ap-6763	261	15	outperforms	outperform	VERB
ap-6763	261	16	all	all	DET
ap-6763	261	17	existing	exist	VERB
ap-6763	261	18	algorithms	algorithm	NOUN
ap-6763	261	19	.	.	PUNCT
ap-6763	262	1	table	table	NOUN
ap-6763	262	2	14	14	NUM
ap-6763	262	3	shows	show	VERB
ap-6763	262	4	the	the	DET
ap-6763	262	5	number	number	NOUN
ap-6763	262	6	of	of	ADP
ap-6763	262	7	the	the	DET
ap-6763	262	8	most	most	ADV
ap-6763	262	9	efficient	efficient	ADJ
ap-6763	262	10	iterations	iteration	NOUN
ap-6763	262	11	provided	provide	VERB
ap-6763	262	12	by	by	ADP
ap-6763	262	13	the	the	DET
ap-6763	262	14	npspfcm	npspfcm	NOUN
ap-6763	262	15	.	.	PUNCT
ap-6763	263	1	likewise	likewise	ADV
ap-6763	263	2	,	,	PUNCT
ap-6763	263	3	in	in	ADP
ap-6763	263	4	table	table	NOUN
ap-6763	263	5	15	15	NUM
ap-6763	263	6	,	,	PUNCT
ap-6763	263	7	the	the	DET
ap-6763	263	8	smallest	small	ADJ
ap-6763	263	9	centroid	centroid	NOUN
ap-6763	263	10	errors	error	NOUN
ap-6763	263	11	are	be	AUX
ap-6763	263	12	given	give	VERB
ap-6763	263	13	by	by	ADP
ap-6763	263	14	our	our	PRON
ap-6763	263	15	npspfcm	npspfcm	NOUN
ap-6763	263	16	.	.	PUNCT
ap-6763	264	1	artificial	artificial	ADJ
ap-6763	264	2	data	datum	NOUN
ap-6763	264	3	set	set	VERB
ap-6763	264	4	iii	iii	NUM
ap-6763	264	5	is	be	AUX
ap-6763	264	6	a	a	DET
ap-6763	264	7	data	data	NOUN
ap-6763	264	8	set	set	VERB
ap-6763	264	9	consisting	consist	VERB
ap-6763	264	10	of	of	ADP
ap-6763	264	11	five	five	NUM
ap-6763	264	12	clusters	cluster	NOUN
ap-6763	264	13	.	.	PUNCT
ap-6763	265	1	the	the	DET
ap-6763	265	2	experiments	experiment	NOUN
ap-6763	265	3	conducted	conduct	VERB
ap-6763	265	4	on	on	ADP
ap-6763	265	5	the	the	DET
ap-6763	265	6	iris	iris	NOUN
ap-6763	265	7	data	datum	NOUN
ap-6763	265	8	sets	set	NOUN
ap-6763	265	9	,	,	PUNCT
ap-6763	265	10	wine	wine	NOUN
ap-6763	265	11	data	data	NOUN
ap-6763	265	12	sets	set	NOUN
ap-6763	265	13	,	,	PUNCT
ap-6763	265	14	artificial	artificial	ADJ
ap-6763	265	15	data	datum	NOUN
ap-6763	265	16	set	set	VERB
ap-6763	265	17	i	i	PRON
ap-6763	265	18	,	,	PUNCT
ap-6763	265	19	and	and	CCONJ
ap-6763	265	20	artificial	artificial	ADJ
ap-6763	265	21	data	datum	NOUN
ap-6763	265	22	set	set	PROPN
ap-6763	265	23	ii	ii	PROPN
ap-6763	265	24	,	,	PUNCT
ap-6763	265	25	consist	consist	VERB
ap-6763	265	26	of	of	ADP
ap-6763	265	27	two	two	NUM
ap-6763	265	28	clusters	cluster	NOUN
ap-6763	265	29	each	each	PRON
ap-6763	265	30	.	.	PUNCT
ap-6763	266	1	the	the	DET
ap-6763	266	2	comparison	comparison	NOUN
ap-6763	266	3	of	of	ADP
ap-6763	266	4	the	the	DET
ap-6763	266	5	performance	performance	NOUN
ap-6763	266	6	of	of	ADP
ap-6763	266	7	the	the	DET
ap-6763	266	8	ocspfcm	ocspfcm	NOUN
ap-6763	266	9	and	and	CCONJ
ap-6763	266	10	npspfcm	npspfcm	ADJ
ap-6763	266	11	on	on	ADP
ap-6763	266	12	data	datum	NOUN
ap-6763	266	13	sets	set	NOUN
ap-6763	266	14	with	with	ADP
ap-6763	266	15	two	two	NUM
ap-6763	266	16	clusters	cluster	NOUN
ap-6763	266	17	and	and	CCONJ
ap-6763	266	18	five	five	NUM
ap-6763	266	19	clusters	cluster	NOUN
ap-6763	266	20	is	be	AUX
ap-6763	266	21	shown	show	VERB
ap-6763	266	22	in	in	ADP
ap-6763	266	23	figures	figure	NOUN
ap-6763	266	24	2	2	NUM
ap-6763	266	25	,	,	PUNCT
ap-6763	266	26	3	3	NUM
ap-6763	266	27	,	,	PUNCT
ap-6763	266	28	and	and	CCONJ
ap-6763	266	29	4	4	NUM
ap-6763	266	30	respectively	respectively	ADV
ap-6763	266	31	.	.	PUNCT
ap-6763	267	1	figure	figure	NOUN
ap-6763	267	2	2	2	NUM
ap-6763	267	3	shows	show	VERB
ap-6763	267	4	the	the	DET
ap-6763	267	5	performance	performance	NOUN
ap-6763	267	6	of	of	ADP
ap-6763	267	7	the	the	DET
ap-6763	267	8	ocspfcm	ocspfcm	NOUN
ap-6763	267	9	and	and	CCONJ
ap-6763	267	10	npspfcm	npspfcm	ADJ
ap-6763	267	11	in	in	ADP
ap-6763	267	12	terms	term	NOUN
ap-6763	267	13	of	of	ADP
ap-6763	267	14	the	the	DET
ap-6763	267	15	accuracy	accuracy	NOUN
ap-6763	267	16	percentage	percentage	NOUN
ap-6763	267	17	on	on	ADP
ap-6763	267	18	data	datum	NOUN
ap-6763	267	19	sets	set	NOUN
ap-6763	267	20	with	with	ADP
ap-6763	267	21	two	two	NUM
ap-6763	267	22	clusters	cluster	NOUN
ap-6763	267	23	and	and	CCONJ
ap-6763	267	24	five	five	NUM
ap-6763	267	25	clusters	cluster	NOUN
ap-6763	267	26	.	.	PUNCT
ap-6763	268	1	in	in	ADP
ap-6763	268	2	the	the	DET
ap-6763	268	3	case	case	NOUN
ap-6763	268	4	of	of	ADP
ap-6763	268	5	the	the	DET
ap-6763	268	6	artificial	artificial	ADJ
ap-6763	268	7	data	datum	NOUN
ap-6763	268	8	set	set	VERB
ap-6763	268	9	iii	iii	NOUN
ap-6763	268	10	,	,	PUNCT
ap-6763	268	11	which	which	PRON
ap-6763	268	12	consisted	consist	VERB
ap-6763	268	13	of	of	ADP
ap-6763	268	14	five	five	NUM
ap-6763	268	15	clusters	cluster	NOUN
ap-6763	268	16	,	,	PUNCT
ap-6763	268	17	the	the	DET
ap-6763	268	18	ocspfcm	ocspfcm	NOUN
ap-6763	268	19	showed	show	VERB
ap-6763	268	20	a	a	DET
ap-6763	268	21	lower	low	ADJ
ap-6763	268	22	performance	performance	NOUN
ap-6763	268	23	compared	compare	VERB
ap-6763	268	24	to	to	ADP
ap-6763	268	25	other	other	ADJ
ap-6763	268	26	data	datum	NOUN
ap-6763	268	27	sets	set	NOUN
ap-6763	268	28	which	which	PRON
ap-6763	268	29	consisted	consist	VERB
ap-6763	268	30	of	of	ADP
ap-6763	268	31	two	two	NUM
ap-6763	268	32	clusters	cluster	NOUN
ap-6763	268	33	.	.	PUNCT
ap-6763	269	1	in	in	ADP
ap-6763	269	2	contrast	contrast	NOUN
ap-6763	269	3	,	,	PUNCT
ap-6763	269	4	the	the	DET
ap-6763	269	5	percentage	percentage	NOUN
ap-6763	269	6	accuracy	accuracy	NOUN
ap-6763	269	7	of	of	ADP
ap-6763	269	8	the	the	DET
ap-6763	269	9	npspfcm	npspfcm	NOUN
ap-6763	269	10	on	on	ADP
ap-6763	269	11	artificial	artificial	ADJ
ap-6763	269	12	dataset	dataset	NOUN
ap-6763	269	13	iii	iii	X
ap-6763	269	14	(	(	PUNCT
ap-6763	269	15	five	five	NUM
ap-6763	269	16	clusters	cluster	NOUN
ap-6763	269	17	)	)	PUNCT
ap-6763	269	18	outperformed	outperform	VERB
ap-6763	269	19	other	other	ADJ
ap-6763	269	20	datasets	dataset	NOUN
ap-6763	269	21	consisting	consist	VERB
ap-6763	269	22	of	of	ADP
ap-6763	269	23	two	two	NUM
ap-6763	269	24	clusters	cluster	NOUN
ap-6763	269	25	,	,	PUNCT
ap-6763	269	26	except	except	SCONJ
ap-6763	269	27	for	for	ADP
ap-6763	269	28	artificial	artificial	ADJ
ap-6763	269	29	data	datum	NOUN
ap-6763	269	30	set	set	PROPN
ap-6763	269	31	ii	ii	PROPN
ap-6763	269	32	,	,	PUNCT
ap-6763	269	33	where	where	SCONJ
ap-6763	269	34	the	the	DET
ap-6763	269	35	370	370	NUM
ap-6763	269	36	vol	vol	NOUN
ap-6763	269	37	.	.	PUNCT
ap-6763	270	1	61	61	NUM
ap-6763	270	2	no	no	NOUN
ap-6763	270	3	.	.	PUNCT
ap-6763	271	1	2/2021	2/2021	NUM
ap-6763	271	2	modified	modify	VERB
ap-6763	271	3	possibilistic	possibilistic	ADJ
ap-6763	271	4	fuzzy	fuzzy	ADJ
ap-6763	271	5	c	c	NOUN
ap-6763	271	6	-	-	PUNCT
ap-6763	271	7	means	means	NOUN
ap-6763	271	8	algorithm	algorithm	NOUN
ap-6763	271	9	missing	miss	VERB
ap-6763	271	10	values	value	NOUN
ap-6763	271	11	oscpfcm	oscpfcm	VERB
ap-6763	271	12	npspfcm	npspfcm	ADJ
ap-6763	271	13	ocsfcm	ocsfcm	PROPN
ap-6763	271	14	npsfcm	npsfcm	PROPN
ap-6763	271	15	kfcm	kfcm	PROPN
ap-6763	272	1	(	(	PUNCT
ap-6763	272	2	%	%	NOUN
ap-6763	272	3	)	)	PUNCT
ap-6763	272	4	(	(	PUNCT
ap-6763	272	5	%	%	INTJ
ap-6763	272	6	)	)	PUNCT
ap-6763	272	7	(	(	PUNCT
ap-6763	272	8	%	%	INTJ
ap-6763	272	9	)	)	PUNCT
ap-6763	272	10	(	(	PUNCT
ap-6763	272	11	%	%	INTJ
ap-6763	272	12	)	)	PUNCT
ap-6763	272	13	(	(	PUNCT
ap-6763	272	14	%	%	INTJ
ap-6763	272	15	)	)	PUNCT
ap-6763	272	16	(	(	PUNCT
ap-6763	272	17	%	%	INTJ
ap-6763	272	18	)	)	PUNCT
ap-6763	272	19	5	5	NUM
ap-6763	272	20	37.03	37.03	NUM
ap-6763	272	21	33.73	33.73	NUM
ap-6763	272	22	26.10	26.10	NUM
ap-6763	272	23	25.80	25.80	NUM
ap-6763	272	24	100	100	NUM
ap-6763	272	25	10	10	NUM
ap-6763	272	26	55.10	55.10	NUM
ap-6763	272	27	35.50	35.50	NUM
ap-6763	272	28	30.40	30.40	NUM
ap-6763	272	29	27.33	27.33	NUM
ap-6763	272	30	100	100	NUM
ap-6763	272	31	15	15	NUM
ap-6763	272	32	61.90	61.90	NUM
ap-6763	272	33	37.87	37.87	NUM
ap-6763	272	34	43.10	43.10	NUM
ap-6763	272	35	42.60	42.60	NUM
ap-6763	272	36	100	100	NUM
ap-6763	272	37	20	20	NUM
ap-6763	272	38	72.53	72.53	NUM
ap-6763	272	39	48.17	48.17	NUM
ap-6763	272	40	46.70	46.70	NUM
ap-6763	272	41	48.00	48.00	NUM
ap-6763	272	42	100	100	NUM
ap-6763	272	43	25	25	NUM
ap-6763	273	1	92.47	92.47	NUM
ap-6763	273	2	55.63	55.63	NUM
ap-6763	273	3	47.80	47.80	NUM
ap-6763	273	4	47.20	47.20	NUM
ap-6763	273	5	100	100	NUM
ap-6763	273	6	30	30	NUM
ap-6763	273	7	99.00	99.00	NUM
ap-6763	273	8	64.00	64.00	NUM
ap-6763	273	9	51.80	51.80	NUM
ap-6763	273	10	51.20	51.20	NUM
ap-6763	273	11	100	100	NUM
ap-6763	273	12	table	table	NOUN
ap-6763	273	13	5	5	NUM
ap-6763	273	14	.	.	PUNCT
ap-6763	274	1	the	the	DET
ap-6763	274	2	average	average	ADJ
ap-6763	274	3	iterations	iteration	NOUN
ap-6763	274	4	for	for	ADP
ap-6763	274	5	wine	wine	NOUN
ap-6763	274	6	data	datum	NOUN
ap-6763	274	7	sets	set	NOUN
ap-6763	274	8	missing	miss	VERB
ap-6763	274	9	values	value	NOUN
ap-6763	274	10	oscpfcm	oscpfcm	VERB
ap-6763	274	11	npspfcm	npspfcm	ADJ
ap-6763	274	12	ocsfcm	ocsfcm	PROPN
ap-6763	274	13	npsfcm	npsfcm	PROPN
ap-6763	274	14	kfcm	kfcm	PROPN
ap-6763	274	15	(	(	PUNCT
ap-6763	274	16	%	%	NOUN
ap-6763	274	17	)	)	PUNCT
ap-6763	274	18	(	(	PUNCT
ap-6763	274	19	%	%	INTJ
ap-6763	274	20	)	)	PUNCT
ap-6763	274	21	(	(	PUNCT
ap-6763	274	22	%	%	INTJ
ap-6763	274	23	)	)	PUNCT
ap-6763	274	24	(	(	PUNCT
ap-6763	274	25	%	%	INTJ
ap-6763	274	26	)	)	PUNCT
ap-6763	274	27	(	(	PUNCT
ap-6763	274	28	%	%	INTJ
ap-6763	274	29	)	)	PUNCT
ap-6763	274	30	(	(	PUNCT
ap-6763	274	31	%	%	INTJ
ap-6763	274	32	)	)	PUNCT
ap-6763	274	33	5	5	NUM
ap-6763	274	34	11.41	11.41	NUM
ap-6763	274	35	9.02	9.02	NUM
ap-6763	274	36	3.69	3.69	NUM
ap-6763	274	37	2.76	2.76	NUM
ap-6763	274	38	467.25	467.25	NUM
ap-6763	274	39	10	10	NUM
ap-6763	274	40	37.11	37.11	NUM
ap-6763	274	41	15.48	15.48	NUM
ap-6763	274	42	8.85	8.85	NUM
ap-6763	274	43	8.75	8.75	NUM
ap-6763	274	44	464.77	464.77	NUM
ap-6763	274	45	15	15	NUM
ap-6763	274	46	46.37	46.37	NUM
ap-6763	274	47	73.58	73.58	NUM
ap-6763	274	48	13.02	13.02	NUM
ap-6763	274	49	13.08	13.08	NUM
ap-6763	274	50	478.59	478.59	NUM
ap-6763	274	51	20	20	NUM
ap-6763	274	52	102.34	102.34	NUM
ap-6763	274	53	92.75	92.75	NUM
ap-6763	274	54	24.07	24.07	NUM
ap-6763	274	55	24.79	24.79	NUM
ap-6763	274	56	503.25	503.25	NUM
ap-6763	274	57	25	25	NUM
ap-6763	274	58	153.55	153.55	NUM
ap-6763	274	59	98.98	98.98	NUM
ap-6763	274	60	28.72	28.72	NUM
ap-6763	274	61	28.65	28.65	NUM
ap-6763	274	62	658.78	658.78	NUM
ap-6763	274	63	30	30	NUM
ap-6763	274	64	185.21	185.21	NUM
ap-6763	274	65	113.36	113.36	NUM
ap-6763	274	66	31.37	31.37	NUM
ap-6763	274	67	31.60	31.60	NUM
ap-6763	274	68	665.07	665.07	NUM
ap-6763	274	69	table	table	NOUN
ap-6763	274	70	6	6	NUM
ap-6763	274	71	.	.	PUNCT
ap-6763	275	1	the	the	DET
ap-6763	275	2	average	average	ADJ
ap-6763	275	3	centroid	centroid	NOUN
ap-6763	275	4	errors	error	NOUN
ap-6763	275	5	for	for	ADP
ap-6763	275	6	wine	wine	NOUN
ap-6763	275	7	data	datum	NOUN
ap-6763	275	8	sets	set	NOUN
ap-6763	275	9	missing	miss	VERB
ap-6763	275	10	values	value	NOUN
ap-6763	275	11	oscpfcm	oscpfcm	VERB
ap-6763	275	12	npspfcm	npspfcm	ADJ
ap-6763	275	13	ocsfcm	ocsfcm	PROPN
ap-6763	275	14	npsfcm	npsfcm	PROPN
ap-6763	275	15	kfcm	kfcm	PROPN
ap-6763	275	16	(	(	PUNCT
ap-6763	275	17	%	%	NOUN
ap-6763	275	18	)	)	PUNCT
ap-6763	275	19	(	(	PUNCT
ap-6763	275	20	%	%	INTJ
ap-6763	275	21	)	)	PUNCT
ap-6763	275	22	(	(	PUNCT
ap-6763	275	23	%	%	INTJ
ap-6763	275	24	)	)	PUNCT
ap-6763	275	25	(	(	PUNCT
ap-6763	275	26	%	%	INTJ
ap-6763	275	27	)	)	PUNCT
ap-6763	275	28	(	(	PUNCT
ap-6763	275	29	%	%	INTJ
ap-6763	275	30	)	)	PUNCT
ap-6763	275	31	(	(	PUNCT
ap-6763	275	32	%	%	INTJ
ap-6763	275	33	)	)	PUNCT
ap-6763	275	34	5	5	NUM
ap-6763	275	35	98.10	98.10	NUM
ap-6763	275	36	98.71	98.71	NUM
ap-6763	275	37	99.38	99.38	NUM
ap-6763	275	38	98.29	98.29	NUM
ap-6763	275	39	98.00	98.00	NUM
ap-6763	275	40	10	10	NUM
ap-6763	275	41	95.80	95.80	NUM
ap-6763	275	42	96.57	96.57	NUM
ap-6763	275	43	98.62	98.62	NUM
ap-6763	275	44	96.67	96.67	NUM
ap-6763	275	45	95.50	95.50	NUM
ap-6763	275	46	15	15	NUM
ap-6763	275	47	92.50	92.50	NUM
ap-6763	275	48	94.29	94.29	NUM
ap-6763	275	49	96.89	96.89	NUM
ap-6763	275	50	95.18	95.18	NUM
ap-6763	275	51	93.10	93.10	NUM
ap-6763	275	52	20	20	NUM
ap-6763	275	53	91.40	91.40	NUM
ap-6763	275	54	93.05	93.05	NUM
ap-6763	275	55	95.46	95.46	NUM
ap-6763	275	56	92.90	92.90	NUM
ap-6763	275	57	89.20	89.20	NUM
ap-6763	275	58	25	25	NUM
ap-6763	275	59	87.70	87.70	NUM
ap-6763	275	60	92.11	92.11	NUM
ap-6763	275	61	95.37	95.37	NUM
ap-6763	275	62	89.83	89.83	NUM
ap-6763	275	63	88.10	88.10	NUM
ap-6763	275	64	30	30	NUM
ap-6763	275	65	84.90	84.90	NUM
ap-6763	275	66	88.86	88.86	NUM
ap-6763	275	67	92.78	92.78	NUM
ap-6763	275	68	88.36	88.36	NUM
ap-6763	275	69	85.20	85.20	NUM
ap-6763	275	70	table	table	NOUN
ap-6763	275	71	7	7	NUM
ap-6763	275	72	.	.	PUNCT
ap-6763	276	1	the	the	DET
ap-6763	276	2	average	average	ADJ
ap-6763	276	3	accuracy	accuracy	NOUN
ap-6763	276	4	percentage	percentage	NOUN
ap-6763	276	5	for	for	ADP
ap-6763	276	6	artificial	artificial	ADJ
ap-6763	276	7	data	datum	NOUN
ap-6763	276	8	set	set	VERB
ap-6763	276	9	i	i	PRON
ap-6763	276	10	missing	miss	VERB
ap-6763	276	11	values	value	NOUN
ap-6763	276	12	oscpfcm	oscpfcm	VERB
ap-6763	276	13	npspfcm	npspfcm	ADJ
ap-6763	276	14	ocsfcm	ocsfcm	PROPN
ap-6763	276	15	npsfcm	npsfcm	PROPN
ap-6763	276	16	kfcm	kfcm	PROPN
ap-6763	277	1	(	(	PUNCT
ap-6763	277	2	%	%	NOUN
ap-6763	277	3	)	)	PUNCT
ap-6763	277	4	(	(	PUNCT
ap-6763	277	5	%	%	INTJ
ap-6763	277	6	)	)	PUNCT
ap-6763	277	7	(	(	PUNCT
ap-6763	277	8	%	%	INTJ
ap-6763	277	9	)	)	PUNCT
ap-6763	277	10	(	(	PUNCT
ap-6763	277	11	%	%	INTJ
ap-6763	277	12	)	)	PUNCT
ap-6763	277	13	(	(	PUNCT
