id	sid	tid	token	lemma	pos
arestyrurj-232	1	1	aresty	aresty	PROPN
arestyrurj-232	1	2	rutgers	rutgers	PROPN
arestyrurj-232	1	3	undergraduate	undergraduate	PROPN
arestyrurj-232	1	4	research	research	PROPN
arestyrurj-232	1	5	journal	journal	PROPN
arestyrurj-232	1	6	,	,	PUNCT
arestyrurj-232	1	7	volume	volume	NOUN
arestyrurj-232	1	8	i	i	PRON
arestyrurj-232	1	9	,	,	PUNCT
arestyrurj-232	1	10	issue	issue	NOUN
arestyrurj-232	1	11	v	v	ADP
arestyrurj-232	1	12	this	this	DET
arestyrurj-232	1	13	work	work	NOUN
arestyrurj-232	1	14	is	be	AUX
arestyrurj-232	1	15	licensed	license	VERB
arestyrurj-232	1	16	under	under	ADP
arestyrurj-232	1	17	a	a	DET
arestyrurj-232	1	18	creative	creative	ADJ
arestyrurj-232	1	19	commons	common	NOUN
arestyrurj-232	1	20	attribution	attribution	NOUN
arestyrurj-232	1	21	-	-	PUNCT
arestyrurj-232	1	22	noncommercial	noncommercial	ADJ
arestyrurj-232	1	23	-	-	PUNCT
arestyrurj-232	1	24	sharealike	sharealike	ADJ
arestyrurj-232	1	25	4.0	4.0	NUM
arestyrurj-232	1	26	international	international	ADJ
arestyrurj-232	1	27	license	license	NOUN
arestyrurj-232	1	28	.	.	PUNCT
arestyrurj-232	2	1	classification	classification	NOUN
arestyrurj-232	2	2	of	of	ADP
arestyrurj-232	2	3	fall	fall	NOUN
arestyrurj-232	2	4	out	out	ADP
arestyrurj-232	2	5	boy	boy	NOUN
arestyrurj-232	2	6	eras	era	NOUN
arestyrurj-232	2	7	shifra	shifra	PROPN
arestyrurj-232	2	8	l.	l.	PROPN
arestyrurj-232	2	9	isaacs	isaacs	PROPN
arestyrurj-232	2	10	,	,	PUNCT
arestyrurj-232	2	11	joseph	joseph	PROPN
arestyrurj-232	2	12	yudelson	yudelson	PROPN
arestyrurj-232	2	13	,	,	PUNCT
arestyrurj-232	2	14	dr	dr	PROPN
arestyrurj-232	2	15	.	.	PROPN
arestyrurj-232	2	16	endre	endre	PROPN
arestyrurj-232	2	17	boros	boros	PROPN
arestyrurj-232	2	18	✵	✵	PROPN
arestyrurj-232	2	19	abstract	abstract	PROPN
arestyrurj-232	2	20	this	this	DET
arestyrurj-232	2	21	paper	paper	NOUN
arestyrurj-232	2	22	explored	explore	VERB
arestyrurj-232	2	23	the	the	DET
arestyrurj-232	2	24	use	use	NOUN
arestyrurj-232	2	25	of	of	ADP
arestyrurj-232	2	26	machine	machine	NOUN
arestyrurj-232	2	27	learning	learn	VERB
arestyrurj-232	2	28	techniques	technique	NOUN
arestyrurj-232	2	29	to	to	PART
arestyrurj-232	2	30	differentiate	differentiate	VERB
arestyrurj-232	2	31	between	between	ADP
arestyrurj-232	2	32	two	two	NUM
arestyrurj-232	2	33	different	different	ADJ
arestyrurj-232	2	34	musical	musical	ADJ
arestyrurj-232	2	35	eras	era	NOUN
arestyrurj-232	2	36	of	of	ADP
arestyrurj-232	2	37	the	the	DET
arestyrurj-232	2	38	same	same	ADJ
arestyrurj-232	2	39	rock	rock	NOUN
arestyrurj-232	2	40	band	band	NOUN
arestyrurj-232	2	41	,	,	PUNCT
arestyrurj-232	2	42	including	include	VERB
arestyrurj-232	2	43	the	the	DET
arestyrurj-232	2	44	technique	technique	NOUN
arestyrurj-232	2	45	of	of	ADP
arestyrurj-232	2	46	logistic	logistic	ADJ
arestyrurj-232	2	47	regression	regression	NOUN
arestyrurj-232	2	48	.	.	PUNCT
arestyrurj-232	3	1	logistic	logistic	ADJ
arestyrurj-232	3	2	regression	regression	NOUN
arestyrurj-232	3	3	(	(	PUNCT
arestyrurj-232	3	4	lr	lr	NOUN
arestyrurj-232	3	5	)	)	PUNCT
arestyrurj-232	3	6	is	be	AUX
arestyrurj-232	3	7	a	a	DET
arestyrurj-232	3	8	widely	widely	ADV
arestyrurj-232	3	9	-	-	PUNCT
arestyrurj-232	3	10	used	use	VERB
arestyrurj-232	3	11	statistical	statistical	ADJ
arestyrurj-232	3	12	modeling	modeling	NOUN
arestyrurj-232	3	13	method	method	NOUN
arestyrurj-232	3	14	for	for	ADP
arestyrurj-232	3	15	binary	binary	ADJ
arestyrurj-232	3	16	classification	classification	NOUN
arestyrurj-232	3	17	in	in	ADP
arestyrurj-232	3	18	supervised	supervised	ADJ
arestyrurj-232	3	19	machine	machine	NOUN
arestyrurj-232	3	20	learning	learning	NOUN
arestyrurj-232	3	21	.	.	PUNCT
arestyrurj-232	4	1	it	it	PRON
arestyrurj-232	4	2	is	be	AUX
arestyrurj-232	4	3	often	often	ADV
arestyrurj-232	4	4	used	use	VERB
arestyrurj-232	4	5	to	to	PART
arestyrurj-232	4	6	predict	predict	VERB
arestyrurj-232	4	7	whether	whether	SCONJ
arestyrurj-232	4	8	a	a	DET
arestyrurj-232	4	9	given	give	VERB
arestyrurj-232	4	10	event	event	NOUN
arestyrurj-232	4	11	belongs	belong	VERB
arestyrurj-232	4	12	to	to	ADP
arestyrurj-232	4	13	one	one	NUM
arestyrurj-232	4	14	of	of	ADP
arestyrurj-232	4	15	two	two	NUM
arestyrurj-232	4	16	categories	category	NOUN
arestyrurj-232	4	17	.	.	PUNCT
arestyrurj-232	5	1	the	the	DET
arestyrurj-232	5	2	process	process	NOUN
arestyrurj-232	5	3	helps	help	VERB
arestyrurj-232	5	4	data	data	NOUN
arestyrurj-232	5	5	scientists	scientist	NOUN
arestyrurj-232	5	6	understand	understand	VERB
arestyrurj-232	5	7	which	which	PRON
arestyrurj-232	5	8	variables	variable	NOUN
arestyrurj-232	5	9	are	be	AUX
arestyrurj-232	5	10	good	good	ADJ
arestyrurj-232	5	11	predictors	predictor	NOUN
arestyrurj-232	5	12	of	of	ADP
arestyrurj-232	5	13	class	class	NOUN
arestyrurj-232	5	14	membership	membership	NOUN
arestyrurj-232	5	15	.	.	PUNCT
arestyrurj-232	6	1	applications	application	NOUN
arestyrurj-232	6	2	of	of	ADP
arestyrurj-232	6	3	logistic	logistic	ADJ
arestyrurj-232	6	4	regression	regression	NOUN
arestyrurj-232	6	5	include	include	VERB
arestyrurj-232	6	6	loan	loan	NOUN
arestyrurj-232	6	7	classification	classification	NOUN
arestyrurj-232	6	8	in	in	ADP
arestyrurj-232	6	9	the	the	DET
arestyrurj-232	6	10	financial	financial	ADJ
arestyrurj-232	6	11	industry	industry	NOUN
arestyrurj-232	6	12	and	and	CCONJ
arestyrurj-232	6	13	predicting	predict	VERB
arestyrurj-232	6	14	susceptibility	susceptibility	NOUN
arestyrurj-232	6	15	to	to	PART
arestyrurj-232	6	16	disease	disease	NOUN
arestyrurj-232	6	17	in	in	ADP
arestyrurj-232	6	18	the	the	DET
arestyrurj-232	6	19	medical	medical	ADJ
arestyrurj-232	6	20	field	field	NOUN
arestyrurj-232	6	21	.	.	PUNCT
arestyrurj-232	7	1	in	in	ADP
arestyrurj-232	7	2	this	this	DET
arestyrurj-232	7	3	particular	particular	ADJ
arestyrurj-232	7	4	project	project	NOUN
arestyrurj-232	7	5	,	,	PUNCT
arestyrurj-232	7	6	a	a	DET
arestyrurj-232	7	7	dataset	dataset	NOUN
arestyrurj-232	7	8	was	be	AUX
arestyrurj-232	7	9	constructed	construct	VERB
arestyrurj-232	7	10	using	use	VERB
arestyrurj-232	7	11	data	datum	NOUN
arestyrurj-232	7	12	from	from	ADP
arestyrurj-232	7	13	spotify	spotify	NOUN
arestyrurj-232	7	14	and	and	CCONJ
arestyrurj-232	7	15	genius	genius	NOUN
arestyrurj-232	7	16	consisting	consist	VERB
arestyrurj-232	7	17	of	of	ADP
arestyrurj-232	7	18	songs	song	NOUN
arestyrurj-232	7	19	and	and	CCONJ
arestyrurj-232	7	20	lyrics	lyric	NOUN
arestyrurj-232	7	21	written	write	VERB
arestyrurj-232	7	22	by	by	ADP
arestyrurj-232	7	23	the	the	DET
arestyrurj-232	7	24	band	band	NOUN
arestyrurj-232	7	25	fall	fall	VERB
arestyrurj-232	7	26	out	out	ADP
arestyrurj-232	7	27	boy	boy	NOUN
arestyrurj-232	7	28	.	.	PUNCT
arestyrurj-232	8	1	a	a	DET
arestyrurj-232	8	2	logistic	logistic	ADJ
arestyrurj-232	8	3	regression	regression	NOUN
arestyrurj-232	8	4	model	model	NOUN
arestyrurj-232	8	5	was	be	AUX
arestyrurj-232	8	6	developed	develop	VERB
arestyrurj-232	8	7	from	from	ADP
arestyrurj-232	8	8	scratch	scratch	NOUN
arestyrurj-232	8	9	to	to	PART
arestyrurj-232	8	10	classify	classify	VERB
arestyrurj-232	8	11	the	the	DET
arestyrurj-232	8	12	songs	song	NOUN
arestyrurj-232	8	13	and	and	CCONJ
arestyrurj-232	8	14	lyrics	lyric	NOUN
arestyrurj-232	8	15	into	into	ADP
arestyrurj-232	8	16	one	one	NUM
arestyrurj-232	8	17	of	of	ADP
arestyrurj-232	8	18	two	two	NUM
arestyrurj-232	8	19	eras	era	NOUN
arestyrurj-232	8	20	of	of	ADP
arestyrurj-232	8	21	the	the	DET
arestyrurj-232	8	22	band	band	NOUN
arestyrurj-232	8	23	:	:	PUNCT
arestyrurj-232	8	24	before	before	ADP
arestyrurj-232	8	25	their	their	PRON
arestyrurj-232	8	26	2009	2009	NUM
arestyrurj-232	8	27	hiatus	hiatus	NOUN
arestyrurj-232	8	28	and	and	CCONJ
arestyrurj-232	8	29	afterward	afterward	ADV
arestyrurj-232	8	30	.	.	PUNCT
arestyrurj-232	9	1	the	the	DET
arestyrurj-232	9	2	study	study	NOUN
arestyrurj-232	9	3	aimed	aim	VERB
arestyrurj-232	9	4	to	to	PART
arestyrurj-232	9	5	determine	determine	VERB
arestyrurj-232	9	6	if	if	SCONJ
arestyrurj-232	9	7	a	a	DET
arestyrurj-232	9	8	computer	computer	NOUN
arestyrurj-232	9	9	could	could	AUX
arestyrurj-232	9	10	differentiate	differentiate	VERB
arestyrurj-232	9	11	between	between	ADP
arestyrurj-232	9	12	the	the	DET
arestyrurj-232	9	13	two	two	NUM
arestyrurj-232	9	14	eras	era	NOUN
arestyrurj-232	9	15	.	.	PUNCT
arestyrurj-232	10	1	the	the	DET
arestyrurj-232	10	2	model	model	NOUN
arestyrurj-232	10	3	was	be	AUX
arestyrurj-232	10	4	also	also	ADV
arestyrurj-232	10	5	tested	test	VERB
arestyrurj-232	10	6	against	against	ADP
arestyrurj-232	10	7	other	other	ADJ
arestyrurj-232	10	8	binary	binary	ADJ
arestyrurj-232	10	9	classification	classification	NOUN
arestyrurj-232	10	10	algorithms	algorithm	NOUN
arestyrurj-232	10	11	,	,	PUNCT
arestyrurj-232	10	12	including	include	VERB
arestyrurj-232	10	13	random	random	ADJ
arestyrurj-232	10	14	forest	forest	NOUN
arestyrurj-232	10	15	and	and	CCONJ
arestyrurj-232	10	16	support	support	VERB
arestyrurj-232	10	17	vector	vector	NOUN
arestyrurj-232	10	18	machines	machine	NOUN
arestyrurj-232	10	19	.	.	PUNCT
arestyrurj-232	11	1	2	2	NUM
arestyrurj-232	11	2	data	data	NOUN
arestyrurj-232	11	3	extraction	extraction	NOUN
arestyrurj-232	11	4	audio	audio	NOUN
arestyrurj-232	11	5	and	and	CCONJ
arestyrurj-232	11	6	lyric	lyric	ADJ
arestyrurj-232	11	7	features	feature	NOUN
arestyrurj-232	11	8	from	from	ADP
arestyrurj-232	11	9	fall	fall	NOUN
arestyrurj-232	11	10	out	out	ADP
arestyrurj-232	11	11	boy	boy	NOUN
arestyrurj-232	11	12	’s	’s	PART
arestyrurj-232	11	13	(	(	PUNCT
arestyrurj-232	11	14	fob	fob	NOUN
arestyrurj-232	11	15	)	)	PUNCT
arestyrurj-232	11	16	music	music	NOUN
arestyrurj-232	11	17	were	be	AUX
arestyrurj-232	11	18	extracted	extract	VERB
arestyrurj-232	11	19	utilizing	utilize	VERB
arestyrurj-232	11	20	the	the	DET
arestyrurj-232	11	21	spotipy	spotipy	NOUN
arestyrurj-232	11	22	and	and	CCONJ
arestyrurj-232	11	23	lyricsgenius	lyricsgenius	NOUN
arestyrurj-232	11	24	apis	apis	ADJ
arestyrurj-232	11	25	.	.	PUNCT
arestyrurj-232	12	1	detailed	detailed	ADJ
arestyrurj-232	12	2	information	information	NOUN
arestyrurj-232	12	3	about	about	ADP
arestyrurj-232	12	4	the	the	DET
arestyrurj-232	12	5	songs	song	NOUN
arestyrurj-232	12	6	used	use	VERB
arestyrurj-232	12	7	for	for	ADP
arestyrurj-232	12	8	the	the	DET
arestyrurj-232	12	9	project	project	NOUN
arestyrurj-232	12	10	can	can	AUX
arestyrurj-232	12	11	be	be	AUX
arestyrurj-232	12	12	found	find	VERB
arestyrurj-232	12	13	in	in	ADP
arestyrurj-232	12	14	appendix	appendix	ADJ
arestyrurj-232	12	15	b	b	PROPN
arestyrurj-232	12	16	of	of	ADP
arestyrurj-232	12	17	the	the	DET
arestyrurj-232	12	18	supplemental	supplemental	ADJ
arestyrurj-232	12	19	document	document	NOUN
arestyrurj-232	12	20	.	.	PUNCT
arestyrurj-232	13	1	the	the	DET
arestyrurj-232	13	2	extracted	extract	VERB
arestyrurj-232	13	3	data	datum	NOUN
arestyrurj-232	13	4	was	be	AUX
arestyrurj-232	13	5	subsequently	subsequently	ADV
arestyrurj-232	13	6	cleaned	clean	VERB
arestyrurj-232	13	7	and	and	CCONJ
arestyrurj-232	13	8	combined	combine	VERB
arestyrurj-232	13	9	to	to	PART
arestyrurj-232	13	10	form	form	VERB
arestyrurj-232	13	11	a	a	DET
arestyrurj-232	13	12	cohesive	cohesive	ADJ
arestyrurj-232	13	13	dataset	dataset	NOUN
arestyrurj-232	13	14	,	,	PUNCT
arestyrurj-232	13	15	which	which	PRON
arestyrurj-232	13	16	was	be	AUX
arestyrurj-232	13	17	then	then	ADV
arestyrurj-232	13	18	explored	explore	VERB
arestyrurj-232	13	19	and	and	CCONJ
arestyrurj-232	13	20	visualized	visualize	VERB
arestyrurj-232	13	21	.	.	PUNCT
arestyrurj-232	14	1	before	before	ADP
arestyrurj-232	14	2	modeling	modeling	NOUN
arestyrurj-232	14	3	,	,	PUNCT
arestyrurj-232	14	4	the	the	DET
arestyrurj-232	14	5	dataset	dataset	NOUN
arestyrurj-232	14	6	was	be	AUX
arestyrurj-232	14	7	split	split	VERB
arestyrurj-232	14	8	into	into	ADP
arestyrurj-232	14	9	a	a	DET
arestyrurj-232	14	10	training	training	NOUN
arestyrurj-232	14	11	set	set	NOUN
arestyrurj-232	14	12	of	of	ADP
arestyrurj-232	14	13	98	98	NUM
arestyrurj-232	14	14	records	record	NOUN
arestyrurj-232	14	15	and	and	CCONJ
arestyrurj-232	14	16	test	test	NOUN
arestyrurj-232	14	17	set	set	VERB
arestyrurj-232	14	18	of	of	ADP
arestyrurj-232	14	19	43	43	NUM
arestyrurj-232	14	20	records	record	NOUN
arestyrurj-232	14	21	,	,	PUNCT
arestyrurj-232	14	22	for	for	ADP
arestyrurj-232	14	23	a	a	DET
arestyrurj-232	14	24	total	total	NOUN
arestyrurj-232	14	25	of	of	ADP
arestyrurj-232	14	26	141	141	NUM
arestyrurj-232	14	27	records	record	NOUN
arestyrurj-232	14	28	.	.	PUNCT
arestyrurj-232	15	1	the	the	DET
arestyrurj-232	15	2	data	data	NOUN
arestyrurj-232	15	3	extraction	extraction	NOUN
arestyrurj-232	15	4	stage	stage	NOUN
arestyrurj-232	15	5	presented	present	VERB
arestyrurj-232	15	6	several	several	ADJ
arestyrurj-232	15	7	challenges	challenge	NOUN
arestyrurj-232	15	8	,	,	PUNCT
arestyrurj-232	15	9	such	such	ADJ
arestyrurj-232	15	10	as	as	ADP
arestyrurj-232	15	11	the	the	DET
arestyrurj-232	15	12	need	need	NOUN
arestyrurj-232	15	13	to	to	PART
arestyrurj-232	15	14	clean	clean	VERB
arestyrurj-232	15	15	up	up	ADP
arestyrurj-232	15	16	sub	sub	NOUN
arestyrurj-232	15	17	-	-	NOUN
arestyrurj-232	15	18	headings	heading	NOUN
arestyrurj-232	15	19	within	within	ADP
arestyrurj-232	15	20	the	the	DET
arestyrurj-232	15	21	lyrics	lyric	NOUN
arestyrurj-232	15	22	using	use	VERB
arestyrurj-232	15	23	complex	complex	ADJ
arestyrurj-232	15	24	regular	regular	ADJ
arestyrurj-232	15	25	expressions	expression	NOUN
arestyrurj-232	15	26	.	.	PUNCT
arestyrurj-232	16	1	additionally	additionally	ADV
arestyrurj-232	16	2	,	,	PUNCT
arestyrurj-232	16	3	the	the	DET
arestyrurj-232	16	4	spotipy	spotipy	PROPN
arestyrurj-232	16	5	api	api	NOUN
arestyrurj-232	16	6	featured	feature	VERB
arestyrurj-232	16	7	interesting	interesting	ADJ
arestyrurj-232	16	8	edge	edge	NOUN
arestyrurj-232	16	9	cases	case	NOUN
arestyrurj-232	16	10	,	,	PUNCT
arestyrurj-232	16	11	such	such	ADJ
arestyrurj-232	16	12	as	as	ADP
arestyrurj-232	16	13	a	a	DET
arestyrurj-232	16	14	post	post	ADJ
arestyrurj-232	16	15	-	-	ADJ
arestyrurj-232	16	16	hiatus	hiatus	ADJ
arestyrurj-232	16	17	elton	elton	PROPN
arestyrurj-232	16	18	john	john	PROPN
arestyrurj-232	16	19	cover	cover	VERB
arestyrurj-232	16	20	that	that	PRON
arestyrurj-232	16	21	was	be	AUX
arestyrurj-232	16	22	incorrectly	incorrectly	ADV
arestyrurj-232	16	23	labeled	label	VERB
arestyrurj-232	16	24	as	as	ADP
arestyrurj-232	16	25	a	a	DET
arestyrurj-232	16	26	1973	1973	NUM
arestyrurj-232	16	27	release	release	NOUN
arestyrurj-232	16	28	.	.	PUNCT
arestyrurj-232	17	1	additionally	additionally	ADV
arestyrurj-232	17	2	,	,	PUNCT
arestyrurj-232	17	3	one	one	NUM
arestyrurj-232	17	4	spotify	spotify	NOUN
arestyrurj-232	17	5	audio	audio	ADJ
arestyrurj-232	17	6	feature	feature	NOUN
arestyrurj-232	17	7	proved	prove	VERB
arestyrurj-232	17	8	difficult	difficult	ADJ
arestyrurj-232	17	9	to	to	PART
arestyrurj-232	17	10	handle	handle	VERB
arestyrurj-232	17	11	due	due	ADP
arestyrurj-232	17	12	to	to	ADP
arestyrurj-232	17	13	its	its	PRON
arestyrurj-232	17	14	format	format	NOUN
arestyrurj-232	17	15	.	.	PUNCT
arestyrurj-232	18	1	for	for	ADP
arestyrurj-232	18	2	example	example	NOUN
arestyrurj-232	18	3	,	,	PUNCT
arestyrurj-232	18	4	the	the	DET
arestyrurj-232	18	5	api	api	NOUN
arestyrurj-232	18	6	described	describe	VERB
arestyrurj-232	18	7	song	song	NOUN
arestyrurj-232	18	8	durations	duration	NOUN
arestyrurj-232	18	9	in	in	ADP
arestyrurj-232	18	10	milliseconds	millisecond	NOUN
arestyrurj-232	18	11	,	,	PUNCT
arestyrurj-232	18	12	which	which	PRON
arestyrurj-232	18	13	were	be	AUX
arestyrurj-232	18	14	subsequently	subsequently	ADV
arestyrurj-232	18	15	converted	convert	VERB
arestyrurj-232	18	16	to	to	ADP
arestyrurj-232	18	17	minutes	minute	NOUN
arestyrurj-232	18	18	.	.	PUNCT
arestyrurj-232	19	1	care	care	NOUN
arestyrurj-232	19	2	was	be	AUX
arestyrurj-232	19	3	taken	take	VERB
arestyrurj-232	19	4	to	to	PART
arestyrurj-232	19	5	leave	leave	VERB
arestyrurj-232	19	6	comments	comment	NOUN
arestyrurj-232	19	7	explaining	explain	VERB
arestyrurj-232	19	8	that	that	SCONJ
arestyrurj-232	19	9	a	a	DET
arestyrurj-232	19	10	value	value	NOUN
arestyrurj-232	19	11	of	of	ADP
arestyrurj-232	19	12	3.05	3.05	NUM
arestyrurj-232	19	13	,	,	PUNCT
arestyrurj-232	19	14	for	for	ADP
arestyrurj-232	19	15	example	example	NOUN
arestyrurj-232	19	16	,	,	PUNCT
arestyrurj-232	19	17	should	should	AUX
arestyrurj-232	19	18	be	be	AUX
arestyrurj-232	19	19	read	read	VERB
arestyrurj-232	19	20	as	as	ADP
arestyrurj-232	19	21	3.05	3.05	NUM
arestyrurj-232	19	22	minutes	minute	NOUN
