Speeding up the wrapper feature subset selection in regression by mutual information relevance and redundancy analysis

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 4131 LNCS - I, Issue , 2006, Pages 31-40

  Van Dijck, Gert ^a   Van Hulle, Marc M ^a  

^a KU LEUVEN UNIVERSITY OF LEUVEN   (Belgium)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; BENCHMARKING; COMPUTATION THEORY; INFORMATION THEORY; MATHEMATICAL MODELS; REDUNDANCY; REGRESSION ANALYSIS;

HYBRID FILTERS; TARGET VARIABLES; WRAPPER FEATURE;

FEATURE EXTRACTION;

EID: 33749830485     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/11840817_4     Document Type: Conference Paper

References (15)

1. Guyon, I. Elisseeff, A.: An Introduction to Variable and Feature Selection. Journal of Machine Learning Research 3 (2003) 1157-1182.
2. Kurgan, L.A., Cios, K.J.: CAIM Discretization Algorithm. IEEE Transactions on Knowledge and Data Engineering 16 (2004) 145-153.
3. Kohavi, R., John G. H.: Wrappers for Feature Subset Selection. Artificial Intelligence 97 (1997) 273-324.
4. Van Dijck G., Van Huile M. M., Wevers, M.: Hierarchical Feature Subset Selection for Features Computed from the Continuous Wavelet Transform. 2005 IEEE Workshop on Machine Learning for Signal Processing (2005) 81-86.
5. Cover, T. M., Thomas, J. A.: Elements of information theory. John Wiley & Sons, New York (1991).
6. Schreiber, T., Schmitz, A.: Surrogate Time Series, Physica D 142 (2000) 346-382.
7. Kraskov, A., Stögbauer, H., Grassberger, P.: Estimating Mutual Information. Phys. Rev. E. 69 (2004) 066138.
8. Francois, D., Wertz, V., Verleysen, M.: The Permutation Test for Feature Selection by Mutual Information. European Symposium on Artificial Neural Networks (2006) 239-244.
9. John, G., Kohavi, R. Pfleger, K.: Irrelevant Features and the Subset Selection Problem. In Proc. of the Eleventh Int. Conf. on Machine Learning, (1994) 121-129.
10. Duda, R.O., Hart, P.E., Stork, D. G. Pattern Classification, John Wiley & Sons Inc., New York (2001).
11. Bishop, C.M. Neural Networks for Pattern Recognition. Oxford University Press Inc., New York (1997).
12. Narendra, P. M., Fukunaga, K.: A Branch and Bound Algorithm for Feature Subset Selection. IEEE Trans. Computers 26 (1977) 917-922.
13. Pudil, P., Novovicova, J., Kittler, J., Floating Search Methods in Feature Selection. Pattern Recognition Letters 15 (1994) 1119-1125.
14. Michalewicz, Z.: Genetic Algorithms + Data Structures = Evolution Programs. 3rd edn. Springer-Verlag, Berlin Heidelberg New York (1996).
15. Kudo, M., Sklansky, J., Comparison of Algorithms that Select Features for Pattern Recognition. Pattern Recognition 33 (2000) 25-41.