ap-6763	277	14	%	%	INTJ
ap-6763	277	15	)	)	PUNCT
ap-6763	277	16	(	(	PUNCT
ap-6763	277	17	%	%	INTJ
ap-6763	277	18	)	)	PUNCT
ap-6763	277	19	5	5	NUM
ap-6763	277	20	13.80	13.80	NUM
ap-6763	277	21	13.77	13.77	NUM
ap-6763	277	22	17.10	17.10	NUM
ap-6763	277	23	8.90	8.90	NUM
ap-6763	277	24	25.10	25.10	NUM
ap-6763	277	25	10	10	NUM
ap-6763	277	26	14.83	14.83	NUM
ap-6763	277	27	14.23	14.23	NUM
ap-6763	277	28	15.00	15.00	NUM
ap-6763	277	29	10.00	10.00	NUM
ap-6763	277	30	26.70	26.70	NUM
ap-6763	277	31	15	15	NUM
ap-6763	277	32	17.77	17.77	NUM
ap-6763	277	33	15.63	15.63	NUM
ap-6763	277	34	22.70	22.70	NUM
ap-6763	277	35	11.70	11.70	NUM
ap-6763	277	36	30.10	30.10	NUM
ap-6763	277	37	20	20	NUM
ap-6763	277	38	18.83	18.83	NUM
ap-6763	277	39	19.87	19.87	NUM
ap-6763	277	40	25.40	25.40	NUM
ap-6763	277	41	13.40	13.40	NUM
ap-6763	277	42	33.30	33.30	NUM
ap-6763	277	43	25	25	NUM
ap-6763	277	44	21.13	21.13	NUM
ap-6763	277	45	21.83	21.83	NUM
ap-6763	277	46	21.00	21.00	NUM
ap-6763	277	47	15.90	15.90	NUM
ap-6763	277	48	34.00	34.00	NUM
ap-6763	277	49	30	30	NUM
ap-6763	277	50	27.03	27.03	NUM
ap-6763	277	51	24.60	24.60	NUM
ap-6763	277	52	35.80	35.80	NUM
ap-6763	277	53	17.90	17.90	NUM
ap-6763	277	54	38.00	38.00	NUM
ap-6763	277	55	table	table	NOUN
ap-6763	277	56	8	8	NUM
ap-6763	277	57	.	.	PUNCT
ap-6763	278	1	the	the	DET
ap-6763	278	2	average	average	ADJ
ap-6763	278	3	iterations	iteration	NOUN
ap-6763	278	4	for	for	ADP
ap-6763	278	5	artificial	artificial	ADJ
ap-6763	278	6	data	datum	NOUN
ap-6763	278	7	set	set	VERB
ap-6763	278	8	i	i	PRON
ap-6763	278	9	missing	miss	VERB
ap-6763	278	10	values	value	NOUN
ap-6763	278	11	oscpfcm	oscpfcm	VERB
ap-6763	278	12	npspfcm	npspfcm	ADJ
ap-6763	278	13	ocsfcm	ocsfcm	PROPN
ap-6763	278	14	npsfcm	npsfcm	PROPN
ap-6763	278	15	kfcm	kfcm	PROPN
ap-6763	279	1	(	(	PUNCT
ap-6763	279	2	%	%	NOUN
ap-6763	279	3	)	)	PUNCT
ap-6763	279	4	(	(	PUNCT
ap-6763	279	5	%	%	INTJ
ap-6763	279	6	)	)	PUNCT
ap-6763	279	7	(	(	PUNCT
ap-6763	279	8	%	%	INTJ
ap-6763	279	9	)	)	PUNCT
ap-6763	279	10	(	(	PUNCT
ap-6763	279	11	%	%	INTJ
ap-6763	279	12	)	)	PUNCT
ap-6763	279	13	(	(	PUNCT
ap-6763	279	14	%	%	INTJ
ap-6763	279	15	)	)	PUNCT
ap-6763	279	16	(	(	PUNCT
ap-6763	279	17	%	%	INTJ
ap-6763	279	18	)	)	PUNCT
ap-6763	279	19	5	5	NUM
ap-6763	280	1	0.01	0.01	NUM
ap-6763	280	2	0.004	0.004	NUM
ap-6763	280	3	0.001	0.001	NUM
ap-6763	280	4	0.005	0.005	NUM
ap-6763	280	5	0.0301	0.0301	NUM
ap-6763	280	6	10	10	NUM
ap-6763	280	7	0.08	0.08	NUM
ap-6763	280	8	0.015	0.015	NUM
ap-6763	280	9	0.003	0.003	NUM
ap-6763	280	10	0.015	0.015	NUM
ap-6763	280	11	0.1091	0.1091	NUM
ap-6763	280	12	15	15	NUM
ap-6763	280	13	0.24	0.24	NUM
ap-6763	280	14	0.039	0.039	NUM
ap-6763	280	15	0.011	0.011	NUM
ap-6763	280	16	0.036	0.036	NUM
ap-6763	280	17	0.2484	0.2484	NUM
ap-6763	280	18	20	20	NUM
ap-6763	280	19	0.34	0.34	NUM
ap-6763	280	20	0.059	0.059	NUM
ap-6763	280	21	0.012	0.012	NUM
ap-6763	280	22	0.069	0.069	NUM
ap-6763	280	23	0.4403	0.4403	NUM
ap-6763	280	24	25	25	NUM
ap-6763	280	25	0.80	0.80	NUM
ap-6763	280	26	0.072	0.072	NUM
ap-6763	280	27	0.014	0.014	NUM
ap-6763	280	28	0.157	0.157	NUM
ap-6763	280	29	0.7099	0.7099	NUM
ap-6763	280	30	30	30	NUM
ap-6763	280	31	1.43	1.43	NUM
ap-6763	280	32	0.124	0.124	NUM
ap-6763	280	33	0.035	0.035	NUM
ap-6763	280	34	0.182	0.182	NUM
ap-6763	280	35	1.0799	1.0799	NUM
ap-6763	280	36	table	table	NOUN
ap-6763	280	37	9	9	NUM
ap-6763	280	38	.	.	PUNCT
ap-6763	281	1	the	the	DET
ap-6763	281	2	average	average	ADJ
ap-6763	281	3	centroid	centroid	NOUN
ap-6763	281	4	errors	error	NOUN
ap-6763	281	5	for	for	ADP
ap-6763	281	6	artificial	artificial	ADJ
ap-6763	281	7	data	datum	NOUN
ap-6763	281	8	set	set	VERB
ap-6763	281	9	i	i	PRON
ap-6763	281	10	371	371	NUM
ap-6763	281	11	rustam	rustam	PROPN
ap-6763	281	12	,	,	PUNCT
ap-6763	281	13	k.	k.	PROPN
ap-6763	281	14	usman	usman	PROPN
ap-6763	281	15	,	,	PUNCT
ap-6763	281	16	m.	m.	NOUN
ap-6763	281	17	kamaruddin	kamaruddin	PROPN
ap-6763	281	18	et	et	PROPN
ap-6763	281	19	al	al	PROPN
ap-6763	281	20	.	.	PROPN
ap-6763	282	1	acta	acta	PROPN
ap-6763	282	2	polytechnica	polytechnica	PROPN
ap-6763	282	3	missing	miss	VERB
ap-6763	282	4	values	value	NOUN
ap-6763	282	5	oscpfcm	oscpfcm	VERB
ap-6763	282	6	npspfcm	npspfcm	ADJ
ap-6763	282	7	ocsfcm	ocsfcm	PROPN
ap-6763	282	8	npsfcm	npsfcm	PROPN
ap-6763	282	9	kfcm	kfcm	PROPN
ap-6763	283	1	(	(	PUNCT
ap-6763	283	2	%	%	NOUN
ap-6763	283	3	)	)	PUNCT
ap-6763	283	4	(	(	PUNCT
ap-6763	283	5	%	%	INTJ
ap-6763	283	6	)	)	PUNCT
ap-6763	283	7	(	(	PUNCT
ap-6763	283	8	%	%	INTJ
ap-6763	283	9	)	)	PUNCT
ap-6763	283	10	(	(	PUNCT
ap-6763	283	11	%	%	INTJ
ap-6763	283	12	)	)	PUNCT
ap-6763	283	13	(	(	PUNCT
ap-6763	283	14	%	%	INTJ
ap-6763	283	15	)	)	PUNCT
ap-6763	283	16	(	(	PUNCT
ap-6763	283	17	%	%	INTJ
ap-6763	283	18	)	)	PUNCT
ap-6763	283	19	5	5	NUM
ap-6763	283	20	99.80	99.80	NUM
ap-6763	283	21	99.95	99.95	NUM
ap-6763	283	22	100	100	NUM
ap-6763	283	23	99.93	99.93	NUM
ap-6763	283	24	97.30	97.30	NUM
ap-6763	283	25	10	10	NUM
ap-6763	283	26	99.30	99.30	NUM
ap-6763	283	27	99.85	99.85	NUM
ap-6763	283	28	100	100	NUM
ap-6763	283	29	99.86	99.86	NUM
ap-6763	283	30	95.00	95.00	NUM
ap-6763	283	31	15	15	NUM
ap-6763	283	32	98.50	98.50	NUM
ap-6763	283	33	99.50	99.50	NUM
ap-6763	283	34	100	100	NUM
ap-6763	283	35	99.64	99.64	NUM
ap-6763	283	36	91.70	91.70	NUM
ap-6763	283	37	20	20	NUM
ap-6763	283	38	97.70	97.70	NUM
ap-6763	283	39	99.04	99.04	NUM
ap-6763	283	40	99.96	99.96	NUM
ap-6763	283	41	99.24	99.24	NUM
ap-6763	283	42	88.00	88.00	NUM
ap-6763	283	43	25	25	NUM
ap-6763	283	44	96.70	96.70	NUM
ap-6763	283	45	98.51	98.51	NUM
ap-6763	284	1	99.95	99.95	NUM
ap-6763	284	2	98.48	98.48	NUM
ap-6763	284	3	73.40	73.40	NUM
ap-6763	284	4	30	30	NUM
ap-6763	284	5	95.30	95.30	NUM
ap-6763	284	6	97.57	97.57	NUM
ap-6763	284	7	99.62	99.62	NUM
ap-6763	284	8	97.17	97.17	NUM
ap-6763	284	9	50.30	50.30	NUM
ap-6763	284	10	table	table	NOUN
ap-6763	284	11	10	10	NUM
ap-6763	284	12	.	.	PUNCT
ap-6763	285	1	the	the	DET
ap-6763	285	2	average	average	ADJ
ap-6763	285	3	accuracy	accuracy	NOUN
ap-6763	285	4	percentage	percentage	NOUN
ap-6763	285	5	for	for	ADP
ap-6763	285	6	artificial	artificial	ADJ
ap-6763	285	7	data	datum	NOUN
ap-6763	285	8	set	set	VERB
ap-6763	285	9	ii	ii	PROPN
ap-6763	285	10	missing	miss	VERB
ap-6763	285	11	values	value	NOUN
ap-6763	285	12	oscpfcm	oscpfcm	VERB
ap-6763	285	13	npspfcm	npspfcm	ADJ
ap-6763	285	14	ocsfcm	ocsfcm	PROPN
ap-6763	285	15	npsfcm	npsfcm	PROPN
ap-6763	285	16	kfcm	kfcm	PROPN
ap-6763	286	1	(	(	PUNCT
ap-6763	286	2	%	%	NOUN
ap-6763	286	3	)	)	PUNCT
ap-6763	286	4	(	(	PUNCT
ap-6763	286	5	%	%	INTJ
ap-6763	286	6	)	)	PUNCT
ap-6763	286	7	(	(	PUNCT
ap-6763	286	8	%	%	INTJ
ap-6763	286	9	)	)	PUNCT
ap-6763	286	10	(	(	PUNCT
ap-6763	286	11	%	%	INTJ
ap-6763	286	12	)	)	PUNCT
ap-6763	286	13	(	(	PUNCT
ap-6763	286	14	%	%	INTJ
ap-6763	286	15	)	)	PUNCT
ap-6763	286	16	(	(	PUNCT
ap-6763	286	17	%	%	INTJ
ap-6763	286	18	)	)	PUNCT
ap-6763	286	19	5	5	NUM
ap-6763	286	20	9.43	9.43	NUM
ap-6763	286	21	8.62	8.62	NUM
ap-6763	286	22	8.60	8.60	NUM
ap-6763	286	23	6.90	6.90	NUM
ap-6763	286	24	30.80	30.80	NUM
ap-6763	286	25	10	10	NUM
ap-6763	286	26	10.77	10.77	NUM
ap-6763	286	27	10.03	10.03	NUM
ap-6763	286	28	9.30	9.30	NUM
ap-6763	286	29	8.70	8.70	NUM
ap-6763	286	30	47.34	47.34	NUM
ap-6763	286	31	15	15	NUM
ap-6763	286	32	12.77	12.77	NUM
ap-6763	286	33	11.07	11.07	NUM
ap-6763	286	34	10.30	10.30	NUM
ap-6763	286	35	9.90	9.90	NUM
ap-6763	286	36	57.03	57.03	NUM
ap-6763	286	37	20	20	NUM
ap-6763	286	38	13.77	13.77	NUM
ap-6763	286	39	13.00	13.00	NUM
ap-6763	286	40	13.10	13.10	NUM
ap-6763	286	41	11.60	11.60	NUM
ap-6763	286	42	61.20	61.20	NUM
ap-6763	286	43	25	25	NUM
ap-6763	286	44	16.87	16.87	NUM
ap-6763	286	45	14.21	14.21	NUM
ap-6763	286	46	15.00	15.00	NUM
ap-6763	286	47	12.20	12.20	NUM
ap-6763	286	48	68.34	68.34	NUM
ap-6763	286	49	30	30	NUM
ap-6763	286	50	20.40	20.40	NUM
ap-6763	286	51	16.28	16.28	NUM
ap-6763	286	52	16.90	16.90	NUM
ap-6763	286	53	13.20	13.20	NUM
ap-6763	286	54	79.34	79.34	NUM
ap-6763	286	55	table	table	NOUN
ap-6763	286	56	11	11	NUM
ap-6763	286	57	.	.	PUNCT
ap-6763	287	1	the	the	DET
ap-6763	287	2	average	average	ADJ
ap-6763	287	3	iterations	iteration	NOUN
ap-6763	287	4	for	for	ADP
ap-6763	287	5	artificial	artificial	ADJ
ap-6763	287	6	data	datum	NOUN
ap-6763	287	7	set	set	VERB
ap-6763	287	8	ii	ii	PROPN
ap-6763	287	9	missing	miss	VERB
ap-6763	287	10	values	value	NOUN
ap-6763	287	11	oscpfcm	oscpfcm	VERB
ap-6763	287	12	npspfcm	npspfcm	ADJ
ap-6763	287	13	ocsfcm	ocsfcm	PROPN
ap-6763	287	14	npsfcm	npsfcm	PROPN
ap-6763	287	15	kfcm	kfcm	PROPN
ap-6763	288	1	(	(	PUNCT
ap-6763	288	2	%	%	NOUN
ap-6763	288	3	)	)	PUNCT
ap-6763	288	4	(	(	PUNCT
ap-6763	288	5	%	%	INTJ
ap-6763	288	6	)	)	PUNCT
ap-6763	288	7	(	(	PUNCT
ap-6763	288	8	%	%	INTJ
ap-6763	288	9	)	)	PUNCT
ap-6763	288	10	(	(	PUNCT
ap-6763	288	11	%	%	INTJ
ap-6763	288	12	)	)	PUNCT
ap-6763	288	13	(	(	PUNCT
ap-6763	288	14	%	%	INTJ
ap-6763	288	15	)	)	PUNCT
ap-6763	288	16	(	(	PUNCT
ap-6763	288	17	%	%	INTJ
ap-6763	288	18	)	)	PUNCT
ap-6763	288	19	5	5	NUM
ap-6763	288	20	0.02	0.02	NUM
ap-6763	288	21	0.0002	0.0002	NUM
ap-6763	288	22	0.0002	0.0002	NUM
ap-6763	288	23	0.0002	0.0002	NUM
ap-6763	288	24	0.4425	0.4425	NUM
ap-6763	288	25	10	10	NUM
ap-6763	288	26	0.08	0.08	NUM
ap-6763	288	27	0.0004	0.0004	NUM
ap-6763	288	28	0.0005	0.0005	NUM
ap-6763	288	29	0.0004	0.0004	NUM
ap-6763	289	1	2.9061	2.9061	NUM
ap-6763	289	2	15	15	NUM
ap-6763	289	3	0.21	0.21	NUM
ap-6763	289	4	0.0008	0.0008	NUM
ap-6763	289	5	0.0005	0.0005	NUM
ap-6763	289	6	0.0007	0.0007	NUM
ap-6763	289	7	13.108	13.108	NUM
ap-6763	289	8	20	20	NUM
ap-6763	289	9	0.40	0.40	NUM
ap-6763	289	10	0.0012	0.0012	NUM
ap-6763	289	11	0.0005	0.0005	NUM
ap-6763	289	12	0.0015	0.0015	NUM
ap-6763	289	13	17.459	17.459	NUM
ap-6763	289	14	25	25	NUM
ap-6763	289	15	0.72	0.72	NUM
ap-6763	289	16	0.0024	0.0024	NUM
ap-6763	289	17	0.0011	0.0011	NUM
ap-6763	289	18	0.0031	0.0031	NUM
ap-6763	289	19	22.806	22.806	NUM
ap-6763	289	20	30	30	NUM
ap-6763	289	21	1.09	1.09	NUM
ap-6763	289	22	0.0063	0.0063	NUM
ap-6763	289	23	0.0014	0.0014	NUM
ap-6763	289	24	0.0095	0.0095	NUM
ap-6763	289	25	30.112	30.112	NUM
ap-6763	289	26	table	table	NOUN
ap-6763	289	27	12	12	NUM
ap-6763	289	28	.	.	PUNCT
ap-6763	290	1	the	the	DET
ap-6763	290	2	average	average	ADJ
ap-6763	290	3	centroid	centroid	NOUN
ap-6763	290	4	errors	error	NOUN
ap-6763	290	5	for	for	ADP
ap-6763	290	6	artificial	artificial	ADJ
ap-6763	290	7	data	datum	NOUN
ap-6763	290	8	set	set	VERB
ap-6763	290	9	ii	ii	PROPN
ap-6763	290	10	missing	miss	VERB
ap-6763	290	11	values	value	NOUN
ap-6763	290	12	oscpfcm	oscpfcm	VERB
ap-6763	290	13	npspfcm	npspfcm	ADJ
ap-6763	290	14	ocsfcm	ocsfcm	PROPN
ap-6763	290	15	npsfcm	npsfcm	PROPN
ap-6763	290	16	kfcm	kfcm	PROPN
ap-6763	291	1	(	(	PUNCT
ap-6763	291	2	%	%	NOUN
ap-6763	291	3	)	)	PUNCT
ap-6763	291	4	(	(	PUNCT
ap-6763	291	5	%	%	INTJ
ap-6763	291	6	)	)	PUNCT
ap-6763	291	7	(	(	PUNCT
ap-6763	291	8	%	%	INTJ
ap-6763	291	9	)	)	PUNCT
ap-6763	291	10	(	(	PUNCT
ap-6763	291	11	%	%	INTJ
ap-6763	291	12	)	)	PUNCT
ap-6763	291	13	(	(	PUNCT
ap-6763	291	14	%	%	INTJ
ap-6763	291	15	)	)	PUNCT
ap-6763	291	16	(	(	PUNCT
ap-6763	291	17	%	%	INTJ
ap-6763	291	18	)	)	PUNCT
ap-6763	291	19	5	5	NUM
ap-6763	291	20	96.52	96.52	NUM
ap-6763	291	21	100	100	NUM
ap-6763	291	22	100	100	NUM
ap-6763	291	23	100	100	NUM
ap-6763	291	24	91.58	91.58	NUM
ap-6763	291	25	10	10	NUM
ap-6763	291	26	93.64	93.64	NUM
ap-6763	291	27	99.97	99.97	NUM
ap-6763	291	28	99.64	99.64	NUM
ap-6763	291	29	99.96	99.96	NUM
ap-6763	291	30	85.02	85.02	NUM
ap-6763	291	31	15	15	NUM
ap-6763	291	32	85.77	85.77	NUM
ap-6763	291	33	99.85	99.85	NUM
ap-6763	291	34	99.36	99.36	NUM
ap-6763	291	35	99.59	99.59	NUM
ap-6763	291	36	80.04	80.04	NUM
ap-6763	291	37	20	20	NUM
ap-6763	291	38	73.83	73.83	NUM
ap-6763	291	39	98.99	98.99	NUM
ap-6763	291	40	98.34	98.34	NUM
ap-6763	291	41	98.98	98.98	NUM
ap-6763	291	42	70.82	70.82	NUM
ap-6763	291	43	25	25	NUM
ap-6763	291	44	65.05	65.05	NUM
ap-6763	291	45	97.72	97.72	NUM
ap-6763	291	46	96.64	96.64	NUM
ap-6763	291	47	97.58	97.58	NUM
ap-6763	291	48	63.42	63.42	NUM
ap-6763	291	49	30	30	NUM
ap-6763	291	50	55.50	55.50	NUM
ap-6763	291	51	96.99	96.99	NUM
ap-6763	291	52	95.09	95.09	NUM
ap-6763	291	53	96.43	96.43	NUM
ap-6763	291	54	51.16	51.16	NUM
ap-6763	291	55	table	table	NOUN
ap-6763	291	56	13	13	NUM
ap-6763	291	57	.	.	PUNCT
ap-6763	292	1	the	the	DET
ap-6763	292	2	average	average	ADJ
ap-6763	292	3	accuracy	accuracy	NOUN
ap-6763	292	4	percentage	percentage	NOUN
ap-6763	292	5	for	for	ADP
ap-6763	292	6	artificial	artificial	ADJ
ap-6763	292	7	data	datum	NOUN
ap-6763	292	8	set	set	VERB
ap-6763	292	9	iii	iii	NUM
ap-6763	292	10	missing	miss	VERB
ap-6763	292	11	values	value	NOUN
ap-6763	292	12	oscpfcm	oscpfcm	VERB
ap-6763	292	13	npspfcm	npspfcm	ADJ
ap-6763	292	14	ocsfcm	ocsfcm	PROPN
ap-6763	292	15	npsfcm	npsfcm	PROPN
ap-6763	292	16	kfcm	kfcm	PROPN
ap-6763	292	17	(	(	PUNCT
ap-6763	292	18	%	%	NOUN
ap-6763	292	19	)	)	PUNCT
ap-6763	292	20	(	(	PUNCT
ap-6763	292	21	%	%	INTJ
ap-6763	292	22	)	)	PUNCT
ap-6763	292	23	(	(	PUNCT
ap-6763	292	24	%	%	INTJ
ap-6763	292	25	)	)	PUNCT
ap-6763	292	26	(	(	PUNCT
ap-6763	292	27	%	%	INTJ
ap-6763	292	28	)	)	PUNCT
ap-6763	292	29	(	(	PUNCT
ap-6763	292	30	%	%	INTJ
ap-6763	292	31	)	)	PUNCT
ap-6763	292	32	(	(	PUNCT
ap-6763	292	33	%	%	INTJ
ap-6763	292	34	)	)	PUNCT
ap-6763	292	35	5	5	NUM
ap-6763	292	36	8.64	8.64	NUM
ap-6763	292	37	8.00	8.00	NUM
ap-6763	292	38	8.60	8.60	NUM
ap-6763	292	39	9.40	9.40	NUM
ap-6763	292	40	100	100	NUM
ap-6763	292	41	10	10	NUM