arestyrurj-232	19	23	rather	rather	ADV
arestyrurj-232	19	24	than	than	ADP
arestyrurj-232	19	25	3	3	NUM
arestyrurj-232	19	26	minutes	minute	NOUN
arestyrurj-232	19	27	and	and	CCONJ
arestyrurj-232	19	28	5	5	NUM
arestyrurj-232	19	29	seconds	second	NOUN
arestyrurj-232	19	30	.	.	PUNCT
arestyrurj-232	20	1	descriptions	description	NOUN
arestyrurj-232	20	2	for	for	ADP
arestyrurj-232	20	3	all	all	DET
arestyrurj-232	20	4	the	the	DET
arestyrurj-232	20	5	spotify	spotify	NOUN
arestyrurj-232	20	6	features	feature	NOUN
arestyrurj-232	20	7	can	can	AUX
arestyrurj-232	20	8	be	be	AUX
arestyrurj-232	20	9	found	find	VERB
arestyrurj-232	20	10	in	in	ADP
arestyrurj-232	20	11	appendix	appendix	NOUN
arestyrurj-232	20	12	a	a	PRON
arestyrurj-232	20	13	of	of	ADP
arestyrurj-232	20	14	the	the	DET
arestyrurj-232	20	15	supplemental	supplemental	ADJ
arestyrurj-232	20	16	document	document	NOUN
arestyrurj-232	20	17	.	.	PUNCT
arestyrurj-232	21	1	2	2	NUM
arestyrurj-232	21	2	data	datum	NOUN
arestyrurj-232	21	3	analysis	analysis	NOUN
arestyrurj-232	21	4	prior	prior	ADV
arestyrurj-232	21	5	to	to	ADP
arestyrurj-232	21	6	the	the	DET
arestyrurj-232	21	7	modeling	modeling	NOUN
arestyrurj-232	21	8	process	process	NOUN
arestyrurj-232	21	9	,	,	PUNCT
arestyrurj-232	21	10	it	it	PRON
arestyrurj-232	21	11	is	be	AUX
arestyrurj-232	21	12	common	common	ADJ
arestyrurj-232	21	13	practice	practice	NOUN
arestyrurj-232	21	14	to	to	PART
arestyrurj-232	21	15	engage	engage	VERB
arestyrurj-232	21	16	in	in	ADP
arestyrurj-232	21	17	exploratory	exploratory	ADJ
arestyrurj-232	21	18	data	datum	NOUN
arestyrurj-232	21	19	analysis	analysis	NOUN
arestyrurj-232	21	20	(	(	PUNCT
arestyrurj-232	21	21	eda	eda	X
arestyrurj-232	21	22	)	)	PUNCT
arestyrurj-232	21	23	and	and	CCONJ
arestyrurj-232	21	24	dive	dive	VERB
arestyrurj-232	21	25	deeper	deeply	ADV
arestyrurj-232	21	26	into	into	ADP
arestyrurj-232	21	27	the	the	DET
arestyrurj-232	21	28	features	feature	NOUN
arestyrurj-232	21	29	that	that	PRON
arestyrurj-232	21	30	will	will	AUX
arestyrurj-232	21	31	be	be	AUX
arestyrurj-232	21	32	modeled	model	VERB
arestyrurj-232	21	33	.	.	PUNCT
arestyrurj-232	22	1	this	this	DET
arestyrurj-232	22	2	section	section	NOUN
arestyrurj-232	22	3	will	will	AUX
arestyrurj-232	22	4	discuss	discuss	VERB
arestyrurj-232	22	5	the	the	DET
arestyrurj-232	22	6	analyses	analysis	NOUN
arestyrurj-232	22	7	performed	perform	VERB
arestyrurj-232	22	8	on	on	ADP
arestyrurj-232	22	9	the	the	DET
arestyrurj-232	22	10	fall	fall	NOUN
arestyrurj-232	22	11	out	out	ADP
arestyrurj-232	22	12	boy	boy	NOUN
arestyrurj-232	22	13	songs	song	NOUN
arestyrurj-232	22	14	dataset	dataset	VERB
arestyrurj-232	22	15	.	.	PUNCT
arestyrurj-232	23	1	for	for	ADP
arestyrurj-232	23	2	the	the	DET
arestyrurj-232	23	3	quantitative	quantitative	ADJ
arestyrurj-232	23	4	audio	audio	NOUN
arestyrurj-232	23	5	features	feature	NOUN
arestyrurj-232	23	6	,	,	PUNCT
arestyrurj-232	23	7	histograms	histogram	NOUN
arestyrurj-232	23	8	were	be	AUX
arestyrurj-232	23	9	created	create	VERB
arestyrurj-232	23	10	to	to	PART
arestyrurj-232	23	11	provide	provide	VERB
arestyrurj-232	23	12	a	a	DET
arestyrurj-232	23	13	graphical	graphical	ADJ
arestyrurj-232	23	14	representation	representation	NOUN
arestyrurj-232	23	15	of	of	ADP
arestyrurj-232	23	16	the	the	DET
arestyrurj-232	23	17	data	data	NOUN
arestyrurj-232	23	18	distributions	distribution	NOUN
arestyrurj-232	23	19	.	.	PUNCT
arestyrurj-232	24	1	in	in	ADP
arestyrurj-232	24	2	addition	addition	NOUN
arestyrurj-232	24	3	,	,	PUNCT
arestyrurj-232	24	4	scatterplot	scatterplot	NOUN
arestyrurj-232	24	5	matrices	matrix	NOUN
arestyrurj-232	24	6	were	be	AUX
arestyrurj-232	24	7	used	use	VERB
arestyrurj-232	24	8	to	to	PART
arestyrurj-232	24	9	visualize	visualize	VERB
arestyrurj-232	24	10	any	any	DET
arestyrurj-232	24	11	correlations	correlation	NOUN
arestyrurj-232	24	12	between	between	ADP
arestyrurj-232	24	13	the	the	DET
arestyrurj-232	24	14	different	different	ADJ
arestyrurj-232	24	15	features	feature	NOUN
arestyrurj-232	24	16	.	.	PUNCT
arestyrurj-232	25	1	figure	figure	NOUN
arestyrurj-232	25	2	1	1	NUM
arestyrurj-232	25	3	shows	show	VERB
arestyrurj-232	25	4	the	the	DET
arestyrurj-232	25	5	distributions	distribution	NOUN
arestyrurj-232	25	6	of	of	ADP
arestyrurj-232	25	7	the	the	DET
arestyrurj-232	25	8	valence	valence	NOUN
arestyrurj-232	25	9	and	and	CCONJ
arestyrurj-232	25	10	tempo	tempo	NOUN
arestyrurj-232	25	11	features	feature	NOUN
arestyrurj-232	25	12	and	and	CCONJ
arestyrurj-232	25	13	indicates	indicate	VERB
arestyrurj-232	25	14	the	the	DET
arestyrurj-232	25	15	possibility	possibility	NOUN
arestyrurj-232	25	16	of	of	ADP
arestyrurj-232	25	17	a	a	DET
arestyrurj-232	25	18	small	small	ADJ
arestyrurj-232	25	19	positive	positive	ADJ
arestyrurj-232	25	20	correlation	correlation	NOUN
arestyrurj-232	25	21	between	between	ADP
arestyrurj-232	25	22	them	they	PRON
arestyrurj-232	25	23	.	.	PUNCT
arestyrurj-232	26	1	this	this	PRON
arestyrurj-232	26	2	is	be	AUX
arestyrurj-232	26	3	feasible	feasible	ADJ
arestyrurj-232	26	4	considering	consider	VERB
arestyrurj-232	26	5	that	that	SCONJ
arestyrurj-232	26	6	happier	happy	ADJ
arestyrurj-232	26	7	,	,	PUNCT
arestyrurj-232	26	8	high	high	ADJ
arestyrurj-232	26	9	-	-	PUNCT
arestyrurj-232	26	10	valence	valence	NOUN
arestyrurj-232	26	11	songs	song	NOUN
arestyrurj-232	26	12	,	,	PUNCT
arestyrurj-232	26	13	broadly	broadly	ADV
arestyrurj-232	26	14	tend	tend	VERB
arestyrurj-232	26	15	to	to	PART
arestyrurj-232	26	16	have	have	VERB
arestyrurj-232	26	17	faster	fast	ADJ
arestyrurj-232	26	18	tempos	tempos	NOUN
arestyrurj-232	26	19	.	.	PUNCT
arestyrurj-232	27	1	to	to	PART
arestyrurj-232	27	2	analyze	analyze	VERB
arestyrurj-232	27	3	the	the	DET
arestyrurj-232	27	4	categorical	categorical	ADJ
arestyrurj-232	27	5	audio	audio	NOUN
arestyrurj-232	27	6	features	feature	NOUN
arestyrurj-232	27	7	,	,	PUNCT
arestyrurj-232	27	8	the	the	DET
arestyrurj-232	27	9	distribution	distribution	NOUN
arestyrurj-232	27	10	of	of	ADP
arestyrurj-232	27	11	categories	category	NOUN
arestyrurj-232	27	12	was	be	AUX
arestyrurj-232	27	13	examined	examine	VERB
arestyrurj-232	27	14	across	across	ADP
arestyrurj-232	27	15	the	the	DET
arestyrurj-232	27	16	pre	pre	NOUN
arestyrurj-232	27	17	-	-	NOUN
arestyrurj-232	27	18	hiatus	hiatus	ADJ
arestyrurj-232	27	19	and	and	CCONJ
arestyrurj-232	27	20	post	post	ADJ
arestyrurj-232	27	21	-	-	ADJ
arestyrurj-232	27	22	hiatus	hiatus	ADJ
arestyrurj-232	27	23	classes	class	NOUN
arestyrurj-232	27	24	.	.	PUNCT
arestyrurj-232	28	1	as	as	ADP
arestyrurj-232	28	2	for	for	ADP
arestyrurj-232	28	3	the	the	DET
arestyrurj-232	28	4	lyrical	lyrical	ADJ
arestyrurj-232	28	5	features	feature	NOUN
arestyrurj-232	28	6	,	,	PUNCT
arestyrurj-232	28	7	a	a	DET
arestyrurj-232	28	8	hypothesis	hypothesis	NOUN
arestyrurj-232	28	9	was	be	AUX
arestyrurj-232	28	10	formed	form	VERB
arestyrurj-232	28	11	that	that	SCONJ
arestyrurj-232	28	12	pre	pre	ADJ
arestyrurj-232	28	13	-	-	ADJ
arestyrurj-232	28	14	hiatus	hiatus	ADJ
arestyrurj-232	28	15	songs	song	NOUN
arestyrurj-232	28	16	generally	generally	ADV
arestyrurj-232	28	17	contain	contain	VERB
arestyrurj-232	28	18	more	more	ADV
arestyrurj-232	28	19	unique	unique	ADJ
arestyrurj-232	28	20	words	word	NOUN
arestyrurj-232	28	21	than	than	ADP
arestyrurj-232	28	22	post	post	ADJ
arestyrurj-232	28	23	-	-	ADJ
arestyrurj-232	28	24	hiatus	hiatus	ADJ
arestyrurj-232	28	25	songs	song	NOUN
arestyrurj-232	28	26	.	.	PUNCT
arestyrurj-232	29	1	a	a	DET
arestyrurj-232	29	2	preliminary	preliminary	ADJ
arestyrurj-232	29	3	analysis	analysis	NOUN
arestyrurj-232	29	4	of	of	ADP
arestyrurj-232	29	5	the	the	DET
arestyrurj-232	29	6	relevant	relevant	ADJ
arestyrurj-232	29	7	histograms	histogram	NOUN
arestyrurj-232	29	8	suggests	suggest	VERB
arestyrurj-232	29	9	that	that	SCONJ
arestyrurj-232	29	10	this	this	PRON
arestyrurj-232	29	11	may	may	AUX
arestyrurj-232	29	12	be	be	AUX
arestyrurj-232	29	13	the	the	DET
arestyrurj-232	29	14	case	case	NOUN
arestyrurj-232	29	15	.	.	PUNCT
arestyrurj-232	30	1	aresty	aresty	ADJ
arestyrurj-232	30	2	rutgers	rutgers	PROPN
arestyrurj-232	30	3	undergraduate	undergraduate	PROPN
arestyrurj-232	30	4	research	research	PROPN
arestyrurj-232	30	5	journal	journal	PROPN
arestyrurj-232	30	6	,	,	PUNCT
arestyrurj-232	30	7	volume	volume	NOUN
arestyrurj-232	30	8	i	i	PRON
arestyrurj-232	30	9	,	,	PUNCT
arestyrurj-232	30	10	issue	issue	VERB
arestyrurj-232	30	11	v	v	X
arestyrurj-232	30	12	2	2	NUM
arestyrurj-232	30	13	figure	figure	NOUN
arestyrurj-232	30	14	1	1	NUM
arestyrurj-232	30	15	:	:	PUNCT
arestyrurj-232	30	16	scatterplot	scatterplot	NOUN
arestyrurj-232	30	17	matrix	matrix	NOUN
arestyrurj-232	30	18	of	of	ADP
arestyrurj-232	30	19	valence	valence	NOUN
arestyrurj-232	30	20	and	and	CCONJ
arestyrurj-232	30	21	tempo	tempo	NOUN
arestyrurj-232	30	22	audio	audio	NOUN
arestyrurj-232	30	23	features	feature	NOUN
arestyrurj-232	30	24	.	.	PUNCT
arestyrurj-232	31	1	valence	valence	NOUN
arestyrurj-232	31	2	is	be	AUX
arestyrurj-232	31	3	the	the	DET
arestyrurj-232	31	4	mood	mood	NOUN
arestyrurj-232	31	5	of	of	ADP
arestyrurj-232	31	6	a	a	DET
arestyrurj-232	31	7	song	song	NOUN
arestyrurj-232	31	8	,	,	PUNCT
arestyrurj-232	31	9	with	with	ADP
arestyrurj-232	31	10	high	high	ADJ
arestyrurj-232	31	11	values	value	NOUN
arestyrurj-232	31	12	indicating	indicate	VERB
arestyrurj-232	31	13	positive	positive	ADJ
arestyrurj-232	31	14	mood	mood	NOUN
arestyrurj-232	31	15	.	.	PUNCT
arestyrurj-232	32	1	figure	figure	VERB
arestyrurj-232	32	2	2	2	NUM
arestyrurj-232	32	3	:	:	PUNCT
arestyrurj-232	32	4	distribution	distribution	NOUN
arestyrurj-232	32	5	of	of	ADP
arestyrurj-232	32	6	unique_words	unique_word	NOUN
arestyrurj-232	32	7	feature	feature	VERB
arestyrurj-232	32	8	across	across	ADP
arestyrurj-232	32	9	prehiatus	prehiatus	NOUN
arestyrurj-232	32	10	and	and	CCONJ
arestyrurj-232	32	11	post	post	ADJ
arestyrurj-232	32	12	-	-	ADJ
arestyrurj-232	32	13	hiatus	hiatus	ADJ
arestyrurj-232	32	14	songs	song	NOUN
arestyrurj-232	32	15	figure	figure	VERB
arestyrurj-232	32	16	3	3	NUM
arestyrurj-232	32	17	:	:	PUNCT
arestyrurj-232	32	18	frequency	frequency	NOUN
arestyrurj-232	32	19	plot	plot	NOUN
arestyrurj-232	32	20	for	for	ADP
arestyrurj-232	32	21	key	key	ADJ
arestyrurj-232	32	22	feature	feature	NOUN
arestyrurj-232	32	23	across	across	ADP
arestyrurj-232	32	24	classes	class	NOUN
arestyrurj-232	32	25	however	however	ADV
arestyrurj-232	32	26	,	,	PUNCT
arestyrurj-232	32	27	a	a	DET
arestyrurj-232	32	28	two	two	NUM
arestyrurj-232	32	29	-	-	PUNCT
arestyrurj-232	32	30	sample	sample	NOUN
arestyrurj-232	32	31	z	z	NOUN
arestyrurj-232	32	32	-	-	PUNCT
arestyrurj-232	32	33	test	test	NOUN
arestyrurj-232	32	34	of	of	ADP
arestyrurj-232	32	35	these	these	DET
arestyrurj-232	32	36	datasets	dataset	NOUN
arestyrurj-232	32	37	yielded	yield	VERB
arestyrurj-232	32	38	a	a	DET
arestyrurj-232	32	39	p	p	NOUN
arestyrurj-232	32	40	-	-	PUNCT
arestyrurj-232	32	41	value	value	NOUN
arestyrurj-232	32	42	of	of	ADP
arestyrurj-232	32	43	approximately	approximately	ADV
arestyrurj-232	32	44	0.46	0.46	NUM
arestyrurj-232	32	45	.	.	PUNCT
arestyrurj-232	33	1	a	a	DET
arestyrurj-232	33	2	ztest	zt	ADJ
arestyrurj-232	33	3	is	be	AUX
arestyrurj-232	33	4	a	a	DET
arestyrurj-232	33	5	statistical	statistical	ADJ
arestyrurj-232	33	6	hypothesis	hypothesis	NOUN
arestyrurj-232	33	7	test	test	NOUN
arestyrurj-232	33	8	used	use	VERB
arestyrurj-232	33	9	to	to	PART
arestyrurj-232	33	10	compare	compare	VERB
arestyrurj-232	33	11	the	the	DET
arestyrurj-232	33	12	means	mean	NOUN
arestyrurj-232	33	13	of	of	ADP
arestyrurj-232	33	14	two	two	NUM
arestyrurj-232	33	15	independent	independent	ADJ
arestyrurj-232	33	16	samples	sample	NOUN
arestyrurj-232	33	17	and	and	CCONJ
arestyrurj-232	33	18	determine	determine	VERB
arestyrurj-232	33	19	if	if	SCONJ
arestyrurj-232	33	20	they	they	PRON
arestyrurj-232	33	21	are	be	AUX
arestyrurj-232	33	22	significantly	significantly	ADV
arestyrurj-232	33	23	different	different	ADJ
arestyrurj-232	33	24	.	.	PUNCT
arestyrurj-232	34	1	the	the	DET
arestyrurj-232	34	2	p	p	NOUN
arestyrurj-232	34	3	-	-	PUNCT
arestyrurj-232	34	4	value	value	NOUN
arestyrurj-232	34	5	of	of	ADP
arestyrurj-232	34	6	0.46	0.46	NUM
arestyrurj-232	34	7	suggests	suggest	VERB
arestyrurj-232	34	8	that	that	SCONJ
arestyrurj-232	34	9	there	there	PRON
arestyrurj-232	34	10	is	be	VERB
arestyrurj-232	34	11	not	not	PART
arestyrurj-232	34	12	enough	enough	ADJ
arestyrurj-232	34	13	evidence	evidence	NOUN
arestyrurj-232	34	14	to	to	PART
arestyrurj-232	34	15	reject	reject	VERB
arestyrurj-232	34	16	the	the	DET
arestyrurj-232	34	17	null	null	ADJ
arestyrurj-232	34	18	hypothesis	hypothesis	NOUN
arestyrurj-232	34	19	,	,	PUNCT
arestyrurj-232	34	20	which	which	PRON
arestyrurj-232	34	21	states	state	VERB
arestyrurj-232	34	22	that	that	SCONJ
arestyrurj-232	34	23	the	the	DET
arestyrurj-232	34	24	two	two	NUM
arestyrurj-232	34	25	samples	sample	NOUN
arestyrurj-232	34	26	have	have	VERB
arestyrurj-232	34	27	no	no	DET
arestyrurj-232	34	28	significant	significant	ADJ
arestyrurj-232	34	29	difference	difference	NOUN
arestyrurj-232	34	30	.	.	PUNCT
arestyrurj-232	35	1	this	this	PRON
arestyrurj-232	35	2	indicates	indicate	VERB
arestyrurj-232	35	3	no	no	DET
arestyrurj-232	35	4	evidence	evidence	NOUN
arestyrurj-232	35	5	of	of	ADP
arestyrurj-232	35	6	a	a	DET
arestyrurj-232	35	7	substantial	substantial	ADJ
arestyrurj-232	35	8	difference	difference	NOUN
arestyrurj-232	35	9	in	in	ADP
arestyrurj-232	35	10	the	the	DET
arestyrurj-232	35	11	mean	mean	ADJ
arestyrurj-232	35	12	unique	unique	ADJ
arestyrurj-232	35	13	lyrics	lyric	NOUN
arestyrurj-232	35	14	between	between	ADP
arestyrurj-232	35	15	pre	pre	ADJ
arestyrurj-232	35	16	-	-	ADJ
arestyrurj-232	35	17	hiatus	hiatus	ADJ
arestyrurj-232	35	18	songs	song	NOUN
arestyrurj-232	35	19	and	and	CCONJ
arestyrurj-232	35	20	post	post	ADJ
arestyrurj-232	35	21	-	-	ADJ
arestyrurj-232	35	22	hiatus	hiatus	ADJ
arestyrurj-232	35	23	songs	song	NOUN
arestyrurj-232	35	24	.	.	NOUN
arestyrurj-232	35	25	3	3	NUM
arestyrurj-232	35	26	feature	feature	NOUN
arestyrurj-232	35	27	engineering	engineering	NOUN
arestyrurj-232	35	28	in	in	ADP
arestyrurj-232	35	29	machine	machine	NOUN
arestyrurj-232	35	30	learning	learn	VERB
arestyrurj-232	35	31	modeling	modeling	NOUN
arestyrurj-232	35	32	,	,	PUNCT
arestyrurj-232	35	33	it	it	PRON
arestyrurj-232	35	34	is	be	AUX
arestyrurj-232	35	35	common	common	ADJ
arestyrurj-232	35	36	practice	practice	NOUN
arestyrurj-232	35	37	to	to	PART
arestyrurj-232	35	38	scale	scale	VERB
arestyrurj-232	35	39	all	all	DET
arestyrurj-232	35	40	the	the	DET
arestyrurj-232	35	41	numerical	numerical	ADJ
arestyrurj-232	35	42	features	feature	NOUN
arestyrurj-232	35	43	within	within	ADP
arestyrurj-232	35	44	a	a	DET
arestyrurj-232	35	45	fixed	fix	VERB
arestyrurj-232	35	46	range	range	NOUN
arestyrurj-232	35	47	while	while	SCONJ
arestyrurj-232	35	48	preserving	preserve	VERB
arestyrurj-232	35	49	their	their	PRON
arestyrurj-232	35	50	relative	relative	ADJ
arestyrurj-232	35	51	distance	distance	NOUN
arestyrurj-232	35	52	.	.	PUNCT
arestyrurj-232	36	1	this	this	DET
arestyrurj-232	36	2	technique	technique	NOUN
arestyrurj-232	36	3	speeds	speed	VERB
arestyrurj-232	36	4	up	up	ADP
arestyrurj-232	36	5	the	the	DET
arestyrurj-232	36	6	process	process	NOUN
arestyrurj-232	36	7	and	and	CCONJ
arestyrurj-232	36	8	improves	improve	VERB
arestyrurj-232	36	9	model	model	NOUN
arestyrurj-232	36	10	accuracy	accuracy	NOUN
arestyrurj-232	36	11	because	because	SCONJ
arestyrurj-232	36	12	algorithms	algorithm	NOUN
arestyrurj-232	36	13	are	be	AUX
arestyrurj-232	36	14	designed	design	VERB
arestyrurj-232	36	15	to	to	PART
arestyrurj-232	36	16	work	work	VERB
arestyrurj-232	36	17	with	with	ADP
arestyrurj-232	36	18	a	a	DET
arestyrurj-232	36	19	fixed	fix	VERB
arestyrurj-232	36	20	value	value	NOUN
arestyrurj-232	36	21	set	set	NOUN
arestyrurj-232	36	22	.	.	PUNCT
arestyrurj-232	37	1	the	the	DET
arestyrurj-232	37	2	majority	majority	NOUN
arestyrurj-232	37	3	of	of	ADP
arestyrurj-232	37	4	audio	audio	NOUN
arestyrurj-232	37	5	features	feature	NOUN
arestyrurj-232	37	6	obtained	obtain	VERB
arestyrurj-232	37	7	from	from	ADP
arestyrurj-232	37	8	the	the	DET
arestyrurj-232	37	9	spotipy	spotipy	ADJ
arestyrurj-232	37	10	api	api	NOUN
arestyrurj-232	37	11	were	be	AUX
arestyrurj-232	37	12	already	already	ADV
arestyrurj-232	37	13	scaled	scale	VERB
arestyrurj-232	37	14	between	between	ADP
arestyrurj-232	37	15	0	0	NUM
arestyrurj-232	37	16	and	and	CCONJ
