-
1
-
-
33745561205
-
An Introduction to Variable and Feature Selection
-
Isabelle Guyon, Andre Elisseeff, "An Introduction to Variable and Feature Selection", JMLR, 3 (2003), 1157-1182.
-
(2003)
JMLR
, vol.3
, pp. 1157-1182
-
-
Guyon, I.1
Elisseeff, A.2
-
2
-
-
0036161259
-
Gene selection for cancer classification using support vector machines
-
DOI 10.1023/A:1012487302797
-
I. Guyon, J.Weston, S. Barhill, and V. Vapnik, "Gene Selection for Cancer Classification using support Vector Machines," Mach. Learn., vol. 46, pp. 389-422, 2002. (Pubitemid 34129977)
-
(2002)
Machine Learning
, vol.46
, Issue.1-3
, pp. 389-422
-
-
Guyon, I.1
Weston, J.2
Barnhill, S.3
Vapnik, V.4
-
3
-
-
17644384367
-
Minimum Redundancy Feature Selection from Microarray Gene Expression Data
-
Chris Ding, Hanchuan Peng, "Minimum Redundancy Feature Selection From Microarray Gene Expression Data", Journal of Bioinformatics and Computational Biology, Vol. 3, No. 2 (2005), 185-205.
-
(2005)
Journal of Bioinformatics and Computational Biology
, vol.3
, Issue.2
, pp. 185-205
-
-
Ding, C.1
Peng, H.2
-
4
-
-
2942731012
-
An extensive empirical study of feature selection metrics for text classification
-
G. Forman,"An extensive empirical study of feature selection metrics for text classification," JMLR, 3:1289-1306 (this issue), 2003.
-
(2003)
JMLR
, vol.3
, Issue.THIS ISSUE
, pp. 1289-1306
-
-
Forman, G.1
-
5
-
-
0026966646
-
A training algorithm for optimal margin classifiers
-
Pittsburgh, ACM
-
B. Boser, I. Guyon, and V. Vapnik," A training algorithm for optimal margin classifiers," In Fifth Annual Workshop on Computational Learning Theory, pages 144-152, Pittsburgh, 1992. ACM.
-
(1992)
Fifth Annual Workshop on Computational Learning Theory
, pp. 144-152
-
-
Boser, B.1
Guyon, I.2
Vapnik, V.3
-
7
-
-
0031381525
-
Wrappers for Feature Subset Selection
-
Ron Kohavi, George H. John," Wrappers for Feature Subset Selection", Artificial Intelligence, 97 (1997), 273-324.
-
(1997)
Artificial Intelligence
, vol.97
, pp. 273-324
-
-
Kohavi, R.1
John, G.H.2
-
9
-
-
0028547556
-
Floating Search Methods in Feature Selection
-
P. Pudil, J. Novovicova, J. Kittler, "Floating Search Methods in Feature Selection", Pattern Recognition Letters 15 (1994), 1119-1125.
-
(1994)
Pattern Recognition Letters
, vol.15
, pp. 1119-1125
-
-
Pudil, P.1
Novovicova, J.2
Kittler, J.3
-
10
-
-
0003722376
-
-
Addison-Wesley, Reading, MA
-
D. Goldberg, Genetic algorithms in search, optimization and machine learning, Addison-Wesley, Reading, MA, 1989.
-
(1989)
Genetic Algorithms in Search, Optimization and Machine Learning
-
-
Goldberg, D.1
-
11
-
-
0028468293
-
Using Mutual Information for Selecting Features in Supervised Neural Net Learning
-
July
-
Roberto Battiti, "Using Mutual Information for Selecting Features in Supervised Neural Net Learning", IEEE Transactions on Neural Networks, Vol. 5, No. 4, July 1994.
-
(1994)
IEEE Transactions on Neural Networks
, vol.5
, Issue.4
-
-
Battiti, R.1
-
12
-
-
0000012317
-
Towards optimal feature selection
-
Daphne Koller and M. Sahami," Towards optimal feature selection", ICML-96, pages 284-292, 1996.
-
(1996)
ICML-96
, pp. 284-292
-
-
Koller, D.1
Sahami, M.2
-
13
-
-
84890445089
-
Overfitting in Making Comparisons between Variable Selection Methods
-
Juha Reunanen, "Overfitting in Making Comparisons between Variable Selection Methods", JMLR 3 (2003) 1371-1382.
-
(2003)
JMLR
, vol.3
, pp. 1371-1382
-
-
Reunanen, J.1
-
14
-
-
0033220764
-
Adaptive floating search methods in feature selection
-
DOI 10.1016/S0167-8655(99)00083-5
-
P. Somol, P. Pudil, J. Novovicova, P. Paclik, "Adaptive Floating Search Methods in Feature Selection", Pattern Recognition Letters 20 (1999) 1157-1163. (Pubitemid 32261893)
-
(1999)
Pattern Recognition Letters
, vol.20
, Issue.11-13
, pp. 1157-1163
-
-
Somol, P.1
Pudil, P.2
Novovicova, J.3
Paclik, P.4
-
16
-
-
67349133167
-
An improvement on Floating Search Algorithms for Feature Subset Selection
-
S. Nakariyakul, David P. Casasent," An improvement on Floating Search Algorithms for Feature Subset Selection," Pattern Recognition 42 (2009), pp. 1932-1940.