ap-6763	292	42	10.82	10.82	NUM
ap-6763	292	43	10.00	10.00	NUM
ap-6763	292	44	12.80	12.80	NUM
ap-6763	292	45	13.20	13.20	NUM
ap-6763	292	46	100	100	NUM
ap-6763	292	47	15	15	NUM
ap-6763	292	48	39.10	39.10	NUM
ap-6763	292	49	11.00	11.00	NUM
ap-6763	292	50	15.00	15.00	NUM
ap-6763	292	51	16.20	16.20	NUM
ap-6763	292	52	100	100	NUM
ap-6763	292	53	20	20	NUM
ap-6763	292	54	44.00	44.00	NUM
ap-6763	292	55	13.20	13.20	NUM
ap-6763	292	56	17.40	17.40	NUM
ap-6763	292	57	17.40	17.40	NUM
ap-6763	292	58	100	100	NUM
ap-6763	292	59	25	25	NUM
ap-6763	292	60	65.34	65.34	NUM
ap-6763	292	61	15.00	15.00	NUM
ap-6763	292	62	19.40	19.40	NUM
ap-6763	292	63	20.00	20.00	NUM
ap-6763	292	64	100	100	NUM
ap-6763	292	65	30	30	NUM
ap-6763	292	66	75.00	75.00	NUM
ap-6763	292	67	17.60	17.60	NUM
ap-6763	292	68	21.30	21.30	NUM
ap-6763	292	69	24.80	24.80	NUM
ap-6763	292	70	100	100	NUM
ap-6763	292	71	table	table	NOUN
ap-6763	292	72	14	14	NUM
ap-6763	292	73	.	.	PUNCT
ap-6763	293	1	the	the	DET
ap-6763	293	2	average	average	ADJ
ap-6763	293	3	iterations	iteration	NOUN
ap-6763	293	4	for	for	ADP
ap-6763	293	5	artificial	artificial	ADJ
ap-6763	293	6	data	datum	NOUN
ap-6763	293	7	set	set	VERB
ap-6763	293	8	iii	iii	NUM
ap-6763	293	9	372	372	NUM
ap-6763	293	10	vol	vol	NOUN
ap-6763	293	11	.	.	PUNCT
ap-6763	294	1	61	61	NUM
ap-6763	294	2	no	no	NOUN
ap-6763	294	3	.	.	PUNCT
ap-6763	295	1	2/2021	2/2021	NUM
ap-6763	295	2	modified	modify	VERB
ap-6763	295	3	possibilistic	possibilistic	ADJ
ap-6763	295	4	fuzzy	fuzzy	ADJ
ap-6763	295	5	c	c	NOUN
ap-6763	295	6	-	-	PUNCT
ap-6763	295	7	means	means	NOUN
ap-6763	295	8	algorithm	algorithm	NOUN
ap-6763	295	9	missing	miss	VERB
ap-6763	295	10	values	value	NOUN
ap-6763	295	11	oscpfcm	oscpfcm	VERB
ap-6763	295	12	npspfcm	npspfcm	ADJ
ap-6763	295	13	ocsfcm	ocsfcm	PROPN
ap-6763	295	14	npsfcm	npsfcm	PROPN
ap-6763	295	15	kfcm	kfcm	PROPN
ap-6763	296	1	(	(	PUNCT
ap-6763	296	2	%	%	NOUN
ap-6763	296	3	)	)	PUNCT
ap-6763	296	4	(	(	PUNCT
ap-6763	296	5	%	%	INTJ
ap-6763	296	6	)	)	PUNCT
ap-6763	296	7	(	(	PUNCT
ap-6763	296	8	%	%	INTJ
ap-6763	296	9	)	)	PUNCT
ap-6763	296	10	(	(	PUNCT
ap-6763	296	11	%	%	INTJ
ap-6763	296	12	)	)	PUNCT
ap-6763	296	13	(	(	PUNCT
ap-6763	296	14	%	%	INTJ
ap-6763	296	15	)	)	PUNCT
ap-6763	296	16	(	(	PUNCT
ap-6763	296	17	%	%	INTJ
ap-6763	296	18	)	)	PUNCT
ap-6763	296	19	5	5	NUM
ap-6763	296	20	0.0251	0.0251	NUM
ap-6763	296	21	0.00006	0.00006	NUM
ap-6763	296	22	0.00009	0.00009	NUM
ap-6763	296	23	0.00009	0.00009	NUM
ap-6763	296	24	0.0058	0.0058	NUM
ap-6763	296	25	10	10	NUM
ap-6763	296	26	0.1736	0.1736	NUM
ap-6763	296	27	0.00016	0.00016	NUM
ap-6763	297	1	0.00013	0.00013	NUM
ap-6763	297	2	0.00014	0.00014	NUM
ap-6763	297	3	0.0343	0.0343	NUM
ap-6763	297	4	15	15	NUM
ap-6763	297	5	0.1769	0.1769	NUM
ap-6763	297	6	0.00025	0.00025	NUM
ap-6763	297	7	0.00030	0.00030	NUM
ap-6763	297	8	0.00025	0.00025	NUM
ap-6763	297	9	0.0895	0.0895	NUM
ap-6763	297	10	20	20	NUM
ap-6763	297	11	0.1934	0.1934	NUM
ap-6763	297	12	0.00056	0.00056	NUM
ap-6763	297	13	0.00067	0.00067	NUM
ap-6763	297	14	0.00068	0.00068	NUM
ap-6763	297	15	0.1142	0.1142	NUM
ap-6763	297	16	25	25	NUM
ap-6763	297	17	0.2640	0.2640	NUM
ap-6763	297	18	0.00095	0.00095	NUM
ap-6763	297	19	0.00135	0.00135	NUM
ap-6763	297	20	0.00098	0.00098	NUM
ap-6763	297	21	0.1455	0.1455	NUM
ap-6763	297	22	30	30	NUM
ap-6763	297	23	0.3494	0.3494	NUM
ap-6763	297	24	0.00113	0.00113	NUM
ap-6763	297	25	0.00120	0.00120	NUM
ap-6763	297	26	0.00238	0.00238	NUM
ap-6763	297	27	0.1637	0.1637	NUM
ap-6763	297	28	table	table	NOUN
ap-6763	297	29	15	15	NUM
ap-6763	297	30	.	.	PUNCT
ap-6763	298	1	the	the	DET
ap-6763	298	2	average	average	ADJ
ap-6763	298	3	centroid	centroid	NOUN
ap-6763	298	4	errors	error	NOUN
ap-6763	298	5	for	for	ADP
ap-6763	298	6	artificial	artificial	ADJ
ap-6763	298	7	data	datum	NOUN
ap-6763	298	8	set	set	VERB
ap-6763	298	9	iii	iii	NUM
ap-6763	298	10	figure	figure	NOUN
ap-6763	298	11	2	2	NUM
ap-6763	298	12	.	.	PUNCT
ap-6763	298	13	comparison	comparison	NOUN
ap-6763	298	14	of	of	ADP
ap-6763	298	15	the	the	DET
ap-6763	298	16	percentage	percentage	NOUN
ap-6763	298	17	accuracy	accuracy	NOUN
ap-6763	298	18	of	of	ADP
ap-6763	298	19	data	datum	NOUN
ap-6763	298	20	sets	set	NOUN
ap-6763	298	21	with	with	ADP
ap-6763	298	22	two	two	NUM
ap-6763	298	23	-	-	PUNCT
ap-6763	298	24	cluster	cluster	NOUN
ap-6763	298	25	and	and	CCONJ
ap-6763	298	26	five	five	NUM
ap-6763	298	27	-	-	PUNCT
ap-6763	298	28	cluster	cluster	NOUN
ap-6763	298	29	structure	structure	NOUN
ap-6763	298	30	npspfcm	npspfcm	NOUN
ap-6763	298	31	has	have	VERB
ap-6763	298	32	almost	almost	ADV
ap-6763	298	33	the	the	DET
ap-6763	298	34	same	same	ADJ
ap-6763	298	35	accuracy	accuracy	NOUN
ap-6763	298	36	percentage	percentage	NOUN
ap-6763	298	37	.	.	PUNCT
ap-6763	299	1	in	in	ADP
ap-6763	299	2	general	general	ADJ
ap-6763	299	3	,	,	PUNCT
ap-6763	299	4	the	the	DET
ap-6763	299	5	npspfcm	npspfcm	NOUN
ap-6763	299	6	is	be	AUX
ap-6763	299	7	more	more	ADV
ap-6763	299	8	reliable	reliable	ADJ
ap-6763	299	9	than	than	ADP
ap-6763	299	10	the	the	DET
ap-6763	299	11	ocspfcm	ocspfcm	NOUN
ap-6763	299	12	for	for	ADP
ap-6763	299	13	both	both	CCONJ
ap-6763	299	14	the	the	DET
ap-6763	299	15	data	datum	NOUN
ap-6763	299	16	set	set	VERB
ap-6763	299	17	with	with	ADP
ap-6763	299	18	two	two	NUM
ap-6763	299	19	clusters	cluster	NOUN
ap-6763	299	20	and	and	CCONJ
ap-6763	299	21	five	five	NUM
ap-6763	299	22	clusters	cluster	NOUN
ap-6763	299	23	.	.	PUNCT
ap-6763	300	1	figure	figure	NOUN
ap-6763	300	2	3	3	NUM
ap-6763	300	3	shows	show	VERB
ap-6763	300	4	the	the	DET
ap-6763	300	5	performance	performance	NOUN
ap-6763	300	6	of	of	ADP
ap-6763	300	7	the	the	DET
ap-6763	300	8	number	number	NOUN
ap-6763	300	9	of	of	ADP
ap-6763	300	10	iterations	iteration	NOUN
ap-6763	300	11	of	of	ADP
ap-6763	300	12	the	the	DET
ap-6763	300	13	ocspfcm	ocspfcm	NOUN
ap-6763	300	14	and	and	CCONJ
ap-6763	300	15	npspfcm	npspfcm	ADJ
ap-6763	300	16	on	on	ADP
ap-6763	300	17	data	datum	NOUN
ap-6763	300	18	sets	set	NOUN
ap-6763	300	19	with	with	ADP
ap-6763	300	20	two	two	NUM
ap-6763	300	21	clusters	cluster	NOUN
ap-6763	300	22	and	and	CCONJ
ap-6763	300	23	five	five	NUM
ap-6763	300	24	clusters	cluster	NOUN
ap-6763	300	25	.	.	PUNCT
ap-6763	301	1	the	the	DET
ap-6763	301	2	ocspfcm	ocspfcm	NOUN
ap-6763	301	3	requires	require	VERB
ap-6763	301	4	more	more	ADJ
ap-6763	301	5	iterations	iteration	NOUN
ap-6763	301	6	for	for	ADP
ap-6763	301	7	data	datum	NOUN
ap-6763	301	8	sets	set	NOUN
ap-6763	301	9	with	with	ADP
ap-6763	301	10	five	five	NUM
ap-6763	301	11	clusters	cluster	NOUN
ap-6763	301	12	than	than	ADP
ap-6763	301	13	two	two	NUM
ap-6763	301	14	clusters	cluster	NOUN
ap-6763	301	15	.	.	PUNCT
ap-6763	302	1	however	however	ADV
ap-6763	302	2	,	,	PUNCT
ap-6763	302	3	the	the	DET
ap-6763	302	4	number	number	NOUN
ap-6763	302	5	of	of	ADP
ap-6763	302	6	iterations	iteration	NOUN
ap-6763	302	7	needed	need	VERB
ap-6763	302	8	for	for	ADP
ap-6763	302	9	the	the	DET
ap-6763	302	10	wine	wine	NOUN
ap-6763	302	11	data	data	NOUN
ap-6763	302	12	sets	set	NOUN
ap-6763	302	13	(	(	PUNCT
ap-6763	302	14	two	two	NUM
ap-6763	302	15	clusters	cluster	NOUN
ap-6763	302	16	)	)	PUNCT
ap-6763	302	17	is	be	AUX
ap-6763	302	18	higher	high	ADJ
ap-6763	302	19	than	than	ADP
ap-6763	302	20	the	the	DET
ap-6763	302	21	one	one	NOUN
ap-6763	302	22	for	for	ADP
ap-6763	302	23	artificial	artificial	ADJ
ap-6763	302	24	data	datum	NOUN
ap-6763	302	25	sets	set	VERB
ap-6763	302	26	iii	iii	X
ap-6763	302	27	(	(	PUNCT
ap-6763	302	28	five	five	NUM
ap-6763	302	29	clusters	cluster	NOUN
ap-6763	302	30	)	)	PUNCT
ap-6763	302	31	.	.	PUNCT
ap-6763	303	1	meanwhile	meanwhile	ADV
ap-6763	303	2	,	,	PUNCT
ap-6763	303	3	the	the	DET
ap-6763	303	4	npspfcm	npspfcm	NOUN
ap-6763	303	5	provides	provide	VERB
ap-6763	303	6	an	an	DET
ap-6763	303	7	efficient	efficient	ADJ
ap-6763	303	8	number	number	NOUN
ap-6763	303	9	of	of	ADP
ap-6763	303	10	iterations	iteration	NOUN
ap-6763	303	11	,	,	PUNCT
ap-6763	303	12	for	for	ADP
ap-6763	303	13	both	both	CCONJ
ap-6763	303	14	the	the	DET
ap-6763	303	15	data	data	NOUN
ap-6763	303	16	sets	set	VERB
ap-6763	303	17	with	with	ADP
ap-6763	303	18	a	a	DET
ap-6763	303	19	two	two	NUM
ap-6763	303	20	-	-	PUNCT
ap-6763	303	21	cluster	cluster	NOUN
ap-6763	303	22	structure	structure	NOUN
ap-6763	303	23	and	and	CCONJ
ap-6763	303	24	the	the	DET
ap-6763	303	25	data	data	NOUN
ap-6763	303	26	sets	set	VERB
ap-6763	303	27	with	with	ADP
ap-6763	303	28	a	a	DET
ap-6763	303	29	five	five	NUM
ap-6763	303	30	-	-	PUNCT
ap-6763	303	31	cluster	cluster	NOUN
ap-6763	303	32	structure	structure	NOUN
ap-6763	303	33	.	.	PUNCT
ap-6763	304	1	these	these	DET
ap-6763	304	2	results	result	NOUN
ap-6763	304	3	indicate	indicate	VERB
ap-6763	304	4	the	the	DET
ap-6763	304	5	npspfcm	npspfcm	NOUN
ap-6763	304	6	outperformed	outperform	VERB
ap-6763	304	7	the	the	DET
ap-6763	304	8	ocspfcm	ocspfcm	NOUN
ap-6763	304	9	in	in	ADP
ap-6763	304	10	the	the	DET
ap-6763	304	11	number	number	NOUN
ap-6763	304	12	of	of	ADP
ap-6763	304	13	iterations	iteration	NOUN
ap-6763	304	14	for	for	ADP
ap-6763	304	15	both	both	CCONJ
ap-6763	304	16	the	the	DET
ap-6763	304	17	two	two	NUM
ap-6763	304	18	-	-	PUNCT
ap-6763	304	19	cluster	cluster	NOUN
ap-6763	304	20	and	and	CCONJ
ap-6763	304	21	the	the	DET
ap-6763	304	22	five	five	NUM
ap-6763	304	23	-	-	PUNCT
ap-6763	304	24	cluster	cluster	NOUN
ap-6763	304	25	data	data	NOUN
ap-6763	304	26	sets	set	NOUN
ap-6763	304	27	.	.	PUNCT
ap-6763	305	1	figure	figure	NOUN
ap-6763	305	2	4	4	NUM
ap-6763	305	3	shows	show	VERB
ap-6763	305	4	the	the	DET
ap-6763	305	5	centroid	centroid	NOUN
ap-6763	305	6	errors	error	NOUN
ap-6763	305	7	of	of	ADP
ap-6763	305	8	the	the	DET
ap-6763	305	9	ocspfcm	ocspfcm	NOUN
ap-6763	305	10	and	and	CCONJ
ap-6763	305	11	npspfcm	npspfcm	ADJ
ap-6763	305	12	for	for	ADP
ap-6763	305	13	data	datum	NOUN
ap-6763	305	14	sets	set	NOUN
ap-6763	305	15	with	with	ADP
ap-6763	305	16	two	two	NUM
ap-6763	305	17	clusters	cluster	NOUN
ap-6763	305	18	and	and	CCONJ
ap-6763	305	19	five	five	NUM
ap-6763	305	20	clusters	cluster	NOUN
ap-6763	305	21	.	.	PUNCT
ap-6763	306	1	centroid	centroid	NOUN
ap-6763	306	2	errors	error	NOUN
ap-6763	306	3	for	for	ADP
ap-6763	306	4	wine	wine	NOUN
ap-6763	306	5	data	data	NOUN
ap-6763	306	6	sets	set	NOUN
ap-6763	306	7	(	(	PUNCT
ap-6763	306	8	two	two	NUM
ap-6763	306	9	clusters	cluster	NOUN
ap-6763	306	10	)	)	PUNCT
ap-6763	306	11	for	for	ADP
ap-6763	306	12	the	the	DET
ap-6763	306	13	ocspfcm	ocspfcm	NOUN
ap-6763	306	14	and	and	CCONJ
ap-6763	306	15	npspfcm	npspfcm	ADJ
ap-6763	306	16	are	be	AUX
ap-6763	306	17	not	not	PART
ap-6763	306	18	displayed	display	VERB
ap-6763	306	19	because	because	SCONJ
ap-6763	306	20	they	they	PRON
ap-6763	306	21	are	be	AUX
ap-6763	306	22	in	in	ADP
ap-6763	306	23	the	the	DET
ap-6763	306	24	order	order	NOUN
ap-6763	306	25	of	of	ADP
ap-6763	306	26	102	102	NUM
ap-6763	306	27	,	,	PUNCT
ap-6763	306	28	so	so	SCONJ
ap-6763	306	29	it	it	PRON
ap-6763	306	30	would	would	AUX
ap-6763	306	31	cause	cause	VERB
ap-6763	306	32	the	the	DET
ap-6763	306	33	other	other	ADJ
ap-6763	306	34	data	data	NOUN
ap-6763	306	35	sets	set	NOUN
ap-6763	306	36	(	(	PUNCT
ap-6763	306	37	two	two	NUM
ap-6763	306	38	clusters	cluster	NOUN
ap-6763	306	39	and	and	CCONJ
ap-6763	306	40	five	five	NUM
ap-6763	306	41	clusters	cluster	NOUN
ap-6763	306	42	)	)	PUNCT
ap-6763	306	43	with	with	ADP
ap-6763	306	44	the	the	DET
ap-6763	306	45	order	order	NOUN
ap-6763	306	46	of	of	ADP
ap-6763	306	47	10−2	10−2	NUM
ap-6763	306	48	to	to	PART
ap-6763	306	49	not	not	PART
ap-6763	306	50	be	be	AUX
ap-6763	306	51	visible	visible	ADJ
ap-6763	306	52	.	.	PUNCT
ap-6763	307	1	in	in	ADP
ap-6763	307	2	figure	figure	NOUN
ap-6763	307	3	4	4	NUM
ap-6763	307	4	,	,	PUNCT
ap-6763	307	5	we	we	PRON
ap-6763	307	6	can	can	AUX
ap-6763	307	7	see	see	VERB
ap-6763	307	8	that	that	SCONJ
ap-6763	307	9	the	the	DET
ap-6763	307	10	ocspfcm	ocspfcm	PROPN
ap-6763	307	11	has	have	VERB
ap-6763	307	12	a	a	DET
ap-6763	307	13	relatively	relatively	ADV
ap-6763	307	14	smaller	small	ADJ
ap-6763	307	15	error	error	NOUN
ap-6763	307	16	centroid	centroid	NOUN
ap-6763	307	17	for	for	SCONJ
ap-6763	307	18	the	the	DET
ap-6763	307	19	artificial	artificial	ADJ
ap-6763	307	20	data	datum	NOUN
ap-6763	307	21	set	set	VERB
ap-6763	307	22	iii	iii	PROPN
ap-6763	307	23	(	(	PUNCT
ap-6763	307	24	five	five	NUM
ap-6763	307	25	clusters	cluster	NOUN
ap-6763	307	26	)	)	PUNCT
ap-6763	307	27	than	than	ADP
ap-6763	307	28	for	for	ADP
ap-6763	307	29	the	the	DET
ap-6763	307	30	artificial	artificial	ADJ
ap-6763	307	31	data	datum	NOUN
ap-6763	307	32	sets	set	VERB
ap-6763	307	33	i	i	PRON
ap-6763	307	34	and	and	CCONJ
ap-6763	307	35	ii	ii	PROPN
ap-6763	307	36	(	(	PUNCT
ap-6763	307	37	two	two	NUM
ap-6763	307	38	clusters	cluster	NOUN
ap-6763	307	39	)	)	PUNCT
ap-6763	307	40	,	,	PUNCT
ap-6763	307	41	however	however	ADV
ap-6763	307	42	,	,	PUNCT
ap-6763	307	43	not	not	PART
ap-6763	307	44	smaller	small	ADJ
ap-6763	307	45	than	than	ADP
ap-6763	307	46	for	for	ADP
ap-6763	307	47	the	the	DET
ap-6763	307	48	iris	iris	NOUN
ap-6763	307	49	data	datum	NOUN
ap-6763	307	50	sets	set	NOUN
ap-6763	307	51	(	(	PUNCT
ap-6763	307	52	two	two	NUM
ap-6763	307	53	clusters	cluster	NOUN
ap-6763	307	54	)	)	PUNCT
ap-6763	307	55	.	.	PUNCT
ap-6763	308	1	meanwhile	meanwhile	ADV
ap-6763	308	2	,	,	PUNCT
ap-6763	308	3	the	the	DET
ap-6763	308	4	npspfcm	npspfcm	NOUN
ap-6763	308	5	has	have	VERB
ap-6763	308	6	the	the	DET
ap-6763	308	7	smallest	small	ADJ
ap-6763	308	8	centroid	centroid	NOUN