arestyrurj-232	37	17	1	1	NUM
arestyrurj-232	37	18	;	;	PUNCT
arestyrurj-232	37	19	therefore	therefore	ADV
arestyrurj-232	37	20	,	,	PUNCT
arestyrurj-232	37	21	minmaxscaler	minmaxscaler	NOUN
arestyrurj-232	37	22	was	be	AUX
arestyrurj-232	37	23	used	use	VERB
arestyrurj-232	37	24	to	to	PART
arestyrurj-232	37	25	scale	scale	VERB
arestyrurj-232	37	26	other	other	ADJ
arestyrurj-232	37	27	variables	variable	NOUN
arestyrurj-232	37	28	to	to	ADP
arestyrurj-232	37	29	the	the	DET
arestyrurj-232	37	30	same	same	ADJ
arestyrurj-232	37	31	range	range	NOUN
arestyrurj-232	37	32	.	.	PUNCT
arestyrurj-232	38	1	categorical	categorical	ADJ
arestyrurj-232	38	2	features	feature	NOUN
arestyrurj-232	38	3	and	and	CCONJ
arestyrurj-232	38	4	the	the	DET
arestyrurj-232	38	5	target	target	NOUN
arestyrurj-232	38	6	variable	variable	NOUN
arestyrurj-232	38	7	were	be	AUX
arestyrurj-232	38	8	then	then	ADV
arestyrurj-232	38	9	one	one	NUM
arestyrurj-232	38	10	-	-	PUNCT
arestyrurj-232	38	11	hot	hot	ADJ
arestyrurj-232	38	12	encoded	encode	VERB
arestyrurj-232	38	13	.	.	PUNCT
arestyrurj-232	39	1	backward	backward	ADJ
arestyrurj-232	39	2	feature	feature	NOUN
arestyrurj-232	39	3	selection	selection	NOUN
arestyrurj-232	39	4	was	be	AUX
arestyrurj-232	39	5	employed	employ	VERB
arestyrurj-232	39	6	to	to	PART
arestyrurj-232	39	7	determine	determine	VERB
arestyrurj-232	39	8	the	the	DET
arestyrurj-232	39	9	optimal	optimal	ADJ
arestyrurj-232	39	10	feature	feature	NOUN
arestyrurj-232	39	11	set	set	VERB
arestyrurj-232	39	12	based	base	VERB
arestyrurj-232	39	13	on	on	ADP
arestyrurj-232	39	14	f1	f1	PROPN
arestyrurj-232	39	15	scores	score	NOUN
arestyrurj-232	39	16	,	,	PUNCT
arestyrurj-232	39	17	which	which	PRON
arestyrurj-232	39	18	measure	measure	VERB
arestyrurj-232	39	19	a	a	DET
arestyrurj-232	39	20	model	model	NOUN
arestyrurj-232	39	21	’s	’s	PART
arestyrurj-232	39	22	ability	ability	NOUN
arestyrurj-232	39	23	to	to	PART
arestyrurj-232	39	24	predict	predict	VERB
arestyrurj-232	39	25	true	true	ADJ
arestyrurj-232	39	26	positives	positive	NOUN
arestyrurj-232	39	27	accurately	accurately	ADV
arestyrurj-232	39	28	and	and	CCONJ
arestyrurj-232	39	29	identify	identify	VERB
arestyrurj-232	39	30	true	true	ADJ
arestyrurj-232	39	31	positives	positive	NOUN
arestyrurj-232	39	32	correctly	correctly	ADV
arestyrurj-232	39	33	.	.	PUNCT
arestyrurj-232	40	1	the	the	DET
arestyrurj-232	40	2	algorithm	algorithm	NOUN
arestyrurj-232	40	3	resulted	result	VERB
arestyrurj-232	40	4	in	in	ADP
arestyrurj-232	40	5	the	the	DET
arestyrurj-232	40	6	selection	selection	NOUN
arestyrurj-232	40	7	of	of	ADP
arestyrurj-232	40	8	8	8	NUM
arestyrurj-232	40	9	features	feature	NOUN
arestyrurj-232	40	10	:	:	PUNCT
arestyrurj-232	40	11	danceability	danceability	NOUN
arestyrurj-232	40	12	,	,	PUNCT
arestyrurj-232	40	13	instrumentalness	instrumentalness	NOUN
arestyrurj-232	40	14	,	,	PUNCT
arestyrurj-232	40	15	total_words	total_words	PROPN
arestyrurj-232	40	16	,	,	PUNCT
arestyrurj-232	40	17	mode	mode	NOUN
arestyrurj-232	40	18	,	,	PUNCT
arestyrurj-232	40	19	key_6	key_6	X
arestyrurj-232	40	20	,	,	PUNCT
arestyrurj-232	40	21	key_9	key_9	NOUN
arestyrurj-232	40	22	,	,	PUNCT
arestyrurj-232	40	23	key_10	key_10	PROPN
arestyrurj-232	40	24	,	,	PUNCT
arestyrurj-232	40	25	and	and	CCONJ
arestyrurj-232	40	26	key_11	key_11	PROPN
arestyrurj-232	40	27	.	.	PUNCT
arestyrurj-232	41	1	the	the	DET
arestyrurj-232	41	2	mode	mode	NOUN
arestyrurj-232	41	3	feature	feature	NOUN
arestyrurj-232	41	4	,	,	PUNCT
arestyrurj-232	41	5	which	which	PRON
arestyrurj-232	41	6	indicates	indicate	VERB
arestyrurj-232	41	7	whether	whether	SCONJ
arestyrurj-232	41	8	a	a	DET
arestyrurj-232	41	9	song	song	NOUN
arestyrurj-232	41	10	's	's	PART
arestyrurj-232	41	11	key	key	NOUN
arestyrurj-232	41	12	is	be	AUX
arestyrurj-232	41	13	major	major	ADJ
arestyrurj-232	41	14	or	or	CCONJ
arestyrurj-232	41	15	minor	minor	ADJ
arestyrurj-232	41	16	,	,	PUNCT
arestyrurj-232	41	17	proved	prove	VERB
arestyrurj-232	41	18	to	to	PART
arestyrurj-232	41	19	be	be	AUX
arestyrurj-232	41	20	a	a	DET
arestyrurj-232	41	21	strong	strong	ADJ
arestyrurj-232	41	22	predictor	predictor	NOUN
arestyrurj-232	41	23	despite	despite	SCONJ
arestyrurj-232	41	24	its	its	PRON
arestyrurj-232	41	25	inability	inability	NOUN
arestyrurj-232	41	26	to	to	PART
arestyrurj-232	41	27	capture	capture	VERB
arestyrurj-232	41	28	the	the	DET
arestyrurj-232	41	29	musicality	musicality	NOUN
arestyrurj-232	41	30	of	of	ADP
arestyrurj-232	41	31	most	most	ADJ
arestyrurj-232	41	32	songs	song	NOUN
arestyrurj-232	41	33	.	.	PUNCT
arestyrurj-232	42	1	the	the	DET
arestyrurj-232	42	2	key	key	ADJ
arestyrurj-232	42	3	numbers	number	NOUN
arestyrurj-232	42	4	above	above	ADP
arestyrurj-232	42	5	refer	refer	VERB
arestyrurj-232	42	6	to	to	ADP
arestyrurj-232	42	7	specific	specific	ADJ
arestyrurj-232	42	8	musical	musical	ADJ
arestyrurj-232	42	9	notes	note	NOUN
arestyrurj-232	42	10	;	;	PUNCT
arestyrurj-232	42	11	for	for	ADP
arestyrurj-232	42	12	example	example	NOUN
arestyrurj-232	42	13	,	,	PUNCT
arestyrurj-232	42	14	key_6	key_6	X
arestyrurj-232	42	15	refers	refer	VERB
arestyrurj-232	42	16	to	to	ADP
arestyrurj-232	42	17	the	the	DET
arestyrurj-232	42	18	musical	musical	ADJ
arestyrurj-232	42	19	key	key	NOUN
arestyrurj-232	42	20	of	of	ADP
arestyrurj-232	42	21	f.	f.	PROPN
arestyrurj-232	42	22	meanwhile	meanwhile	ADV
arestyrurj-232	42	23	,	,	PUNCT
arestyrurj-232	42	24	the	the	DET
arestyrurj-232	42	25	instrumentalness	instrumentalness	NOUN
arestyrurj-232	42	26	feature	feature	NOUN
arestyrurj-232	42	27	represents	represent	VERB
arestyrurj-232	42	28	the	the	DET
arestyrurj-232	42	29	likelihood	likelihood	NOUN
arestyrurj-232	42	30	from	from	ADP
arestyrurj-232	42	31	0	0	NUM
arestyrurj-232	42	32	-	-	SYM
arestyrurj-232	42	33	1	1	NUM
arestyrurj-232	42	34	that	that	SCONJ
arestyrurj-232	42	35	the	the	DET
arestyrurj-232	42	36	track	track	NOUN
arestyrurj-232	42	37	is	be	AUX
arestyrurj-232	42	38	instrumental	instrumental	ADJ
arestyrurj-232	42	39	and	and	CCONJ
arestyrurj-232	42	40	contains	contain	VERB
arestyrurj-232	42	41	no	no	DET
arestyrurj-232	42	42	vocals	vocal	NOUN
arestyrurj-232	42	43	.	.	PUNCT
arestyrurj-232	43	1	after	after	SCONJ
arestyrurj-232	43	2	a	a	DET
arestyrurj-232	43	3	heatmap	heatmap	NOUN
arestyrurj-232	43	4	correlation	correlation	NOUN
arestyrurj-232	43	5	matrix	matrix	NOUN
arestyrurj-232	43	6	confirmed	confirm	VERB
arestyrurj-232	43	7	that	that	SCONJ
arestyrurj-232	43	8	there	there	PRON
arestyrurj-232	43	9	were	be	VERB
arestyrurj-232	43	10	no	no	DET
arestyrurj-232	43	11	significant	significant	ADJ
arestyrurj-232	43	12	linear	linear	ADJ
arestyrurj-232	43	13	correlations	correlation	NOUN
arestyrurj-232	43	14	among	among	ADP
arestyrurj-232	43	15	the	the	DET
arestyrurj-232	43	16	selected	select	VERB
arestyrurj-232	43	17	features	feature	NOUN
arestyrurj-232	43	18	,	,	PUNCT
arestyrurj-232	43	19	the	the	DET
arestyrurj-232	43	20	modeling	modeling	NOUN
arestyrurj-232	43	21	step	step	NOUN
arestyrurj-232	43	22	was	be	AUX
arestyrurj-232	43	23	initiated	initiate	VERB
arestyrurj-232	43	24	.	.	PUNCT
arestyrurj-232	44	1	aresty	aresty	ADJ
arestyrurj-232	44	2	rutgers	rutgers	PROPN
arestyrurj-232	44	3	undergraduate	undergraduate	PROPN
arestyrurj-232	44	4	research	research	PROPN
arestyrurj-232	44	5	journal	journal	PROPN
arestyrurj-232	44	6	,	,	PUNCT
arestyrurj-232	44	7	volume	volume	NOUN
arestyrurj-232	44	8	i	i	PRON
arestyrurj-232	44	9	,	,	PUNCT
arestyrurj-232	44	10	issue	issue	VERB
arestyrurj-232	44	11	v	v	NUM
arestyrurj-232	44	12	figure	figure	NOUN
arestyrurj-232	44	13	4	4	NUM
arestyrurj-232	44	14	:	:	PUNCT
arestyrurj-232	44	15	heatmap	heatmap	NOUN
arestyrurj-232	44	16	showing	show	VERB
arestyrurj-232	44	17	minimal	minimal	ADJ
arestyrurj-232	44	18	correlation	correlation	NOUN
arestyrurj-232	44	19	in	in	ADP
arestyrurj-232	44	20	feature	feature	NOUN
arestyrurj-232	44	21	set	set	VERB
arestyrurj-232	44	22	4	4	NUM
arestyrurj-232	44	23	logistic	logistic	ADJ
arestyrurj-232	44	24	regression	regression	NOUN
arestyrurj-232	44	25	from	from	ADP
arestyrurj-232	44	26	scratch	scratch	NOUN
arestyrurj-232	44	27	a	a	DET
arestyrurj-232	44	28	logistic	logistic	ADJ
arestyrurj-232	44	29	regression	regression	NOUN
arestyrurj-232	44	30	(	(	PUNCT
arestyrurj-232	44	31	lr	lr	NOUN
arestyrurj-232	44	32	)	)	PUNCT
arestyrurj-232	44	33	algorithm	algorithm	NOUN
arestyrurj-232	44	34	was	be	AUX
arestyrurj-232	44	35	constructed	construct	VERB
arestyrurj-232	44	36	from	from	ADP
arestyrurj-232	44	37	scratch	scratch	NOUN
arestyrurj-232	44	38	in	in	ADP
arestyrurj-232	44	39	python	python	PROPN
arestyrurj-232	44	40	,	,	PUNCT
arestyrurj-232	44	41	along	along	ADP
arestyrurj-232	44	42	with	with	ADP
arestyrurj-232	44	43	class	class	NOUN
arestyrurj-232	44	44	methods	method	NOUN
arestyrurj-232	44	45	to	to	PART
arestyrurj-232	44	46	facilitate	facilitate	VERB
arestyrurj-232	44	47	model	model	NOUN
arestyrurj-232	44	48	evaluation	evaluation	NOUN
arestyrurj-232	44	49	and	and	CCONJ
arestyrurj-232	44	50	visualization	visualization	NOUN
arestyrurj-232	44	51	.	.	PUNCT
arestyrurj-232	45	1	the	the	DET
arestyrurj-232	45	2	class	class	NOUN
arestyrurj-232	45	3	was	be	AUX
arestyrurj-232	45	4	well	well	ADV
arestyrurj-232	45	5	-	-	PUNCT
arestyrurj-232	45	6	documented	document	VERB
arestyrurj-232	45	7	in	in	ADP
arestyrurj-232	45	8	section	section	NOUN
arestyrurj-232	45	9	vi	vi	PROPN
arestyrurj-232	45	10	of	of	ADP
arestyrurj-232	45	11	the	the	DET
arestyrurj-232	45	12	supplemental	supplemental	ADJ
arestyrurj-232	45	13	document	document	NOUN
arestyrurj-232	45	14	.	.	PUNCT
arestyrurj-232	46	1	before	before	ADP
arestyrurj-232	46	2	describing	describe	VERB
arestyrurj-232	46	3	the	the	DET
arestyrurj-232	46	4	process	process	NOUN
arestyrurj-232	46	5	in	in	ADP
arestyrurj-232	46	6	detail	detail	NOUN
arestyrurj-232	46	7	,	,	PUNCT
arestyrurj-232	46	8	this	this	DET
arestyrurj-232	46	9	section	section	NOUN
arestyrurj-232	46	10	will	will	AUX
arestyrurj-232	46	11	introduce	introduce	VERB
arestyrurj-232	46	12	the	the	DET
arestyrurj-232	46	13	general	general	ADJ
arestyrurj-232	46	14	modeling	modeling	NOUN
arestyrurj-232	46	15	process	process	NOUN
arestyrurj-232	46	16	:	:	PUNCT
arestyrurj-232	46	17	•	•	NUM
arestyrurj-232	46	18	model	model	NOUN
arestyrurj-232	46	19	selection	selection	NOUN
arestyrurj-232	46	20	:	:	PUNCT
arestyrurj-232	46	21	design	design	NOUN
arestyrurj-232	46	22	modeling	modeling	NOUN
arestyrurj-232	46	23	task	task	NOUN
arestyrurj-232	46	24	based	base	VERB
arestyrurj-232	46	25	on	on	ADP
arestyrurj-232	46	26	the	the	DET
arestyrurj-232	46	27	item	item	NOUN
arestyrurj-232	46	28	to	to	PART
arestyrurj-232	46	29	be	be	AUX
arestyrurj-232	46	30	modeled	model	VERB
arestyrurj-232	46	31	or	or	CCONJ
arestyrurj-232	46	32	predicted	predict	VERB
arestyrurj-232	46	33	and	and	CCONJ
arestyrurj-232	46	34	select	select	VERB
arestyrurj-232	46	35	the	the	DET
arestyrurj-232	46	36	model	model	NOUN
arestyrurj-232	46	37	best	well	ADV
arestyrurj-232	46	38	suited	suit	VERB
arestyrurj-232	46	39	to	to	ADP
arestyrurj-232	46	40	that	that	DET
arestyrurj-232	46	41	task	task	NOUN
arestyrurj-232	46	42	•	•	NUM
arestyrurj-232	46	43	data	datum	NOUN
arestyrurj-232	46	44	pre	pre	ADJ
arestyrurj-232	46	45	-	-	NOUN
arestyrurj-232	46	46	processing	processing	ADJ
arestyrurj-232	46	47	:	:	PUNCT
arestyrurj-232	46	48	prepare	prepare	VERB
arestyrurj-232	46	49	data	datum	NOUN
arestyrurj-232	46	50	for	for	ADP
arestyrurj-232	46	51	modeling	modeling	NOUN
arestyrurj-232	46	52	and	and	CCONJ
arestyrurj-232	46	53	split	split	ADJ
arestyrurj-232	46	54	data	datum	NOUN
arestyrurj-232	46	55	into	into	ADP
arestyrurj-232	46	56	training	training	NOUN
arestyrurj-232	46	57	and	and	CCONJ
arestyrurj-232	46	58	testing	testing	NOUN
arestyrurj-232	46	59	sets	set	NOUN
arestyrurj-232	46	60	•	•	ADV
arestyrurj-232	46	61	typically	typically	ADV
arestyrurj-232	46	62	80	80	NUM
arestyrurj-232	46	63	%	%	NOUN
arestyrurj-232	46	64	of	of	ADP
arestyrurj-232	46	65	the	the	DET
arestyrurj-232	46	66	data	datum	NOUN
arestyrurj-232	46	67	is	be	AUX
arestyrurj-232	46	68	used	use	VERB
arestyrurj-232	46	69	for	for	ADP
arestyrurj-232	46	70	training	training	NOUN
arestyrurj-232	46	71	and	and	CCONJ
arestyrurj-232	46	72	20	20	NUM
arestyrurj-232	46	73	%	%	NOUN
arestyrurj-232	46	74	for	for	ADP
arestyrurj-232	46	75	testing	testing	NOUN
arestyrurj-232	46	76	•	•	ADV
arestyrurj-232	46	77	sometimes	sometimes	ADV
arestyrurj-232	46	78	a	a	DET
arestyrurj-232	46	79	third	third	ADJ
arestyrurj-232	46	80	validation	validation	NOUN
arestyrurj-232	46	81	set	set	NOUN
arestyrurj-232	46	82	is	be	AUX
arestyrurj-232	46	83	used	use	VERB
arestyrurj-232	46	84	,	,	PUNCT
arestyrurj-232	46	85	but	but	CCONJ
arestyrurj-232	46	86	this	this	DET
arestyrurj-232	46	87	dataset	dataset	NOUN
arestyrurj-232	46	88	is	be	AUX
arestyrurj-232	46	89	far	far	ADV
arestyrurj-232	46	90	too	too	ADV
arestyrurj-232	46	91	small	small	ADJ
arestyrurj-232	46	92	for	for	ADP
arestyrurj-232	46	93	that	that	DET
arestyrurj-232	46	94	•	•	NOUN
arestyrurj-232	46	95	model	model	NOUN
arestyrurj-232	46	96	building	building	NOUN
arestyrurj-232	46	97	•	•	NOUN
arestyrurj-232	46	98	model	model	NOUN
arestyrurj-232	46	99	training	training	NOUN
arestyrurj-232	46	100	:	:	PUNCT
arestyrurj-232	46	101	run	run	VERB
arestyrurj-232	46	102	the	the	DET
arestyrurj-232	46	103	model	model	NOUN
arestyrurj-232	46	104	iteratively	iteratively	ADV
arestyrurj-232	46	105	on	on	ADP
arestyrurj-232	46	106	the	the	DET
arestyrurj-232	46	107	training	training	NOUN
arestyrurj-232	46	108	set	set	NOUN
arestyrurj-232	46	109	and	and	CCONJ
arestyrurj-232	46	110	update	update	VERB
arestyrurj-232	46	111	the	the	DET
arestyrurj-232	46	112	model	model	NOUN
arestyrurj-232	46	113	parameters	parameter	NOUN
arestyrurj-232	46	114	on	on	ADP
arestyrurj-232	46	115	each	each	DET
arestyrurj-232	46	116	epoch	epoch	NOUN
arestyrurj-232	46	117	to	to	PART
arestyrurj-232	46	118	improve	improve	VERB
arestyrurj-232	46	119	the	the	DET
arestyrurj-232	46	120	model	model	NOUN
arestyrurj-232	46	121	results	result	NOUN
arestyrurj-232	46	122	•	•	NOUN
arestyrurj-232	46	123	model	model	NOUN
arestyrurj-232	46	124	testing	testing	NOUN
arestyrurj-232	46	125	:	:	PUNCT
arestyrurj-232	46	126	run	run	VERB
arestyrurj-232	46	127	the	the	DET
arestyrurj-232	46	128	model	model	NOUN
arestyrurj-232	46	129	on	on	ADP
arestyrurj-232	46	130	the	the	DET
arestyrurj-232	46	131	test	test	NOUN
arestyrurj-232	46	132	data	datum	NOUN
arestyrurj-232	46	133	on	on	ADP
arestyrurj-232	46	134	each	each	DET
arestyrurj-232	46	135	epoch	epoch	NOUN
arestyrurj-232	46	136	•	•	NOUN
arestyrurj-232	46	137	model	model	NOUN
arestyrurj-232	46	138	evaluation	evaluation	NOUN
arestyrurj-232	46	139	:	:	PUNCT
arestyrurj-232	46	140	run	run	VERB
arestyrurj-232	46	141	metrics	metric	NOUN
arestyrurj-232	46	142	such	such	ADJ
arestyrurj-232	46	143	as	as	ADP
arestyrurj-232	46	144	accuracy	accuracy	NOUN
arestyrurj-232	46	145	and	and	CCONJ
arestyrurj-232	46	146	f1	f1	NOUN
arestyrurj-232	46	147	score	score	NOUN
arestyrurj-232	46	148	to	to	PART
arestyrurj-232	46	149	determine	determine	VERB
arestyrurj-232	46	150	quality	quality	NOUN
arestyrurj-232	46	151	of	of	ADP
arestyrurj-232	46	152	model	model	NOUN
arestyrurj-232	46	153	performance	performance	NOUN
arestyrurj-232	46	154	after	after	ADP
arestyrurj-232	46	155	creating	create	VERB
arestyrurj-232	46	156	the	the	DET
arestyrurj-232	46	157	basic	basic	ADJ
arestyrurj-232	46	158	class	class	NOUN
arestyrurj-232	46	159	properties	property	NOUN
arestyrurj-232	46	160	and	and	CCONJ
arestyrurj-232	46	161	methods	method	NOUN
arestyrurj-232	46	162	for	for	ADP
arestyrurj-232	46	163	the	the	DET
arestyrurj-232	46	164	model	model	NOUN
arestyrurj-232	46	165	,	,	PUNCT
arestyrurj-232	46	166	the	the	DET
arestyrurj-232	46	167	focus	focus	NOUN
arestyrurj-232	46	168	was	be	AUX
arestyrurj-232	46	169	on	on	ADP
arestyrurj-232	46	170	the	the	DET
arestyrurj-232	46	171	algorithm	algorithm	NOUN
arestyrurj-232	46	172	itself	itself	PRON
arestyrurj-232	46	173	.	.	PUNCT
arestyrurj-232	47	1	a	a	DET
arestyrurj-232	47	2	stable	stable	ADJ
arestyrurj-232	47	3	sigmoid	sigmoid	NOUN
arestyrurj-232	47	4	function	function	NOUN
arestyrurj-232	47	5	was	be	AUX
arestyrurj-232	47	6	chosen	choose	VERB
arestyrurj-232	47	7	instead	instead	ADV
arestyrurj-232	47	8	of	of	ADP
arestyrurj-232	47	9	a	a	DET
arestyrurj-232	47	10	typical	typical	ADJ
arestyrurj-232	47	11	sigmoid	sigmoid	NOUN
arestyrurj-232	47	12	function	function	NOUN
arestyrurj-232	47	13	;	;	PUNCT
