-
1
-
-
0031334221
-
Selection of relevant features and examples in machine learning
-
A.P. Blum, and P. Langley Selection of relevant features and examples in machine learning Artificial Intelligence 97 1997 245 271
-
(1997)
Artificial Intelligence
, vol.97
, pp. 245-271
-
-
Blum, A.P.1
Langley, P.2
-
4
-
-
0036161011
-
Choosing multiple parameters for support vector machines
-
DOI 10.1023/A:1012450327387
-
O. Chapelle, V. Vapnik, O. Bousquet, and S. Mukherjee Choosing multiple parameters for support vector machines Machine Learning 46 1 2002 131 159 (Pubitemid 34129966)
-
(2002)
Machine Learning
, vol.46
, Issue.1-3
, pp. 131-159
-
-
Chapelle, O.1
Vapnik, V.2
Bousquet, O.3
Mukherjee, S.4
-
7
-
-
0036161259
-
Gene selection for cancer classification using support vector machines
-
I. Guyon, J. Weston, S. Barnhill, and V. Vapnik Gene selection for cancer classification using support vector machines Machine Learning 46 1-3 2002 389 422
-
(2002)
Machine Learning
, vol.46
, Issue.13
, pp. 389-422
-
-
Guyon, I.1
Weston, J.2
Barnhill, S.3
Vapnik, V.4
-
8
-
-
0003704318
-
-
University of California, Department of Information and Computer Science Irvine, CA
-
S. Hettich, and S.D. Bay The UCI KDD Archive 1999 University of California, Department of Information and Computer Science Irvine, CA
-
(1999)
The UCI KDD Archive
-
-
Hettich, S.1
Bay, S.D.2
-
9
-
-
33646099818
-
FS-SFS: A novel feature selection method for support vector machines
-
Y. Liu, and Y.F. Zheng FS-SFS: A novel feature selection method for support vector machines Pattern Recognition 39 2006 1333 1345
-
(2006)
Pattern Recognition
, vol.39
, pp. 1333-1345
-
-
Liu, Y.1
Zheng, Y.F.2
-
10
-
-
64749086339
-
A wrapper method for feature selection using support vector machines
-
S. Maldonado, and R. Weber A wrapper method for feature selection using support vector machines Information Sciences 179 13 2009 2208 2217
-
(2009)
Information Sciences
, vol.179
, Issue.13
, pp. 2208-2217
-
-
Maldonado, S.1
Weber, R.2
-
11
-
-
77958098707
-
Feature selection for support vector regression via kernel penalization
-
Barcelona, Spain
-
S. Maldonado, R. Weber, Feature selection for support vector regression via kernel penalization, in: Proceedings of the 2010 International Joint Conference on Neural Networks, Barcelona, Spain, 2010, pp. 1973-1979.
-
(2010)
Proceedings of the 2010 International Joint Conference on Neural Networks
, pp. 1973-1979
-
-
Maldonado, S.1
Weber, R.2
-
12
-
-
33646724524
-
Linear penalization support vector machines for feature selection
-
PReMI 2005
-
J. Miranda, R. Montoya, and R. Weber Linear penalization support vector machines for feature selection S.K. Pal, PReMI 2005 LNCS vol. 3776 2005 Springer-Verlag Berlin, Heidelberg 188 192
-
(2005)
LNCS
, vol.3776
, pp. 188-192
-
-
Miranda, J.1
Montoya, R.2
Weber, R.3
-
13
-
-
30044438683
-
Combined SVM-based feature selection and classification
-
J. Neumann, C. Schnörr, and G. Steidl Combined SVM-based feature selection and classification Machine Learning 61 1-3 2005 129 150
-
(2005)
Machine Learning
, vol.61
, Issue.13
, pp. 129-150
-
-
Neumann, J.1
Schnörr, C.2
Steidl, G.3
-
18
-
-
44949258241
-
Multiclass SVM-RFE for product form feature selection
-
M.-D. Shieh, and C.-C. Yang Multiclass SVM-RFE for product form feature selection Expert Systems with Applications 35 1-2 2008 531 541
-
(2008)
Expert Systems with Applications
, vol.35
, Issue.12
, pp. 531-541
-
-
Shieh, M.-D.1
Yang, C.-C.2
-
19
-
-
33751002948
-
A novel feature selection approach: Combining feature wrappers and filters
-
Ö. Uncu, and I.B. Türksen A novel feature selection approach: combining feature wrappers and filters Information Sciences 177 2007 449 466
-
(2007)
Information Sciences
, vol.177
, pp. 449-466
-
-
Uncu, Ö.1
Türksen, I.B.2
-
20
-
-
77956611003
-
2PSO: A maximum relevance minimum redundancy feature selection method based on swarm intelligence for support vector machine classification
-
in press
-
2PSO: A maximum relevance minimum redundancy feature selection method based on swarm intelligence for support vector machine classification, Information Sciences, in press, doi:10.1016/j.ins.2010.05.037.
-
Information Sciences
-
-
Unler, A.1
Murat, A.2
Chinnam, R.B.3
-
22
-
-
84898948710
-
Feature selection for SVMs
-
MIT Press Cambridge, MA
-
J. Weston, S. Mukherjee, O. Chapelle, M. Ponntil, T. Poggio, and V. Vapnik Feature selection for SVMs Advances in Neural Information Processing Systems vol. 13 2001 MIT Press Cambridge, MA
-
(2001)
Advances in Neural Information Processing Systems
, vol.13
-
-
Weston, J.1
Mukherjee, S.2
Chapelle, O.3
Ponntil, M.4
Poggio, T.5
Vapnik, V.6
-
24
-
-
67650995440
-
Feature selection for multi-label naive Bayes classification
-
M.L. Zhang, J.M. Pena, and V. Robles Feature selection for multi-label naive Bayes classification Information Sciences 179 19 2009 3218 3229
-
(2009)
Information Sciences
, vol.179
, Issue.19
, pp. 3218-3229
-
-
Zhang, M.L.1
Pena, J.M.2
Robles, V.3
|