ap-6763	308	9	errors	error	NOUN
ap-6763	308	10	for	for	ADP
ap-6763	308	11	the	the	DET
ap-6763	308	12	artificial	artificial	ADJ
ap-6763	308	13	dataset	dataset	NOUN
ap-6763	308	14	iii	iii	X
ap-6763	308	15	(	(	PUNCT
ap-6763	308	16	five	five	NUM
ap-6763	308	17	clusters	cluster	NOUN
ap-6763	308	18	)	)	PUNCT
ap-6763	308	19	as	as	SCONJ
ap-6763	308	20	compared	compare	VERB
ap-6763	308	21	to	to	ADP
ap-6763	308	22	other	other	ADJ
ap-6763	308	23	data	datum	NOUN
ap-6763	308	24	sets	set	NOUN
ap-6763	308	25	with	with	ADP
ap-6763	308	26	a	a	DET
ap-6763	308	27	two	two	NUM
ap-6763	308	28	-	-	PUNCT
ap-6763	308	29	cluster	cluster	NOUN
ap-6763	308	30	structure	structure	NOUN
ap-6763	308	31	.	.	PUNCT
ap-6763	309	1	from	from	ADP
ap-6763	309	2	the	the	DET
ap-6763	309	3	experiments	experiment	NOUN
ap-6763	309	4	that	that	PRON
ap-6763	309	5	have	have	AUX
ap-6763	309	6	been	be	AUX
ap-6763	309	7	carried	carry	VERB
ap-6763	309	8	out	out	ADP
ap-6763	309	9	on	on	ADP
ap-6763	309	10	the	the	DET
ap-6763	309	11	aforementioned	aforementioned	ADJ
ap-6763	309	12	data	data	NOUN
ap-6763	309	13	sets	set	NOUN
ap-6763	309	14	,	,	PUNCT
ap-6763	309	15	it	it	PRON
ap-6763	309	16	can	can	AUX
ap-6763	309	17	be	be	AUX
ap-6763	309	18	concluded	conclude	VERB
ap-6763	309	19	that	that	SCONJ
ap-6763	309	20	our	our	PRON
ap-6763	309	21	algorithm	algorithm	NOUN
ap-6763	309	22	is	be	AUX
ap-6763	309	23	robust	robust	ADJ
ap-6763	309	24	,	,	PUNCT
ap-6763	309	25	specifically	specifically	ADV
ap-6763	309	26	for	for	ADP
ap-6763	309	27	data	datum	NOUN
ap-6763	309	28	sets	set	NOUN
ap-6763	309	29	with	with	ADP
ap-6763	309	30	a	a	DET
ap-6763	309	31	two	two	NUM
ap-6763	309	32	-	-	PUNCT
ap-6763	309	33	cluster	cluster	NOUN
ap-6763	309	34	and	and	CCONJ
ap-6763	309	35	five	five	NUM
ap-6763	309	36	-	-	PUNCT
ap-6763	309	37	cluster	cluster	NOUN
ap-6763	309	38	structure	structure	NOUN
ap-6763	309	39	.	.	PUNCT
ap-6763	310	1	we	we	PRON
ap-6763	310	2	also	also	ADV
ap-6763	310	3	plot	plot	VERB
ap-6763	310	4	the	the	DET
ap-6763	310	5	objective	objective	ADJ
ap-6763	310	6	value	value	NOUN
ap-6763	310	7	of	of	ADP
ap-6763	310	8	our	our	PRON
ap-6763	310	9	algorithm	algorithm	NOUN
ap-6763	310	10	at	at	ADP
ap-6763	310	11	each	each	DET
ap-6763	310	12	iteration	iteration	NOUN
ap-6763	310	13	as	as	SCONJ
ap-6763	310	14	shown	show	VERB
ap-6763	310	15	in	in	ADP
ap-6763	310	16	figures	figure	NOUN
ap-6763	310	17	5	5	NUM
ap-6763	310	18	and	and	CCONJ
ap-6763	310	19	6	6	NUM
ap-6763	310	20	.	.	X
ap-6763	311	1	for	for	ADP
ap-6763	311	2	each	each	DET
ap-6763	311	3	data	datum	NOUN
ap-6763	311	4	set	set	VERB
ap-6763	311	5	the	the	DET
ap-6763	311	6	objective	objective	ADJ
ap-6763	311	7	value	value	NOUN
ap-6763	311	8	decreases	decrease	VERB
ap-6763	311	9	monotonically	monotonically	ADV
ap-6763	311	10	and	and	CCONJ
ap-6763	311	11	converges	converge	VERB
ap-6763	311	12	over	over	ADP
ap-6763	311	13	few	few	ADJ
ap-6763	311	14	iterations	iteration	NOUN
ap-6763	311	15	.	.	PUNCT
ap-6763	312	1	subsequently	subsequently	ADV
ap-6763	312	2	,	,	PUNCT
ap-6763	312	3	the	the	DET
ap-6763	312	4	average	average	ADJ
ap-6763	312	5	running	running	NOUN
ap-6763	312	6	time	time	NOUN
ap-6763	312	7	of	of	ADP
ap-6763	312	8	the	the	DET
ap-6763	312	9	ocspfcm	ocspfcm	NOUN
ap-6763	312	10	for	for	ADP
ap-6763	312	11	the	the	DET
ap-6763	312	12	iris	iris	NOUN
ap-6763	312	13	,	,	PUNCT
ap-6763	312	14	wine	wine	NOUN
ap-6763	312	15	,	,	PUNCT
ap-6763	312	16	artificial	artificial	ADJ
ap-6763	312	17	data	datum	NOUN
ap-6763	312	18	sets	set	VERB
ap-6763	312	19	i	i	PRON
ap-6763	312	20	,	,	PUNCT
ap-6763	312	21	ii	ii	PROPN
ap-6763	312	22	,	,	PUNCT
ap-6763	312	23	and	and	CCONJ
ap-6763	312	24	iii	iii	X
ap-6763	312	25	are	be	AUX
ap-6763	312	26	3.58	3.58	NUM
ap-6763	312	27	second	second	ADJ
ap-6763	312	28	,	,	PUNCT
ap-6763	312	29	4.17	4.17	NUM
ap-6763	312	30	second	second	NOUN
ap-6763	312	31	,	,	PUNCT
ap-6763	312	32	4.49	4.49	NUM
ap-6763	312	33	second	second	ADJ
ap-6763	312	34	,	,	PUNCT
ap-6763	312	35	4.86	4.86	NUM
ap-6763	312	36	second	second	ADJ
ap-6763	312	37	,	,	PUNCT
ap-6763	312	38	and	and	CCONJ
ap-6763	312	39	13.86	13.86	NUM
ap-6763	312	40	second	second	ADJ
ap-6763	312	41	,	,	PUNCT
ap-6763	312	42	respectively	respectively	ADV
ap-6763	312	43	.	.	PUNCT
ap-6763	313	1	meanwhile	meanwhile	ADV
ap-6763	313	2	,	,	PUNCT
ap-6763	313	3	the	the	DET
ap-6763	313	4	average	average	ADJ
ap-6763	313	5	running	running	NOUN
ap-6763	313	6	time	time	NOUN
ap-6763	313	7	of	of	ADP
ap-6763	313	8	the	the	DET
ap-6763	313	9	npspfcm	npspfcm	NOUN
ap-6763	313	10	for	for	ADP
ap-6763	313	11	the	the	DET
ap-6763	313	12	iris	iris	NOUN
ap-6763	313	13	,	,	PUNCT
ap-6763	313	14	wine	wine	NOUN
ap-6763	313	15	,	,	PUNCT
ap-6763	313	16	artificial	artificial	ADJ
ap-6763	313	17	data	datum	NOUN
ap-6763	313	18	sets	set	VERB
ap-6763	313	19	i	i	PRON
ap-6763	313	20	,	,	PUNCT
ap-6763	313	21	ii	ii	PROPN
ap-6763	313	22	and	and	CCONJ
ap-6763	313	23	iii	iii	NUM
ap-6763	313	24	are	be	AUX
ap-6763	313	25	3.70	3.70	NUM
ap-6763	313	26	second	second	ADJ
ap-6763	313	27	,	,	PUNCT
ap-6763	313	28	4.39	4.39	NUM
ap-6763	313	29	second	second	ADJ
ap-6763	313	30	,	,	PUNCT
ap-6763	313	31	4.61	4.61	NUM
ap-6763	313	32	second	second	ADJ
ap-6763	313	33	,	,	PUNCT
ap-6763	313	34	4.79	4.79	NUM
ap-6763	313	35	second	second	ADJ
ap-6763	313	36	,	,	PUNCT
ap-6763	313	37	and	and	CCONJ
ap-6763	313	38	12.87	12.87	NUM
ap-6763	313	39	second	second	ADJ
ap-6763	313	40	,	,	PUNCT
ap-6763	313	41	respectively	respectively	ADV
ap-6763	313	42	.	.	PUNCT
ap-6763	314	1	there	there	PRON
ap-6763	314	2	is	be	VERB
ap-6763	314	3	no	no	DET
ap-6763	314	4	significant	significant	ADJ
ap-6763	314	5	difference	difference	NOUN
ap-6763	314	6	in	in	ADP
ap-6763	314	7	the	the	DET
ap-6763	314	8	running	running	NOUN
ap-6763	314	9	time	time	NOUN
ap-6763	314	10	for	for	ADP
ap-6763	314	11	the	the	DET
ap-6763	314	12	ocspfcm	ocspfcm	NOUN
ap-6763	314	13	and	and	CCONJ
ap-6763	314	14	npspfcm	npspfcm	ADJ
ap-6763	314	15	.	.	PUNCT
ap-6763	315	1	the	the	DET
ap-6763	315	2	experiments	experiment	NOUN
ap-6763	315	3	carried	carry	VERB
ap-6763	315	4	out	out	ADP
ap-6763	315	5	on	on	ADP
ap-6763	315	6	the	the	DET
ap-6763	315	7	five	five	NUM
ap-6763	315	8	data	datum	NOUN
ap-6763	315	9	sets	set	NOUN
ap-6763	315	10	showed	show	VERB
ap-6763	315	11	that	that	SCONJ
ap-6763	315	12	the	the	DET
ap-6763	315	13	proposed	propose	VERB
ap-6763	315	14	algorithms	algorithm	NOUN
ap-6763	315	15	have	have	VERB
ap-6763	315	16	the	the	DET
ap-6763	315	17	potential	potential	NOUN
ap-6763	315	18	and	and	CCONJ
ap-6763	315	19	ability	ability	NOUN
ap-6763	315	20	to	to	PART
ap-6763	315	21	cluster	cluster	VERB
ap-6763	315	22	incomplete	incomplete	ADJ
ap-6763	315	23	data	datum	NOUN
ap-6763	315	24	sets	set	NOUN
ap-6763	315	25	.	.	PUNCT
ap-6763	316	1	the	the	DET
ap-6763	316	2	results	result	NOUN
ap-6763	316	3	also	also	ADV
ap-6763	316	4	showed	show	VERB
ap-6763	316	5	that	that	SCONJ
ap-6763	316	6	in	in	ADP
ap-6763	316	7	the	the	DET
ap-6763	316	8	terms	term	NOUN
ap-6763	316	9	of	of	ADP
ap-6763	316	10	the	the	DET
ap-6763	316	11	percentage	percentage	NOUN
ap-6763	316	12	accuracy	accuracy	NOUN
ap-6763	316	13	,	,	PUNCT
ap-6763	316	14	the	the	DET
ap-6763	316	15	npspfcm	npspfcm	NOUN
ap-6763	316	16	always	always	ADV
ap-6763	316	17	outperformed	outperform	VERB
ap-6763	316	18	the	the	DET
ap-6763	316	19	ocspfcm	ocspfcm	NOUN
ap-6763	316	20	.	.	PUNCT
ap-6763	317	1	the	the	DET
ap-6763	317	2	authors	author	NOUN
ap-6763	317	3	also	also	ADV
ap-6763	317	4	performed	perform	VERB
ap-6763	317	5	comparisons	comparison	NOUN
ap-6763	317	6	with	with	ADP
ap-6763	317	7	some	some	DET
ap-6763	317	8	existing	exist	VERB
ap-6763	317	9	incomplete	incomplete	ADJ
ap-6763	317	10	data	datum	NOUN
ap-6763	317	11	clustering	cluster	VERB
ap-6763	317	12	algorithms	algorithm	NOUN
ap-6763	317	13	including	include	VERB
ap-6763	317	14	the	the	DET
ap-6763	317	15	kfcm	kfcm	PROPN
ap-6763	317	16	,	,	PUNCT
ap-6763	317	17	ocsfcm	ocsfcm	PROPN
ap-6763	317	18	,	,	PUNCT
ap-6763	317	19	and	and	CCONJ
ap-6763	317	20	npsfcm	npsfcm	NOUN
ap-6763	317	21	.	.	PUNCT
ap-6763	318	1	the	the	DET
ap-6763	318	2	result	result	NOUN
ap-6763	318	3	showed	show	VERB
ap-6763	318	4	that	that	SCONJ
ap-6763	318	5	in	in	ADP
ap-6763	318	6	the	the	DET
ap-6763	318	7	case	case	NOUN
ap-6763	318	8	of	of	ADP
ap-6763	318	9	iris	iris	NOUN
ap-6763	318	10	data	datum	NOUN
ap-6763	318	11	sets	set	NOUN
ap-6763	318	12	,	,	PUNCT
ap-6763	318	13	the	the	DET
ap-6763	318	14	ocsfcm	ocsfcm	PROPN
ap-6763	318	15	and	and	CCONJ
ap-6763	318	16	npsfcm	npsfcm	PROPN
ap-6763	318	17	outperformed	outperform	VERB
ap-6763	318	18	the	the	DET
ap-6763	318	19	373	373	NUM
ap-6763	318	20	rustam	rustam	NOUN
ap-6763	318	21	,	,	PUNCT
ap-6763	318	22	k.	k.	PROPN
ap-6763	318	23	usman	usman	PROPN
ap-6763	318	24	,	,	PUNCT
ap-6763	318	25	m.	m.	NOUN
ap-6763	318	26	kamaruddin	kamaruddin	PROPN
ap-6763	318	27	et	et	PROPN
ap-6763	318	28	al	al	PROPN
ap-6763	318	29	.	.	PROPN
ap-6763	318	30	acta	acta	PROPN
ap-6763	318	31	polytechnica	polytechnica	PROPN
ap-6763	318	32	figure	figure	NOUN
ap-6763	318	33	3	3	NUM
ap-6763	318	34	.	.	NOUN
ap-6763	318	35	comparison	comparison	NOUN
ap-6763	318	36	of	of	ADP
ap-6763	318	37	the	the	DET
ap-6763	318	38	number	number	NOUN
ap-6763	318	39	of	of	ADP
ap-6763	318	40	iterations	iteration	NOUN
ap-6763	318	41	of	of	ADP
ap-6763	318	42	data	datum	NOUN
ap-6763	318	43	sets	set	NOUN
ap-6763	318	44	with	with	ADP
ap-6763	318	45	two	two	NUM
ap-6763	318	46	-	-	PUNCT
ap-6763	318	47	cluster	cluster	NOUN
ap-6763	318	48	and	and	CCONJ
ap-6763	318	49	five	five	NUM
ap-6763	318	50	-	-	PUNCT
ap-6763	318	51	cluster	cluster	NOUN
ap-6763	318	52	structure	structure	NOUN
ap-6763	318	53	figure	figure	NOUN
ap-6763	318	54	4	4	NUM
ap-6763	318	55	.	.	NOUN
ap-6763	318	56	comparison	comparison	NOUN
ap-6763	318	57	of	of	ADP
ap-6763	318	58	the	the	DET
ap-6763	318	59	centroid	centroid	NOUN
ap-6763	318	60	errors	error	NOUN
ap-6763	318	61	of	of	ADP
ap-6763	318	62	data	datum	NOUN
ap-6763	318	63	sets	set	NOUN
ap-6763	318	64	with	with	ADP
ap-6763	318	65	two	two	NUM
ap-6763	318	66	-	-	PUNCT
ap-6763	318	67	cluster	cluster	NOUN
ap-6763	318	68	and	and	CCONJ
ap-6763	318	69	five	five	NUM
ap-6763	318	70	-	-	PUNCT
ap-6763	318	71	cluster	cluster	NOUN
ap-6763	318	72	structure	structure	NOUN
ap-6763	318	73	figure	figure	NOUN
ap-6763	318	74	5	5	NUM
ap-6763	318	75	.	.	PUNCT
ap-6763	319	1	the	the	DET
ap-6763	319	2	objective	objective	ADJ
ap-6763	319	3	values	value	NOUN
ap-6763	319	4	of	of	ADP
ap-6763	319	5	the	the	DET
ap-6763	319	6	ocspfcm	ocspfcm	PROPN
ap-6763	319	7	algorithm	algorithm	NOUN
ap-6763	319	8	374	374	NUM
ap-6763	319	9	vol	vol	NOUN
ap-6763	319	10	.	.	PUNCT
ap-6763	320	1	61	61	NUM
ap-6763	320	2	no	no	NOUN
ap-6763	320	3	.	.	PUNCT
ap-6763	321	1	2/2021	2/2021	NUM
ap-6763	321	2	modified	modify	VERB
ap-6763	321	3	possibilistic	possibilistic	ADJ
ap-6763	321	4	fuzzy	fuzzy	ADJ
ap-6763	321	5	c	c	NOUN
ap-6763	321	6	-	-	PUNCT
ap-6763	321	7	means	mean	VERB
ap-6763	321	8	algorithm	algorithm	NOUN
ap-6763	321	9	figure	figure	NOUN
ap-6763	321	10	6	6	NUM
ap-6763	321	11	.	.	PUNCT
ap-6763	322	1	the	the	DET
ap-6763	322	2	objective	objective	ADJ
ap-6763	322	3	values	value	NOUN
ap-6763	322	4	of	of	ADP
ap-6763	322	5	the	the	DET
ap-6763	322	6	npspfcm	npspfcm	ADJ
ap-6763	322	7	algorithm	algorithm	NOUN
ap-6763	322	8	npspfcm	npspfcm	NOUN
ap-6763	322	9	,	,	PUNCT
ap-6763	322	10	while	while	SCONJ
ap-6763	322	11	in	in	ADP
ap-6763	322	12	the	the	DET
ap-6763	322	13	case	case	NOUN
ap-6763	322	14	of	of	ADP
ap-6763	322	15	wine	wine	NOUN
ap-6763	322	16	data	data	NOUN
ap-6763	322	17	sets	set	NOUN
ap-6763	322	18	,	,	PUNCT
ap-6763	322	19	the	the	DET
ap-6763	322	20	npspfcm	npspfcm	NOUN
ap-6763	322	21	outperformed	outperform	VERB
ap-6763	322	22	others	other	NOUN
ap-6763	322	23	.	.	PUNCT
ap-6763	323	1	in	in	ADP
ap-6763	323	2	the	the	DET
ap-6763	323	3	case	case	NOUN
ap-6763	323	4	of	of	ADP
ap-6763	323	5	artificial	artificial	ADJ
ap-6763	323	6	data	datum	NOUN
ap-6763	323	7	sets	set	VERB
ap-6763	323	8	i	i	PRON
ap-6763	323	9	and	and	CCONJ
ap-6763	323	10	ii	ii	PROPN
ap-6763	323	11	,	,	PUNCT
ap-6763	323	12	the	the	DET
ap-6763	323	13	ocsfcm	ocsfcm	PROPN
ap-6763	323	14	outperformed	outperform	VERB
ap-6763	323	15	npspfcm	npspfcm	PROPN
ap-6763	323	16	,	,	PUNCT
ap-6763	323	17	which	which	PRON
ap-6763	323	18	outperformed	outperform	VERB
ap-6763	323	19	the	the	DET
ap-6763	323	20	npsfcm	npsfcm	NOUN
ap-6763	323	21	and	and	CCONJ
ap-6763	323	22	kfcm	kfcm	PROPN
ap-6763	323	23	.	.	PUNCT
ap-6763	324	1	in	in	ADP
ap-6763	324	2	the	the	DET
ap-6763	324	3	case	case	NOUN
ap-6763	324	4	of	of	ADP
ap-6763	324	5	artificial	artificial	ADJ
ap-6763	324	6	data	datum	NOUN
ap-6763	324	7	sets	set	VERB
ap-6763	324	8	iii	iii	NOUN
ap-6763	324	9	,	,	PUNCT
ap-6763	324	10	containing	contain	VERB
ap-6763	324	11	larger	large	ADJ
ap-6763	324	12	data	datum	NOUN
ap-6763	324	13	sets	set	NOUN
ap-6763	324	14	,	,	PUNCT
ap-6763	324	15	the	the	DET
ap-6763	324	16	npspfcm	npspfcm	NOUN
ap-6763	324	17	outperformed	outperform	VERB
ap-6763	324	18	all	all	DET
ap-6763	324	19	others	other	NOUN
ap-6763	324	20	,	,	PUNCT
ap-6763	324	21	thereby	thereby	ADV
ap-6763	324	22	making	make	VERB
ap-6763	324	23	it	it	PRON
ap-6763	324	24	the	the	DET
ap-6763	324	25	best	good	ADJ
ap-6763	324	26	tool	tool	NOUN
ap-6763	324	27	for	for	ADP
ap-6763	324	28	larger	large	ADJ
ap-6763	324	29	incomplete	incomplete	ADJ
ap-6763	324	30	data	datum	NOUN
ap-6763	324	31	sets	set	NOUN
ap-6763	324	32	.	.	PUNCT
ap-6763	325	1	by	by	ADP