arestyrurj-232	47	14	the	the	DET
arestyrurj-232	47	15	regular	regular	ADJ
arestyrurj-232	47	16	sigmoid	sigmoid	NOUN
arestyrurj-232	47	17	can	can	AUX
arestyrurj-232	47	18	sometimes	sometimes	ADV
arestyrurj-232	47	19	result	result	VERB
arestyrurj-232	47	20	in	in	ADP
arestyrurj-232	47	21	an	an	DET
arestyrurj-232	47	22	impossible	impossible	ADJ
arestyrurj-232	47	23	denominator	denominator	NOUN
arestyrurj-232	47	24	of	of	ADP
arestyrurj-232	47	25	zero	zero	NUM
arestyrurj-232	47	26	,	,	PUNCT
arestyrurj-232	47	27	whereas	whereas	SCONJ
arestyrurj-232	47	28	the	the	DET
arestyrurj-232	47	29	changes	change	NOUN
arestyrurj-232	47	30	in	in	ADP
arestyrurj-232	47	31	the	the	DET
arestyrurj-232	47	32	stable	stable	ADJ
arestyrurj-232	47	33	sigmoid	sigmoid	NOUN
arestyrurj-232	47	34	prevent	prevent	VERB
arestyrurj-232	47	35	zero	zero	NUM
arestyrurj-232	47	36	-	-	PUNCT
arestyrurj-232	47	37	division	division	NOUN
arestyrurj-232	47	38	errors	error	NOUN
arestyrurj-232	47	39	.	.	PUNCT
arestyrurj-232	48	1	the	the	DET
arestyrurj-232	48	2	most	most	ADV
arestyrurj-232	48	3	complex	complex	ADJ
arestyrurj-232	48	4	aspect	aspect	NOUN
arestyrurj-232	48	5	of	of	ADP
arestyrurj-232	48	6	the	the	DET
arestyrurj-232	48	7	algorithm	algorithm	NOUN
arestyrurj-232	48	8	was	be	AUX
arestyrurj-232	48	9	the	the	DET
arestyrurj-232	48	10	implementation	implementation	NOUN
arestyrurj-232	48	11	of	of	ADP
arestyrurj-232	48	12	the	the	DET
arestyrurj-232	48	13	fit	fit	ADJ
arestyrurj-232	48	14	method	method	NOUN
arestyrurj-232	48	15	,	,	PUNCT
arestyrurj-232	48	16	which	which	PRON
arestyrurj-232	48	17	involved	involve	VERB
arestyrurj-232	48	18	several	several	ADJ
arestyrurj-232	48	19	steps	step	NOUN
arestyrurj-232	48	20	:	:	PUNCT
arestyrurj-232	48	21	•	•	NUM
arestyrurj-232	48	22	collecting	collect	VERB
arestyrurj-232	48	23	properties	property	NOUN
arestyrurj-232	48	24	from	from	ADP
arestyrurj-232	48	25	the	the	DET
arestyrurj-232	48	26	input	input	NOUN
arestyrurj-232	48	27	data	datum	NOUN
arestyrurj-232	48	28	.	.	PUNCT
arestyrurj-232	49	1	•	•	NOUN
arestyrurj-232	49	2	constructing	construct	VERB
arestyrurj-232	49	3	a	a	DET
arestyrurj-232	49	4	linear	linear	ADJ
arestyrurj-232	49	5	model	model	NOUN
arestyrurj-232	49	6	based	base	VERB
arestyrurj-232	49	7	on	on	ADP
arestyrurj-232	49	8	the	the	DET
arestyrurj-232	49	9	input	input	NOUN
arestyrurj-232	49	10	data	datum	NOUN
arestyrurj-232	49	11	.	.	PUNCT
arestyrurj-232	50	1	•	•	PUNCT
arestyrurj-232	50	2	computing	compute	VERB
arestyrurj-232	50	3	binary	binary	PROPN
arestyrurj-232	50	4	cross	cross	PROPN
arestyrurj-232	50	5	-	-	ADJ
arestyrurj-232	50	6	entropy	entropy	ADJ
arestyrurj-232	50	7	loss	loss	NOUN
arestyrurj-232	50	8	as	as	ADP
arestyrurj-232	50	9	a	a	DET
arestyrurj-232	50	10	measure	measure	NOUN
arestyrurj-232	50	11	of	of	ADP
arestyrurj-232	50	12	model	model	NOUN
arestyrurj-232	50	13	error	error	NOUN
arestyrurj-232	50	14	.	.	PUNCT
arestyrurj-232	51	1	•	•	NOUN
arestyrurj-232	51	2	performing	perform	VERB
arestyrurj-232	51	3	gradient	gradient	ADJ
arestyrurj-232	51	4	descent	descent	NOUN
arestyrurj-232	51	5	during	during	ADP
arestyrurj-232	51	6	training	training	NOUN
arestyrurj-232	51	7	.	.	PUNCT
arestyrurj-232	52	1	•	•	NOUN
arestyrurj-232	52	2	storing	store	VERB
arestyrurj-232	52	3	loss	loss	NOUN
arestyrurj-232	52	4	values	value	NOUN
arestyrurj-232	52	5	at	at	ADP
arestyrurj-232	52	6	each	each	DET
arestyrurj-232	52	7	training	training	NOUN
arestyrurj-232	52	8	and	and	CCONJ
arestyrurj-232	52	9	testing	testing	NOUN
arestyrurj-232	52	10	stage	stage	NOUN
arestyrurj-232	52	11	.	.	PUNCT
arestyrurj-232	53	1	the	the	DET
arestyrurj-232	53	2	final	final	ADJ
arestyrurj-232	53	3	steps	step	NOUN
arestyrurj-232	53	4	of	of	ADP
arestyrurj-232	53	5	the	the	DET
arestyrurj-232	53	6	algorithm	algorithm	NOUN
arestyrurj-232	53	7	involved	involve	VERB
arestyrurj-232	53	8	converting	convert	VERB
arestyrurj-232	53	9	the	the	DET
arestyrurj-232	53	10	fit	fit	ADJ
arestyrurj-232	53	11	scores	score	NOUN
arestyrurj-232	53	12	to	to	ADP
arestyrurj-232	53	13	probabilities	probability	NOUN
arestyrurj-232	53	14	using	use	VERB
arestyrurj-232	53	15	the	the	DET
arestyrurj-232	53	16	stable	stable	ADJ
arestyrurj-232	53	17	sigmoid	sigmoid	NOUN
arestyrurj-232	53	18	function	function	NOUN
arestyrurj-232	53	19	,	,	PUNCT
arestyrurj-232	53	20	and	and	CCONJ
arestyrurj-232	53	21	then	then	ADV
arestyrurj-232	53	22	converting	convert	VERB
arestyrurj-232	53	23	those	those	DET
arestyrurj-232	53	24	probabilities	probability	NOUN
arestyrurj-232	53	25	into	into	ADP
arestyrurj-232	53	26	class	class	NOUN
arestyrurj-232	53	27	predictions	prediction	NOUN
arestyrurj-232	53	28	for	for	ADP
arestyrurj-232	53	29	either	either	CCONJ
arestyrurj-232	53	30	the	the	DET
arestyrurj-232	53	31	pre	pre	NOUN
arestyrurj-232	53	32	-	-	NOUN
arestyrurj-232	53	33	hiatus	hiatus	NOUN
arestyrurj-232	53	34	or	or	CCONJ
arestyrurj-232	53	35	post	post	ADJ
arestyrurj-232	53	36	-	-	ADJ
arestyrurj-232	53	37	hiatus	hiatus	ADJ
arestyrurj-232	53	38	era	era	NOUN
arestyrurj-232	53	39	.	.	PUNCT
arestyrurj-232	54	1	to	to	PART
arestyrurj-232	54	2	evaluate	evaluate	VERB
arestyrurj-232	54	3	the	the	DET
arestyrurj-232	54	4	model	model	NOUN
arestyrurj-232	54	5	,	,	PUNCT
arestyrurj-232	54	6	a	a	DET
arestyrurj-232	54	7	method	method	NOUN
arestyrurj-232	54	8	was	be	AUX
arestyrurj-232	54	9	added	add	VERB
arestyrurj-232	54	10	to	to	PART
arestyrurj-232	54	11	calculate	calculate	VERB
arestyrurj-232	54	12	a	a	DET
arestyrurj-232	54	13	confusion	confusion	NOUN
arestyrurj-232	54	14	matrix	matrix	NOUN
arestyrurj-232	54	15	and	and	CCONJ
arestyrurj-232	54	16	conventional	conventional	ADJ
arestyrurj-232	54	17	performance	performance	NOUN
arestyrurj-232	54	18	metrics	metric	NOUN
arestyrurj-232	54	19	,	,	PUNCT
arestyrurj-232	54	20	including	include	VERB
arestyrurj-232	54	21	accuracy	accuracy	NOUN
arestyrurj-232	54	22	,	,	PUNCT
arestyrurj-232	54	23	precision	precision	NOUN
arestyrurj-232	54	24	,	,	PUNCT
arestyrurj-232	54	25	recall	recall	NOUN
arestyrurj-232	54	26	,	,	PUNCT
arestyrurj-232	54	27	and	and	CCONJ
arestyrurj-232	54	28	the	the	DET
arestyrurj-232	54	29	f1	f1	PROPN
arestyrurj-232	54	30	score	score	NOUN
arestyrurj-232	54	31	.	.	PUNCT
arestyrurj-232	55	1	a	a	DET
arestyrurj-232	55	2	model	model	NOUN
arestyrurj-232	55	3	tracking	tracking	NOUN
arestyrurj-232	55	4	method	method	NOUN
arestyrurj-232	55	5	was	be	AUX
arestyrurj-232	55	6	also	also	ADV
arestyrurj-232	55	7	included	include	VERB
arestyrurj-232	55	8	to	to	PART
arestyrurj-232	55	9	graph	graph	VERB
arestyrurj-232	55	10	training	training	NOUN
arestyrurj-232	55	11	and	and	CCONJ
arestyrurj-232	55	12	test	test	NOUN
arestyrurj-232	55	13	error	error	NOUN
arestyrurj-232	55	14	.	.	PUNCT
arestyrurj-232	56	1	aresty	aresty	PROPN
arestyrurj-232	56	2	rutgers	rutgers	PROPN
arestyrurj-232	56	3	undergraduate	undergraduate	PROPN
arestyrurj-232	56	4	research	research	PROPN
arestyrurj-232	56	5	journal	journal	PROPN
arestyrurj-232	56	6	,	,	PUNCT
arestyrurj-232	56	7	volume	volume	NOUN
arestyrurj-232	56	8	i	i	PRON
arestyrurj-232	56	9	,	,	PUNCT
arestyrurj-232	56	10	issue	issue	VERB
arestyrurj-232	56	11	v	v	X
arestyrurj-232	56	12	2	2	NUM
arestyrurj-232	56	13	figure	figure	NOUN
arestyrurj-232	56	14	5	5	NUM
arestyrurj-232	56	15	:	:	PUNCT
arestyrurj-232	56	16	graph	graph	NOUN
arestyrurj-232	56	17	of	of	ADP
arestyrurj-232	56	18	training	training	NOUN
arestyrurj-232	56	19	and	and	CCONJ
arestyrurj-232	56	20	test	test	NOUN
arestyrurj-232	56	21	error	error	NOUN
arestyrurj-232	56	22	figure	figure	NOUN
arestyrurj-232	56	23	5	5	NUM
arestyrurj-232	56	24	shows	show	VERB
arestyrurj-232	56	25	that	that	SCONJ
arestyrurj-232	56	26	the	the	DET
arestyrurj-232	56	27	training	training	NOUN
arestyrurj-232	56	28	error	error	NOUN
arestyrurj-232	56	29	declined	decline	VERB
arestyrurj-232	56	30	gradually	gradually	ADV
arestyrurj-232	56	31	over	over	ADP
arestyrurj-232	56	32	the	the	DET
arestyrurj-232	56	33	training	training	NOUN
arestyrurj-232	56	34	period	period	NOUN
arestyrurj-232	56	35	.	.	PUNCT
arestyrurj-232	57	1	meanwhile	meanwhile	ADV
arestyrurj-232	57	2	,	,	PUNCT
arestyrurj-232	57	3	the	the	DET
arestyrurj-232	57	4	testing	testing	NOUN
arestyrurj-232	57	5	error	error	NOUN
arestyrurj-232	57	6	remained	remain	VERB
arestyrurj-232	57	7	at	at	ADP
arestyrurj-232	57	8	a	a	DET
arestyrurj-232	57	9	plateau	plateau	NOUN
arestyrurj-232	57	10	near	near	ADP
arestyrurj-232	57	11	0.78	0.78	NUM
arestyrurj-232	57	12	throughout	throughout	ADP
arestyrurj-232	57	13	training	training	NOUN
arestyrurj-232	57	14	.	.	PUNCT
arestyrurj-232	58	1	this	this	PRON
arestyrurj-232	58	2	is	be	AUX
arestyrurj-232	58	3	quite	quite	ADV
arestyrurj-232	58	4	unusual	unusual	ADJ
arestyrurj-232	58	5	;	;	PUNCT
arestyrurj-232	58	6	normally	normally	ADV
arestyrurj-232	58	7	the	the	DET
arestyrurj-232	58	8	testing	testing	NOUN
arestyrurj-232	58	9	error	error	NOUN
arestyrurj-232	58	10	should	should	AUX
arestyrurj-232	58	11	decline	decline	VERB
arestyrurj-232	58	12	as	as	ADV
arestyrurj-232	58	13	well	well	ADV
arestyrurj-232	58	14	.	.	PUNCT
arestyrurj-232	59	1	this	this	DET
arestyrurj-232	59	2	anomaly	anomaly	NOUN
arestyrurj-232	59	3	was	be	AUX
arestyrurj-232	59	4	not	not	PART
arestyrurj-232	59	5	investigated	investigate	VERB
arestyrurj-232	59	6	further	far	ADV
arestyrurj-232	59	7	because	because	SCONJ
arestyrurj-232	59	8	the	the	DET
arestyrurj-232	59	9	model	model	NOUN
arestyrurj-232	59	10	performed	perform	VERB
arestyrurj-232	59	11	decently	decently	ADV
arestyrurj-232	59	12	well	well	ADV
arestyrurj-232	59	13	despite	despite	SCONJ
arestyrurj-232	59	14	it	it	PRON
arestyrurj-232	59	15	.	.	PUNCT
arestyrurj-232	60	1	however	however	ADV
arestyrurj-232	60	2	,	,	PUNCT
arestyrurj-232	60	3	the	the	DET
arestyrurj-232	60	4	lack	lack	NOUN
arestyrurj-232	60	5	of	of	ADP
arestyrurj-232	60	6	change	change	NOUN
arestyrurj-232	60	7	is	be	AUX
arestyrurj-232	60	8	likely	likely	ADJ
arestyrurj-232	60	9	due	due	ADP
arestyrurj-232	60	10	to	to	ADP
arestyrurj-232	60	11	the	the	DET
arestyrurj-232	60	12	small	small	ADJ
arestyrurj-232	60	13	size	size	NOUN
arestyrurj-232	60	14	of	of	ADP
arestyrurj-232	60	15	the	the	DET
arestyrurj-232	60	16	test	test	NOUN
arestyrurj-232	60	17	sample	sample	NOUN
arestyrurj-232	60	18	,	,	PUNCT
arestyrurj-232	60	19	which	which	PRON
arestyrurj-232	60	20	was	be	AUX
arestyrurj-232	60	21	only	only	ADV
arestyrurj-232	60	22	43	43	NUM
arestyrurj-232	60	23	records	record	NOUN
arestyrurj-232	60	24	.	.	PUNCT
arestyrurj-232	61	1	it	it	PRON
arestyrurj-232	61	2	’s	’	VERB
arestyrurj-232	61	3	also	also	ADV
arestyrurj-232	61	4	possible	possible	ADJ
arestyrurj-232	61	5	that	that	SCONJ
arestyrurj-232	61	6	the	the	DET
arestyrurj-232	61	7	model	model	NOUN
arestyrurj-232	61	8	was	be	AUX
arestyrurj-232	61	9	slightly	slightly	ADV
arestyrurj-232	61	10	overfitting	overfitte	VERB
arestyrurj-232	61	11	,	,	PUNCT
arestyrurj-232	61	12	or	or	CCONJ
arestyrurj-232	61	13	fitting	fitting	ADJ
arestyrurj-232	61	14	too	too	ADV
arestyrurj-232	61	15	well	well	ADV
arestyrurj-232	61	16	,	,	PUNCT
arestyrurj-232	61	17	to	to	ADP
arestyrurj-232	61	18	the	the	DET
arestyrurj-232	61	19	training	training	NOUN
arestyrurj-232	61	20	data	datum	NOUN
arestyrurj-232	61	21	such	such	ADJ
arestyrurj-232	61	22	that	that	SCONJ
arestyrurj-232	61	23	the	the	DET
arestyrurj-232	61	24	training	training	NOUN
arestyrurj-232	61	25	process	process	NOUN
arestyrurj-232	61	26	did	do	VERB
arestyrurj-232	61	27	n’t	not	PART
arestyrurj-232	61	28	significantly	significantly	ADV
arestyrurj-232	61	29	impact	impact	VERB
arestyrurj-232	61	30	the	the	DET
arestyrurj-232	61	31	testing	testing	NOUN
arestyrurj-232	61	32	performance	performance	NOUN
arestyrurj-232	61	33	.	.	PUNCT
arestyrurj-232	62	1	as	as	ADP
arestyrurj-232	62	2	a	a	DET
arestyrurj-232	62	3	final	final	ADJ
arestyrurj-232	62	4	step	step	NOUN
arestyrurj-232	62	5	,	,	PUNCT
arestyrurj-232	62	6	a	a	DET
arestyrurj-232	62	7	naive	naive	ADJ
arestyrurj-232	62	8	model	model	NOUN
arestyrurj-232	62	9	was	be	AUX
arestyrurj-232	62	10	included	include	VERB
arestyrurj-232	62	11	for	for	ADP
arestyrurj-232	62	12	comparison	comparison	NOUN
arestyrurj-232	62	13	purposes	purpose	NOUN
arestyrurj-232	62	14	that	that	PRON
arestyrurj-232	62	15	classified	classified	ADJ
arestyrurj-232	62	16	fob	fob	NOUN
arestyrurj-232	62	17	songs	song	NOUN
arestyrurj-232	62	18	randomly	randomly	ADV
arestyrurj-232	62	19	.	.	PUNCT
arestyrurj-232	63	1	5	5	NUM
arestyrurj-232	63	2	comparative	comparative	ADJ
arestyrurj-232	63	3	modeling	modeling	NOUN
arestyrurj-232	63	4	results	result	NOUN
arestyrurj-232	63	5	to	to	PART
arestyrurj-232	63	6	contextualize	contextualize	VERB
arestyrurj-232	63	7	the	the	DET
arestyrurj-232	63	8	performance	performance	NOUN
arestyrurj-232	63	9	of	of	ADP
arestyrurj-232	63	10	the	the	DET
arestyrurj-232	63	11	custom	custom	ADV
arestyrurj-232	63	12	-	-	PUNCT
arestyrurj-232	63	13	built	build	VERB
arestyrurj-232	63	14	logistic	logistic	ADJ
arestyrurj-232	63	15	regression	regression	NOUN
arestyrurj-232	63	16	model	model	NOUN
arestyrurj-232	63	17	,	,	PUNCT
arestyrurj-232	63	18	several	several	ADJ
arestyrurj-232	63	19	other	other	ADJ
arestyrurj-232	63	20	binary	binary	ADJ
arestyrurj-232	63	21	classification	classification	NOUN
arestyrurj-232	63	22	algorithms	algorithm	NOUN
arestyrurj-232	63	23	were	be	AUX
arestyrurj-232	63	24	run	run	VERB
arestyrurj-232	63	25	using	use	VERB
arestyrurj-232	63	26	the	the	DET
arestyrurj-232	63	27	scikit	scikit	NOUN
arestyrurj-232	63	28	learn	learn	VERB
arestyrurj-232	63	29	python	python	NOUN
arestyrurj-232	63	30	library	library	NOUN
arestyrurj-232	63	31	.	.	PUNCT
arestyrurj-232	64	1	as	as	ADP
arestyrurj-232	64	2	an	an	DET
arestyrurj-232	64	3	additional	additional	ADJ
arestyrurj-232	64	4	experiment	experiment	NOUN
arestyrurj-232	64	5	,	,	PUNCT
arestyrurj-232	64	6	logistic	logistic	ADJ
arestyrurj-232	64	7	regression	regression	NOUN
arestyrurj-232	64	8	was	be	AUX
arestyrurj-232	64	9	implemented	implement	VERB
arestyrurj-232	64	10	as	as	ADP
arestyrurj-232	64	11	a	a	DET
arestyrurj-232	64	12	single	single	ADJ
arestyrurj-232	64	13	-	-	PUNCT
arestyrurj-232	64	14	layer	layer	NOUN
arestyrurj-232	64	15	neural	neural	ADJ
arestyrurj-232	64	16	network	network	NOUN
arestyrurj-232	64	17	(	(	PUNCT
arestyrurj-232	64	18	nn	nn	NOUN
arestyrurj-232	64	19	)	)	PUNCT
arestyrurj-232	64	20	using	use	VERB
arestyrurj-232	64	21	a	a	DET
arestyrurj-232	64	22	linear	linear	ADJ
arestyrurj-232	64	23	layer	layer	NOUN
arestyrurj-232	64	24	that	that	PRON
arestyrurj-232	64	25	was	be	AUX
arestyrurj-232	64	26	optimized	optimize	VERB
arestyrurj-232	64	27	with	with	ADP
arestyrurj-232	64	28	stochastic	stochastic	ADJ
arestyrurj-232	64	29	gradient	gradient	ADJ
arestyrurj-232	64	30	descent	descent	NOUN
arestyrurj-232	64	31	.	.	PUNCT
arestyrurj-232	65	1	these	these	DET
arestyrurj-232	65	2	complex	complex	ADJ
arestyrurj-232	65	3	mathematical	mathematical	ADJ
arestyrurj-232	65	4	processes	process	NOUN
arestyrurj-232	65	5	were	be	AUX
arestyrurj-232	65	6	implemented	implement	VERB
arestyrurj-232	65	7	using	use	VERB
arestyrurj-232	65	8	just	just	ADV
arestyrurj-232	65	9	two	two	NUM
arestyrurj-232	65	10	concise	concise	ADJ
arestyrurj-232	65	11	lines	line	NOUN
arestyrurj-232	65	12	of	of	ADP
arestyrurj-232	65	13	code	code	NOUN
arestyrurj-232	65	14	in	in	ADP
arestyrurj-232	65	15	pytorch	pytorch	NOUN
arestyrurj-232	65	16	.	.	PUNCT
arestyrurj-232	66	1	the	the	DET
arestyrurj-232	66	2	model	model	NOUN
arestyrurj-232	66	3	hyperparameters	hyperparameter	NOUN
arestyrurj-232	66	4	were	be	AUX
arestyrurj-232	66	5	tuned	tune	VERB
arestyrurj-232	66	6	by	by	ADP
arestyrurj-232	66	7	implementing	implement	VERB
arestyrurj-232	66	8	a	a	DET
arestyrurj-232	66	9	grid	grid	NOUN
arestyrurj-232	66	10	search	search	NOUN
arestyrurj-232	66	11	cross	cross	ADJ
arestyrurj-232	66	12	-	-	ADJ
arestyrurj-232	66	13	validation	validation	ADJ
arestyrurj-232	66	14	algorithm	algorithm	NOUN
arestyrurj-232	66	15	.	.	PUNCT
arestyrurj-232	67	1	the	the	DET
arestyrurj-232	67	2	model	model	NOUN
arestyrurj-232	67	3	correctness	correctness	NOUN
arestyrurj-232	67	4	was	be	AUX
arestyrurj-232	67	5	then	then	ADV
arestyrurj-232	67	6	measured	measure	VERB
arestyrurj-232	67	7	by	by	ADP
arestyrurj-232	67	8	counting	count	VERB
arestyrurj-232	67	9	the	the	DET
arestyrurj-232	67	10	numbers	number	NOUN
arestyrurj-232	67	11	of	of	ADP
arestyrurj-232	67	12	true	true	ADJ
arestyrurj-232	67	13	positives	positive	NOUN
