LIBSVM Data: Classification, Regression, and Multi-label

This page contains many classification, regression, and multi-label data sets used in our papers. Many are from UCI, Statlog, StatLib and other collections. We really thank their efforts. For most sets, we directly transform the file into LIBSVM format and linearly scale each attribute to [-1,1]. The testing data (if provided) is adjusted accordingly. Some training data are further separated to "training" (tr) and "validation" (val) sets. Details can be found in the description of each data set.

A summary of all data sets is in the following. If you have used LIBSVM with these sets, and find them useful, please cite our work as:
Chih-Chung Chang and Chih-Jen Lin, LIBSVM : a library for support vector machines, 2001. Software available at http://www.csie.ntu.edu.tw/~cjlin/libsvm.

Please also cite the source of the data sets (references given below).

Go to pages of classification (binary, multi-class), regression, and multi-label.

name	source	type	class	training size	testing size	feature
a1a	UCI	classification	2	1,605	30,956	123
a2a	UCI	classification	2	2,265	30,296	123
a3a	UCI	classification	2	3,185	29,376	123
a4a	UCI	classification	2	4,781	27,780	123
a5a	UCI	classification	2	6,414	26,147	123
a6a	UCI	classification	2	11,220	21,341	123
a7a	UCI	classification	2	16,100	16,461	123
a8a	UCI	classification	2	22,696	9,865	123
a9a	UCI	classification	2	32,561	16,281	123
australian	Statlog	classification	2	690		14
breast-cancer	UCI	classification	2	683		10
colon-cancer	[AU99a]	classification	2	62		2,000
covtype.binary	UCI	classification	2	581,012		54
diabetes	UCI	classification	2	768		8
duke breast-cancer	[MW01a]	classification	2	44		7,129
fourclass	[TKH96a]	classification	2	862		2
german.numer	Statlog	classification	2	1,000		24
heart	Statlog	classification	2	270		13
ijcnn1	[DP01a]	classification	2	49,990	91,701	22
ionosphere	UCI	classification	2	351		34
leukemia	[TG99a]	classification	2	38	34	7129
liver-disorders	UCI	classification	2	345		6
mushrooms	UCI	classification	2	8124		112
news20.binary	[SSK05a]	classification	2	19,996		1,355,191
rcv1.binary	[DL04b]	classification	2	20,242	677,399	47,236
real-sim	A. McCallum	classification	2	72,309		20,958
splice	Delve	classification	2	1,000	2,175	60
sonar	UCI	classification	2	208		60
svmguide1	[CWH03a]	classification	2	3,089	4,000	4
svmguide3	[CWH03a]	classification	2	1,243	41	21
w1a	[JP98a]	classification	2	2,477	47,272	300
w2a	[JP98a]	classification	2	3,470	46,279	300
w3a	[JP98a]	classification	2	4,912	44,837	300
w4a	[JP98a]	classification	2	7,366	42,383	300
w5a	[JP98a]	classification	2	9,888	39,861	300
w6a	[JP98a]	classification	2	17,188	32,561	300
w7a	[JP98a]	classification	2	24,692	25,057	300
w8a	[JP98a]	classification	2	49,749	14,951	300
webspam	Webb Spam Corpus [ST06a]	classification	2	350,000		16,609,143
connect-4	UCI	classification	3	67,557		126
covtype	UCI	classification	7	581,012		54
dna	Statlog	classification	3	2,000	1,186	180
glass	UCI	classification	6	214		9
iris	UCI	classification	3	150		4
letter	Statlog	classification	26	15,000	5,000	16
mnist	[YL98a]	classification	10	60,000	10,000	780
mnist8m	Invariant SVM [GL07b]	classification	10	8,100,000		784
news20	[KL95a]	classification	20	15,935	3,993	62,061
poker	UCI	classification	10	25,010	1,000,000	10
protein	[JYW02a]	classification	3	17,766	6,621	357
satimage	Statlog	classification	6	4,435	2,000	36
sector	[AM98a]	classification	105	6,412	3,207	55,197
segment	Statlog	classification	7	2,310		19
shuttle	Statlog	classification	7	43,500	14,500	9
svmguide2	[CWH03a]	classification	3	391		20
usps	[JJH94a]	classification	10	7,291	2,007	256
SensIT Vehicle (acoustic)	Sensit [MD04a]	classification	3	78,823	19,705	50
SensIT Vehicle (seismic)	Sensit [MD04a]	classification	3	78,823	19,705	50
SensIT Vehicle (combined)	Sensit [MD04a]	classification	3	78,823	19,705	100
vehicle	Statlog	classification	4	846		18
vowel	UCI	classification	11	528	462	10
wine	UCI	classification	3	178		13
abalone	UCI	regression		4,177		8
bodyfat	StatLib	regression		252		14
cadata	StatLib	regression		20,640		8
cpusmall	Delve	regression		8,192		12
housing	UCI	regression		506		13
mg	[GWF01a]	regression		1,385		6
mpg	UCI	regression		392		7
pyrim	UCI	regression		74		27
space_ga	StatLib	regression		3,107		6
triazines	UCI	regression		186		60
mediamill (exp1)	Mediamill	multi-label	101	30,993	12,914	120
rcv1v2 (topics; subsets)	[DL04b]	multi-label	101	3,000	3,000	47,236
rcv1v2 (topics; full sets)	[DL04b]	multi-label	101	23,149	781,265	47,236
rcv1v2 (industries; full sets)	[DL04b]	multi-label	313	23,149	781,265	47,236
rcv1v2 (regions; full sets)	[DL04b]	multi-label	228	23,149	781,265	47,236
scene-classification	[MB04a]	multi-label	6	1,211	1,196	294
siam-competition2007	SIAM Text Mining Competition 2007	multi-label	22	21,519	7,077	30,438
yeast	[AE02a]	multi-label	14	1,500	917	103

We have tried the best to obtain the permission from most original sources for distributing these sets. Please follow their respective copyrights for using them.

Author: Rong-En Fan at National Taiwan University. Please contact Chih-Jen Lin for any question.