ap-6763	325	2	taking	take	VERB
ap-6763	325	3	the	the	DET
ap-6763	325	4	average	average	ADJ
ap-6763	325	5	percentage	percentage	NOUN
ap-6763	325	6	accuracy	accuracy	NOUN
ap-6763	325	7	for	for	ADP
ap-6763	325	8	all	all	DET
ap-6763	325	9	experiments	experiment	NOUN
ap-6763	325	10	data	data	NOUN
ap-6763	325	11	sets	set	NOUN
ap-6763	325	12	,	,	PUNCT
ap-6763	325	13	it	it	PRON
ap-6763	325	14	was	be	AUX
ap-6763	325	15	found	find	VERB
ap-6763	325	16	that	that	SCONJ
ap-6763	325	17	the	the	DET
ap-6763	325	18	ocspfcm	ocspfcm	NOUN
ap-6763	325	19	and	and	CCONJ
ap-6763	325	20	npspfcm	npspfcm	ADV
ap-6763	325	21	provide	provide	VERB
ap-6763	325	22	an	an	DET
ap-6763	325	23	average	average	ADJ
ap-6763	325	24	accuracy	accuracy	NOUN
ap-6763	325	25	between	between	ADP
ap-6763	325	26	97.75	97.75	NUM
ap-6763	325	27	%	%	NOUN
ap-6763	325	28	-78.98	-78.98	CCONJ
ap-6763	325	29	%	%	NOUN
ap-6763	325	30	and	and	CCONJ
ap-6763	325	31	98.86	98.86	NUM
ap-6763	325	32	%	%	NOUN
ap-6763	325	33	-92.49	-92.49	NUM
ap-6763	325	34	%	%	NOUN
ap-6763	325	35	,	,	PUNCT
ap-6763	325	36	respectively	respectively	ADV
ap-6763	325	37	.	.	PUNCT
ap-6763	326	1	the	the	DET
ap-6763	326	2	performance	performance	NOUN
ap-6763	326	3	of	of	ADP
ap-6763	326	4	the	the	DET
ap-6763	326	5	npspfcm	npspfcm	ADJ
ap-6763	326	6	algorithm	algorithm	NOUN
ap-6763	326	7	in	in	ADP
ap-6763	326	8	terms	term	NOUN
ap-6763	326	9	of	of	ADP
ap-6763	326	10	the	the	DET
ap-6763	326	11	number	number	NOUN
ap-6763	326	12	of	of	ADP
ap-6763	326	13	iterations	iteration	NOUN
ap-6763	326	14	for	for	ADP
ap-6763	326	15	all	all	DET
ap-6763	326	16	data	datum	NOUN
ap-6763	326	17	sets	set	NOUN
ap-6763	326	18	is	be	AUX
ap-6763	326	19	better	well	ADJ
ap-6763	326	20	than	than	ADP
ap-6763	326	21	that	that	PRON
ap-6763	326	22	of	of	ADP
ap-6763	326	23	the	the	DET
ap-6763	326	24	ocspfcm	ocspfcm	NOUN
ap-6763	326	25	,	,	PUNCT
ap-6763	326	26	except	except	SCONJ
ap-6763	326	27	for	for	ADP
ap-6763	326	28	the	the	DET
ap-6763	326	29	artificial	artificial	ADJ
ap-6763	326	30	data	datum	NOUN
ap-6763	326	31	set	set	VERB
ap-6763	326	32	i	i	PRON
ap-6763	326	33	,	,	PUNCT
ap-6763	326	34	in	in	ADP
ap-6763	326	35	this	this	DET
ap-6763	326	36	case	case	NOUN
ap-6763	326	37	,	,	PUNCT
ap-6763	326	38	the	the	DET
ap-6763	326	39	ocspfcm	ocspfcm	NOUN
ap-6763	326	40	outperformed	outperform	VERB
ap-6763	326	41	the	the	DET
ap-6763	326	42	npspfcm	npspfcm	NOUN
ap-6763	326	43	.	.	PUNCT
ap-6763	327	1	however	however	ADV
ap-6763	327	2	,	,	PUNCT
ap-6763	327	3	in	in	ADP
ap-6763	327	4	general	general	ADJ
ap-6763	327	5	,	,	PUNCT
ap-6763	327	6	the	the	DET
ap-6763	327	7	number	number	NOUN
ap-6763	327	8	of	of	ADP
ap-6763	327	9	iterations	iteration	NOUN
ap-6763	327	10	in	in	ADP
ap-6763	327	11	the	the	DET
ap-6763	327	12	case	case	NOUN
ap-6763	327	13	of	of	ADP
ap-6763	327	14	the	the	DET
ap-6763	327	15	artificial	artificial	ADJ
ap-6763	327	16	data	datum	NOUN
ap-6763	327	17	set	set	VERB
ap-6763	327	18	i	i	PRON
ap-6763	327	19	was	be	AUX
ap-6763	327	20	relatively	relatively	ADV
ap-6763	327	21	equal	equal	ADJ
ap-6763	327	22	between	between	ADP
ap-6763	327	23	the	the	DET
ap-6763	327	24	ocspfcm	ocspfcm	NOUN
ap-6763	327	25	and	and	CCONJ
ap-6763	327	26	npspfcm	npspfcm	ADJ
ap-6763	327	27	algorithms	algorithm	NOUN
ap-6763	327	28	.	.	PUNCT
ap-6763	328	1	the	the	DET
ap-6763	328	2	efficient	efficient	ADJ
ap-6763	328	3	number	number	NOUN
ap-6763	328	4	of	of	ADP
ap-6763	328	5	iterations	iteration	NOUN
ap-6763	328	6	of	of	ADP
ap-6763	328	7	the	the	DET
ap-6763	328	8	npspfcm	npspfcm	NOUN
ap-6763	328	9	was	be	AUX
ap-6763	328	10	due	due	ADJ
ap-6763	328	11	to	to	ADP
ap-6763	328	12	the	the	DET
ap-6763	328	13	fact	fact	NOUN
ap-6763	328	14	that	that	SCONJ
ap-6763	328	15	the	the	DET
ap-6763	328	16	missing	miss	VERB
ap-6763	328	17	values	value	NOUN
ap-6763	328	18	imputation	imputation	NOUN
ap-6763	328	19	are	be	AUX
ap-6763	328	20	updated	update	VERB
ap-6763	328	21	using	use	VERB
ap-6763	328	22	values	value	NOUN
ap-6763	328	23	available	available	ADJ
ap-6763	328	24	at	at	ADP
ap-6763	328	25	the	the	DET
ap-6763	328	26	nearest	near	ADJ
ap-6763	328	27	cluster	cluster	NOUN
ap-6763	328	28	center	center	NOUN
ap-6763	328	29	.	.	PUNCT
ap-6763	329	1	this	this	PRON
ap-6763	329	2	accelerates	accelerate	VERB
ap-6763	329	3	the	the	DET
ap-6763	329	4	convergence	convergence	NOUN
ap-6763	329	5	of	of	ADP
ap-6763	329	6	cluster	cluster	NOUN
ap-6763	329	7	centres	centre	NOUN
ap-6763	329	8	directly	directly	ADV
ap-6763	329	9	,	,	PUNCT
ap-6763	329	10	or	or	CCONJ
ap-6763	329	11	the	the	DET
ap-6763	329	12	condition	condition	NOUN
ap-6763	329	13	∥∥∥v(l	∥∥∥v(l	NOUN
ap-6763	329	14	)	)	PUNCT
ap-6763	330	1	i	i	PRON
ap-6763	330	2	−	−	VERB
ap-6763	330	3	v(l−1	v(l−1	NOUN
ap-6763	330	4	)	)	PUNCT
ap-6763	331	1	i	i	PRON
ap-6763	331	2	∥∥∥	∥∥∥	PROPN
ap-6763	331	3	<	<	X
ap-6763	331	4	ε	ε	PROPN
ap-6763	331	5	is	be	AUX
ap-6763	331	6	achieved	achieve	VERB
ap-6763	331	7	faster	fast	ADV
ap-6763	331	8	by	by	ADP
ap-6763	331	9	the	the	DET
ap-6763	331	10	npspfcm	npspfcm	ADJ
ap-6763	331	11	algorithm	algorithm	NOUN
ap-6763	331	12	than	than	ADP
ap-6763	331	13	the	the	DET
ap-6763	331	14	ocspfcm	ocspfcm	PROPN
ap-6763	331	15	algorithm	algorithm	NOUN
ap-6763	331	16	.	.	PUNCT
ap-6763	332	1	meanwhile	meanwhile	ADV
ap-6763	332	2	,	,	PUNCT
ap-6763	332	3	in	in	ADP
ap-6763	332	4	case	case	NOUN
ap-6763	332	5	of	of	ADP
ap-6763	332	6	the	the	DET
ap-6763	332	7	ocspfcm	ocspfcm	PROPN
ap-6763	332	8	algorithm	algorithm	NOUN
ap-6763	332	9	,	,	PUNCT
ap-6763	332	10	the	the	DET
ap-6763	332	11	imputation	imputation	NOUN
ap-6763	332	12	of	of	ADP
ap-6763	332	13	the	the	DET
ap-6763	332	14	missing	miss	VERB
ap-6763	332	15	values	value	NOUN
ap-6763	332	16	was	be	AUX
ap-6763	332	17	updated	update	VERB
ap-6763	332	18	using	use	VERB
ap-6763	332	19	the	the	DET
ap-6763	332	20	sum	sum	NOUN
ap-6763	332	21	of	of	ADP
ap-6763	332	22	fuzzy	fuzzy	ADJ
ap-6763	332	23	and	and	CCONJ
ap-6763	332	24	possibilistic	possibilistic	ADJ
ap-6763	332	25	membership	membership	NOUN
ap-6763	332	26	degrees	degree	NOUN
ap-6763	332	27	,	,	PUNCT
ap-6763	332	28	which	which	PRON
ap-6763	332	29	is	be	AUX
ap-6763	332	30	multiplied	multiply	VERB
ap-6763	332	31	by	by	ADP
ap-6763	332	32	available	available	ADJ
ap-6763	332	33	values	value	NOUN
ap-6763	332	34	in	in	ADP
ap-6763	332	35	the	the	DET
ap-6763	332	36	cluster	cluster	NOUN
ap-6763	332	37	centre	centre	NOUN
ap-6763	332	38	.	.	PUNCT
ap-6763	333	1	therefore	therefore	ADV
ap-6763	333	2	,	,	PUNCT
ap-6763	333	3	it	it	PRON
ap-6763	333	4	causes	cause	VERB
ap-6763	333	5	the	the	DET
ap-6763	333	6	slower	slow	ADJ
ap-6763	333	7	convergence	convergence	NOUN
ap-6763	333	8	of	of	ADP
ap-6763	333	9	the	the	DET
ap-6763	333	10	ocspfcm	ocspfcm	NOUN
ap-6763	333	11	.	.	PUNCT
ap-6763	334	1	finally	finally	ADV
ap-6763	334	2	,	,	PUNCT
ap-6763	334	3	the	the	DET
ap-6763	334	4	performance	performance	NOUN
ap-6763	334	5	of	of	ADP
ap-6763	334	6	the	the	DET
ap-6763	334	7	ocspfcm	ocspfcm	NOUN
ap-6763	334	8	and	and	CCONJ
ap-6763	334	9	npspfcm	npspfcm	ADJ
ap-6763	334	10	algorithms	algorithm	NOUN
ap-6763	334	11	was	be	AUX
ap-6763	334	12	evaluated	evaluate	VERB
ap-6763	334	13	on	on	ADP
ap-6763	334	14	centroid	centroid	NOUN
ap-6763	334	15	errors	error	NOUN
ap-6763	334	16	in	in	ADP
ap-6763	334	17	each	each	DET
ap-6763	334	18	data	datum	NOUN
ap-6763	334	19	set	set	VERB
ap-6763	334	20	.	.	PUNCT
ap-6763	335	1	the	the	DET
ap-6763	335	2	results	result	NOUN
ap-6763	335	3	showed	show	VERB
ap-6763	335	4	that	that	SCONJ
ap-6763	335	5	the	the	DET
ap-6763	335	6	centroid	centroid	NOUN
ap-6763	335	7	errors	error	NOUN
ap-6763	335	8	of	of	ADP
ap-6763	335	9	the	the	DET
ap-6763	335	10	npspfcm	npspfcm	ADJ
ap-6763	335	11	algorithm	algorithm	NOUN
ap-6763	335	12	for	for	ADP
ap-6763	335	13	all	all	DET
ap-6763	335	14	data	datum	NOUN
ap-6763	335	15	sets	set	NOUN
ap-6763	335	16	are	be	AUX
ap-6763	335	17	smaller	small	ADJ
ap-6763	335	18	than	than	ADP
ap-6763	335	19	that	that	PRON
ap-6763	335	20	of	of	ADP
ap-6763	335	21	the	the	DET
ap-6763	335	22	ocspfcm	ocspfcm	PROPN
ap-6763	335	23	algorithm	algorithm	NOUN
ap-6763	335	24	.	.	PUNCT
ap-6763	336	1	the	the	DET
ap-6763	336	2	smaller	small	ADJ
ap-6763	336	3	centroid	centroid	NOUN
ap-6763	336	4	errors	error	NOUN
ap-6763	336	5	of	of	ADP
ap-6763	336	6	the	the	DET
ap-6763	336	7	npspfcm	npspfcm	ADJ
ap-6763	336	8	algorithm	algorithm	NOUN
ap-6763	336	9	can	can	AUX
ap-6763	336	10	be	be	AUX
ap-6763	336	11	attributed	attribute	VERB
ap-6763	336	12	to	to	ADP
ap-6763	336	13	its	its	PRON
ap-6763	336	14	ability	ability	NOUN
ap-6763	336	15	to	to	PART
ap-6763	336	16	produce	produce	VERB
ap-6763	336	17	cluster	cluster	NOUN
ap-6763	336	18	centres	centre	NOUN
ap-6763	336	19	for	for	ADP
ap-6763	336	20	incomplete	incomplete	ADJ
ap-6763	336	21	data	datum	NOUN
ap-6763	336	22	sets	set	NOUN
ap-6763	336	23	with	with	ADP
ap-6763	336	24	a	a	DET
ap-6763	336	25	location	location	NOUN
ap-6763	336	26	that	that	PRON
ap-6763	336	27	is	be	AUX
ap-6763	336	28	not	not	PART
ap-6763	336	29	far	far	ADV
ap-6763	336	30	from	from	ADP
ap-6763	336	31	cluster	cluster	NOUN
ap-6763	336	32	centres	centre	NOUN
ap-6763	336	33	of	of	ADP
ap-6763	336	34	the	the	DET
ap-6763	336	35	base	base	NOUN
ap-6763	336	36	data	data	NOUN
ap-6763	336	37	sets	set	NOUN
ap-6763	336	38	.	.	PUNCT
ap-6763	337	1	this	this	PRON
ap-6763	337	2	is	be	AUX
ap-6763	337	3	the	the	DET
ap-6763	337	4	implication	implication	NOUN
ap-6763	337	5	of	of	ADP
ap-6763	337	6	the	the	DET
ap-6763	337	7	process	process	NOUN
ap-6763	337	8	of	of	ADP
ap-6763	337	9	updating	update	VERB
ap-6763	337	10	the	the	DET
ap-6763	337	11	imputation	imputation	NOUN
ap-6763	337	12	of	of	ADP
ap-6763	337	13	the	the	DET
ap-6763	337	14	missing	miss	VERB
ap-6763	337	15	values	value	NOUN
ap-6763	337	16	,	,	PUNCT
ap-6763	337	17	where	where	SCONJ
ap-6763	337	18	the	the	DET
ap-6763	337	19	npspfcm	npspfcm	ADJ
ap-6763	337	20	algorithm	algorithm	NOUN
ap-6763	337	21	produces	produce	VERB
ap-6763	337	22	values	value	NOUN
ap-6763	337	23	close	close	ADJ
ap-6763	337	24	to	to	ADP
ap-6763	337	25	the	the	DET
ap-6763	337	26	actual	actual	ADJ
ap-6763	337	27	value	value	NOUN
ap-6763	337	28	.	.	PUNCT
ap-6763	338	1	6	6	X
ap-6763	338	2	.	.	X
ap-6763	338	3	conclusions	conclusion	NOUN
ap-6763	338	4	in	in	ADP
ap-6763	338	5	conclusion	conclusion	NOUN
ap-6763	338	6	,	,	PUNCT
ap-6763	338	7	this	this	DET
ap-6763	338	8	study	study	NOUN
ap-6763	338	9	analysed	analyse	VERB
ap-6763	338	10	the	the	DET
ap-6763	338	11	potential	potential	ADJ
ap-6763	338	12	and	and	CCONJ
ap-6763	338	13	performance	performance	NOUN
ap-6763	338	14	modification	modification	NOUN
ap-6763	338	15	of	of	ADP
ap-6763	338	16	the	the	DET
ap-6763	338	17	pfcm	pfcm	ADJ
ap-6763	338	18	algorithm	algorithm	NOUN
ap-6763	338	19	for	for	ADP
ap-6763	338	20	clustering	cluster	VERB
ap-6763	338	21	incomplete	incomplete	ADJ
ap-6763	338	22	data	datum	NOUN
ap-6763	338	23	sets	set	NOUN
ap-6763	338	24	.	.	PUNCT
ap-6763	339	1	these	these	DET
ap-6763	339	2	modifications	modification	NOUN
ap-6763	339	3	,	,	PUNCT
ap-6763	339	4	which	which	PRON
ap-6763	339	5	emerge	emerge	VERB
ap-6763	339	6	from	from	ADP
ap-6763	339	7	the	the	DET
ap-6763	339	8	pfcm	pfcm	NOUN
ap-6763	339	9	,	,	PUNCT
ap-6763	339	10	as	as	SCONJ
ap-6763	339	11	ocspfcm	ocspfcm	PROPN
ap-6763	339	12	and	and	CCONJ
ap-6763	339	13	npspfcm	npspfcm	ADJ
ap-6763	339	14	are	be	AUX
ap-6763	339	15	associated	associate	VERB
ap-6763	339	16	with	with	ADP
ap-6763	339	17	incomplete	incomplete	ADJ
ap-6763	339	18	data	datum	NOUN
ap-6763	339	19	sets	set	NOUN
ap-6763	339	20	clustering	cluster	VERB
ap-6763	339	21	.	.	PUNCT
ap-6763	340	1	therefore	therefore	ADV
ap-6763	340	2	,	,	PUNCT
ap-6763	340	3	this	this	DET
ap-6763	340	4	research	research	NOUN
ap-6763	340	5	is	be	AUX
ap-6763	340	6	divided	divide	VERB
ap-6763	340	7	into	into	ADP
ap-6763	340	8	three	three	NUM
ap-6763	340	9	stages	stage	NOUN
ap-6763	340	10	.	.	PUNCT
ap-6763	341	1	in	in	ADP
ap-6763	341	2	the	the	DET
ap-6763	341	3	first	first	ADJ
ap-6763	341	4	stage	stage	NOUN
ap-6763	341	5	,	,	PUNCT
ap-6763	341	6	a	a	DET
ap-6763	341	7	clustering	clustering	NOUN
ap-6763	341	8	of	of	ADP
ap-6763	341	9	complete	complete	ADJ
ap-6763	341	10	data	datum	NOUN
ap-6763	341	11	sets	set	NOUN
ap-6763	341	12	was	be	AUX
ap-6763	341	13	carried	carry	VERB
ap-6763	341	14	out	out	ADP
ap-6763	341	15	using	use	VERB
ap-6763	341	16	the	the	DET
ap-6763	341	17	pfcm	pfcm	PROPN
ap-6763	341	18	algorithm	algorithm	NOUN
ap-6763	341	19	.	.	PUNCT
ap-6763	342	1	the	the	DET
ap-6763	342	2	cluster	cluster	NOUN
ap-6763	342	3	results	result	NOUN
ap-6763	342	4	obtained	obtain	VERB
ap-6763	342	5	at	at	ADP
ap-6763	342	6	this	this	DET
ap-6763	342	7	stage	stage	NOUN
ap-6763	342	8	are	be	AUX
ap-6763	342	9	the	the	DET
ap-6763	342	10	base	base	NOUN
ap-6763	342	11	for	for	ADP
ap-6763	342	12	evaluating	evaluate	VERB
ap-6763	342	13	the	the	DET
ap-6763	342	14	performance	performance	NOUN
ap-6763	342	15	of	of	ADP
ap-6763	342	16	the	the	DET
ap-6763	342	17	oscpfcm	oscpfcm	NOUN
ap-6763	342	18	and	and	CCONJ
ap-6763	342	19	npspfcm	npspfcm	ADJ
ap-6763	342	20	algorithms	algorithm	NOUN
ap-6763	342	21	.	.	PUNCT
ap-6763	343	1	furthermore	furthermore	ADV
ap-6763	343	2	,	,	PUNCT
ap-6763	343	3	the	the	DET
ap-6763	343	4	performance	performance	NOUN
ap-6763	343	5	of	of	ADP
ap-6763	343	6	the	the	DET
ap-6763	343	7	ocspfcm	ocspfcm	NOUN
ap-6763	343	8	and	and	CCONJ
ap-6763	343	9	npspfcm	npspfcm	ADJ
ap-6763	343	10	was	be	AUX
ap-6763	343	11	analysed	analyse	VERB
ap-6763	343	12	based	base	VERB