arestyrurj-232	67	14	(	(	PUNCT
arestyrurj-232	67	15	tp	tp	NOUN
arestyrurj-232	67	16	)	)	PUNCT
arestyrurj-232	67	17	,	,	PUNCT
arestyrurj-232	67	18	false	false	ADJ
arestyrurj-232	67	19	positives	positive	NOUN
arestyrurj-232	67	20	(	(	PUNCT
arestyrurj-232	67	21	fp	fp	NOUN
arestyrurj-232	67	22	)	)	PUNCT
arestyrurj-232	67	23	,	,	PUNCT
arestyrurj-232	67	24	true	true	ADJ
arestyrurj-232	67	25	negatives	negative	NOUN
arestyrurj-232	67	26	(	(	PUNCT
arestyrurj-232	67	27	tn	tn	NOUN
arestyrurj-232	67	28	)	)	PUNCT
arestyrurj-232	67	29	,	,	PUNCT
arestyrurj-232	67	30	and	and	CCONJ
arestyrurj-232	67	31	false	false	ADJ
arestyrurj-232	67	32	negatives	negative	NOUN
arestyrurj-232	67	33	(	(	PUNCT
arestyrurj-232	67	34	fn	fn	NOUN
arestyrurj-232	67	35	)	)	PUNCT
arestyrurj-232	67	36	found	find	VERB
arestyrurj-232	67	37	by	by	ADP
arestyrurj-232	67	38	the	the	DET
arestyrurj-232	67	39	model	model	NOUN
arestyrurj-232	67	40	.	.	PUNCT
arestyrurj-232	68	1	those	those	DET
arestyrurj-232	68	2	counts	count	NOUN
arestyrurj-232	68	3	are	be	AUX
arestyrurj-232	68	4	expanded	expand	VERB
arestyrurj-232	68	5	into	into	ADP
arestyrurj-232	68	6	specific	specific	ADJ
arestyrurj-232	68	7	metrics	metric	NOUN
arestyrurj-232	68	8	which	which	PRON
arestyrurj-232	68	9	are	be	AUX
arestyrurj-232	68	10	used	use	VERB
arestyrurj-232	68	11	to	to	PART
arestyrurj-232	68	12	evaluate	evaluate	VERB
arestyrurj-232	68	13	model	model	NOUN
arestyrurj-232	68	14	performance	performance	NOUN
arestyrurj-232	68	15	:	:	PUNCT
arestyrurj-232	68	16	figure	figure	VERB
arestyrurj-232	68	17	6	6	NUM
arestyrurj-232	68	18	:	:	PUNCT
arestyrurj-232	68	19	comparative	comparative	ADJ
arestyrurj-232	68	20	model	model	NOUN
arestyrurj-232	68	21	metrics	metric	NOUN
arestyrurj-232	68	22	(	(	PUNCT
arestyrurj-232	68	23	source	source	NOUN
arestyrurj-232	68	24	)	)	PUNCT
arestyrurj-232	68	25	the	the	DET
arestyrurj-232	68	26	resulting	result	VERB
arestyrurj-232	68	27	metrics	metric	NOUN
arestyrurj-232	68	28	from	from	ADP
arestyrurj-232	68	29	all	all	DET
arestyrurj-232	68	30	models	model	NOUN
arestyrurj-232	68	31	were	be	AUX
arestyrurj-232	68	32	as	as	SCONJ
arestyrurj-232	68	33	follows	follow	VERB
arestyrurj-232	68	34	:	:	PUNCT
arestyrurj-232	68	35	figure	figure	VERB
arestyrurj-232	68	36	7	7	NUM
arestyrurj-232	68	37	:	:	PUNCT
arestyrurj-232	68	38	comparative	comparative	ADJ
arestyrurj-232	68	39	model	model	NOUN
arestyrurj-232	68	40	metrics	metric	NOUN
arestyrurj-232	68	41	.	.	PUNCT
arestyrurj-232	69	1	svc	svc	PROPN
arestyrurj-232	69	2	refers	refer	VERB
arestyrurj-232	69	3	to	to	PART
arestyrurj-232	69	4	support	support	VERB
arestyrurj-232	69	5	vector	vector	NOUN
arestyrurj-232	69	6	machines	machine	NOUN
arestyrurj-232	69	7	,	,	PUNCT
arestyrurj-232	69	8	gaussiannb	gaussiannb	PROPN
arestyrurj-232	69	9	refers	refer	VERB
arestyrurj-232	69	10	to	to	ADP
arestyrurj-232	69	11	gaussian	gaussian	ADJ
arestyrurj-232	69	12	naive	naive	ADJ
arestyrurj-232	69	13	bayes	baye	NOUN
arestyrurj-232	69	14	,	,	PUNCT
arestyrurj-232	69	15	and	and	CCONJ
arestyrurj-232	69	16	knn	knn	PROPN
arestyrurj-232	69	17	refers	refer	VERB
arestyrurj-232	69	18	to	to	ADP
arestyrurj-232	69	19	k	k	ADJ
arestyrurj-232	69	20	-	-	PUNCT
arestyrurj-232	69	21	nearest	near	ADJ
arestyrurj-232	69	22	neighbors	neighbor	NOUN
arestyrurj-232	69	23	model	model	NOUN
arestyrurj-232	69	24	accuracy	accuracy	NOUN
arestyrurj-232	69	25	f1	f1	PROPN
arestyrurj-232	69	26	score	score	NOUN
arestyrurj-232	69	27	precision	precision	NOUN
arestyrurj-232	69	28	recall	recall	VERB
arestyrurj-232	69	29	svc	svc	PROPN
arestyrurj-232	69	30	62.79	62.79	NUM
arestyrurj-232	69	31	%	%	NOUN
arestyrurj-232	69	32	52.94	52.94	NUM
arestyrurj-232	69	33	%	%	NOUN
arestyrurj-232	69	34	52.94	52.94	NUM
arestyrurj-232	69	35	%	%	NOUN
arestyrurj-232	69	36	52.94	52.94	NUM
arestyrurj-232	69	37	%	%	NOUN
arestyrurj-232	69	38	linearsvc	linearsvc	NOUN
arestyrurj-232	69	39	67.44	67.44	NUM
arestyrurj-232	69	40	%	%	NOUN
arestyrurj-232	69	41	36.36	36.36	NUM
arestyrurj-232	69	42	%	%	NOUN
arestyrurj-232	69	43	23.53	23.53	NUM
arestyrurj-232	69	44	%	%	NOUN
arestyrurj-232	69	45	80.00	80.00	NUM
arestyrurj-232	69	46	%	%	NOUN
arestyrurj-232	69	47	gaussiannb	gaussiannb	NOUN
arestyrurj-232	69	48	69.77	69.77	NUM
arestyrurj-232	69	49	%	%	NOUN
arestyrurj-232	69	50	60.61	60.61	NUM
arestyrurj-232	69	51	%	%	NOUN
arestyrurj-232	69	52	58.82	58.82	NUM
arestyrurj-232	69	53	%	%	NOUN
arestyrurj-232	69	54	62.50	62.50	NUM
arestyrurj-232	69	55	%	%	NOUN
arestyrurj-232	69	56	knn	knn	NOUN
arestyrurj-232	69	57	65.12	65.12	NUM
arestyrurj-232	69	58	%	%	NOUN
arestyrurj-232	69	59	44.44	44.44	NUM
arestyrurj-232	69	60	%	%	NOUN
arestyrurj-232	69	61	35.29	35.29	NUM
arestyrurj-232	69	62	%	%	NOUN
arestyrurj-232	69	63	60.00	60.00	NUM
arestyrurj-232	69	64	%	%	NOUN
arestyrurj-232	69	65	nn	nn	PROPN
arestyrurj-232	69	66	25.58	25.58	NUM
arestyrurj-232	69	67	%	%	NOUN
arestyrurj-232	69	68	10.53	10.53	NUM
arestyrurj-232	69	69	%	%	NOUN
arestyrurj-232	69	70	100.00	100.00	NUM
arestyrurj-232	69	71	%	%	NOUN
arestyrurj-232	69	72	11.76	11.76	NUM
arestyrurj-232	69	73	%	%	NOUN
arestyrurj-232	69	74	random	random	ADJ
arestyrurj-232	69	75	forest	forest	NOUN
arestyrurj-232	69	76	79.07	79.07	NUM
arestyrurj-232	69	77	%	%	NOUN
arestyrurj-232	69	78	70.97	70.97	NUM
arestyrurj-232	69	79	%	%	NOUN
arestyrurj-232	69	80	64.71	64.71	NUM
arestyrurj-232	69	81	%	%	NOUN
arestyrurj-232	69	82	78.57	78.57	NUM
arestyrurj-232	69	83	%	%	NOUN
arestyrurj-232	69	84	lr	lr	X
arestyrurj-232	69	85	(	(	PUNCT
arestyrurj-232	69	86	scratch	scratch	PROPN
arestyrurj-232	69	87	)	)	PUNCT
arestyrurj-232	69	88	41.86	41.86	NUM
arestyrurj-232	69	89	%	%	NOUN
arestyrurj-232	69	90	28.81	28.81	NUM
arestyrurj-232	69	91	%	%	NOUN
arestyrurj-232	69	92	40.48	40.48	NUM
arestyrurj-232	69	93	%	%	NOUN
arestyrurj-232	69	94	100.00	100.00	NUM
arestyrurj-232	69	95	%	%	NOUN
arestyrurj-232	69	96	lr	lr	X
arestyrurj-232	69	97	(	(	PUNCT
arestyrurj-232	69	98	scikit	scikit	PROPN
arestyrurj-232	69	99	)	)	PUNCT
arestyrurj-232	69	100	76.74	76.74	NUM
arestyrurj-232	69	101	%	%	NOUN
arestyrurj-232	69	102	64.29	64.29	NUM
arestyrurj-232	69	103	%	%	NOUN
arestyrurj-232	69	104	52.94	52.94	NUM
arestyrurj-232	69	105	%	%	NOUN
arestyrurj-232	69	106	81.82	81.82	NUM
arestyrurj-232	69	107	%	%	NOUN
arestyrurj-232	69	108	https://www.researchgate.net/post/what_is_the_best_metric_precision_recall_f1_and_accuracy_to_evaluate_the_machine_learning_model_for_imbalanced_data	https://www.researchgate.net/post/what_is_the_best_metric_precision_recall_f1_and_accuracy_to_evaluate_the_machine_learning_model_for_imbalanced_data	NOUN
arestyrurj-232	69	109	aresty	aresty	PROPN
arestyrurj-232	69	110	rutgers	rutgers	PROPN
arestyrurj-232	69	111	undergraduate	undergraduate	PROPN
arestyrurj-232	69	112	research	research	PROPN
arestyrurj-232	69	113	journal	journal	PROPN
arestyrurj-232	69	114	,	,	PUNCT
arestyrurj-232	69	115	volume	volume	NOUN
arestyrurj-232	69	116	i	i	PRON
arestyrurj-232	69	117	,	,	PUNCT
arestyrurj-232	69	118	issue	issue	VERB
arestyrurj-232	69	119	v	v	ADP
arestyrurj-232	69	120	3	3	NUM
arestyrurj-232	69	121	as	as	SCONJ
arestyrurj-232	69	122	expected	expect	VERB
arestyrurj-232	69	123	,	,	PUNCT
arestyrurj-232	69	124	the	the	DET
arestyrurj-232	69	125	random	random	ADJ
arestyrurj-232	69	126	forest	forest	NOUN
arestyrurj-232	69	127	classifier	classifier	NOUN
arestyrurj-232	69	128	performed	perform	VERB
arestyrurj-232	69	129	well	well	ADV
arestyrurj-232	69	130	on	on	ADP
arestyrurj-232	69	131	all	all	DET
arestyrurj-232	69	132	metrics	metric	NOUN
arestyrurj-232	69	133	,	,	PUNCT
arestyrurj-232	69	134	as	as	SCONJ
arestyrurj-232	69	135	it	it	PRON
arestyrurj-232	69	136	is	be	AUX
arestyrurj-232	69	137	an	an	DET
arestyrurj-232	69	138	ensemble	ensemble	ADJ
arestyrurj-232	69	139	method	method	NOUN
arestyrurj-232	69	140	that	that	PRON
arestyrurj-232	69	141	utilizes	utilize	VERB
arestyrurj-232	69	142	multiple	multiple	ADJ
arestyrurj-232	69	143	learners	learner	NOUN
arestyrurj-232	69	144	.	.	PUNCT
arestyrurj-232	70	1	both	both	DET
arestyrurj-232	70	2	implementations	implementation	NOUN
arestyrurj-232	70	3	of	of	ADP
arestyrurj-232	70	4	the	the	DET
arestyrurj-232	70	5	logistic	logistic	ADJ
arestyrurj-232	70	6	regression	regression	NOUN
arestyrurj-232	70	7	algorithm	algorithm	NOUN
arestyrurj-232	70	8	performed	perform	VERB
arestyrurj-232	70	9	better	well	ADV
arestyrurj-232	70	10	than	than	ADP
arestyrurj-232	70	11	random	random	ADJ
arestyrurj-232	70	12	forest	forest	NOUN
arestyrurj-232	70	13	in	in	ADP
arestyrurj-232	70	14	terms	term	NOUN
arestyrurj-232	70	15	of	of	ADP
arestyrurj-232	70	16	recall	recall	NOUN
arestyrurj-232	70	17	,	,	PUNCT
arestyrurj-232	70	18	which	which	PRON
arestyrurj-232	70	19	initially	initially	ADV
arestyrurj-232	70	20	suggests	suggest	VERB
arestyrurj-232	70	21	impressive	impressive	ADJ
arestyrurj-232	70	22	performance	performance	NOUN
arestyrurj-232	70	23	.	.	PUNCT
arestyrurj-232	71	1	however	however	ADV
arestyrurj-232	71	2	,	,	PUNCT
arestyrurj-232	71	3	the	the	DET
arestyrurj-232	71	4	low	low	ADJ
arestyrurj-232	71	5	accuracy	accuracy	NOUN
arestyrurj-232	71	6	of	of	ADP
arestyrurj-232	71	7	the	the	DET
arestyrurj-232	71	8	custom	custom	ADV
arestyrurj-232	71	9	-	-	PUNCT
arestyrurj-232	71	10	built	build	VERB
arestyrurj-232	71	11	logistic	logistic	ADJ
arestyrurj-232	71	12	regression	regression	NOUN
arestyrurj-232	71	13	model	model	NOUN
arestyrurj-232	71	14	renders	render	VERB
arestyrurj-232	71	15	the	the	DET
arestyrurj-232	71	16	high	high	ADJ
arestyrurj-232	71	17	recall	recall	NOUN
arestyrurj-232	71	18	essentially	essentially	ADV
arestyrurj-232	71	19	meaningless	meaningless	ADJ
arestyrurj-232	71	20	.	.	PUNCT
arestyrurj-232	72	1	it	it	PRON
arestyrurj-232	72	2	is	be	AUX
arestyrurj-232	72	3	worth	worth	ADJ
arestyrurj-232	72	4	noting	note	VERB
arestyrurj-232	72	5	that	that	SCONJ
arestyrurj-232	72	6	the	the	DET
arestyrurj-232	72	7	optimal	optimal	ADJ
arestyrurj-232	72	8	logistic	logistic	ADJ
arestyrurj-232	72	9	regression	regression	NOUN
arestyrurj-232	72	10	algorithm	algorithm	NOUN
arestyrurj-232	72	11	using	use	VERB
arestyrurj-232	72	12	the	the	DET
arestyrurj-232	72	13	scikit	scikit	NOUN
arestyrurj-232	72	14	learn	learn	VERB
arestyrurj-232	72	15	library	library	NOUN
arestyrurj-232	72	16	employed	employ	VERB
arestyrurj-232	72	17	l1	l1	PROPN
arestyrurj-232	72	18	regularization	regularization	NOUN
arestyrurj-232	72	19	,	,	PUNCT
arestyrurj-232	72	20	which	which	PRON
arestyrurj-232	72	21	is	be	AUX
arestyrurj-232	72	22	typically	typically	ADV
arestyrurj-232	72	23	used	use	VERB
arestyrurj-232	72	24	to	to	PART
arestyrurj-232	72	25	prevent	prevent	VERB
arestyrurj-232	72	26	overfitting	overfitting	NOUN
arestyrurj-232	72	27	.	.	PUNCT
arestyrurj-232	73	1	although	although	SCONJ
arestyrurj-232	73	2	the	the	DET
arestyrurj-232	73	3	conventional	conventional	ADJ
arestyrurj-232	73	4	logistic	logistic	ADJ
arestyrurj-232	73	5	regression	regression	NOUN
arestyrurj-232	73	6	model	model	NOUN
arestyrurj-232	73	7	was	be	AUX
arestyrurj-232	73	8	not	not	PART
arestyrurj-232	73	9	overfitting	overfitte	VERB
arestyrurj-232	73	10	and	and	CCONJ
arestyrurj-232	73	11	did	do	AUX
arestyrurj-232	73	12	not	not	PART
arestyrurj-232	73	13	appear	appear	VERB
arestyrurj-232	73	14	to	to	PART
arestyrurj-232	73	15	require	require	VERB
arestyrurj-232	73	16	l1	l1	PROPN
arestyrurj-232	73	17	regularization	regularization	NOUN
arestyrurj-232	73	18	,	,	PUNCT
arestyrurj-232	73	19	its	its	PRON
arestyrurj-232	73	20	inclusion	inclusion	NOUN
arestyrurj-232	73	21	improved	improve	VERB
arestyrurj-232	73	22	all	all	PRON
arestyrurj-232	73	23	of	of	ADP
arestyrurj-232	73	24	the	the	DET
arestyrurj-232	73	25	recorded	record	VERB
arestyrurj-232	73	26	metrics	metric	NOUN
arestyrurj-232	73	27	.	.	PUNCT
arestyrurj-232	74	1	6	6	NUM
arestyrurj-232	74	2	conclusion	conclusion	NOUN
arestyrurj-232	74	3	and	and	CCONJ
arestyrurj-232	74	4	next	next	ADJ
arestyrurj-232	74	5	steps	step	NOUN
arestyrurj-232	74	6	this	this	DET
arestyrurj-232	74	7	project	project	NOUN
arestyrurj-232	74	8	involved	involve	VERB
arestyrurj-232	74	9	several	several	ADJ
arestyrurj-232	74	10	key	key	ADJ
arestyrurj-232	74	11	steps	step	NOUN
arestyrurj-232	74	12	:	:	PUNCT
arestyrurj-232	74	13	•	•	ADV
arestyrurj-232	74	14	aggregating	aggregate	VERB
arestyrurj-232	74	15	data	datum	NOUN
arestyrurj-232	74	16	from	from	ADP
arestyrurj-232	74	17	multiple	multiple	ADJ
arestyrurj-232	74	18	apis	apis	ADJ
arestyrurj-232	74	19	.	.	PUNCT
arestyrurj-232	75	1	•	•	PUNCT
arestyrurj-232	75	2	exploring	explore	VERB
arestyrurj-232	75	3	and	and	CCONJ
arestyrurj-232	75	4	analyzing	analyze	VERB
arestyrurj-232	75	5	the	the	DET
arestyrurj-232	75	6	sourced	source	VERB
arestyrurj-232	75	7	data	datum	NOUN
arestyrurj-232	75	8	for	for	ADP
arestyrurj-232	75	9	feature	feature	NOUN
arestyrurj-232	75	10	engineering	engineering	NOUN
arestyrurj-232	75	11	.	.	PUNCT
arestyrurj-232	76	1	•	•	NUM
arestyrurj-232	76	2	building	building	NOUN
arestyrurj-232	76	3	models	model	NOUN
arestyrurj-232	76	4	to	to	PART
arestyrurj-232	76	5	evaluate	evaluate	VERB
arestyrurj-232	76	6	their	their	PRON
arestyrurj-232	76	7	performance	performance	NOUN
arestyrurj-232	76	8	on	on	ADP
arestyrurj-232	76	9	a	a	DET
arestyrurj-232	76	10	binary	binary	ADJ
arestyrurj-232	76	11	classification	classification	NOUN
arestyrurj-232	76	12	task	task	NOUN
arestyrurj-232	76	13	.	.	PUNCT
arestyrurj-232	77	1	•	•	PUNCT
arestyrurj-232	78	1	answering	answer	VERB
arestyrurj-232	78	2	the	the	DET
arestyrurj-232	78	3	question	question	NOUN
arestyrurj-232	78	4	:	:	PUNCT
arestyrurj-232	78	5	can	can	AUX
arestyrurj-232	78	6	a	a	DET
arestyrurj-232	78	7	machine	machine	NOUN
arestyrurj-232	78	8	differentiate	differentiate	NOUN
arestyrurj-232	78	9	between	between	ADP
arestyrurj-232	78	10	the	the	DET
arestyrurj-232	78	11	old	old	ADJ
arestyrurj-232	78	12	and	and	CCONJ
arestyrurj-232	78	13	new	new	ADJ
arestyrurj-232	78	14	music	music	NOUN
arestyrurj-232	78	15	of	of	ADP
arestyrurj-232	78	16	fall	fall	NOUN
arestyrurj-232	78	17	out	out	ADP
arestyrurj-232	78	18	boy	boy	NOUN
arestyrurj-232	78	19	(	(	PUNCT
arestyrurj-232	78	20	fob	fob	PROPN
arestyrurj-232	78	21	)	)	PUNCT
arestyrurj-232	78	22	?	?	PUNCT
arestyrurj-232	79	1	the	the	DET
arestyrurj-232	79	2	details	detail	NOUN
arestyrurj-232	79	3	of	of	ADP
arestyrurj-232	79	4	all	all	PRON
arestyrurj-232	79	5	of	of	ADP
arestyrurj-232	79	6	these	these	DET
arestyrurj-232	79	7	steps	step	NOUN
arestyrurj-232	79	8	can	can	AUX
arestyrurj-232	79	9	be	be	AUX
arestyrurj-232	79	10	found	find	VERB
arestyrurj-232	79	11	in	in	ADP
arestyrurj-232	79	12	the	the	DET
arestyrurj-232	79	13	supplemental	supplemental	ADJ
arestyrurj-232	79	14	document	document	NOUN
arestyrurj-232	79	15	along	along	ADP
arestyrurj-232	79	16	with	with	ADP
arestyrurj-232	79	17	relevant	relevant	ADJ
arestyrurj-232	79	18	code	code	NOUN
arestyrurj-232	79	19	blocks	block	NOUN
arestyrurj-232	79	20	and	and	CCONJ
arestyrurj-232	79	21	information	information	NOUN
arestyrurj-232	79	22	sources	source	NOUN
arestyrurj-232	79	23	.	.	PUNCT
arestyrurj-232	80	1	the	the	DET
arestyrurj-232	80	2	results	result	NOUN
arestyrurj-232	80	3	of	of	ADP
arestyrurj-232	80	4	this	this	DET
arestyrurj-232	80	5	project	project	NOUN
arestyrurj-232	80	6	indicate	indicate	VERB
arestyrurj-232	80	7	that	that	SCONJ
arestyrurj-232	80	8	logistic	logistic	ADJ
arestyrurj-232	80	9	regression	regression	NOUN
arestyrurj-232	80	10	performed	perform	VERB
arestyrurj-232	80	11	surprisingly	surprisingly	ADV
arestyrurj-232	80	12	well	well	ADV
arestyrurj-232	80	13	on	on	ADP
arestyrurj-232	80	14	a	a	DET
arestyrurj-232	80	15	small	small	ADJ
arestyrurj-232	80	16	dataset	dataset	NOUN
arestyrurj-232	80	17	of	of	ADP
arestyrurj-232	80	18	around	around	ADP
arestyrurj-232	80	19	140	140	NUM
arestyrurj-232	80	20	rows	row	NOUN
arestyrurj-232	80	21	.	.	PUNCT
arestyrurj-232	81	1	random	random	ADJ
arestyrurj-232	81	2	forest	forest	NOUN
arestyrurj-232	81	3	also	also	ADV
arestyrurj-232	81	4	performed	perform	VERB
arestyrurj-232	81	5	well	well	ADV
arestyrurj-232	81	6	,	,	PUNCT
arestyrurj-232	81	7	as	as	SCONJ
arestyrurj-232	81	8	the	the	DET
arestyrurj-232	81	9	ensemble	ensemble	ADJ
arestyrurj-232	81	10	learning	learning	NOUN
arestyrurj-232	81	11	compensated	compensate	VERB
arestyrurj-232	81	12	for	for	ADP
arestyrurj-232	81	13	the	the	DET
arestyrurj-232	81	14	smaller	small	ADJ
arestyrurj-232	81	15	size	size	NOUN
arestyrurj-232	81	16	of	of	ADP
arestyrurj-232	81	17	the	the	DET
