Variable selection in model-based discriminant analysis

Journal of Multivariate Analysis

Volumn 102, Issue 10, 2011, Pages 1374-1387

  Maugis, C ^a   Celeux, G ^b   Martin Magniette, M L ^c,d  

^a UNIVERSITÉ DE TOULOUSE   (France)

^b INRIA SACLAY   (France)

^c AgroParisTech   (France)

^d INSTITUTE OF PLANT SCIENCES PARIS SACLAY IPS2   (France)

Author keywords

BIC; Discriminant, redundant or independent variables; Gaussian classification models; Linear regression; Variable selection

Indexed keywords

EID: 79960073938     PISSN: 0047259X     EISSN: 10957243     Source Type: Journal    
DOI: 10.1016/j.jmva.2011.05.004     Document Type: Article

References (23)

1. Banfield J.D., Raftery A.E. Model-based Gaussian and non-Gaussian clustering. Biometrics 1993, 49:803-821.
2. Bensmail H., Celeux G. Regularized Gaussian discriminant analysis through eignenvalue decomposition. Journal of the American Statistical Association 1996, 91:1743-1748.
3. Biernacki C., Celeux G., Govaert G., Langrognet F. Model-based cluster and discriminant analysis with the mixmod software. Computational Statistics and Data Analysis 2006, 51:587-600.
4. Bishop C.M. Pattern Recognition and Machine Learning 2006, Springer, New York.
5. Celeux G., Govaert G. Gaussian parsimonious clustering models. Pattern Recognition 1995, 28:781-793.
6. Fraley C., Raftery A.E. Enhanced software for model-based clustering, density estimation, and discriminant analysis: mclust. Journal of Classification 2003, 20:263-286.
7. Golub T.R., Slonim D.K., Tamayo P., Huard C., Gaasenbeek M., Mesirov J.P., Coller H., Loh M.L., Downing J.R., Caligiuri M.A., Bloomfield C.D., Lander E.S. Molecular classification of cancer: Class discovery and class prediction by gene expression monitoring. Science 1999, 286:531-537.
8. Guyon I., Ellisseeff A. An introduction to variable and feature selection. Journal of Machine Learning research 2003, 3:1157-1182.
9. Hastie T., Tibshirani R., Friedman J. The Elements of Statistical Learning 2009, Springer, New York. Second Ed.
10. Krishnapuram B., Carin L., Hartemink A. Gene expression analysis: Joint feature selection and classifier design. Kernel Methods in Computational Biology 2004, MIT Press, Cambridge, MA.
11. Mary-Huard T., Robin S. Tailored aggregation for classification. IEEE Transactions on Pattern Analysis and Machine Intelligence 2009, 31:2098-2105.
12. Mary-Huard T., Robin S., Daudin J.J. A penalized criterion for variable selection in classification. Journal of Multivariate Analysis 2007, 98:695-705.
13. Maugis C., Celeux G., Martin-Magniette M.L. Variable Selection for Clustering with Gaussian mixture models. Biometrics 2009, 65:701-709.
14. Maugis C., Celeux G., Martin-Magniette M.L. variable selection in model-based clustering: A general variable role modeling. Computational Statistics and Data Analysis 2009, 53:3872-3882.
15. C. Maugis, G. Celeux, M.L. Martin-Magniette, Variable selection in model-based discriminant analysis, Technical Report RR-7290, INRIA, 2010.
16. McLachlan G. Discriminant Analysis and Statistical Pattern Analysis 1992, Wiley-Interscience, New York.
17. Murphy B.T., Raftery A.E., Dean N. Variable selection and updating in model-based discriminant analysis for high-dimensional data with food authenticity applications. Annals of Applied Statistics 2010, 4:396-421.
18. Raftery A.E., Dean N. variable selection for model-based clustering. Journal of the American Statistical Association 2006, 101:168-178.
19. Schwarz G. Estimating the dimension of a model. The Annals of Statistics 1978, 6:461-464.
20. Su Y., Murali T., Pavlovic V., Schaffer M., Kasif S. Rank Gene: Identification of diagnostic genes based on expression data. Bioinformatics 2003, 19:1578-1579.
21. Yang A.J., Xin-Yuan S. Bayesian variable selection for disease classification using gene expression data. Bioinformatics 2010, 26:215-222.
22. Young D.M., Odell P.L. Feature-subset selection for statistical classification problems involving unequal covariance matrices. Communication in Statistics-Theory and Methods 1986, 15:137-157.
23. Q. Zhang, H. Wang, A bic criterion for gaussian mixture model selection with application in discriminant analysis, Technical Report, Guanghua School of Management, Peking University, 2008.