ap-6763	343	13	on	on	ADP
ap-6763	343	14	three	three	NUM
ap-6763	343	15	parameters	parameter	NOUN
ap-6763	343	16	,	,	PUNCT
ap-6763	343	17	accuracy	accuracy	NOUN
ap-6763	343	18	percentage	percentage	NOUN
ap-6763	343	19	,	,	PUNCT
ap-6763	343	20	the	the	DET
ap-6763	343	21	number	number	NOUN
ap-6763	343	22	of	of	ADP
ap-6763	343	23	iterations	iteration	NOUN
ap-6763	343	24	,	,	PUNCT
ap-6763	343	25	and	and	CCONJ
ap-6763	343	26	centroid	centroid	NOUN
ap-6763	343	27	errors	error	NOUN
ap-6763	343	28	.	.	PUNCT
ap-6763	344	1	in	in	ADP
ap-6763	344	2	the	the	DET
ap-6763	344	3	second	second	ADJ
ap-6763	344	4	stage	stage	NOUN
ap-6763	344	5	,	,	PUNCT
ap-6763	344	6	the	the	DET
ap-6763	344	7	complete	complete	ADJ
ap-6763	344	8	data	data	NOUN
ap-6763	344	9	sets	set	NOUN
ap-6763	344	10	were	be	AUX
ap-6763	344	11	made	make	VERB
ap-6763	344	12	incomplete	incomplete	ADJ
ap-6763	344	13	with	with	ADP
ap-6763	344	14	missing	miss	VERB
ap-6763	344	15	values	value	NOUN
ap-6763	344	16	at	at	ADP
ap-6763	344	17	predetermined	predetermine	VERB
ap-6763	344	18	percentages	percentage	NOUN
ap-6763	344	19	.	.	PUNCT
ap-6763	345	1	in	in	ADP
ap-6763	345	2	the	the	DET
ap-6763	345	3	third	third	ADJ
ap-6763	345	4	stage	stage	NOUN
ap-6763	345	5	,	,	PUNCT
ap-6763	345	6	the	the	DET
ap-6763	345	7	incomplete	incomplete	ADJ
ap-6763	345	8	data	datum	NOUN
ap-6763	345	9	sets	set	VERB
ap-6763	345	10	375	375	NUM
ap-6763	345	11	rustam	rustam	NOUN
ap-6763	345	12	,	,	PUNCT
ap-6763	345	13	k.	k.	PROPN
ap-6763	345	14	usman	usman	PROPN
ap-6763	345	15	,	,	PUNCT
ap-6763	345	16	m.	m.	NOUN
ap-6763	345	17	kamaruddin	kamaruddin	PROPN
ap-6763	345	18	et	et	PROPN
ap-6763	345	19	al	al	PROPN
ap-6763	345	20	.	.	PROPN
ap-6763	346	1	acta	acta	PROPN
ap-6763	346	2	polytechnica	polytechnica	PROPN
ap-6763	346	3	were	be	AUX
ap-6763	346	4	clustered	cluster	VERB
ap-6763	346	5	using	use	VERB
ap-6763	346	6	the	the	DET
ap-6763	346	7	ocspfcm	ocspfcm	NOUN
ap-6763	346	8	and	and	CCONJ
ap-6763	346	9	npspfcm	npspfcm	ADJ
ap-6763	346	10	.	.	PUNCT
ap-6763	347	1	the	the	DET
ap-6763	347	2	results	result	NOUN
ap-6763	347	3	showed	show	VERB
ap-6763	347	4	that	that	SCONJ
ap-6763	347	5	both	both	DET
ap-6763	347	6	algorithms	algorithm	NOUN
ap-6763	347	7	have	have	VERB
ap-6763	347	8	the	the	DET
ap-6763	347	9	potential	potential	NOUN
ap-6763	347	10	to	to	PART
ap-6763	347	11	cluster	cluster	VERB
ap-6763	347	12	incomplete	incomplete	ADJ
ap-6763	347	13	data	datum	NOUN
ap-6763	347	14	sets	set	NOUN
ap-6763	347	15	.	.	PUNCT
ap-6763	348	1	however	however	ADV
ap-6763	348	2	,	,	PUNCT
ap-6763	348	3	the	the	DET
ap-6763	348	4	npspfcm	npspfcm	NOUN
ap-6763	348	5	outperforms	outperform	VERB
ap-6763	348	6	the	the	DET
ap-6763	348	7	ocspfcm	ocspfcm	NOUN
ap-6763	348	8	based	base	VERB
ap-6763	348	9	on	on	ADP
ap-6763	348	10	the	the	DET
ap-6763	348	11	three	three	NUM
ap-6763	348	12	evaluated	evaluated	ADJ
ap-6763	348	13	processes	process	NOUN
ap-6763	348	14	.	.	PUNCT
ap-6763	349	1	the	the	DET
ap-6763	349	2	npspfcm	npspfcm	NOUN
ap-6763	349	3	outperforms	outperform	VERB
ap-6763	349	4	the	the	DET
ap-6763	349	5	ocspfcm	ocspfcm	NOUN
ap-6763	349	6	with	with	ADP
ap-6763	349	7	the	the	DET
ap-6763	349	8	missing	miss	VERB
ap-6763	349	9	values	value	NOUN
ap-6763	349	10	ranging	range	VERB
ap-6763	349	11	from	from	ADP
ap-6763	349	12	5%-30	5%-30	NUM
ap-6763	349	13	%	%	NOUN
ap-6763	349	14	for	for	ADP
ap-6763	349	15	all	all	DET
ap-6763	349	16	experimental	experimental	ADJ
ap-6763	349	17	data	datum	NOUN
ap-6763	349	18	sets	set	NOUN
ap-6763	349	19	.	.	PUNCT
ap-6763	350	1	therefore	therefore	ADV
ap-6763	350	2	,	,	PUNCT
ap-6763	350	3	this	this	DET
ap-6763	350	4	research	research	NOUN
ap-6763	350	5	recommends	recommend	VERB
ap-6763	350	6	the	the	DET
ap-6763	350	7	use	use	NOUN
ap-6763	350	8	of	of	ADP
ap-6763	350	9	the	the	DET
ap-6763	350	10	npspfcm	npspfcm	NOUN
ap-6763	350	11	for	for	ADP
ap-6763	350	12	clustering	cluster	VERB
ap-6763	350	13	incomplete	incomplete	ADJ
ap-6763	350	14	data	datum	NOUN
ap-6763	350	15	sets	set	NOUN
ap-6763	350	16	.	.	PUNCT
ap-6763	351	1	furthermore	furthermore	ADV
ap-6763	351	2	,	,	PUNCT
ap-6763	351	3	the	the	DET
ap-6763	351	4	modification	modification	NOUN
ap-6763	351	5	of	of	ADP
ap-6763	351	6	the	the	DET
ap-6763	351	7	pfcm	pfcm	PROPN
ap-6763	351	8	proposed	propose	VERB
ap-6763	351	9	in	in	ADP
ap-6763	351	10	this	this	DET
ap-6763	351	11	research	research	NOUN
ap-6763	351	12	has	have	AUX
ap-6763	351	13	enriched	enrich	VERB
ap-6763	351	14	the	the	DET
ap-6763	351	15	reference	reference	NOUN
ap-6763	351	16	of	of	ADP
ap-6763	351	17	the	the	DET
ap-6763	351	18	incomplete	incomplete	ADJ
ap-6763	351	19	data	datum	NOUN
ap-6763	351	20	set	set	VERB
ap-6763	351	21	clustering	cluster	VERB
ap-6763	351	22	algorithm	algorithm	NOUN
ap-6763	351	23	.	.	PUNCT
ap-6763	352	1	acknowledgements	acknowledgement	NOUN
ap-6763	352	2	the	the	DET
ap-6763	352	3	authors	author	NOUN
ap-6763	352	4	would	would	AUX
ap-6763	352	5	like	like	VERB
ap-6763	352	6	to	to	PART
ap-6763	352	7	express	express	VERB
ap-6763	352	8	their	their	PRON
ap-6763	352	9	gratitude	gratitude	NOUN
ap-6763	352	10	to	to	PART
ap-6763	352	11	telkom	telkom	VERB
ap-6763	352	12	university	university	NOUN
ap-6763	352	13	for	for	ADP
ap-6763	352	14	its	its	PRON
ap-6763	352	15	financial	financial	ADJ
ap-6763	352	16	support	support	NOUN
ap-6763	352	17	.	.	PUNCT
ap-6763	353	1	list	list	NOUN
ap-6763	353	2	of	of	ADP
ap-6763	353	3	symbols	symbols	PROPN
ap-6763	353	4	rd	rd	PROPN
ap-6763	353	5	space	space	NOUN
ap-6763	353	6	of	of	ADP
ap-6763	353	7	real	real	ADJ
ap-6763	353	8	d	d	NOUN
ap-6763	353	9	-	-	PUNCT
ap-6763	353	10	vectors	vector	NOUN
ap-6763	353	11	xk	xk	PROPN
ap-6763	353	12	data	data	PROPN
ap-6763	353	13	vector	vector	PROPN
ap-6763	353	14	(	(	PUNCT
ap-6763	353	15	data	data	NOUN
ap-6763	353	16	point	point	NOUN
ap-6763	353	17	)	)	PUNCT
ap-6763	353	18	vi	vi	NOUN
ap-6763	353	19	cluster	cluster	NOUN
ap-6763	353	20	centre	centre	NOUN
ap-6763	353	21	dik	dik	ADJ
ap-6763	353	22	uclidean	uclidean	ADJ
ap-6763	353	23	distance	distance	NOUN
ap-6763	353	24	between	between	ADP
ap-6763	353	25	xk	xk	PROPN
ap-6763	353	26	and	and	CCONJ
ap-6763	353	27	vi	vi	PROPN
ap-6763	353	28	uik	uik	NOUN
ap-6763	353	29	fuzzy	fuzzy	ADJ
ap-6763	353	30	membership	membership	NOUN
ap-6763	353	31	degree	degree	NOUN
ap-6763	353	32	tik	tik	PROPN
ap-6763	353	33	possibilistic	possibilistic	ADJ
ap-6763	353	34	membership	membership	NOUN
ap-6763	353	35	degree	degree	NOUN
ap-6763	353	36	α	α	PRON
ap-6763	353	37	importance	importance	NOUN
ap-6763	353	38	level	level	NOUN
ap-6763	353	39	of	of	ADP
ap-6763	353	40	uik	uik	NOUN
ap-6763	353	41	β	β	NOUN
ap-6763	353	42	importance	importance	NOUN
ap-6763	353	43	level	level	NOUN
ap-6763	353	44	of	of	ADP
ap-6763	353	45	tik	tik	NOUN
ap-6763	353	46	δi	δi	PROPN
ap-6763	353	47	possibilistic	possibilistic	ADJ
ap-6763	353	48	typicality	typicality	PROPN
ap-6763	353	49	m	m	VERB
ap-6763	353	50	fuzzy	fuzzy	ADJ
ap-6763	353	51	parameter	parameter	NOUN
ap-6763	353	52	τ	τ	PROPN
ap-6763	353	53	possibilistic	possibilistic	ADJ
ap-6763	353	54	parameter	parameter	NOUN
ap-6763	353	55	references	reference	NOUN
ap-6763	353	56	[	[	X
ap-6763	353	57	1	1	NUM
ap-6763	353	58	]	]	PUNCT
ap-6763	353	59	l.	l.	PROPN
ap-6763	353	60	himmelspach	himmelspach	PROPN
ap-6763	353	61	.	.	PUNCT
ap-6763	354	1	fuzzy	fuzzy	ADJ
ap-6763	354	2	clustering	clustering	NOUN
ap-6763	354	3	of	of	ADP
ap-6763	354	4	incomplete	incomplete	ADJ
ap-6763	354	5	data	datum	NOUN
ap-6763	354	6	.	.	PUNCT
ap-6763	355	1	ph.d	ph.d	PROPN
ap-6763	355	2	.	.	PUNCT
ap-6763	356	1	thesis	thesis	NOUN
ap-6763	356	2	,	,	PUNCT
ap-6763	356	3	2016	2016	NUM
ap-6763	356	4	.	.	PUNCT
ap-6763	357	1	[	[	X
ap-6763	357	2	2	2	X
ap-6763	357	3	]	]	PUNCT
ap-6763	357	4	j.	j.	PROPN
ap-6763	357	5	c.	c.	PROPN
ap-6763	357	6	bezdek	bezdek	PROPN
ap-6763	357	7	,	,	PUNCT
ap-6763	357	8	r.	r.	PROPN
ap-6763	357	9	ehrlich	ehrlich	PROPN
ap-6763	357	10	,	,	PUNCT
ap-6763	357	11	w.	w.	PROPN
ap-6763	357	12	full	full	PROPN
ap-6763	357	13	.	.	PUNCT
ap-6763	358	1	fcm	fcm	PROPN
ap-6763	358	2	:	:	PUNCT
ap-6763	358	3	the	the	DET
ap-6763	358	4	fuzzy	fuzzy	ADJ
ap-6763	358	5	c	c	NOUN
ap-6763	358	6	-	-	PUNCT
ap-6763	358	7	means	mean	VERB
ap-6763	358	8	clustering	clustering	ADJ
ap-6763	358	9	algorithm	algorithm	NOUN
ap-6763	358	10	.	.	PUNCT
ap-6763	359	1	computers	computer	NOUN
ap-6763	359	2	&	&	CCONJ
ap-6763	359	3	geosciences	geoscience	NOUN
ap-6763	359	4	10(2	10(2	PROPN
ap-6763	359	5	-	-	SYM
ap-6763	359	6	3):191–203	3):191–203	NUM
ap-6763	359	7	,	,	PUNCT
ap-6763	359	8	1984	1984	NUM
ap-6763	359	9	.	.	PUNCT
ap-6763	360	1	https://doi.org/10.1016/0098-3004(84)90020-7	https://doi.org/10.1016/0098-3004(84)90020-7	PROPN
ap-6763	360	2	.	.	PUNCT
ap-6763	361	1	[	[	X
ap-6763	361	2	3	3	X
ap-6763	361	3	]	]	X
ap-6763	361	4	r.	r.	PROPN
ap-6763	361	5	krishnapuram	krishnapuram	PROPN
ap-6763	361	6	,	,	PUNCT
ap-6763	361	7	j.	j.	PROPN
ap-6763	361	8	m.	m.	PROPN
ap-6763	361	9	keller	keller	PROPN
ap-6763	361	10	.	.	PUNCT
ap-6763	362	1	a	a	DET
ap-6763	362	2	possibilistic	possibilistic	ADJ
ap-6763	362	3	approach	approach	NOUN
ap-6763	362	4	to	to	ADP
ap-6763	362	5	clustering	clustering	NOUN
ap-6763	362	6	.	.	PUNCT
ap-6763	363	1	ieee	ieee	NOUN
ap-6763	363	2	transactions	transaction	NOUN
ap-6763	363	3	on	on	ADP
ap-6763	363	4	fuzzy	fuzzy	ADJ
ap-6763	363	5	systems	system	NOUN
ap-6763	363	6	1(2):98–110	1(2):98–110	NUM
ap-6763	363	7	,	,	PUNCT
ap-6763	363	8	1993	1993	NUM
ap-6763	363	9	.	.	PUNCT
ap-6763	364	1	https://doi.org/10.1109/91.227387	https://doi.org/10.1109/91.227387	NOUN
ap-6763	364	2	.	.	PUNCT
ap-6763	365	1	[	[	X
ap-6763	365	2	4	4	X
ap-6763	365	3	]	]	PUNCT
ap-6763	365	4	r.	r.	PROPN
ap-6763	365	5	j.	j.	PROPN
ap-6763	365	6	hathaway	hathaway	PROPN
ap-6763	365	7	,	,	PUNCT
ap-6763	365	8	j.	j.	PROPN
ap-6763	365	9	c.	c.	PROPN
ap-6763	365	10	bezdek	bezdek	PROPN
ap-6763	365	11	.	.	PUNCT
ap-6763	366	1	fuzzy	fuzzy	ADJ
ap-6763	366	2	c	c	NOUN
ap-6763	366	3	-	-	PUNCT
ap-6763	366	4	means	means	NOUN
ap-6763	366	5	clustering	clustering	NOUN
ap-6763	366	6	of	of	ADP
ap-6763	366	7	incomplete	incomplete	ADJ
ap-6763	366	8	data	datum	NOUN
ap-6763	366	9	.	.	PUNCT
ap-6763	367	1	ieee	ieee	NOUN
ap-6763	367	2	transactions	transaction	NOUN
ap-6763	367	3	on	on	ADP
ap-6763	367	4	systems	system	NOUN
ap-6763	367	5	,	,	PUNCT
ap-6763	367	6	man	man	NOUN
ap-6763	367	7	,	,	PUNCT
ap-6763	367	8	and	and	CCONJ
ap-6763	367	9	cybernetics	cybernetic	NOUN
ap-6763	367	10	,	,	PUNCT
ap-6763	367	11	part	part	NOUN
ap-6763	367	12	b	b	PROPN
ap-6763	367	13	(	(	PUNCT
ap-6763	367	14	cybernetics	cybernetic	NOUN
ap-6763	367	15	)	)	PUNCT
ap-6763	367	16	31(5):735	31(5):735	NUM
ap-6763	367	17	–	–	PUNCT
ap-6763	367	18	744	744	NUM
ap-6763	367	19	,	,	PUNCT
ap-6763	367	20	2001	2001	NUM
ap-6763	367	21	.	.	PUNCT
ap-6763	368	1	https://doi.org/10.1109/3477.956035	https://doi.org/10.1109/3477.956035	NOUN
ap-6763	368	2	.	.	PUNCT
ap-6763	369	1	[	[	X
ap-6763	369	2	5	5	X
ap-6763	369	3	]	]	PUNCT
ap-6763	369	4	j.	j.	PROPN
ap-6763	369	5	k.	k.	PROPN
ap-6763	369	6	dixon	dixon	PROPN
ap-6763	369	7	.	.	PUNCT
ap-6763	370	1	pattern	pattern	NOUN
ap-6763	370	2	recognition	recognition	NOUN
ap-6763	370	3	with	with	ADP
ap-6763	370	4	partly	partly	ADV
ap-6763	370	5	missing	missing	ADJ
ap-6763	370	6	data	datum	NOUN
ap-6763	370	7	.	.	PUNCT
ap-6763	371	1	ieee	ieee	NOUN
ap-6763	371	2	transactions	transaction	NOUN
ap-6763	371	3	on	on	ADP
ap-6763	371	4	systems	system	NOUN
ap-6763	371	5	,	,	PUNCT
ap-6763	371	6	man	man	NOUN
ap-6763	371	7	,	,	PUNCT
ap-6763	371	8	and	and	CCONJ
ap-6763	371	9	cybernetics	cybernetic	NOUN
ap-6763	371	10	9(10):617–621	9(10):617–621	NUM
ap-6763	371	11	,	,	PUNCT
ap-6763	371	12	1979	1979	NUM
ap-6763	371	13	.	.	PUNCT
ap-6763	372	1	https://doi.org/10.1109/tsmc.1979.4310090	https://doi.org/10.1109/tsmc.1979.4310090	PROPN
ap-6763	372	2	.	.	PUNCT
ap-6763	373	1	[	[	X
ap-6763	373	2	6	6	NUM
ap-6763	373	3	]	]	X
ap-6763	373	4	n.	n.	PROPN
ap-6763	373	5	r.	r.	PROPN
ap-6763	373	6	pal	pal	PROPN
ap-6763	373	7	,	,	PUNCT
ap-6763	373	8	k.	k.	PROPN
ap-6763	373	9	pal	pal	PROPN
ap-6763	373	10	,	,	PUNCT
ap-6763	373	11	j.	j.	PROPN
ap-6763	373	12	m.	m.	PROPN
ap-6763	373	13	keller	keller	PROPN
ap-6763	373	14	,	,	PUNCT
ap-6763	373	15	j.	j.	PROPN
ap-6763	373	16	c.	c.	PROPN
ap-6763	373	17	bezdek	bezdek	PROPN
ap-6763	373	18	.	.	PUNCT
ap-6763	374	1	a	a	DET
ap-6763	374	2	possibilistic	possibilistic	ADJ
ap-6763	374	3	fuzzy	fuzzy	ADJ
ap-6763	374	4	c	c	NOUN
ap-6763	374	5	-	-	PUNCT
ap-6763	374	6	means	mean	VERB
ap-6763	374	7	clustering	clustering	ADJ
ap-6763	374	8	algorithm	algorithm	NOUN
ap-6763	374	9	.	.	PUNCT
ap-6763	375	1	ieee	ieee	NOUN
ap-6763	375	2	transactions	transaction	NOUN
ap-6763	375	3	on	on	ADP
ap-6763	375	4	fuzzy	fuzzy	ADJ
ap-6763	375	5	systems	system	NOUN
ap-6763	375	6	13(4):517–530	13(4):517–530	PROPN
ap-6763	375	7	,	,	PUNCT
ap-6763	375	8	2005	2005	NUM
ap-6763	375	9	.	.	PUNCT
ap-6763	376	1	https://doi.org/10.1109/tfuzz.2004.840099	https://doi.org/10.1109/tfuzz.2004.840099	X
ap-6763	376	2	.	.	PUNCT
ap-6763	377	1	[	[	X
ap-6763	377	2	7	7	X
ap-6763	377	3	]	]	X
ap-6763	377	4	y.	y.	PROPN
ap-6763	377	5	jiang	jiang	PROPN
ap-6763	377	6	,	,	PUNCT
ap-6763	377	7	k.	k.	PROPN
ap-6763	377	8	zhao	zhao	PROPN
ap-6763	377	9	,	,	PUNCT
ap-6763	377	10	k.	k.	PROPN
ap-6763	377	11	xia	xia	PROPN
ap-6763	377	12	,	,	PUNCT
ap-6763	377	13	et	et	PROPN
ap-6763	377	14	al	al	PROPN
ap-6763	377	15	.	.	PUNCT
ap-6763	378	1	a	a	DET
ap-6763	378	2	novel	novel	NOUN
ap-6763	378	3	distributed	distribute	VERB