arestyrurj-232	81	18	data	datum	NOUN
arestyrurj-232	81	19	.	.	PUNCT
arestyrurj-232	82	1	overall	overall	ADV
arestyrurj-232	82	2	,	,	PUNCT
arestyrurj-232	82	3	this	this	DET
arestyrurj-232	82	4	project	project	NOUN
arestyrurj-232	82	5	shows	show	VERB
arestyrurj-232	82	6	that	that	SCONJ
arestyrurj-232	82	7	rudimentary	rudimentary	ADJ
arestyrurj-232	82	8	ai	ai	NOUN
arestyrurj-232	82	9	can	can	AUX
arestyrurj-232	82	10	still	still	ADV
arestyrurj-232	82	11	simulate	simulate	VERB
arestyrurj-232	82	12	the	the	DET
arestyrurj-232	82	13	human	human	ADJ
arestyrurj-232	82	14	experience	experience	NOUN
arestyrurj-232	82	15	to	to	ADP
arestyrurj-232	82	16	some	some	DET
arestyrurj-232	82	17	degree	degree	NOUN
arestyrurj-232	82	18	.	.	PUNCT
arestyrurj-232	83	1	it	it	PRON
arestyrurj-232	83	2	’s	’	VERB
arestyrurj-232	83	3	quite	quite	DET
arestyrurj-232	83	4	a	a	DET
arestyrurj-232	83	5	human	human	ADJ
arestyrurj-232	83	6	thing	thing	NOUN
arestyrurj-232	83	7	to	to	PART
arestyrurj-232	83	8	notice	notice	VERB
arestyrurj-232	83	9	differences	difference	NOUN
arestyrurj-232	83	10	in	in	ADP
arestyrurj-232	83	11	musical	musical	ADJ
arestyrurj-232	83	12	styles	style	NOUN
arestyrurj-232	83	13	,	,	PUNCT
arestyrurj-232	83	14	or	or	CCONJ
arestyrurj-232	83	15	to	to	PART
arestyrurj-232	83	16	differentiate	differentiate	VERB
arestyrurj-232	83	17	an	an	DET
arestyrurj-232	83	18	artist	artist	NOUN
arestyrurj-232	83	19	’s	’s	PART
arestyrurj-232	83	20	old	old	ADJ
arestyrurj-232	83	21	sound	sound	NOUN
arestyrurj-232	83	22	from	from	ADP
arestyrurj-232	83	23	their	their	PRON
arestyrurj-232	83	24	new	new	ADJ
arestyrurj-232	83	25	one	one	NOUN
arestyrurj-232	83	26	,	,	PUNCT
arestyrurj-232	83	27	and	and	CCONJ
arestyrurj-232	83	28	this	this	DET
arestyrurj-232	83	29	simple	simple	ADJ
arestyrurj-232	83	30	ai	ai	NOUN
arestyrurj-232	83	31	can	can	AUX
arestyrurj-232	83	32	still	still	ADV
arestyrurj-232	83	33	accomplish	accomplish	VERB
arestyrurj-232	83	34	that	that	PRON
arestyrurj-232	83	35	.	.	PUNCT
arestyrurj-232	84	1	it	it	PRON
arestyrurj-232	84	2	’s	’	VERB
arestyrurj-232	84	3	noteworthy	noteworthy	ADJ
arestyrurj-232	84	4	that	that	SCONJ
arestyrurj-232	84	5	complex	complex	ADJ
arestyrurj-232	84	6	generative	generative	ADJ
arestyrurj-232	84	7	models	model	NOUN
arestyrurj-232	84	8	like	like	ADP
arestyrurj-232	84	9	chat	chat	NOUN
arestyrurj-232	84	10	gpt	gpt	NOUN
arestyrurj-232	84	11	and	and	CCONJ
arestyrurj-232	84	12	dall	dall	NOUN
arestyrurj-232	84	13	e	e	PROPN
arestyrurj-232	84	14	2	2	NUM
arestyrurj-232	84	15	specialize	specialize	VERB
arestyrurj-232	84	16	in	in	ADP
arestyrurj-232	84	17	tasks	task	NOUN
arestyrurj-232	84	18	such	such	ADJ
arestyrurj-232	84	19	as	as	ADP
arestyrurj-232	84	20	writing	writing	NOUN
arestyrurj-232	84	21	and	and	CCONJ
arestyrurj-232	84	22	visual	visual	ADJ
arestyrurj-232	84	23	art	art	NOUN
arestyrurj-232	84	24	.	.	PUNCT
arestyrurj-232	85	1	we	we	PRON
arestyrurj-232	85	2	once	once	ADV
arestyrurj-232	85	3	thought	think	VERB
arestyrurj-232	85	4	machines	machine	NOUN
arestyrurj-232	85	5	would	would	AUX
arestyrurj-232	85	6	struggle	struggle	VERB
arestyrurj-232	85	7	with	with	ADP
arestyrurj-232	85	8	these	these	DET
arestyrurj-232	85	9	creative	creative	ADJ
arestyrurj-232	85	10	tasks	task	NOUN
arestyrurj-232	85	11	,	,	PUNCT
arestyrurj-232	85	12	but	but	CCONJ
arestyrurj-232	85	13	in	in	ADP
arestyrurj-232	85	14	the	the	DET
arestyrurj-232	85	15	current	current	ADJ
arestyrurj-232	85	16	generative	generative	NOUN
arestyrurj-232	85	17	ai	ai	VERB
arestyrurj-232	85	18	landscape	landscape	NOUN
arestyrurj-232	85	19	,	,	PUNCT
arestyrurj-232	85	20	it	it	PRON
arestyrurj-232	85	21	seems	seem	VERB
arestyrurj-232	85	22	that	that	SCONJ
arestyrurj-232	85	23	tasks	task	NOUN
arestyrurj-232	85	24	thought	think	VERB
arestyrurj-232	85	25	to	to	PART
arestyrurj-232	85	26	be	be	AUX
arestyrurj-232	85	27	most	most	ADV
arestyrurj-232	85	28	human	human	ADJ
arestyrurj-232	85	29	are	be	AUX
arestyrurj-232	85	30	arguably	arguably	ADV
arestyrurj-232	85	31	the	the	DET
arestyrurj-232	85	32	most	most	ADV
arestyrurj-232	85	33	conducive	conducive	ADJ
arestyrurj-232	85	34	to	to	PART
arestyrurj-232	85	35	ai	ai	VERB
arestyrurj-232	85	36	.	.	PUNCT
arestyrurj-232	86	1	a	a	DET
arestyrurj-232	86	2	variety	variety	NOUN
arestyrurj-232	86	3	of	of	ADP
arestyrurj-232	86	4	methods	method	NOUN
arestyrurj-232	86	5	are	be	AUX
arestyrurj-232	86	6	available	available	ADJ
arestyrurj-232	86	7	to	to	PART
arestyrurj-232	86	8	explore	explore	VERB
arestyrurj-232	86	9	these	these	DET
arestyrurj-232	86	10	ai	ai	ADJ
arestyrurj-232	86	11	tasks	task	NOUN
arestyrurj-232	86	12	.	.	PUNCT
arestyrurj-232	87	1	an	an	DET
arestyrurj-232	87	2	alternative	alternative	ADJ
arestyrurj-232	87	3	approach	approach	NOUN
arestyrurj-232	87	4	for	for	ADP
arestyrurj-232	87	5	this	this	DET
arestyrurj-232	87	6	project	project	NOUN
arestyrurj-232	87	7	would	would	AUX
arestyrurj-232	87	8	have	have	AUX
arestyrurj-232	87	9	been	be	AUX
arestyrurj-232	87	10	to	to	PART
arestyrurj-232	87	11	analyze	analyze	VERB
arestyrurj-232	87	12	fob	fob	NOUN
arestyrurj-232	87	13	songs	song	NOUN
arestyrurj-232	87	14	as	as	ADP
arestyrurj-232	87	15	complex	complex	ADJ
arestyrurj-232	87	16	time	time	NOUN
arestyrurj-232	87	17	series	series	NOUN
arestyrurj-232	87	18	,	,	PUNCT
arestyrurj-232	87	19	using	use	VERB
arestyrurj-232	87	20	deep	deep	ADJ
arestyrurj-232	87	21	learning	learning	NOUN
arestyrurj-232	87	22	to	to	PART
arestyrurj-232	87	23	extract	extract	VERB
arestyrurj-232	87	24	relevant	relevant	ADJ
arestyrurj-232	87	25	features	feature	NOUN
arestyrurj-232	87	26	,	,	PUNCT
arestyrurj-232	87	27	and	and	CCONJ
arestyrurj-232	87	28	fine	fine	ADV
arestyrurj-232	87	29	-	-	PUNCT
arestyrurj-232	87	30	tuning	tune	VERB
arestyrurj-232	87	31	a	a	DET
arestyrurj-232	87	32	complex	complex	ADJ
arestyrurj-232	87	33	neural	neural	ADJ
arestyrurj-232	87	34	network	network	NOUN
arestyrurj-232	87	35	as	as	ADV
arestyrurj-232	87	36	precisely	precisely	ADV
arestyrurj-232	87	37	as	as	ADP
arestyrurj-232	87	38	possible	possible	ADJ
arestyrurj-232	87	39	.	.	PUNCT
arestyrurj-232	88	1	however	however	ADV
arestyrurj-232	88	2	,	,	PUNCT
arestyrurj-232	88	3	the	the	DET
arestyrurj-232	88	4	goal	goal	NOUN
arestyrurj-232	88	5	of	of	ADP
arestyrurj-232	88	6	this	this	DET
arestyrurj-232	88	7	project	project	NOUN
arestyrurj-232	88	8	was	be	AUX
arestyrurj-232	88	9	to	to	PART
arestyrurj-232	88	10	gain	gain	VERB
arestyrurj-232	88	11	experience	experience	NOUN
arestyrurj-232	88	12	with	with	ADP
arestyrurj-232	88	13	data	datum	NOUN
arestyrurj-232	88	14	wrangling	wrangle	VERB
arestyrurj-232	88	15	and	and	CCONJ
arestyrurj-232	88	16	popular	popular	ADJ
arestyrurj-232	88	17	machine	machine	NOUN
arestyrurj-232	88	18	learning	learn	VERB
arestyrurj-232	88	19	algorithms	algorithm	NOUN
arestyrurj-232	88	20	,	,	PUNCT
arestyrurj-232	88	21	as	as	SCONJ
arestyrurj-232	88	22	opposed	oppose	VERB
arestyrurj-232	88	23	to	to	ADP
arestyrurj-232	88	24	advanced	advanced	ADJ
arestyrurj-232	88	25	time	time	NOUN
arestyrurj-232	88	26	series	series	NOUN
arestyrurj-232	88	27	modeling	modeling	NOUN
arestyrurj-232	88	28	and	and	CCONJ
arestyrurj-232	88	29	deep	deep	ADJ
arestyrurj-232	88	30	learning	learning	NOUN
arestyrurj-232	88	31	.	.	PUNCT
arestyrurj-232	89	1	the	the	DET
arestyrurj-232	89	2	next	next	ADJ
arestyrurj-232	89	3	steps	step	NOUN
arestyrurj-232	89	4	for	for	ADP
arestyrurj-232	89	5	this	this	DET
arestyrurj-232	89	6	project	project	NOUN
arestyrurj-232	89	7	would	would	AUX
arestyrurj-232	89	8	include	include	VERB
arestyrurj-232	89	9	further	further	ADJ
arestyrurj-232	89	10	model	model	NOUN
arestyrurj-232	89	11	tuning	tuning	NOUN
arestyrurj-232	89	12	and	and	CCONJ
arestyrurj-232	89	13	optimization	optimization	NOUN
arestyrurj-232	89	14	for	for	ADP
arestyrurj-232	89	15	the	the	DET
arestyrurj-232	89	16	algorithms	algorithm	NOUN
arestyrurj-232	89	17	discussed	discuss	VERB
arestyrurj-232	89	18	in	in	ADP
arestyrurj-232	89	19	the	the	DET
arestyrurj-232	89	20	comparative	comparative	ADJ
arestyrurj-232	89	21	modeling	modeling	NOUN
arestyrurj-232	89	22	stage	stage	NOUN
arestyrurj-232	89	23	.	.	PUNCT
arestyrurj-232	90	1	next	next	ADJ
arestyrurj-232	90	2	steps	step	NOUN
arestyrurj-232	90	3	could	could	AUX
arestyrurj-232	90	4	also	also	ADV
arestyrurj-232	90	5	include	include	VERB
arestyrurj-232	90	6	the	the	DET
arestyrurj-232	90	7	alternative	alternative	ADJ
arestyrurj-232	90	8	approach	approach	NOUN
arestyrurj-232	90	9	of	of	ADP
arestyrurj-232	90	10	rigorous	rigorous	ADJ
arestyrurj-232	90	11	time	time	NOUN
arestyrurj-232	90	12	series	series	PROPN
arestyrurj-232	90	13	analysis	analysis	NOUN
arestyrurj-232	90	14	.	.	PUNCT
arestyrurj-232	91	1	this	this	DET
arestyrurj-232	91	2	approach	approach	NOUN
arestyrurj-232	91	3	would	would	AUX
arestyrurj-232	91	4	be	be	AUX
arestyrurj-232	91	5	helpful	helpful	ADJ
arestyrurj-232	91	6	because	because	SCONJ
arestyrurj-232	91	7	researchers	researcher	NOUN
arestyrurj-232	91	8	could	could	AUX
arestyrurj-232	91	9	derive	derive	VERB
arestyrurj-232	91	10	their	their	PRON
arestyrurj-232	91	11	own	own	ADJ
arestyrurj-232	91	12	numerical	numerical	ADJ
arestyrurj-232	91	13	audio	audio	ADJ
arestyrurj-232	91	14	features	feature	NOUN
arestyrurj-232	91	15	using	use	VERB
arestyrurj-232	91	16	time	time	NOUN
arestyrurj-232	91	17	series	series	PROPN
arestyrurj-232	91	18	patterns	pattern	NOUN
arestyrurj-232	91	19	instead	instead	ADV
arestyrurj-232	91	20	of	of	ADP
arestyrurj-232	91	21	using	use	VERB
arestyrurj-232	91	22	spotify	spotify	NOUN
arestyrurj-232	91	23	’s	’s	PART
arestyrurj-232	91	24	limited	limited	ADJ
arestyrurj-232	91	25	features	feature	NOUN
arestyrurj-232	91	26	.	.	PUNCT
arestyrurj-232	92	1	this	this	DET
arestyrurj-232	92	2	process	process	NOUN
arestyrurj-232	92	3	would	would	AUX
arestyrurj-232	92	4	require	require	VERB
arestyrurj-232	92	5	specialized	specialized	ADJ
arestyrurj-232	92	6	audio	audio	ADJ
arestyrurj-232	92	7	analysis	analysis	NOUN
arestyrurj-232	92	8	and	and	CCONJ
arestyrurj-232	92	9	time	time	NOUN
arestyrurj-232	92	10	series	series	NOUN
arestyrurj-232	92	11	tools	tool	NOUN
arestyrurj-232	92	12	which	which	PRON
arestyrurj-232	92	13	could	could	AUX
arestyrurj-232	92	14	be	be	AUX
arestyrurj-232	92	15	found	find	VERB
arestyrurj-232	92	16	in	in	ADP
arestyrurj-232	92	17	the	the	DET
arestyrurj-232	92	18	statsmodels	statsmodel	NOUN
arestyrurj-232	92	19	,	,	PUNCT
arestyrurj-232	92	20	tensorflow	tensorflow	NOUN
arestyrurj-232	92	21	-	-	PUNCT
arestyrurj-232	92	22	io	io	NOUN
arestyrurj-232	92	23	,	,	PUNCT
arestyrurj-232	92	24	and	and	CCONJ
arestyrurj-232	92	25	librosa	librosa	PROPN
arestyrurj-232	92	26	python	python	PROPN
arestyrurj-232	92	27	packages∎	packages∎	ADV
arestyrurj-232	92	28	7	7	NUM
arestyrurj-232	92	29	acknowledgments	acknowledgment	NOUN
arestyrurj-232	92	30	i	i	PRON
arestyrurj-232	92	31	would	would	AUX
arestyrurj-232	92	32	like	like	VERB
arestyrurj-232	92	33	to	to	PART
arestyrurj-232	92	34	express	express	VERB
arestyrurj-232	92	35	my	my	PRON
arestyrurj-232	92	36	appreciation	appreciation	NOUN
arestyrurj-232	92	37	to	to	ADP
arestyrurj-232	92	38	the	the	DET
arestyrurj-232	92	39	following	follow	VERB
arestyrurj-232	92	40	people	people	NOUN
arestyrurj-232	92	41	who	who	PRON
arestyrurj-232	92	42	contributed	contribute	VERB
arestyrurj-232	92	43	a	a	DET
arestyrurj-232	92	44	great	great	ADJ
arestyrurj-232	92	45	deal	deal	NOUN
arestyrurj-232	92	46	to	to	ADP
arestyrurj-232	92	47	this	this	DET
arestyrurj-232	92	48	project	project	NOUN
arestyrurj-232	92	49	:	:	PUNCT
arestyrurj-232	92	50	professor	professor	PROPN
arestyrurj-232	92	51	endre	endre	PROPN
arestyrurj-232	92	52	boros	boros	PROPN
arestyrurj-232	92	53	,	,	PUNCT
arestyrurj-232	92	54	for	for	ADP
arestyrurj-232	92	55	supervising	supervise	VERB
arestyrurj-232	92	56	this	this	DET
arestyrurj-232	92	57	project	project	NOUN
arestyrurj-232	92	58	,	,	PUNCT
arestyrurj-232	92	59	advocating	advocate	VERB
arestyrurj-232	92	60	on	on	ADP
arestyrurj-232	92	61	my	my	PRON
arestyrurj-232	92	62	behalf	behalf	NOUN
arestyrurj-232	92	63	on	on	ADP
arestyrurj-232	92	64	a	a	DET
arestyrurj-232	92	65	number	number	NOUN
arestyrurj-232	92	66	of	of	ADP
arestyrurj-232	92	67	occasions	occasion	NOUN
arestyrurj-232	92	68	,	,	PUNCT
arestyrurj-232	92	69	and	and	CCONJ
arestyrurj-232	92	70	going	go	VERB
arestyrurj-232	92	71	above	above	ADV
arestyrurj-232	92	72	and	and	CCONJ
arestyrurj-232	92	73	beyond	beyond	ADP
arestyrurj-232	92	74	to	to	PART
arestyrurj-232	92	75	give	give	VERB
arestyrurj-232	92	76	me	i	PRON
arestyrurj-232	92	77	the	the	DET
arestyrurj-232	92	78	best	good	ADJ
arestyrurj-232	92	79	possible	possible	ADJ
arestyrurj-232	92	80	college	college	NOUN
arestyrurj-232	92	81	experience	experience	NOUN
arestyrurj-232	92	82	.	.	PUNCT
arestyrurj-232	93	1	fall	fall	VERB
arestyrurj-232	93	2	out	out	ADP
arestyrurj-232	93	3	boy	boy	NOUN
arestyrurj-232	93	4	,	,	PUNCT
arestyrurj-232	93	5	for	for	ADP
arestyrurj-232	93	6	their	their	PRON
arestyrurj-232	93	7	wonderful	wonderful	ADJ
arestyrurj-232	93	8	music	music	NOUN
arestyrurj-232	93	9	and	and	CCONJ
arestyrurj-232	93	10	for	for	ADP
arestyrurj-232	93	11	appreciating	appreciate	VERB
arestyrurj-232	93	12	this	this	DET
arestyrurj-232	93	13	project	project	NOUN
arestyrurj-232	93	14	.	.	PUNCT
arestyrurj-232	94	1	joey	joey	PROPN
arestyrurj-232	94	2	yudelson	yudelson	PROPN
arestyrurj-232	94	3	,	,	PUNCT
arestyrurj-232	94	4	for	for	ADP
arestyrurj-232	94	5	providing	provide	VERB
arestyrurj-232	94	6	strategic	strategic	ADJ
arestyrurj-232	94	7	recommendations	recommendation	NOUN
arestyrurj-232	94	8	,	,	PUNCT
arestyrurj-232	94	9	deep	deep	ADJ
arestyrurj-232	94	10	python	python	NOUN
arestyrurj-232	94	11	expertise	expertise	NOUN
arestyrurj-232	94	12	,	,	PUNCT
arestyrurj-232	94	13	and	and	CCONJ
arestyrurj-232	94	14	impeccable	impeccable	ADJ
arestyrurj-232	94	15	technical	technical	ADJ
arestyrurj-232	94	16	editing	editing	NOUN
arestyrurj-232	94	17	.	.	PUNCT
arestyrurj-232	95	1	nick	nick	PROPN
arestyrurj-232	95	2	singh	singh	PROPN
arestyrurj-232	95	3	,	,	PUNCT
arestyrurj-232	95	4	my	my	PRON
arestyrurj-232	95	5	mentor	mentor	NOUN
arestyrurj-232	95	6	,	,	PUNCT
arestyrurj-232	95	7	for	for	ADP
arestyrurj-232	95	8	encouraging	encourage	VERB
arestyrurj-232	95	9	me	i	PRON
arestyrurj-232	95	10	to	to	PART
arestyrurj-232	95	11	work	work	VERB
arestyrurj-232	95	12	on	on	ADP
arestyrurj-232	95	13	data	datum	NOUN
arestyrurj-232	95	14	science	science	NOUN
arestyrurj-232	95	15	portfolio	portfolio	NOUN
arestyrurj-232	95	16	projects	project	NOUN
arestyrurj-232	95	17	and	and	CCONJ
arestyrurj-232	95	18	teaching	teach	VERB
arestyrurj-232	95	19	me	i	PRON
arestyrurj-232	95	20	how	how	SCONJ
arestyrurj-232	95	21	to	to	PART
arestyrurj-232	95	22	best	good	ADJ
arestyrurj-232	95	23	leverage	leverage	VERB
arestyrurj-232	95	24	my	my	PRON
arestyrurj-232	95	25	results	result	NOUN
arestyrurj-232	95	26	.	.	PUNCT
arestyrurj-232	96	1	siddhant	siddhant	PROPN
arestyrurj-232	96	2	kochrekar	kochrekar	PROPN
arestyrurj-232	96	3	,	,	PUNCT
arestyrurj-232	96	4	for	for	ADP
arestyrurj-232	96	5	providing	provide	VERB
arestyrurj-232	96	6	advice	advice	NOUN
arestyrurj-232	96	7	concerning	concern	VERB
arestyrurj-232	96	8	the	the	DET
arestyrurj-232	96	9	feature	feature	NOUN
arestyrurj-232	96	10	engineering	engineering	NOUN
arestyrurj-232	96	11	process	process	NOUN
arestyrurj-232	96	12	,	,	PUNCT
arestyrurj-232	96	13	model	model	NOUN
arestyrurj-232	96	14	tuning	tuning	NOUN
arestyrurj-232	96	15	,	,	PUNCT
arestyrurj-232	96	16	and	and	CCONJ
arestyrurj-232	96	17	out	out	ADV
arestyrurj-232	96	18	-	-	PUNCT
arestyrurj-232	96	19	of	of	ADP
arestyrurj-232	96	20	-	-	PUNCT
arestyrurj-232	96	21	the	the	DET
arestyrurj-232	96	22	-	-	PUNCT
arestyrurj-232	96	23	box	box	NOUN
arestyrurj-232	96	24	ideas	idea	NOUN
arestyrurj-232	96	25	to	to	PART
arestyrurj-232	96	26	improve	improve	VERB
arestyrurj-232	96	27	this	this	DET
arestyrurj-232	96	28	project	project	NOUN
arestyrurj-232	96	29	.	.	PUNCT
arestyrurj-232	97	1	https://falloutboy.com/	https://falloutboy.com/	NOUN
arestyrurj-232	97	2	https://github.com/jyudelson1	https://github.com/jyudelson1	PROPN
arestyrurj-232	97	3	https://www.linkedin.com/in/nick-singh-tech/	https://www.linkedin.com/in/nick-singh-tech/	VERB
arestyrurj-232	97	4	https://github.com/siddhantkochrekar	https://github.com/siddhantkochrekar	PROPN
arestyrurj-232	97	5	aresty	aresty	PROPN
arestyrurj-232	97	6	rutgers	rutgers	PROPN
