-
1
-
-
33745561205
-
An introduction to variable and feature selection
-
I. Guyon and A. Elisseeff, "An introduction to variable and feature selection," Journal of Machine Learning Research, vol. 3, pp. 1157-1182, 2003.
-
(2003)
Journal of Machine Learning Research
, vol.3
, pp. 1157-1182
-
-
Guyon, I.1
Elisseeff, A.2
-
2
-
-
0031381525
-
Wrappers for feature subset selection
-
R. Kohavi and G.H. John, "Wrappers for feature subset selection," Artificial Intelligence, vol. 97, no. 1-2, pp. 273-324, 1997.
-
(1997)
Artificial Intelligence
, vol.97
, Issue.1-2
, pp. 273-324
-
-
Kohavi, R.1
John, G.H.2
-
3
-
-
85099325734
-
Irrelevant features and the subset selection problem
-
William W. Cohen and Haym Hirsch, Eds., San Fransisco, CA, Morgan Kaufmann Publishers
-
George H. John, Ron Kohavi, and Karl Pfleger, "Irrelevant features and the subset selection problem," in Proceedings of the Eleventh International Conference on Machine Learning, William W. Cohen and Haym Hirsch, Eds., San Fransisco, CA, 1994, pp. 121-129, Morgan Kaufmann Publishers.
-
(1994)
Proceedings of the Eleventh International Conference on Machine Learning
, pp. 121-129
-
-
George, H.1
John, R.K.2
Pfleger, K.3
-
4
-
-
0028547556
-
Floating search methods in feature selection
-
P. Pudil, J. Novovičová, and J. Kittler, "Floating search methods in feature selection," Pattern Recogn. Lett., vol. 15, no. 11, pp. 1119-1125, 1994.
-
(1994)
Pattern Recogn. Lett.
, vol.15
, Issue.11
, pp. 1119-1125
-
-
Pudil, P.1
Novovičová, J.2
Kittler, J.3
-
5
-
-
84863393425
-
Adaptive forward-backward greedy algorithm for sparse learning with linear models
-
D. Koller, D. Schuurmans, Y. Bengio, and L. Bottou, Eds., MIT Press
-
T. Zhang, "Adaptive forward-backward greedy algorithm for sparse learning with linear models," in Advances in Neural Information Processing Systems 21, D. Koller, D. Schuurmans, Y. Bengio, and L. Bottou, Eds., pp. 1921-1928. MIT Press, 2009.
-
(2009)
Advances in Neural Information Processing Systems
, vol.21
, pp. 1921-1928
-
-
Zhang, T.1
-
6
-
-
33749830485
-
Speeding up the wrapper feature subset selection in regression by mutual information relevance and redundancy analysis
-
Proceedings of the 16th International Conference on Artificial Neural Networks (ICANN 2006), S.D. Kollias, A. Stafylopatis, W. Duch, and E. Oja, Eds. 2006 Springer
-
G. Van Dijck and M.M. Van Hulle, "Speeding up the wrapper feature subset selection in regression by mutual information relevance and redundancy analysis," in Proceedings of the 16th International Conference on Artificial Neural Networks (ICANN 2006), S.D. Kollias, A. Stafylopatis, W. Duch, and E. Oja, Eds. 2006, vol. 4131 of Lecture Notes in Computer Science, pp. 31-40, Springer.
-
Lecture Notes in Computer Science
, vol.4131
, pp. 31-40
-
-
Van Dijck, G.1
Van Hulle, M.M.2
-
7
-
-
84942484786
-
Ridge regression: Biased estimation for nonorthogonal problems
-
A. E. Hoerl and R. W. Kennard, "Ridge regression: Biased estimation for nonorthogonal problems," Technometrics, vol. 12, pp. 55-67, 1970.
-
(1970)
Technometrics
, vol.12
, pp. 55-67
-
-
Hoerl, A.E.1
Kennard, R.W.2
-
8
-
-
0037695279
-
-
World Scientific Pub. Co., Singapore
-
J. Suykens, T. Van Gestel, J. De Brabanter, B. De Moor, and J. Vandewalle, Least Squares Support Vector Machines, World Scientific Pub. Co., Singapore, 2002.
-
(2002)
Least Squares Support Vector Machines
-
-
Suykens, J.1
Van Gestel, T.2
De Brabanter, J.3
De Moor, B.4
Vandewalle, J.5
-
9
-
-
9444250658
-
Regularized least-squares classification
-
Advances in Learning Theory: Methods, Model and Applications, J.A.K. Suykens, G. Horvath, S. Basu, C. Micchelli, and J. Vandewalle, Eds., chapter 7, IOS Press, Amsterdam
-
R. Rifkin, G. Yeo, and T. Poggio, "Regularized least-squares classification," in Advances in Learning Theory: Methods, Model and Applications, J.A.K. Suykens, G. Horvath, S. Basu, C. Micchelli, and J. Vandewalle, Eds., vol. 190 of NATO Science Series III: Computer and System Sciences, chapter 7, pp. 131-154. IOS Press, Amsterdam, 2003.