ap-6763	378	4	multitask	multitask	ADJ
ap-6763	378	5	fuzzy	fuzzy	ADJ
ap-6763	378	6	clustering	clustering	ADJ
ap-6763	378	7	algorithm	algorithm	NOUN
ap-6763	378	8	for	for	ADP
ap-6763	378	9	automatic	automatic	ADJ
ap-6763	378	10	mr	mr	PROPN
ap-6763	378	11	brain	brain	NOUN
ap-6763	378	12	image	image	NOUN
ap-6763	378	13	segmentation	segmentation	NOUN
ap-6763	378	14	.	.	PUNCT
ap-6763	379	1	journal	journal	PROPN
ap-6763	379	2	of	of	ADP
ap-6763	379	3	medical	medical	ADJ
ap-6763	379	4	systems	system	NOUN
ap-6763	379	5	43(5):118	43(5):118	NUM
ap-6763	379	6	,	,	PUNCT
ap-6763	379	7	2019	2019	NUM
ap-6763	379	8	.	.	PUNCT
ap-6763	380	1	https://doi.org/10.1007/s10916-019-1245-1	https://doi.org/10.1007/s10916-019-1245-1	NUM
ap-6763	380	2	.	.	PUNCT
ap-6763	381	1	[	[	X
ap-6763	381	2	8	8	NUM
ap-6763	381	3	]	]	PUNCT
ap-6763	381	4	t.	t.	PROPN
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ap-6763	381	6	,	,	PUNCT
ap-6763	381	7	h.	h.	PROPN
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ap-6763	381	12	,	,	PUNCT
ap-6763	381	13	et	et	PROPN
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ap-6763	381	15	.	.	PROPN
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ap-6763	381	18	the	the	DET
ap-6763	381	19	improved	improve	VERB
ap-6763	381	20	fuzzy	fuzzy	ADJ
ap-6763	381	21	clustering	clustering	ADJ
ap-6763	381	22	algorithm	algorithm	NOUN
ap-6763	381	23	and	and	CCONJ
ap-6763	381	24	its	its	PRON
ap-6763	381	25	application	application	NOUN
ap-6763	381	26	in	in	ADP
ap-6763	381	27	brain	brain	NOUN
ap-6763	381	28	image	image	NOUN
ap-6763	381	29	segmentation	segmentation	NOUN
ap-6763	381	30	.	.	PUNCT
ap-6763	382	1	applied	apply	VERB
ap-6763	382	2	soft	soft	ADJ
ap-6763	382	3	computing	computing	NOUN
ap-6763	382	4	81:105503	81:105503	NUM
ap-6763	382	5	,	,	PUNCT
ap-6763	382	6	2019	2019	NUM
ap-6763	382	7	.	.	PUNCT
ap-6763	383	1	https://doi.org/10.1016/j.asoc.2019.105503	https://doi.org/10.1016/j.asoc.2019.105503	ADJ
ap-6763	383	2	.	.	PUNCT
ap-6763	384	1	[	[	X
ap-6763	384	2	9	9	NUM
ap-6763	384	3	]	]	X
ap-6763	384	4	n.	n.	PROPN
ap-6763	384	5	x.	x.	PROPN
ap-6763	384	6	thao	thao	PROPN
ap-6763	384	7	,	,	PUNCT
ap-6763	384	8	m.	m.	PROPN
ap-6763	384	9	ali	ali	PROPN
ap-6763	384	10	,	,	PUNCT
ap-6763	384	11	f.	f.	PROPN
ap-6763	384	12	smarandache	smarandache	PROPN
ap-6763	384	13	.	.	PUNCT
ap-6763	385	1	an	an	DET
ap-6763	385	2	intuitionistic	intuitionistic	ADJ
ap-6763	385	3	fuzzy	fuzzy	ADJ
ap-6763	385	4	clustering	clustering	ADJ
ap-6763	385	5	algorithm	algorithm	NOUN
ap-6763	385	6	based	base	VERB
ap-6763	385	7	on	on	ADP
ap-6763	385	8	a	a	DET
ap-6763	385	9	new	new	ADJ
ap-6763	385	10	correlation	correlation	NOUN
ap-6763	385	11	coefficient	coefficient	NOUN
ap-6763	385	12	with	with	ADP
ap-6763	385	13	application	application	NOUN
ap-6763	385	14	in	in	ADP
ap-6763	385	15	medical	medical	ADJ
ap-6763	385	16	diagnosis	diagnosis	NOUN
ap-6763	385	17	.	.	PUNCT
ap-6763	386	1	journal	journal	NOUN
ap-6763	386	2	of	of	ADP
ap-6763	386	3	intelligent	intelligent	ADJ
ap-6763	386	4	&	&	CCONJ
ap-6763	386	5	fuzzy	fuzzy	ADJ
ap-6763	386	6	systems	system	NOUN
ap-6763	386	7	36(1):189–198	36(1):189–198	PROPN
ap-6763	386	8	,	,	PUNCT
ap-6763	386	9	2019	2019	NUM
ap-6763	386	10	.	.	PUNCT
ap-6763	387	1	https://doi.org/10.3233/jifs-181084	https://doi.org/10.3233/jifs-181084	ADV
ap-6763	387	2	.	.	PUNCT
ap-6763	388	1	[	[	X
ap-6763	388	2	10	10	NUM
ap-6763	388	3	]	]	X
ap-6763	388	4	y.	y.	PROPN
ap-6763	388	5	li	li	PROPN
ap-6763	388	6	,	,	PUNCT
ap-6763	388	7	j.-c	j.-c	PROPN
ap-6763	388	8	.	.	PUNCT
ap-6763	389	1	fan	fan	PROPN
ap-6763	389	2	,	,	PUNCT
ap-6763	389	3	j.-s	j.-s	PROPN
ap-6763	389	4	.	.	PUNCT
ap-6763	390	1	pan	pan	PROPN
ap-6763	390	2	,	,	PUNCT
ap-6763	390	3	et	et	PROPN
ap-6763	390	4	al	al	PROPN
ap-6763	390	5	.	.	PUNCT
ap-6763	391	1	a	a	DET
ap-6763	391	2	novel	novel	ADJ
ap-6763	391	3	rough	rough	ADJ
ap-6763	391	4	fuzzy	fuzzy	ADJ
ap-6763	391	5	clustering	clustering	ADJ
ap-6763	391	6	algorithm	algorithm	NOUN
ap-6763	391	7	with	with	ADP
ap-6763	391	8	a	a	DET
ap-6763	391	9	new	new	ADJ
ap-6763	391	10	similarity	similarity	NOUN
ap-6763	391	11	measurement	measurement	NOUN
ap-6763	391	12	.	.	PUNCT
ap-6763	392	1	journal	journal	PROPN
ap-6763	392	2	of	of	ADP
ap-6763	392	3	internet	internet	NOUN
ap-6763	392	4	technology	technology	NOUN
ap-6763	392	5	20(4):1145–1156	20(4):1145–1156	NOUN
ap-6763	392	6	,	,	PUNCT
ap-6763	392	7	2019	2019	NUM
ap-6763	392	8	.	.	PUNCT
ap-6763	393	1	https://doi.org/10.3966/160792642019072004014	https://doi.org/10.3966/160792642019072004014	X
ap-6763	393	2	.	.	PUNCT
ap-6763	394	1	[	[	X
ap-6763	394	2	11	11	NUM
ap-6763	394	3	]	]	PUNCT
ap-6763	394	4	i.	i.	NOUN
ap-6763	394	5	škrjanc	škrjanc	PROPN
ap-6763	394	6	,	,	PUNCT
ap-6763	394	7	s.	s.	PROPN
ap-6763	394	8	blažič	blažič	PROPN
ap-6763	394	9	,	,	PUNCT
ap-6763	394	10	e.	e.	PROPN
ap-6763	394	11	lughofer	lughofer	PROPN
ap-6763	394	12	,	,	PUNCT
ap-6763	394	13	d.	d.	PROPN
ap-6763	394	14	dovžan	dovžan	PROPN
ap-6763	394	15	.	.	PUNCT
ap-6763	395	1	inner	inner	ADJ
ap-6763	395	2	matrix	matrix	NOUN
ap-6763	395	3	norms	norm	NOUN
ap-6763	395	4	in	in	ADP
ap-6763	395	5	evolving	evolve	VERB
ap-6763	395	6	cauchy	cauchy	ADJ
ap-6763	395	7	possibilistic	possibilistic	ADJ
ap-6763	395	8	clustering	clustering	NOUN
ap-6763	395	9	for	for	ADP
ap-6763	395	10	classification	classification	NOUN
ap-6763	395	11	and	and	CCONJ
ap-6763	395	12	regression	regression	NOUN
ap-6763	395	13	from	from	ADP
ap-6763	395	14	data	datum	NOUN
ap-6763	395	15	streams	stream	NOUN
ap-6763	395	16	.	.	PUNCT
ap-6763	396	1	information	information	NOUN
ap-6763	396	2	sciences	sciences	PROPN
ap-6763	396	3	478:540–563	478:540–563	NUM
ap-6763	396	4	,	,	PUNCT
ap-6763	396	5	2019	2019	NUM
ap-6763	396	6	.	.	PUNCT
ap-6763	397	1	https://doi.org/https://doi.org/10.1016/j.ins.2018.11.040	https://doi.org/https://doi.org/10.1016/j.ins.2018.11.040	NOUN
ap-6763	397	2	.	.	PUNCT
ap-6763	398	1	[	[	X
ap-6763	398	2	12	12	NUM
ap-6763	398	3	]	]	PUNCT
ap-6763	398	4	a.	a.	NOUN
ap-6763	398	5	koutsibella	koutsibella	PROPN
ap-6763	398	6	,	,	PUNCT
ap-6763	398	7	k.	k.	PROPN
ap-6763	398	8	d.	d.	PROPN
ap-6763	398	9	koutroumbas	koutroumbas	PROPN
ap-6763	398	10	.	.	PUNCT
ap-6763	399	1	stochastic	stochastic	ADJ
ap-6763	399	2	gradient	gradient	ADJ
ap-6763	399	3	descent	descent	NOUN
ap-6763	399	4	possibilistic	possibilistic	ADJ
ap-6763	399	5	clustering	clustering	NOUN
ap-6763	399	6	.	.	PUNCT
ap-6763	400	1	in	in	ADP
ap-6763	400	2	11th	11th	ADJ
ap-6763	400	3	hellenic	hellenic	ADJ
ap-6763	400	4	conference	conference	NOUN
ap-6763	400	5	on	on	ADP
ap-6763	400	6	artificial	artificial	ADJ
ap-6763	400	7	intelligence	intelligence	NOUN
ap-6763	400	8	,	,	PUNCT
ap-6763	400	9	pp	pp	ADV
ap-6763	400	10	.	.	PUNCT
ap-6763	401	1	189–194	189–194	NUM
ap-6763	401	2	.	.	NOUN
ap-6763	401	3	2020	2020	NUM
ap-6763	401	4	.	.	PUNCT
ap-6763	402	1	https://doi.org/10.1145/3411408.3411436	https://doi.org/10.1145/3411408.3411436	NOUN
ap-6763	402	2	.	.	PUNCT
ap-6763	403	1	[	[	X
ap-6763	403	2	13	13	NUM
ap-6763	403	3	]	]	PUNCT
ap-6763	403	4	l.	l.	PROPN
ap-6763	403	5	zhang	zhang	PROPN
ap-6763	403	6	,	,	PUNCT
ap-6763	403	7	w.	w.	PROPN
ap-6763	403	8	lu	lu	PROPN
ap-6763	403	9	,	,	PUNCT
ap-6763	403	10	x.	x.	PROPN
ap-6763	403	11	liu	liu	PROPN
ap-6763	403	12	,	,	PUNCT
ap-6763	403	13	et	et	PROPN
ap-6763	403	14	al	al	PROPN
ap-6763	403	15	.	.	PROPN
ap-6763	403	16	fuzzy	fuzzy	ADJ
ap-6763	403	17	c	c	NOUN
ap-6763	403	18	-	-	PUNCT
ap-6763	403	19	means	means	NOUN
ap-6763	403	20	clustering	clustering	NOUN
ap-6763	403	21	of	of	ADP
ap-6763	403	22	incomplete	incomplete	ADJ
ap-6763	403	23	data	datum	NOUN
ap-6763	403	24	based	base	VERB
ap-6763	403	25	on	on	ADP
ap-6763	403	26	probabilistic	probabilistic	ADJ
ap-6763	403	27	information	information	NOUN
ap-6763	403	28	granules	granule	NOUN
ap-6763	403	29	of	of	ADP
ap-6763	403	30	missing	miss	VERB
ap-6763	403	31	values	value	NOUN
ap-6763	403	32	.	.	PUNCT
ap-6763	404	1	knowledge	knowledge	NOUN
ap-6763	404	2	-	-	PUNCT
ap-6763	404	3	based	base	VERB
ap-6763	404	4	systems	system	NOUN
ap-6763	404	5	99:51–70	99:51–70	PROPN
ap-6763	404	6	,	,	PUNCT
ap-6763	404	7	2016	2016	NUM
ap-6763	404	8	.	.	PUNCT
ap-6763	405	1	https://doi.org/10.1016/j.knosys.2016.01.048	https://doi.org/10.1016/j.knosys.2016.01.048	NOUN
ap-6763	405	2	.	.	PUNCT
ap-6763	406	1	[	[	X
ap-6763	406	2	14	14	NUM
ap-6763	406	3	]	]	X
ap-6763	406	4	rustam	rustam	NOUN
ap-6763	406	5	,	,	PUNCT
ap-6763	406	6	a.	a.	PROPN
ap-6763	406	7	y.	y.	PROPN
ap-6763	406	8	gunawan	gunawan	PROPN
ap-6763	406	9	,	,	PUNCT
ap-6763	407	1	m.	m.	NOUN
ap-6763	407	2	t.	t.	PROPN
ap-6763	407	3	a.	a.	PROPN
ap-6763	407	4	p.	p.	PROPN
ap-6763	407	5	kresnowati	kresnowati	PROPN
ap-6763	407	6	.	.	PUNCT
ap-6763	408	1	the	the	DET
ap-6763	408	2	hard	hard	ADJ
ap-6763	408	3	c	c	NOUN
ap-6763	408	4	-	-	PUNCT
ap-6763	408	5	means	means	NOUN
ap-6763	408	6	algorithm	algorithm	NOUN
ap-6763	408	7	for	for	ADP
ap-6763	408	8	clustering	cluster	VERB
ap-6763	408	9	indonesian	indonesian	ADJ
ap-6763	408	10	plantation	plantation	NOUN
ap-6763	408	11	commodity	commodity	NOUN
ap-6763	408	12	based	base	VERB
ap-6763	408	13	on	on	ADP
ap-6763	408	14	metabolites	metabolite	NOUN
ap-6763	408	15	composition	composition	NOUN
ap-6763	408	16	.	.	PUNCT
ap-6763	409	1	in	in	ADP
ap-6763	409	2	journal	journal	PROPN
ap-6763	409	3	of	of	ADP
ap-6763	409	4	physics	physics	PROPN
ap-6763	409	5	:	:	PUNCT
ap-6763	409	6	conference	conference	NOUN
ap-6763	409	7	series	series	NOUN
ap-6763	409	8	,	,	PUNCT
ap-6763	409	9	vol	vol	NOUN
ap-6763	409	10	.	.	PROPN
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ap-6763	409	12	,	,	PUNCT
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ap-6763	409	14	012085	012085	NUM
ap-6763	409	15	.	.	PUNCT
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ap-6763	410	2	publishing	publishing	NOUN
ap-6763	410	3	,	,	PUNCT
ap-6763	410	4	2019	2019	NUM
ap-6763	410	5	.	.	PUNCT
ap-6763	411	1	https://doi.org/10.1088/1742-6596/1315/1/012085	https://doi.org/10.1088/1742-6596/1315/1/012085	PROPN
ap-6763	411	2	.	.	PUNCT
ap-6763	412	1	[	[	X
ap-6763	412	2	15	15	NUM
ap-6763	412	3	]	]	X
ap-6763	412	4	x.	x.	PROPN
ap-6763	412	5	l.	l.	PROPN
ap-6763	412	6	xie	xie	PROPN
ap-6763	412	7	,	,	PUNCT
ap-6763	412	8	g.	g.	PROPN
ap-6763	412	9	beni	beni	PROPN
ap-6763	412	10	.	.	PUNCT
ap-6763	413	1	a	a	DET
ap-6763	413	2	validity	validity	NOUN
ap-6763	413	3	measure	measure	NOUN
ap-6763	413	4	for	for	ADP
ap-6763	413	5	fuzzy	fuzzy	ADJ
ap-6763	413	6	clustering	clustering	NOUN
ap-6763	413	7	.	.	PUNCT
ap-6763	414	1	ieee	ieee	NOUN
ap-6763	414	2	transactions	transaction	NOUN
ap-6763	414	3	on	on	ADP
ap-6763	414	4	pattern	pattern	NOUN
ap-6763	414	5	analysis	analysis	NOUN
ap-6763	414	6	&	&	CCONJ
ap-6763	414	7	machine	machine	NOUN
ap-6763	414	8	intelligence	intelligence	PROPN
ap-6763	414	9	(	(	PUNCT
ap-6763	414	10	8):841–847	8):841–847	NUM
ap-6763	414	11	,	,	PUNCT
ap-6763	414	12	1991	1991	NUM
ap-6763	414	13	.	.	PUNCT
ap-6763	415	1	https://doi.org/10.1109/34.85677	https://doi.org/10.1109/34.85677	PROPN
ap-6763	415	2	.	.	PUNCT
ap-6763	416	1	[	[	X
ap-6763	416	2	16	16	NUM
ap-6763	416	3	]	]	PUNCT
ap-6763	416	4	r.	r.	PROPN
ap-6763	416	5	a.	a.	PROPN
ap-6763	416	6	fisher	fisher	PROPN
ap-6763	416	7	.	.	PUNCT
ap-6763	417	1	the	the	DET
ap-6763	417	2	use	use	NOUN
ap-6763	417	3	of	of	ADP
ap-6763	417	4	multiple	multiple	ADJ
ap-6763	417	5	measurements	measurement	NOUN
ap-6763	417	6	in	in	ADP
ap-6763	417	7	taxonomic	taxonomic	ADJ
ap-6763	417	8	problems	problem	NOUN
ap-6763	417	9	.	.	PUNCT
ap-6763	418	1	annals	annal	NOUN
ap-6763	418	2	of	of	ADP
ap-6763	418	3	eugenics	eugenic	NOUN
ap-6763	418	4	7(2):179–188	7(2):179–188	NOUN
ap-6763	418	5	,	,	PUNCT
ap-6763	418	6	1936	1936	NUM
ap-6763	418	7	.	.	PUNCT
ap-6763	419	1	https://doi.org/10.1111/j.1469-1809.1936.tb02137.x	https://doi.org/10.1111/j.1469-1809.1936.tb02137.x	PROPN
ap-6763	419	2	.	.	PUNCT
ap-6763	420	1	[	[	X
ap-6763	420	2	17	17	NUM
ap-6763	420	3	]	]	PUNCT
ap-6763	420	4	m.	m.	NOUN
ap-6763	420	5	forina	forina	PROPN
ap-6763	420	6	,	,	PUNCT
ap-6763	420	7	s.	s.	PROPN
ap-6763	420	8	lanteri	lanteri	PROPN
ap-6763	420	9	,	,	PUNCT
ap-6763	420	10	c.	c.	PROPN
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ap-6763	420	12	,	,	PUNCT
ap-6763	420	13	et	et	PROPN
ap-6763	420	14	al	al	PROPN
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ap-6763	420	17	-	-	PUNCT
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ap-6763	420	19	extendible	extendible	ADJ
ap-6763	420	20	package	package	NOUN
ap-6763	420	21	for	for	ADP
ap-6763	420	22	data	data	NOUN
ap-6763	420	23	exploration	exploration	NOUN
ap-6763	420	24	,	,	PUNCT
ap-6763	420	25	classification	classification	NOUN
ap-6763	420	26	and	and	CCONJ
ap-6763	420	27	correlation	correlation	NOUN
ap-6763	420	28	,	,	PUNCT
ap-6763	420	29	institute	institute	NOUN
ap-6763	420	30	of	of	ADP
ap-6763	420	31	pharmaceutical	pharmaceutical	NOUN
ap-6763	420	32	and	and	CCONJ
ap-6763	420	33	food	food	NOUN
ap-6763	420	34	analysis	analysis	NOUN
ap-6763	420	35	and	and	CCONJ
ap-6763	420	36	technologies	technology	NOUN
ap-6763	420	37	,	,	PUNCT
ap-6763	420	38	via	via	ADP
ap-6763	420	39	brigata	brigata	PROPN
ap-6763	420	40	salerno	salerno	PROPN
ap-6763	420	41	,	,	PUNCT
ap-6763	420	42	16147	16147	NUM
ap-6763	420	43	genoa	genoa	PROPN
ap-6763	420	44	,	,	PUNCT
ap-6763	420	45	italy	italy	PROPN
ap-6763	420	46	(	(	PUNCT
ap-6763	420	47	1988	1988	NUM
ap-6763	420	48	)	)	PUNCT
ap-6763	420	49	.	.	PUNCT
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ap-6763	421	3	av	av	PROPN