arestyrurj-232	97	7	undergraduate	undergraduate	PROPN
arestyrurj-232	97	8	research	research	PROPN
arestyrurj-232	97	9	journal	journal	PROPN
arestyrurj-232	97	10	,	,	PUNCT
arestyrurj-232	97	11	volume	volume	NOUN
arestyrurj-232	97	12	i	i	PRON
arestyrurj-232	97	13	,	,	PUNCT
arestyrurj-232	97	14	issue	issue	VERB
arestyrurj-232	97	15	v	v	ADP
arestyrurj-232	97	16	4	4	NUM
arestyrurj-232	97	17	vastava	vastava	NOUN
arestyrurj-232	97	18	,	,	PUNCT
arestyrurj-232	97	19	for	for	ADP
arestyrurj-232	97	20	inspiring	inspire	VERB
arestyrurj-232	97	21	this	this	DET
arestyrurj-232	97	22	project	project	NOUN
arestyrurj-232	97	23	with	with	ADP
arestyrurj-232	97	24	her	her	PRON
arestyrurj-232	97	25	content	content	NOUN
arestyrurj-232	97	26	and	and	CCONJ
arestyrurj-232	97	27	her	her	PRON
arestyrurj-232	97	28	code	code	NOUN
arestyrurj-232	97	29	.	.	PUNCT
arestyrurj-232	98	1	zack	zack	PROPN
arestyrurj-232	98	2	ovits	ovit	NOUN
arestyrurj-232	98	3	,	,	PUNCT
arestyrurj-232	98	4	for	for	ADP
arestyrurj-232	98	5	helping	help	VERB
arestyrurj-232	98	6	me	i	PRON
arestyrurj-232	98	7	build	build	VERB
arestyrurj-232	98	8	the	the	DET
arestyrurj-232	98	9	project	project	NOUN
arestyrurj-232	98	10	directory	directory	NOUN
arestyrurj-232	98	11	,	,	PUNCT
arestyrurj-232	98	12	and	and	CCONJ
arestyrurj-232	98	13	for	for	ADP
arestyrurj-232	98	14	providing	provide	VERB
arestyrurj-232	98	15	consistent	consistent	ADJ
arestyrurj-232	98	16	advice	advice	NOUN
arestyrurj-232	98	17	on	on	ADP
arestyrurj-232	98	18	best	good	ADJ
arestyrurj-232	98	19	practices	practice	NOUN
arestyrurj-232	98	20	throughout	throughout	ADP
arestyrurj-232	98	21	the	the	DET
arestyrurj-232	98	22	duration	duration	NOUN
arestyrurj-232	98	23	of	of	ADP
arestyrurj-232	98	24	this	this	DET
arestyrurj-232	98	25	project	project	NOUN
arestyrurj-232	98	26	.	.	PUNCT
arestyrurj-232	99	1	8	8	NUM
arestyrurj-232	99	2	references	reference	NOUN
arestyrurj-232	99	3	[	[	X
arestyrurj-232	99	4	1	1	NUM
arestyrurj-232	99	5	]	]	X
arestyrurj-232	99	6	brownlee	brownlee	PROPN
arestyrurj-232	99	7	,	,	PUNCT
arestyrurj-232	99	8	j.	j.	PROPN
arestyrurj-232	99	9	(	(	PUNCT
arestyrurj-232	99	10	2020	2020	NUM
arestyrurj-232	99	11	,	,	PUNCT
arestyrurj-232	99	12	september	september	PROPN
arestyrurj-232	99	13	14	14	NUM
arestyrurj-232	99	14	)	)	PUNCT
arestyrurj-232	99	15	.	.	PUNCT
arestyrurj-232	100	1	hyperparameter	hyperparameter	NOUN
arestyrurj-232	100	2	optimization	optimization	NOUN
arestyrurj-232	100	3	with	with	ADP
arestyrurj-232	100	4	random	random	ADJ
arestyrurj-232	100	5	search	search	NOUN
arestyrurj-232	100	6	and	and	CCONJ
arestyrurj-232	100	7	grid	grid	NOUN
arestyrurj-232	100	8	search	search	NOUN
arestyrurj-232	100	9	.	.	PUNCT
arestyrurj-232	101	1	machine	machine	NOUN
arestyrurj-232	101	2	learning	learn	VERB
arestyrurj-232	101	3	mastery	mastery	PROPN
arestyrurj-232	101	4	.	.	PUNCT
arestyrurj-232	102	1	retrieved	retrieve	VERB
arestyrurj-232	102	2	november	november	PROPN
arestyrurj-232	102	3	11	11	NUM
arestyrurj-232	102	4	,	,	PUNCT
arestyrurj-232	102	5	1111	1111	NUM
arestyrurj-232	102	6	,	,	PUNCT
arestyrurj-232	102	7	from	from	ADP
arestyrurj-232	102	8	machinelearningmastery.com/hyperparameter-optimization-with-random-search-and-grid-search/	machinelearningmastery.com/hyperparameter-optimization-with-random-search-and-grid-search/	PROPN
arestyrurj-232	103	1	[	[	X
arestyrurj-232	103	2	2	2	NUM
arestyrurj-232	103	3	]	]	X
arestyrurj-232	103	4	[	[	X
arestyrurj-232	103	5	coding	code	VERB
arestyrurj-232	103	6	lane	lane	NOUN
arestyrurj-232	103	7	]	]	X
arestyrurj-232	103	8	.	.	PUNCT
arestyrurj-232	104	1	(	(	PUNCT
arestyrurj-232	104	2	2021	2021	NUM
arestyrurj-232	104	3	,	,	PUNCT
arestyrurj-232	104	4	february	february	PROPN
arestyrurj-232	104	5	4	4	NUM
arestyrurj-232	104	6	)	)	PUNCT
arestyrurj-232	104	7	.	.	PUNCT
arestyrurj-232	105	1	logistic	logistic	ADJ
arestyrurj-232	105	2	regression	regression	NOUN
arestyrurj-232	105	3	in	in	ADP
arestyrurj-232	105	4	python	python	NOUN
arestyrurj-232	105	5	from	from	ADP
arestyrurj-232	105	6	scratch	scratch	NOUN
arestyrurj-232	105	7	|	|	ADV
arestyrurj-232	105	8	simply	simply	ADV
arestyrurj-232	105	9	explained	explain	VERB
arestyrurj-232	105	10	[	[	PUNCT
arestyrurj-232	105	11	video	video	NOUN
arestyrurj-232	105	12	]	]	X
arestyrurj-232	105	13	.	.	PUNCT
arestyrurj-232	106	1	youtube	youtube	PROPN
arestyrurj-232	106	2	.	.	PUNCT
arestyrurj-232	106	3	youtube.com/watch?v=nznp05aybm8	youtube.com/watch?v=nznp05aybm8	PROPN
arestyrurj-232	107	1	[	[	X
arestyrurj-232	107	2	3	3	NUM
arestyrurj-232	107	3	]	]	X
arestyrurj-232	107	4	dola	dola	PROPN
arestyrurj-232	107	5	,	,	PUNCT
arestyrurj-232	107	6	p.	p.	NOUN
arestyrurj-232	107	7	(	(	PUNCT
arestyrurj-232	107	8	2020	2020	NUM
arestyrurj-232	107	9	,	,	PUNCT
arestyrurj-232	107	10	september	september	PROPN
arestyrurj-232	107	11	9	9	NUM
arestyrurj-232	107	12	)	)	PUNCT
arestyrurj-232	107	13	.	.	PUNCT
arestyrurj-232	108	1	exploratory	exploratory	ADJ
arestyrurj-232	108	2	analysis	analysis	NOUN
arestyrurj-232	108	3	of	of	ADP
arestyrurj-232	108	4	spotify	spotify	NOUN
arestyrurj-232	108	5	tracks	track	NOUN
arestyrurj-232	108	6	:	:	PUNCT
arestyrurj-232	108	7	how	how	SCONJ
arestyrurj-232	108	8	has	have	AUX
arestyrurj-232	108	9	music	music	NOUN
arestyrurj-232	108	10	changed	change	VERB
arestyrurj-232	108	11	over	over	ADP
arestyrurj-232	108	12	the	the	DET
arestyrurj-232	108	13	past	past	ADJ
arestyrurj-232	108	14	100	100	NUM
arestyrurj-232	108	15	years	year	NOUN
arestyrurj-232	108	16	?	?	PUNCT
arestyrurj-232	109	1	rpubs	rpub	NOUN
arestyrurj-232	109	2	.	.	PUNCT
arestyrurj-232	110	1	retrieved	retrieve	VERB
arestyrurj-232	110	2	january	january	PROPN
arestyrurj-232	110	3	1	1	NUM
arestyrurj-232	110	4	,	,	PUNCT
arestyrurj-232	110	5	1111	1111	NUM
arestyrurj-232	110	6	,	,	PUNCT
arestyrurj-232	110	7	from	from	ADP
arestyrurj-232	110	8	rpubs.com/peterdola/spotifytracks	rpubs.com/peterdola/spotifytrack	NOUN
arestyrurj-232	110	9	[	[	X
arestyrurj-232	110	10	4	4	X
arestyrurj-232	110	11	]	]	X
arestyrurj-232	110	12	[	[	X
arestyrurj-232	110	13	elbert	elbert	X
arestyrurj-232	110	14	]	]	X
arestyrurj-232	110	15	.	.	PUNCT
arestyrurj-232	111	1	(	(	PUNCT
arestyrurj-232	111	2	2021	2021	NUM
arestyrurj-232	111	3	,	,	PUNCT
arestyrurj-232	111	4	january	january	PROPN
arestyrurj-232	111	5	5	5	NUM
arestyrurj-232	111	6	)	)	PUNCT
arestyrurj-232	111	7	.	.	PUNCT
arestyrurj-232	112	1	how	how	SCONJ
arestyrurj-232	112	2	to	to	PART
arestyrurj-232	112	3	automate	automate	VERB
arestyrurj-232	112	4	with	with	ADP
arestyrurj-232	112	5	python	python	NOUN
arestyrurj-232	112	6	,	,	PUNCT
arestyrurj-232	112	7	spotipy	spotipy	ADJ
arestyrurj-232	112	8	,	,	PUNCT
arestyrurj-232	112	9	and	and	CCONJ
arestyrurj-232	112	10	lyricsgenius	lyricsgenius	NOUN
arestyrurj-232	112	11	[	[	X
arestyrurj-232	112	12	video	video	NOUN
arestyrurj-232	112	13	]	]	X
arestyrurj-232	112	14	.	.	PUNCT
arestyrurj-232	113	1	youtube	youtube	NOUN
arestyrurj-232	113	2	.	.	PUNCT
arestyrurj-232	114	1	youtube.com/watch?v=cu8yh2rhn6a	youtube.com/watch?v=cu8yh2rhn6a	PUNCT
arestyrurj-232	115	1	[	[	X
arestyrurj-232	115	2	5	5	NUM
arestyrurj-232	115	3	]	]	PUNCT
arestyrurj-232	115	4	fob	fob	NOUN
arestyrurj-232	115	5	song	song	NOUN
arestyrurj-232	115	6	data	data	PROPN
arestyrurj-232	115	7	.	.	PUNCT
arestyrurj-232	116	1	(	(	PUNCT
arestyrurj-232	116	2	n.d	n.d	PROPN
arestyrurj-232	116	3	.	.	PROPN
arestyrurj-232	116	4	)	)	PUNCT
arestyrurj-232	116	5	.	.	PUNCT
arestyrurj-232	117	1	spotify	spotify	NOUN
arestyrurj-232	117	2	.	.	PUNCT
arestyrurj-232	118	1	open.spotify.com/playlist/0ubknc9ctdvxlgbf5jicvq	open.spotify.com/playlist/0ubknc9ctdvxlgbf5jicvq	PROPN
arestyrurj-232	118	2	?	?	PUNCT
arestyrurj-232	119	1	si	si	NOUN
arestyrurj-232	119	2	=	=	NOUN
arestyrurj-232	119	3	d1a259083136490a&nd=1	d1a259083136490a&nd=1	NOUN
arestyrurj-232	119	4	[	[	X
arestyrurj-232	119	5	6	6	NUM
arestyrurj-232	119	6	]	]	SYM
arestyrurj-232	119	7	ho1yshif	ho1yshif	PROPN
arestyrurj-232	119	8	.	.	PROPN
arestyrurj-232	119	9	(	(	PUNCT
arestyrurj-232	119	10	n.d	n.d	PROPN
arestyrurj-232	119	11	.	.	PROPN
arestyrurj-232	119	12	)	)	PUNCT
arestyrurj-232	119	13	.	.	PUNCT
arestyrurj-232	120	1	github	github	PROPN
arestyrurj-232	120	2	ho1yshif	ho1yshif	PROPN
arestyrurj-232	120	3	/	/	SYM
arestyrurj-232	120	4	fob_lr_public	fob_lr_public	ADJ
arestyrurj-232	120	5	:	:	PUNCT
arestyrurj-232	120	6	independent	independent	ADJ
arestyrurj-232	120	7	study	study	NOUN
arestyrurj-232	120	8	project	project	NOUN
arestyrurj-232	120	9	:	:	PUNCT
arestyrurj-232	120	10	classification	classification	NOUN
arestyrurj-232	120	11	of	of	ADP
arestyrurj-232	120	12	fall	fall	NOUN
arestyrurj-232	120	13	out	out	ADP
arestyrurj-232	120	14	boy	boy	NOUN
arestyrurj-232	120	15	eras	era	NOUN
arestyrurj-232	120	16	.	.	PUNCT
arestyrurj-232	121	1	github	github	PROPN
arestyrurj-232	121	2	.	.	PUNCT
arestyrurj-232	122	1	github.com/ho1yshif/fob_lr_public	github.com/ho1yshif/fob_lr_public	PROPN
arestyrurj-232	123	1	[	[	X
arestyrurj-232	123	2	7	7	NUM
arestyrurj-232	123	3	]	]	PUNCT
arestyrurj-232	123	4	klosterman	klosterman	NOUN
arestyrurj-232	123	5	,	,	PUNCT
arestyrurj-232	123	6	s.	s.	PROPN
arestyrurj-232	123	7	(	(	PUNCT
arestyrurj-232	123	8	2019	2019	NUM
arestyrurj-232	123	9	)	)	PUNCT
arestyrurj-232	123	10	.	.	PUNCT
arestyrurj-232	124	1	data	datum	NOUN
arestyrurj-232	124	2	science	science	NOUN
arestyrurj-232	124	3	projects	project	NOUN
arestyrurj-232	124	4	with	with	ADP
arestyrurj-232	124	5	python	python	PROPN
arestyrurj-232	124	6	.	.	PUNCT
arestyrurj-232	124	7	packt	packt	PROPN
arestyrurj-232	124	8	.	.	PUNCT
arestyrurj-232	125	1	[	[	X
arestyrurj-232	125	2	8	8	NUM
arestyrurj-232	125	3	]	]	X
arestyrurj-232	125	4	loeber	loeber	ADJ
arestyrurj-232	125	5	p.	p.	NOUN
arestyrurj-232	125	6	(	(	PUNCT
arestyrurj-232	125	7	2019	2019	NUM
arestyrurj-232	125	8	,	,	PUNCT
arestyrurj-232	125	9	september	september	PROPN
arestyrurj-232	125	10	15	15	NUM
arestyrurj-232	125	11	)	)	PUNCT
arestyrurj-232	125	12	.	.	PUNCT
arestyrurj-232	126	1	logistic	logistic	ADJ
arestyrurj-232	126	2	regression	regression	NOUN
arestyrurj-232	126	3	in	in	ADP
arestyrurj-232	126	4	python	python	NOUN
arestyrurj-232	126	5	machine	machine	NOUN
arestyrurj-232	126	6	learning	learn	VERB
arestyrurj-232	126	7	from	from	ADP
arestyrurj-232	126	8	scratch	scratch	NOUN
arestyrurj-232	126	9	03	03	NUM
arestyrurj-232	126	10	python	python	PROPN
arestyrurj-232	126	11	tutorial	tutorial	NOUN
arestyrurj-232	127	1	[	[	X
arestyrurj-232	127	2	video	video	NOUN
arestyrurj-232	127	3	]	]	X
arestyrurj-232	127	4	.	.	PUNCT
arestyrurj-232	128	1	youtube	youtube	NOUN
arestyrurj-232	128	2	.	.	PUNCT
arestyrurj-232	129	1	youtube.com/watch?v=jdu3azh3wkg	youtube.com/watch?v=jdu3azh3wkg	PRON
arestyrurj-232	130	1	[	[	X
arestyrurj-232	130	2	9	9	NUM
arestyrurj-232	130	3	]	]	SYM
arestyrurj-232	130	4	loeber	loeber	ADJ
arestyrurj-232	130	5	p.	p.	NOUN
arestyrurj-232	130	6	(	(	PUNCT
arestyrurj-232	130	7	2019	2019	NUM
arestyrurj-232	130	8	,	,	PUNCT
arestyrurj-232	130	9	december	december	PROPN
arestyrurj-232	130	10	30	30	NUM
arestyrurj-232	130	11	)	)	PUNCT
arestyrurj-232	130	12	.	.	PUNCT
arestyrurj-232	131	1	pytorch	pytorch	NOUN
arestyrurj-232	131	2	tutorial	tutorial	NOUN
arestyrurj-232	131	3	08	08	NUM
arestyrurj-232	131	4	logistic	logistic	ADJ
arestyrurj-232	131	5	regression	regression	NOUN
arestyrurj-232	131	6	[	[	X
arestyrurj-232	131	7	video	video	NOUN
arestyrurj-232	131	8	]	]	X
arestyrurj-232	131	9	.	.	PUNCT
arestyrurj-232	132	1	youtube	youtube	NOUN
arestyrurj-232	132	2	.	.	PUNCT
arestyrurj-232	133	1	youtube.com/watch?v=ogpqxikr4ao	youtube.com/watch?v=ogpqxikr4ao	PROPN
arestyrurj-232	134	1	[	[	X
arestyrurj-232	134	2	10	10	NUM
arestyrurj-232	134	3	]	]	PUNCT
arestyrurj-232	134	4	parveez	parveez	PROPN
arestyrurj-232	134	5	,	,	PUNCT
arestyrurj-232	134	6	s.	s.	PROPN
arestyrurj-232	134	7	,	,	PUNCT
arestyrurj-232	134	8	&	&	CCONJ
arestyrurj-232	134	9	iriondo	iriondo	PROPN
arestyrurj-232	134	10	,	,	PUNCT
arestyrurj-232	134	11	r.	r.	PROPN
arestyrurj-232	134	12	(	(	PUNCT
arestyrurj-232	134	13	2020	2020	NUM
arestyrurj-232	134	14	,	,	PUNCT
arestyrurj-232	134	15	december	december	PROPN
arestyrurj-232	134	16	28	28	NUM
arestyrurj-232	134	17	)	)	PUNCT
arestyrurj-232	134	18	.	.	PUNCT
arestyrurj-232	135	1	gradient	gradient	ADJ
arestyrurj-232	135	2	descent	descent	NOUN
arestyrurj-232	135	3	for	for	ADP
arestyrurj-232	135	4	machine	machine	NOUN
arestyrurj-232	135	5	learning	learning	NOUN
arestyrurj-232	135	6	(	(	PUNCT
arestyrurj-232	135	7	ml	ml	NOUN
arestyrurj-232	135	8	)	)	PUNCT
arestyrurj-232	135	9	101	101	NUM
arestyrurj-232	135	10	with	with	ADP
arestyrurj-232	135	11	python	python	PROPN
arestyrurj-232	135	12	tutorial	tutorial	NOUN
arestyrurj-232	135	13	.	.	PUNCT
arestyrurj-232	136	1	towards	towards	AUX
arestyrurj-232	136	2	ai	ai	PROPN
arestyrurj-232	136	3	.	.	PROPN
arestyrurj-232	136	4	retrieved	retrieve	VERB
arestyrurj-232	136	5	november	november	PROPN
arestyrurj-232	136	6	11	11	NUM
arestyrurj-232	136	7	,	,	PUNCT
arestyrurj-232	136	8	1111	1111	NUM
arestyrurj-232	136	9	,	,	PUNCT
arestyrurj-232	136	10	from	from	ADP
arestyrurj-232	136	11	pub.towardsai.net/gradient-descent-algorithm-formachine-learning-python-tutorial-ml-9ded189ec556	pub.towardsai.net/gradient-descent-algorithm-formachine-learning-python-tutorial-ml-9ded189ec556	PROPN
arestyrurj-232	136	12	[	[	X
arestyrurj-232	136	13	11	11	NUM
arestyrurj-232	136	14	]	]	X
arestyrurj-232	136	15	pedregosa	pedregosa	PROPN
arestyrurj-232	136	16	et	et	PROPN
arestyrurj-232	136	17	al	al	PROPN
arestyrurj-232	136	18	.	.	PUNCT
arestyrurj-232	137	1	(	(	PUNCT
arestyrurj-232	137	2	2011	2011	NUM
arestyrurj-232	137	3	)	)	PUNCT
arestyrurj-232	137	4	.	.	PUNCT
arestyrurj-232	138	1	scikit	scikit	NOUN
arestyrurj-232	138	2	-	-	PUNCT
arestyrurj-232	138	3	learn	learn	VERB
arestyrurj-232	138	4	:	:	PUNCT
arestyrurj-232	138	5	machine	machine	NOUN
arestyrurj-232	138	6	learning	learning	NOUN
arestyrurj-232	138	7	in	in	ADP
arestyrurj-232	138	8	python	python	NOUN
arestyrurj-232	139	1	[	[	X
arestyrurj-232	139	2	12	12	NUM
arestyrurj-232	139	3	]	]	X
arestyrurj-232	139	4	scikit	scikit	NOUN
arestyrurj-232	139	5	-	-	PUNCT
arestyrurj-232	139	6	learn	learn	VERB
arestyrurj-232	139	7	developers	developer	NOUN
arestyrurj-232	139	8	(	(	PUNCT
arestyrurj-232	139	9	2021	2021	NUM
arestyrurj-232	139	10	)	)	PUNCT
arestyrurj-232	139	11	.	.	PUNCT
arestyrurj-232	140	1	1.1.11	1.1.11	X
arestyrurj-232	140	2	.	.	PUNCT
arestyrurj-232	140	3	logistic	logistic	ADJ
arestyrurj-232	140	4	regression	regression	NOUN
arestyrurj-232	140	5	.	.	PUNCT
arestyrurj-232	141	1	scikit	scikit	NOUN
arestyrurj-232	141	2	-	-	PUNCT
arestyrurj-232	141	3	learn	learn	VERB
arestyrurj-232	141	4	.	.	PUNCT
arestyrurj-232	141	5	scikit-learn.org/stable/modules/generated/sklearn.linear_model.logisticregression.html	scikit-learn.org/stable/modules/generated/sklearn.linear_model.logisticregression.html	PUNCT
arestyrurj-232	142	1	[	[	X
arestyrurj-232	142	2	13	13	NUM
arestyrurj-232	142	3	]	]	SYM
arestyrurj-232	142	4	scikit	scikit	NOUN
arestyrurj-232	142	5	-	-	PUNCT
arestyrurj-232	142	6	learn	learn	VERB
arestyrurj-232	142	7	developers	developer	NOUN
arestyrurj-232	142	8	(	(	PUNCT
arestyrurj-232	142	9	2021	2021	NUM
arestyrurj-232	142	10	)	)	PUNCT
arestyrurj-232	142	11	.	.	PUNCT
arestyrurj-232	143	1	1.1.2	1.1.2	X
arestyrurj-232	143	2	.	.	PUNCT
arestyrurj-232	143	3	randomforestclassifier	randomforestclassifier	NOUN
arestyrurj-232	143	4	.	.	PUNCT
arestyrurj-232	144	1	scikit	scikit	NOUN
arestyrurj-232	144	2	-	-	PUNCT
arestyrurj-232	144	3	learn	learn	VERB
arestyrurj-232	144	4	.	.	PUNCT
arestyrurj-232	145	1	scikit-learn.org/stable/modules/generated/sklearn.ensemble.randomforestclassifier.html	scikit-learn.org/stable/modules/generated/sklearn.ensemble.randomforestclassifier.html	X
arestyrurj-232	146	1	[	[	X
arestyrurj-232	146	2	14	14	NUM
arestyrurj-232	146	3	]	]	X
arestyrurj-232	146	4	scikit	scikit	NOUN
arestyrurj-232	146	5	-	-	PUNCT
arestyrurj-232	146	6	learn	learn	VERB
arestyrurj-232	146	7	developers	developer	NOUN
arestyrurj-232	146	8	(	(	PUNCT
arestyrurj-232	146	9	2021	2021	NUM
arestyrurj-232	146	10	)	)	PUNCT
arestyrurj-232	146	11	.	.	PUNCT
arestyrurj-232	147	1	1.4	1.4	NUM
arestyrurj-232	147	2	.	.	PUNCT
arestyrurj-232	148	1	support	support	NOUN
arestyrurj-232	148	2	vector	vector	NOUN
arestyrurj-232	148	3	machines	machine	NOUN
arestyrurj-232	148	4	.	.	PUNCT
arestyrurj-232	149	1	scikit	scikit	NOUN
arestyrurj-232	149	2	-	-	PUNCT
arestyrurj-232	149	3	learn	learn	VERB