-
(2003)
NATO Science Series III: Computer and System Sciences
, vol.190
, pp. 131-154
-
-
Rifkin, R.1
Yeo, G.2
Poggio, T.3
-
10
-
-
60949111976
-
Learning to rank with pairwise regularized least-squares
-
T. Joachims, H. Li, T-Y. Liu, and C. Zhai, Eds.
-
T. Pahikkala, E. Tsivtsivadze, A. Airola, J. Boberg, and T. Salakoski, "Learning to rank with pairwise regularized least-squares," in SIGIR 2007 Workshop on Learning to Rank for Information Retrieval, T. Joachims, H. Li, T-Y. Liu, and C. Zhai, Eds., 2007, pp. 27-33.
-
(2007)
SIGIR 2007 Workshop on Learning to Rank for Information Retrieval
, pp. 27-33
-
-
Pahikkala, T.1
Tsivtsivadze, E.2
Airola, A.3
Boberg, J.4
Salakoski, T.5
-
11
-
-
60949112451
-
An efficient algorithm for learning to rank from preference graphs
-
T. Pahikkala, E. Tsivtsivadze, A. Airola, J. Boberg, and J. Järvinen, "An efficient algorithm for learning to rank from preference graphs," Machine Learning, vol. 75, no. 1, pp. 129-165, 2009.
-
(2009)
Machine Learning
, vol.75
, Issue.1
, pp. 129-165
-
-
Pahikkala, T.1
Tsivtsivadze, E.2
Airola, A.3
Boberg, J.4
Järvinen, J.5
-
12
-
-
84862520910
-
Fast n-fold cross-validation for regularized least-squares
-
T. Honkela, T. Raiko, J. Kortela, and H. Valpola, Eds.
-
T. Pahikkala, J. Boberg, and T. Salakoski, "Fast n-fold cross-validation for regularized least-squares," in Proceedings of the 9th Scandinavian Conference on Artificial Intelligence (SCAI 2006), T. Honkela, T. Raiko, J. Kortela, and H. Valpola, Eds., 2006, pp. 83-90.
-
(2006)
Proceedings of the 9th Scandinavian Conference on Artificial Intelligence (SCAI 2006)
, pp. 83-90
-
-
Pahikkala, T.1
Boberg, J.2
Salakoski, T.3
-
13
-
-
44649153951
-
-
Tech. Rep. MIT-CSAIL-TR-2007-025, Massachusetts Institute of Technology
-
R. Rifkin and R. Lippert, "Notes on regularized least squares," Tech. Rep. MIT-CSAIL-TR-2007-025, Massachusetts Institute of Technology, 2007.
-
(2007)
Notes on Regularized Least Squares
-
-
Rifkin, R.1
Lippert, R.2
-
14
-
-
33645157313
-
Gene selection algorithms for microarray data based on least squares support vector machine
-
E.K. Tang, P.N. Suganthan, and X. Yao, "Gene selection algorithms for microarray data based on least squares support vector machine," BMC Bioinformatics, vol. 7, pp. 95, 2006.
-
(2006)
BMC Bioinformatics
, vol.7
, pp. 95
-
-
Tang, E.K.1
Suganthan, P.N.2
Yao, X.3
-
15
-
-
40649092045
-
Low rank updated LS-SVM classifiers for fast variable selection
-
F. Ojeda, J.A.K. Suykens, and B. De Moor, "Low rank updated LS-SVM classifiers for fast variable selection," Neural Networks, vol. 21, no. 2-3, pp. 437-449, 2008.
-
(2008)
Neural Networks
, vol.21
, Issue.2-3
, pp. 437-449
-
-
Ojeda, F.1
Suykens, J.A.K.2
De Moor, B.3
-
17
-
-
0002619965
-
Ridge regression learning algorithm in dual variables
-
Morgan Kaufmann Publishers Inc.
-
C. Saunders, A. Gammerman, and V. Vovk, "Ridge regression learning algorithm in dual variables," in Proceedings of the Fifteenth International Conference on Machine Learning, San Francisco, CA, USA, 1998, pp. 515-521, Morgan Kaufmann Publishers Inc.
-
(1998)
Proceedings of the Fifteenth International Conference on Machine Learning, San Francisco, CA, USA
, pp. 515-521
-
-
Saunders, C.1
Gammerman, A.2
Vovk, V.3
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