-
(2009)
Pattern Recognition
, vol.42
, pp. 1932-1940
-
-
Nakariyakul, S.1
Casasent, D.P.2
-
17
-
-
12844283500
-
A Two-stage Evolutionary algorithm for Variable Selection in the development of RBF Neural Network Models
-
Alex Alexandridis, Panagiotis Patrinos, Haralambos Sarimveis, George Tsekouras," A Two-stage Evolutionary algorithm for Variable Selection in the development of RBF Neural Network Models", Chemometrics and Intelligent Laboratory Systems 75 (2005) 149-162.
-
(2005)
Chemometrics and Intelligent Laboratory Systems
, vol.75
, pp. 149-162
-
-
Alexandridis, A.1
Patrinos, P.2
Sarimveis, H.3
Tsekouras, G.4
-
18
-
-
0032028297
-
Feature Subset Selection using a Genetic Algorithm
-
IEEE
-
Jihoon Yang and Vasant Honavar," Feature Subset Selection using a Genetic Algorithm," Intelligent Systems and their Applications, IEEE, Vol. 13, no. 2, pp. 44-49, 1998.
-
(1998)
Intelligent Systems and Their Applications
, vol.13
, Issue.2
, pp. 44-49
-
-
Yang, J.1
Honavar, V.2
-
19
-
-
0001334115
-
The CHC adaptive search algorithm. How to have safe search when engaging in nontraditional genetic combination
-
G. Rawlins, editor, Morgan Kaufmann
-
L. Eshelman, "The CHC adaptive search algorithm. How to have safe search when engaging in nontraditional genetic combination," In G. Rawlins, editor, FOGA-1, Morgan Kaufmann, pp. 265-283, 1991.
-
(1991)
FOGA-1
, pp. 265-283
-
-
Eshelman, L.1
-
21
-
-
70350602937
-
Feature Selection using PSO-SVM
-
IJCS-33-1-18
-
Chung-Jui Tu, Li-Yeh Chuang, Jun-Yang Chang and Cheng-Hong Yang, "Feature Selection using PSO-SVM", IAENG International Journal of Computer Science, 33:1, IJCS-33-1-18.
-
IAENG International Journal of Computer Science
, vol.33
, pp. 1
-
-
Tu, C.-J.1
Chuang, L.-Y.2
Chang, J.-Y.3
Yang, C.-H.4
-
22
-
-
63149139219
-
Gene Selection in Cancer Classification using PSO/SVM and GA/SVM Hybrid Algorithms
-
Enrique Alba, José García-Nieto, Laetitia Jourdan and El-Ghazali Talbi," Gene Selection in Cancer Classification using PSO/SVM and GA/SVM Hybrid Algorithms," Evolutionary Computation, 2007. CEC 2007, pp. 284-290.
-
Evolutionary Computation, 2007. CEC 2007
, pp. 284-290
-
-
Alba, E.1
García-Nieto, J.2
Jourdan, L.3
Talbi, E.-G.4
-
23
-
-
77951430107
-
Distributional word clusters vs. words for text categorization
-
R. Bekkerman, R. El-Yaniv, N. Tishby, and Y. Winter," Distributional word clusters vs. words for text categorization", JMLR, 3:1183-1208, 2003.
-
(2003)
JMLR
, vol.3
, pp. 1183-1208
-
-
Bekkerman, R.1
El-Yaniv, R.2
Tishby, N.3
Winter, Y.4
-
24
-
-
79955702502
-
LIBSVM: A library for support vector machines
-
3
-
Chang, Chih-Chung and Lin, Chih-Jen," LIBSVM: A library for support vector machines," ACM Transactions on Intelligent Systems and Technology, Vol. 2, 3-2011, pp. 1-27.
-
(2011)
ACM Transactions on Intelligent Systems and Technology
, vol.2
, pp. 1-27
-
-
Chang, C.-C.1
Lin, C.-J.2
-
27
-
-
59649130080
-
Criterion in Selecting the Clustering Algorithm in Radial Basis Functional Link Nets
-
A. S. Loong, O. H. Choon, and L. H. Chin, "Criterion in Selecting the Clustering Algorithm in Radial Basis Functional Link Nets," WSEAS Transactions on Systems, vol. 7, no. 11, pp. 1290-1299, 2008.
-
(2008)
WSEAS Transactions on Systems
, vol.7
, Issue.11
, pp. 1290-1299
-
-
Loong, A.S.1
Choon, O.H.2
Chin, L.H.3
-
28
-
-
41149089754
-
Radial basis function classifiers to help in the diagnosis of the obstructive sleep apnoea syndrome from nocturnal oximetry
-
DOI 10.1007/s11517-007-0280-0
-
J. V. Marcos, R. Hornero, and D. Alvarez, "Radial basis function classifiers to help in the diagnosis of the obstructive sleep apnoea syndrome from nocturnal oximetry," Medical and Biological Engineering and Computing, vol. 46, no. 4, pp. 323-332, 2008. (Pubitemid 351436977)
-
(2008)
Medical and Biological Engineering and Computing
, vol.46
, Issue.4
, pp. 323-332
-
-
Marcos, J.V.1
Hornero, R.2
Alvarez, D.3
Del, C.F.4
Lopez, M.5
Zamarron, C.6
-
29
-
-
84872370711
-
-
http://archive.ics.uci.edu/ml/
-
-
-
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