arestyrurj-232	149	4	.	.	PUNCT
arestyrurj-232	150	1	scikit-learn.org/stable/modules/svm.html	scikit-learn.org/stable/modules/svm.html	PUNCT
arestyrurj-232	150	2	[	[	X
arestyrurj-232	150	3	15	15	NUM
arestyrurj-232	150	4	]	]	X
arestyrurj-232	150	5	scikit	scikit	NOUN
arestyrurj-232	150	6	-	-	PUNCT
arestyrurj-232	150	7	learn	learn	VERB
arestyrurj-232	150	8	developers	developer	NOUN
arestyrurj-232	150	9	(	(	PUNCT
arestyrurj-232	150	10	2021	2021	NUM
arestyrurj-232	150	11	)	)	PUNCT
arestyrurj-232	150	12	.	.	PUNCT
arestyrurj-232	151	1	1.9	1.9	NUM
arestyrurj-232	151	2	.	.	PUNCT
arestyrurj-232	151	3	naive	naive	ADJ
arestyrurj-232	151	4	bayes	bayes	NOUN
arestyrurj-232	151	5	.	.	PUNCT
arestyrurj-232	152	1	scikit	scikit	NOUN
arestyrurj-232	152	2	-	-	PUNCT
arestyrurj-232	152	3	learn	learn	VERB
arestyrurj-232	152	4	.	.	PUNCT
arestyrurj-232	153	1	scikit-learn.org/stable/modules/naive_bayes.html	scikit-learn.org/stable/modules/naive_bayes.html	NOUN
arestyrurj-232	154	1	[	[	X
arestyrurj-232	154	2	16	16	NUM
arestyrurj-232	154	3	]	]	X
arestyrurj-232	154	4	statistics	statistic	NOUN
arestyrurj-232	154	5	solutions	solution	NOUN
arestyrurj-232	154	6	(	(	PUNCT
arestyrurj-232	154	7	2021	2021	NUM
arestyrurj-232	154	8	)	)	PUNCT
arestyrurj-232	154	9	.	.	PUNCT
arestyrurj-232	155	1	assumptions	assumption	NOUN
arestyrurj-232	155	2	of	of	ADP
arestyrurj-232	155	3	logistic	logistic	ADJ
arestyrurj-232	155	4	regression	regression	NOUN
arestyrurj-232	155	5	.	.	PUNCT
arestyrurj-232	156	1	statisticssolutions.com/free-resources/directory-ofstatistical-analyses/assumptions-of-logistic-regression/	statisticssolutions.com/free-resources/directory-ofstatistical-analyses/assumptions-of-logistic-regression/	PROPN
arestyrurj-232	157	1	[	[	X
arestyrurj-232	157	2	17	17	NUM
arestyrurj-232	157	3	]	]	PUNCT
arestyrurj-232	157	4	[	[	X
arestyrurj-232	157	5	statquest	statquest	NOUN
arestyrurj-232	157	6	with	with	ADP
arestyrurj-232	157	7	josh	josh	PROPN
arestyrurj-232	157	8	starmer	starmer	PROPN
arestyrurj-232	157	9	]	]	PUNCT
arestyrurj-232	157	10	.	.	PUNCT
arestyrurj-232	158	1	(	(	PUNCT
arestyrurj-232	158	2	2018	2018	NUM
arestyrurj-232	158	3	,	,	PUNCT
arestyrurj-232	158	4	june	june	PROPN
arestyrurj-232	158	5	4	4	NUM
arestyrurj-232	158	6	)	)	PUNCT
arestyrurj-232	158	7	.	.	PUNCT
arestyrurj-232	159	1	logistic	logistic	ADJ
arestyrurj-232	159	2	regression	regression	NOUN
arestyrurj-232	159	3	details	detail	NOUN
arestyrurj-232	159	4	pt1	pt1	PROPN
arestyrurj-232	159	5	:	:	PUNCT
arestyrurj-232	159	6	coefficients	coefficient	NOUN
arestyrurj-232	160	1	[	[	X
arestyrurj-232	160	2	video	video	NOUN
arestyrurj-232	160	3	]	]	X
arestyrurj-232	160	4	.	.	PUNCT
arestyrurj-232	161	1	youtube	youtube	NOUN
arestyrurj-232	161	2	.	.	PUNCT
arestyrurj-232	162	1	youtube.com/watch?v=vn5cnn2-hwe	youtube.com/watch?v=vn5cnn2-hwe	X
arestyrurj-232	163	1	[	[	X
arestyrurj-232	163	2	18	18	NUM
arestyrurj-232	163	3	]	]	PUNCT
arestyrurj-232	163	4	[	[	X
arestyrurj-232	163	5	statquest	statquest	NOUN
arestyrurj-232	163	6	with	with	ADP
arestyrurj-232	163	7	josh	josh	PROPN
arestyrurj-232	163	8	starmer	starmer	PROPN
arestyrurj-232	163	9	]	]	PUNCT
arestyrurj-232	163	10	.	.	PUNCT
arestyrurj-232	164	1	(	(	PUNCT
arestyrurj-232	164	2	2018	2018	NUM
arestyrurj-232	164	3	,	,	PUNCT
arestyrurj-232	164	4	june	june	PROPN
arestyrurj-232	164	5	11	11	NUM
arestyrurj-232	164	6	)	)	PUNCT
arestyrurj-232	164	7	.	.	PUNCT
arestyrurj-232	165	1	logistic	logistic	ADJ
arestyrurj-232	165	2	regression	regression	NOUN
arestyrurj-232	165	3	details	detail	NOUN
arestyrurj-232	165	4	pt	pt	INTJ
arestyrurj-232	165	5	2	2	NUM
arestyrurj-232	165	6	:	:	PUNCT
arestyrurj-232	165	7	maximum	maximum	ADJ
arestyrurj-232	165	8	likelihood	likelihood	NOUN
arestyrurj-232	166	1	[	[	X
arestyrurj-232	166	2	video	video	NOUN
arestyrurj-232	166	3	]	]	X
arestyrurj-232	166	4	.	.	PUNCT
arestyrurj-232	167	1	youtube	youtube	PROPN
arestyrurj-232	167	2	.	.	PUNCT
arestyrurj-232	168	1	youtube.com/watch?v=bfkanl1asg0	youtube.com/watch?v=bfkanl1asg0	PROPN
arestyrurj-232	169	1	[	[	X
arestyrurj-232	169	2	19	19	NUM
arestyrurj-232	169	3	]	]	X
arestyrurj-232	169	4	[	[	X
arestyrurj-232	169	5	statquest	statquest	NOUN
arestyrurj-232	169	6	with	with	ADP
arestyrurj-232	169	7	josh	josh	PROPN
arestyrurj-232	169	8	starmer	starmer	PROPN
arestyrurj-232	169	9	]	]	PUNCT
arestyrurj-232	169	10	.	.	PUNCT
arestyrurj-232	170	1	(	(	PUNCT
arestyrurj-232	170	2	2018	2018	NUM
arestyrurj-232	170	3	,	,	PUNCT
arestyrurj-232	170	4	june	june	PROPN
arestyrurj-232	170	5	18	18	NUM
arestyrurj-232	170	6	)	)	PUNCT
arestyrurj-232	170	7	.	.	PUNCT
arestyrurj-232	171	1	logistic	logistic	ADJ
arestyrurj-232	171	2	regression	regression	NOUN
arestyrurj-232	171	3	details	detail	NOUN
arestyrurj-232	171	4	pt	pt	INTJ
arestyrurj-232	171	5	3	3	NUM
arestyrurj-232	171	6	:	:	PUNCT
arestyrurj-232	171	7	r	r	NOUN
arestyrurj-232	171	8	-	-	PUNCT
arestyrurj-232	171	9	squared	square	VERB
arestyrurj-232	171	10	and	and	CCONJ
arestyrurj-232	171	11	p	p	NOUN
arestyrurj-232	171	12	-	-	PUNCT
arestyrurj-232	171	13	value	value	NOUN
arestyrurj-232	171	14	[	[	X
arestyrurj-232	171	15	video	video	NOUN
arestyrurj-232	171	16	]	]	X
arestyrurj-232	171	17	.	.	PUNCT
arestyrurj-232	172	1	youtube	youtube	NOUN
arestyrurj-232	172	2	.	.	PUNCT
arestyrurj-232	173	1	youtube.com/watch?v=xxfyro8quxa	youtube.com/watch?v=xxfyro8quxa	NOUN
arestyrurj-232	174	1	[	[	X
arestyrurj-232	174	2	20	20	NUM
arestyrurj-232	174	3	]	]	PUNCT
arestyrurj-232	174	4	[	[	X
arestyrurj-232	174	5	statquest	statquest	NOUN
arestyrurj-232	174	6	with	with	ADP
arestyrurj-232	174	7	josh	josh	PROPN
arestyrurj-232	174	8	starmer	starmer	PROPN
arestyrurj-232	174	9	]	]	PUNCT
arestyrurj-232	174	10	.	.	PUNCT
arestyrurj-232	175	1	(	(	PUNCT
arestyrurj-232	175	2	2018	2018	NUM
arestyrurj-232	175	3	,	,	PUNCT
arestyrurj-232	175	4	may	may	AUX
arestyrurj-232	175	5	7	7	NUM
arestyrurj-232	175	6	)	)	PUNCT
arestyrurj-232	175	7	.	.	PUNCT
arestyrurj-232	176	1	odds	odd	NOUN
arestyrurj-232	176	2	and	and	CCONJ
arestyrurj-232	176	3	log(odds	log(odd	NOUN
arestyrurj-232	176	4	)	)	PUNCT
arestyrurj-232	176	5	,	,	PUNCT
arestyrurj-232	176	6	clearly	clearly	ADV
arestyrurj-232	176	7	explained	explain	VERB
arestyrurj-232	176	8	!	!	PUNCT
arestyrurj-232	176	9	!	!	PUNCT
arestyrurj-232	176	10	!	!	PUNCT
arestyrurj-232	177	1	[	[	X
arestyrurj-232	177	2	video	video	NOUN
arestyrurj-232	177	3	]	]	X
arestyrurj-232	177	4	.	.	PUNCT
arestyrurj-232	178	1	youtube	youtube	NOUN
arestyrurj-232	178	2	.	.	PUNCT
arestyrurj-232	179	1	youtube.com/watch?v=arfxdskqf1y	youtube.com/watch?v=arfxdskqf1y	PRON
arestyrurj-232	180	1	[	[	X
arestyrurj-232	180	2	21	21	NUM
arestyrurj-232	180	3	]	]	PUNCT
arestyrurj-232	180	4	[	[	X
arestyrurj-232	180	5	statquest	statquest	NOUN
arestyrurj-232	180	6	with	with	ADP
arestyrurj-232	180	7	josh	josh	PROPN
arestyrurj-232	180	8	starmer	starmer	PROPN
arestyrurj-232	180	9	]	]	PUNCT
arestyrurj-232	180	10	.	.	PUNCT
arestyrurj-232	181	1	(	(	PUNCT
arestyrurj-232	181	2	2018	2018	NUM
arestyrurj-232	181	3	,	,	PUNCT
arestyrurj-232	181	4	march	march	PROPN
arestyrurj-232	181	5	5	5	NUM
arestyrurj-232	181	6	)	)	PUNCT
arestyrurj-232	181	7	.	.	PUNCT
arestyrurj-232	182	1	statquest	statquest	NOUN
arestyrurj-232	182	2	:	:	PUNCT
arestyrurj-232	183	1	logistic	logistic	ADJ
arestyrurj-232	183	2	regression	regression	NOUN
arestyrurj-232	183	3	[	[	X
arestyrurj-232	183	4	video	video	NOUN
arestyrurj-232	183	5	]	]	X
arestyrurj-232	183	6	.	.	PUNCT
arestyrurj-232	184	1	youtube	youtube	PROPN
arestyrurj-232	184	2	.	.	PUNCT
arestyrurj-232	184	3	youtube.com/watch?v=yiykr4sgzi8	youtube.com/watch?v=yiykr4sgzi8	PUNCT
arestyrurj-232	185	1	[	[	X
arestyrurj-232	185	2	22	22	NUM
arestyrurj-232	185	3	]	]	X
arestyrurj-232	186	1	[	[	X
arestyrurj-232	186	2	vastava	vastava	X
arestyrurj-232	186	3	]	]	X
arestyrurj-232	186	4	.	.	PUNCT
arestyrurj-232	187	1	(	(	PUNCT
arestyrurj-232	187	2	2020	2020	NUM
arestyrurj-232	187	3	,	,	PUNCT
arestyrurj-232	187	4	december	december	PROPN
arestyrurj-232	187	5	4	4	NUM
arestyrurj-232	187	6	)	)	PUNCT
arestyrurj-232	187	7	.	.	PUNCT
arestyrurj-232	188	1	i	i	PRON
arestyrurj-232	188	2	trained	train	VERB
arestyrurj-232	188	3	an	an	DET
arestyrurj-232	188	4	ai	ai	NOUN
arestyrurj-232	188	5	to	to	PART
arestyrurj-232	188	6	tell	tell	VERB
arestyrurj-232	188	7	me	i	PRON
arestyrurj-232	188	8	corpse	corpse	NOUN
arestyrurj-232	188	9	's	's	PART
arestyrurj-232	188	10	music	music	NOUN
arestyrurj-232	188	11	genre	genre	NOUN
arestyrurj-232	188	12	|	|	NOUN
arestyrurj-232	188	13	data	data	VERB
arestyrurj-232	188	14	science	science	NOUN
arestyrurj-232	188	15	[	[	X
arestyrurj-232	188	16	video	video	NOUN
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arestyrurj-232	191	5	,	,	PUNCT
arestyrurj-232	191	6	s.	s.	PROPN
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arestyrurj-232	191	9	,	,	PUNCT
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arestyrurj-232	191	11	25	25	NUM
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arestyrurj-232	191	15	genre	genre	NOUN
arestyrurj-232	191	16	classifier	classifier	NOUN
arestyrurj-232	192	1	[	[	X
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arestyrurj-232	193	1	github	github	PROPN
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arestyrurj-232	194	1	github.com/vastava/data-science-projects/blob/master/spotify-genre-classifier/get-spotify-data.ipynb	github.com/vastava/data-science-projects/blob/master/spotify-genre-classifier/get-spotify-data.ipynb	PROPN
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arestyrurj-232	195	7	,	,	PUNCT
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arestyrurj-232	198	11	https://github.com/vastava/data-science-projects/blob/master/spotify-genre-classifier/get-spotify-data.ipynb	https://github.com/vastava/data-science-projects/blob/master/spotify-genre-classifier/get-spotify-data.ipynb	PROPN
arestyrurj-232	198	12	https://www.boatbomber.com/	https://www.boatbomber.com/	PROPN
arestyrurj-232	198	13	https://machinelearningmastery.com/hyperparameter-optimization-with-random-search-and-grid-search/	https://machinelearningmastery.com/hyperparameter-optimization-with-random-search-and-grid-search/	PROPN
arestyrurj-232	198	14	https://machinelearningmastery.com/hyperparameter-optimization-with-random-search-and-grid-search/	https://machinelearningmastery.com/hyperparameter-optimization-with-random-search-and-grid-search/	VERB
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arestyrurj-232	198	17	https://www.youtube.com/watch?v=cu8yh2rhn6a	https://www.youtube.com/watch?v=cu8yh2rhn6a	X
arestyrurj-232	198	18	https://open.spotify.com/playlist/0ubknc9ctdvxlgbf5jicvq?si=d1a259083136490a&nd=1	https://open.spotify.com/playlist/0ubknc9ctdvxlgbf5jicvq?si=d1a259083136490a&nd=1	PUNCT
arestyrurj-232	198	19	https://open.spotify.com/playlist/0ubknc9ctdvxlgbf5jicvq?si=d1a259083136490a&nd=1	https://open.spotify.com/playlist/0ubknc9ctdvxlgbf5jicvq?si=d1a259083136490a&nd=1	X
arestyrurj-232	199	1	https://www.youtube.com/watch?v=jdu3azh3wkg	https://www.youtube.com/watch?v=jdu3azh3wkg	PROPN
arestyrurj-232	199	2	https://www.youtube.com/watch?v=ogpqxikr4ao	https://www.youtube.com/watch?v=ogpqxikr4ao	PROPN
arestyrurj-232	199	3	https://pub.towardsai.net/gradient-descent-algorithm-for-machine-learning-python-tutorial-ml-9ded189ec556	https://pub.towardsai.net/gradient-descent-algorithm-for-machine-learning-python-tutorial-ml-9ded189ec556	NOUN
arestyrurj-232	199	4	https://pub.towardsai.net/gradient-descent-algorithm-for-machine-learning-python-tutorial-ml-9ded189ec556	https://pub.towardsai.net/gradient-descent-algorithm-for-machine-learning-python-tutorial-ml-9ded189ec556	NOUN
arestyrurj-232	199	5	https://scikit-learn.org/stable/modules/generated/sklearn.linear_model.logisticregression.html	https://scikit-learn.org/stable/modules/generated/sklearn.linear_model.logisticregression.html	PART
arestyrurj-232	199	6	https://scikit-learn.org/stable/modules/generated/sklearn.linear_model.logisticregression.html	https://scikit-learn.org/stable/modules/generated/sklearn.linear_model.logisticregression.html	PROPN
arestyrurj-232	199	7	https://scikit-learn.org/stable/modules/generated/sklearn.ensemble.randomforestclassifier.html	https://scikit-learn.org/stable/modules/generated/sklearn.ensemble.randomforestclassifier.html	NOUN
arestyrurj-232	199	8	https://scikit-learn.org/stable/modules/generated/sklearn.ensemble.randomforestclassifier.html	https://scikit-learn.org/stable/modules/generated/sklearn.ensemble.randomforestclassifier.html	PROPN
arestyrurj-232	200	1	https://scikit-learn.org/stable/modules/naive_bayes.html	https://scikit-learn.org/stable/modules/naive_bayes.html	PROPN
arestyrurj-232	200	2	https://www.statisticssolutions.com/free-resources/directory-of-statistical-analyses/assumptions-of-logistic-regression/	https://www.statisticssolutions.com/free-resources/directory-of-statistical-analyses/assumptions-of-logistic-regression/	PROPN
arestyrurj-232	200	3	https://www.statisticssolutions.com/free-resources/directory-of-statistical-analyses/assumptions-of-logistic-regression/	https://www.statisticssolutions.com/free-resources/directory-of-statistical-analyses/assumptions-of-logistic-regression/	PROPN
arestyrurj-232	200	4	https://www.statisticssolutions.com/free-resources/directory-of-statistical-analyses/assumptions-of-logistic-regression/	https://www.statisticssolutions.com/free-resources/directory-of-statistical-analyses/assumptions-of-logistic-regression/	PROPN
arestyrurj-232	201	1	https://www.youtube.com/watch?v=vn5cnn2-hwe	https://www.youtube.com/watch?v=vn5cnn2-hwe	PROPN
arestyrurj-232	201	2	https://www.youtube.com/watch?v=bfkanl1asg0	https://www.youtube.com/watch?v=bfkanl1asg0	PROPN
arestyrurj-232	201	3	https://www.youtube.com/watch?v=xxfyro8quxa	https://www.youtube.com/watch?v=xxfyro8quxa	NOUN
arestyrurj-232	201	4	https://www.youtube.com/watch?v=arfxdskqf1y	https://www.youtube.com/watch?v=arfxdskqf1y	NOUN
arestyrurj-232	201	5	https://www.youtube.com/watch?v=yiykr4sgzi8	https://www.youtube.com/watch?v=yiykr4sgzi8	PROPN
arestyrurj-232	201	6	https://www.youtube.com/watch?v=vtu6jla70vy	https://www.youtube.com/watch?v=vtu6jla70vy	PROPN
arestyrurj-232	201	7	https://github.com/vastava/data-science-projects/blob/master/spotify-genre-classifier/get-spotify-data.ipynb	https://github.com/vastava/data-science-projects/blob/master/spotify-genre-classifier/get-spotify-data.ipynb	PROPN
arestyrurj-232	201	8	https://github.com/vastava/data-science-projects/blob/master/spotify-genre-classifier/get-spotify-data.ipynb	https://github.com/vastava/data-science-projects/blob/master/spotify-genre-classifier/get-spotify-data.ipynb	PROPN
arestyrurj-232	202	1	https://www.statology.org/assumptions-of-logistic-regression/	https://www.statology.org/assumptions-of-logistic-regression/	PROPN
arestyrurj-232	202	2	aresty	aresty	PROPN
arestyrurj-232	202	3	rutgers	rutgers	PROPN
arestyrurj-232	202	4	undergraduate	undergraduate	PROPN
arestyrurj-232	202	5	research	research	PROPN
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arestyrurj-232	202	7	,	,	PUNCT
arestyrurj-232	202	8	volume	volume	NOUN
arestyrurj-232	202	9	i	i	PRON
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arestyrurj-232	202	14	isaacs	isaacs	PROPN
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arestyrurj-232	202	34	,	,	PUNCT
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arestyrurj-232	204	7	through	through	ADP
arestyrurj-232	204	8	publications	publication	NOUN
arestyrurj-232	204	9	,	,	PUNCT
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arestyrurj-232	204	11	,	,	PUNCT
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arestyrurj-232	204	22	.	.	PUNCT
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arestyrurj-232	205	13	,	,	PUNCT
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arestyrurj-232	205	15	,	,	PUNCT
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arestyrurj-232	205	17	product	product	NOUN
arestyrurj-232	205	18	management	management	NOUN
arestyrurj-232	205	19	,	,	PUNCT
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arestyrurj-232	205	23	and	and	CCONJ
arestyrurj-232	205	24	adaptability	adaptability	NOUN
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arestyrurj-232	206	8	,	,	PUNCT
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arestyrurj-232	206	15	and	and	CCONJ
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