ap-6763	421	4	o	o	NOUN
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ap-6763	421	6	av	av	PROPN
ap-6763	421	7	hit	hit	NOUN
ap-6763	421	8	-	-	PUNCT
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ap-6763	421	10	1991	1991	NUM
ap-6763	421	11	.	.	PUNCT
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ap-6763	423	5	dua	dua	PROPN
ap-6763	423	6	,	,	PUNCT
ap-6763	423	7	c.	c.	PROPN
ap-6763	423	8	graff	graff	PROPN
ap-6763	423	9	.	.	PUNCT
ap-6763	424	1	uci	uci	PROPN
ap-6763	424	2	machine	machine	NOUN
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ap-6763	424	4	repository	repository	NOUN
ap-6763	424	5	2017	2017	NUM
ap-6763	424	6	.	.	PUNCT
ap-6763	425	1	http://archive.ics.uci.edu/ml	http://archive.ics.uci.edu/ml	NUM
ap-6763	425	2	.	.	PUNCT
ap-6763	426	1	[	[	X
ap-6763	426	2	19	19	NUM
ap-6763	426	3	]	]	X
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ap-6763	427	2	neural	neural	ADJ
ap-6763	427	3	network	network	NOUN
ap-6763	427	4	approach	approach	NOUN
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ap-6763	427	6	the	the	DET
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ap-6763	427	9	clove	clove	NOUN
ap-6763	427	10	buds	bud	NOUN
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ap-6763	427	13	on	on	ADP
ap-6763	427	14	metabolites	metabolite	NOUN
ap-6763	427	15	composition	composition	NOUN
ap-6763	427	16	.	.	PUNCT
ap-6763	428	1	acta	acta	PROPN
ap-6763	428	2	polytechnica	polytechnica	PROPN
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ap-6763	428	6	.	.	PUNCT
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ap-6763	430	4	m.	m.	PROPN
ap-6763	430	5	k.	k.	PROPN
ap-6763	430	6	pakhira	pakhira	PROPN
ap-6763	430	7	,	,	PUNCT
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ap-6763	430	9	bandyopadhyay	bandyopadhyay	PROPN
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ap-6763	430	11	u.	u.	PROPN
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ap-6763	431	1	validity	validity	NOUN
ap-6763	431	2	index	index	NOUN
ap-6763	431	3	for	for	ADP
ap-6763	431	4	crisp	crisp	ADJ
ap-6763	431	5	and	and	CCONJ
ap-6763	431	6	fuzzy	fuzzy	ADJ
ap-6763	431	7	clusters	cluster	NOUN
ap-6763	431	8	.	.	PUNCT
ap-6763	432	1	pattern	pattern	NOUN
ap-6763	432	2	recognition	recognition	NOUN
ap-6763	432	3	37(3):487–501	37(3):487–501	PROPN
ap-6763	432	4	,	,	PUNCT
ap-6763	432	5	2004	2004	NUM
ap-6763	432	6	.	.	PUNCT
ap-6763	433	1	https://doi.org/10.1016/j.patcog.2003.06.005	https://doi.org/10.1016/j.patcog.2003.06.005	PROPN
ap-6763	433	2	.	.	PROPN
ap-6763	434	1	376	376	NUM
ap-6763	434	2	https://doi.org/10.1016/0098-3004(84)90020-7	https://doi.org/10.1016/0098-3004(84)90020-7	PROPN
ap-6763	434	3	https://doi.org/10.1109/91.227387	https://doi.org/10.1109/91.227387	NOUN
ap-6763	434	4	https://doi.org/10.1109/3477.956035	https://doi.org/10.1109/3477.956035	NOUN
ap-6763	434	5	https://doi.org/10.1109/tsmc.1979.4310090	https://doi.org/10.1109/tsmc.1979.4310090	PROPN
ap-6763	434	6	https://doi.org/10.1109/tfuzz.2004.840099	https://doi.org/10.1109/tfuzz.2004.840099	X
ap-6763	434	7	https://doi.org/10.1007/s10916-019-1245-1	https://doi.org/10.1007/s10916-019-1245-1	NUM
ap-6763	434	8	https://doi.org/10.1016/j.asoc.2019.105503	https://doi.org/10.1016/j.asoc.2019.105503	ADJ
ap-6763	434	9	https://doi.org/10.3233/jifs-181084	https://doi.org/10.3233/jifs-181084	ADJ
ap-6763	434	10	https://doi.org/10.3966/160792642019072004014	https://doi.org/10.3966/160792642019072004014	NOUN
ap-6763	434	11	https://doi.org/https://doi.org/10.1016/j.ins.2018.11.040	https://doi.org/https://doi.org/10.1016/j.ins.2018.11.040	PROPN
ap-6763	434	12	https://doi.org/10.1145/3411408.3411436	https://doi.org/10.1145/3411408.3411436	NOUN
ap-6763	434	13	https://doi.org/10.1016/j.knosys.2016.01.048	https://doi.org/10.1016/j.knosys.2016.01.048	PROPN
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ap-6763	434	15	https://doi.org/10.1109/34.85677	https://doi.org/10.1109/34.85677	PROPN
ap-6763	434	16	https://doi.org/10.1111/j.1469-1809.1936.tb02137.x	https://doi.org/10.1111/j.1469-1809.1936.tb02137.x	PROPN
ap-6763	435	1	https://doi.org/10.1002/cem.1180040210	https://doi.org/10.1002/cem.1180040210	PROPN
ap-6763	435	2	http://archive.ics.uci.edu/ml	http://archive.ics.uci.edu/ml	PROPN
ap-6763	435	3	https://doi.org/10.14311/ap.2020.60.0440	https://doi.org/10.14311/ap.2020.60.0440	PROPN
ap-6763	435	4	https://doi.org/10.1016/j.patcog.2003.06.005	https://doi.org/10.1016/j.patcog.2003.06.005	PROPN
ap-6763	435	5	vol	vol	NOUN
ap-6763	435	6	.	.	PROPN
ap-6763	436	1	61	61	NUM
ap-6763	436	2	no	no	NOUN
ap-6763	436	3	.	.	PUNCT
ap-6763	437	1	2/2021	2/2021	NUM
ap-6763	437	2	modified	modify	VERB
ap-6763	437	3	possibilistic	possibilistic	ADJ
ap-6763	437	4	fuzzy	fuzzy	ADJ
ap-6763	437	5	c	c	NOUN
ap-6763	437	6	-	-	PUNCT
ap-6763	437	7	means	means	NOUN
ap-6763	437	8	algorithm	algorithm	NOUN
ap-6763	437	9	[	[	X
ap-6763	437	10	21	21	NUM
ap-6763	437	11	]	]	X
ap-6763	437	12	d.	d.	PROPN
ap-6763	437	13	l.	l.	PROPN
ap-6763	437	14	davies	davies	PROPN
ap-6763	437	15	,	,	PUNCT
ap-6763	437	16	d.	d.	PROPN
ap-6763	437	17	w.	w.	PROPN
ap-6763	437	18	bouldin	bouldin	PROPN
ap-6763	437	19	.	.	PUNCT
ap-6763	438	1	a	a	DET
ap-6763	438	2	cluster	cluster	NOUN
ap-6763	438	3	separation	separation	NOUN
ap-6763	438	4	measure	measure	NOUN
ap-6763	438	5	.	.	PUNCT
ap-6763	439	1	ieee	ieee	NOUN
ap-6763	439	2	transactions	transaction	NOUN
ap-6763	439	3	on	on	ADP
ap-6763	439	4	pattern	pattern	NOUN
ap-6763	439	5	analysis	analysis	NOUN
ap-6763	439	6	and	and	CCONJ
ap-6763	439	7	machine	machine	NOUN
ap-6763	439	8	intelligence	intelligence	NOUN
ap-6763	439	9	(	(	PUNCT
ap-6763	439	10	2):224–227	2):224–227	NUM
ap-6763	439	11	,	,	PUNCT
ap-6763	439	12	1979	1979	NUM
ap-6763	439	13	.	.	PUNCT
ap-6763	440	1	https://doi.org/10.1109/tpami.1979.4766909	https://doi.org/10.1109/tpami.1979.4766909	PROPN
ap-6763	440	2	.	.	PUNCT
ap-6763	441	1	[	[	X
ap-6763	441	2	22	22	NUM
ap-6763	441	3	]	]	X
ap-6763	441	4	d.	d.	PROPN
ap-6763	441	5	zhang	zhang	PROPN
ap-6763	441	6	,	,	PUNCT
ap-6763	441	7	m.	m.	PROPN
ap-6763	441	8	ji	ji	PROPN
ap-6763	441	9	,	,	PUNCT
ap-6763	441	10	j.	j.	PROPN
ap-6763	441	11	yang	yang	PROPN
ap-6763	441	12	,	,	PUNCT
ap-6763	441	13	et	et	PROPN
ap-6763	441	14	al	al	PROPN
ap-6763	441	15	.	.	PUNCT
ap-6763	442	1	a	a	DET
ap-6763	442	2	novel	novel	ADJ
ap-6763	442	3	cluster	cluster	NOUN
ap-6763	442	4	validity	validity	NOUN
ap-6763	442	5	index	index	NOUN
ap-6763	442	6	for	for	ADP
ap-6763	442	7	fuzzy	fuzzy	ADJ
ap-6763	442	8	clustering	clustering	NOUN
ap-6763	442	9	based	base	VERB
ap-6763	442	10	on	on	ADP
ap-6763	442	11	bipartite	bipartite	PROPN
ap-6763	442	12	modularity	modularity	NOUN
ap-6763	442	13	.	.	PUNCT
ap-6763	443	1	fuzzy	fuzzy	ADJ
ap-6763	443	2	sets	set	NOUN
ap-6763	443	3	and	and	CCONJ
ap-6763	443	4	systems	system	NOUN
ap-6763	443	5	253:122–137	253:122–137	NUM
ap-6763	443	6	,	,	PUNCT
ap-6763	443	7	2014	2014	NUM
ap-6763	443	8	.	.	PUNCT
ap-6763	444	1	https://doi.org/10.1016/j.fss.2013.12.013	https://doi.org/10.1016/j.fss.2013.12.013	PROPN
ap-6763	444	2	.	.	PUNCT
ap-6763	445	1	[	[	X
ap-6763	445	2	23	23	NUM
ap-6763	445	3	]	]	X
ap-6763	445	4	r.	r.	PROPN
ap-6763	445	5	n.	n.	PROPN
ap-6763	445	6	dave	dave	PROPN
ap-6763	445	7	.	.	PUNCT
ap-6763	446	1	validating	validate	VERB
ap-6763	446	2	fuzzy	fuzzy	ADJ
ap-6763	446	3	partitions	partition	NOUN
ap-6763	446	4	obtained	obtain	VERB
ap-6763	446	5	through	through	ADP
ap-6763	446	6	c	c	NOUN
ap-6763	446	7	-	-	PUNCT
ap-6763	446	8	shells	shell	NOUN
ap-6763	446	9	clustering	cluster	VERB
ap-6763	446	10	.	.	PUNCT
ap-6763	447	1	pattern	pattern	NOUN
ap-6763	447	2	recognition	recognition	NOUN
ap-6763	447	3	letters	letter	NOUN
ap-6763	447	4	17(6):613–623	17(6):613–623	NUM
ap-6763	447	5	,	,	PUNCT
ap-6763	447	6	1996	1996	NUM
ap-6763	447	7	.	.	PUNCT
ap-6763	448	1	https://doi.org/10.1016/0167-8655(96)00026-8	https://doi.org/10.1016/0167-8655(96)00026-8	PROPN
ap-6763	448	2	.	.	PUNCT
ap-6763	449	1	[	[	X
ap-6763	449	2	24	24	NUM
ap-6763	449	3	]	]	PUNCT
ap-6763	449	4	d.-q	d.-q	PROPN
ap-6763	449	5	.	.	PUNCT
ap-6763	450	1	zhang	zhang	PROPN
ap-6763	450	2	,	,	PUNCT
ap-6763	450	3	s.-c	s.-c	PROPN
ap-6763	450	4	.	.	PUNCT
ap-6763	451	1	chen	chen	PROPN
ap-6763	451	2	.	.	PUNCT
ap-6763	452	1	clustering	cluster	VERB
ap-6763	452	2	incomplete	incomplete	ADJ
ap-6763	452	3	data	datum	NOUN
ap-6763	452	4	using	use	VERB
ap-6763	452	5	kernel	kernel	NOUN
ap-6763	452	6	-	-	PUNCT
ap-6763	452	7	based	base	VERB
ap-6763	452	8	fuzzy	fuzzy	ADJ
ap-6763	452	9	c	c	NOUN
ap-6763	452	10	-	-	PUNCT
ap-6763	452	11	means	means	NOUN
ap-6763	452	12	algorithm	algorithm	NOUN
ap-6763	452	13	.	.	PUNCT
ap-6763	453	1	neural	neural	ADJ
ap-6763	453	2	processing	processing	NOUN
ap-6763	453	3	letters	letter	NOUN
ap-6763	453	4	18(3):155–162	18(3):155–162	PROPN
ap-6763	453	5	,	,	PUNCT
ap-6763	453	6	2003	2003	NUM
ap-6763	453	7	.	.	PUNCT
ap-6763	454	1	https://doi.org/10.1023/b:nepl.0000011135.19145.1b	https://doi.org/10.1023/b:nepl.0000011135.19145.1b	X
ap-6763	454	2	.	.	PUNCT
ap-6763	455	1	377	377	NUM
ap-6763	456	1	https://doi.org/10.1109/tpami.1979.4766909	https://doi.org/10.1109/tpami.1979.4766909	PROPN
ap-6763	456	2	https://doi.org/10.1016/j.fss.2013.12.013	https://doi.org/10.1016/j.fss.2013.12.013	PROPN
ap-6763	456	3	https://doi.org/10.1016/0167-8655(96)00026-8	https://doi.org/10.1016/0167-8655(96)00026-8	PROPN
ap-6763	456	4	https://doi.org/10.1023/b:nepl.0000011135.19145.1b	https://doi.org/10.1023/b:nepl.0000011135.19145.1b	PROPN
ap-6763	456	5	acta	acta	PROPN
ap-6763	456	6	polytechnica	polytechnica	PROPN
ap-6763	456	7	61(2):364–377	61(2):364–377	PROPN
ap-6763	456	8	,	,	PUNCT
ap-6763	456	9	2021	2021	NUM
ap-6763	456	10	1	1	NUM
ap-6763	456	11	introduction	introduction	NOUN
ap-6763	456	12	2	2	NUM
ap-6763	456	13	possibilistic	possibilistic	ADJ
ap-6763	456	14	fuzzy	fuzzy	ADJ
ap-6763	456	15	c	c	NOUN
ap-6763	456	16	-	-	PUNCT
ap-6763	456	17	means	means	NOUN
ap-6763	456	18	(	(	PUNCT
ap-6763	456	19	pfcm	pfcm	PROPN
ap-6763	456	20	)	)	PUNCT
ap-6763	456	21	algorithm	algorithm	NOUN
ap-6763	456	22	of	of	ADP
ap-6763	456	23	complete	complete	ADJ
ap-6763	456	24	data	datum	NOUN
ap-6763	456	25	sets	set	VERB
ap-6763	456	26	2.1	2.1	NUM
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ap-6763	456	28	fuzzy	fuzzy	ADJ
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ap-6763	456	30	-	-	PUNCT
ap-6763	456	31	means	means	NOUN
ap-6763	456	32	(	(	PUNCT
ap-6763	456	33	pfcm	pfcm	PROPN
ap-6763	456	34	)	)	PUNCT
ap-6763	456	35	algorithm	algorithm	NOUN
ap-6763	456	36	3	3	NUM
ap-6763	456	37	possibilistic	possibilistic	ADJ
ap-6763	456	38	fuzzy	fuzzy	ADJ
ap-6763	456	39	c	c	NOUN
ap-6763	456	40	-	-	PUNCT
ap-6763	456	41	means	means	NOUN
ap-6763	456	42	(	(	PUNCT
ap-6763	456	43	pfcm	pfcm	PROPN
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ap-6763	456	45	algorithm	algorithm	NOUN
ap-6763	456	46	of	of	ADP
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ap-6763	456	48	data	datum	NOUN
ap-6763	456	49	sets	set	VERB
ap-6763	456	50	3.1	3.1	NUM
ap-6763	456	51	optimal	optimal	ADJ
ap-6763	456	52	completion	completion	NOUN
ap-6763	456	53	strategy	strategy	NOUN
ap-6763	456	54	possibilistic	possibilistic	ADJ
ap-6763	456	55	fuzzy	fuzzy	ADJ
ap-6763	456	56	c	c	NOUN
ap-6763	456	57	-	-	PUNCT
ap-6763	456	58	means	means	NOUN
ap-6763	456	59	(	(	PUNCT
ap-6763	456	60	ocspfcm	ocspfcm	PROPN
ap-6763	456	61	)	)	PUNCT
ap-6763	456	62	algorithm	algorithm	NOUN
ap-6763	456	63	3.2	3.2	NUM
ap-6763	456	64	nearest	nearest	NOUN
ap-6763	456	65	prototype	prototype	NOUN
ap-6763	456	66	strategy	strategy	NOUN
ap-6763	456	67	possibilistic	possibilistic	ADJ
ap-6763	456	68	fuzzy	fuzzy	ADJ
ap-6763	456	69	c	c	NOUN
ap-6763	456	70	-	-	PUNCT
ap-6763	456	71	means	means	NOUN
ap-6763	456	72	(	(	PUNCT
ap-6763	456	73	npspfcm	npspfcm	NOUN
ap-6763	456	74	)	)	PUNCT
ap-6763	456	75	algorithm	algorithm	NOUN
ap-6763	456	76	4	4	NUM
ap-6763	456	77	experimental	experimental	ADJ
ap-6763	456	78	setup	setup	NOUN
ap-6763	456	79	5	5	NUM
ap-6763	456	80	experimental	experimental	ADJ
ap-6763	456	81	results	result	NOUN
ap-6763	456	82	and	and	CCONJ
ap-6763	456	83	discussions	discussion	NOUN
ap-6763	456	84	5.1	5.1	NUM
ap-6763	456	85	experiment	experiment	NOUN
ap-6763	456	86	on	on	ADP
ap-6763	456	87	iris	iris	NOUN
ap-6763	456	88	data	datum	NOUN
ap-6763	456	89	sets	set	VERB
ap-6763	456	90	5.2	5.2	NUM
ap-6763	456	91	experiment	experiment	NOUN
ap-6763	456	92	on	on	ADP
ap-6763	456	93	wine	wine	NOUN
ap-6763	456	94	data	datum	NOUN
ap-6763	456	95	sets	set	VERB
ap-6763	456	96	5.3	5.3	NUM
ap-6763	456	97	experiment	experiment	NOUN
ap-6763	456	98	on	on	ADP
ap-6763	456	99	artificial	artificial	ADJ
ap-6763	456	100	data	datum	NOUN
ap-6763	456	101	sets	set	VERB
ap-6763	456	102	i	i	PRON
ap-6763	456	103	5.4	5.4	NUM
ap-6763	456	104	experiment	experiment	NOUN
ap-6763	456	105	on	on	ADP
ap-6763	456	106	artificial	artificial	ADJ
ap-6763	456	107	data	datum	NOUN
ap-6763	456	108	set	set	VERB
ap-6763	456	109	ii	ii	PROPN
ap-6763	456	110	5.5	5.5	NUM
ap-6763	456	111	experiment	experiment	NOUN
ap-6763	456	112	on	on	ADP
ap-6763	456	113	artificial	artificial	ADJ
ap-6763	456	114	data	datum	NOUN
ap-6763	456	115	set	set	VERB
ap-6763	456	116	iii	iii	NUM
ap-6763	456	117	6	6	NUM
ap-6763	456	118	conclusions	conclusion	NOUN
ap-6763	456	119	acknowledgements	acknowledgement	NOUN
ap-6763	456	120	list	list	NOUN
ap-6763	456	121	of	of	ADP
ap-6763	456	122	symbols	symbol	NOUN
ap-6763	456	123	references	reference	NOUN