Variable Selection for Clustering by Separability Based on Ridgelines

References

• Caruana, R., and Freitag, D. (1994), “Greedy Attribute Selection,” in Proceedings of the 11th International Conference on Machine Learning, New Brunswick, NJ: Morgan Kaufmann, pp. 28–36.
   Google Scholar
• Dy, J. G., and Brodley, C. E. (2004), “Feature Selection for Unsupervised Learning,” Journal of Machine Learning Research, 5, 845–889.
   Web of Science ®Google Scholar
• Fraley, C., and Raftery, A. E. (1999), “MCLUST: Software for Model-Based Cluster Analysis,” Journal of Classification, 16, 297–306.
   Web of Science ®Google Scholar
• Fraley, C., and Raftery, A. E. (2002), “Model-Based Clustering, Discriminant Analysis, and Density Estimation,” Journal of the American Statistical Association, 97, 661–631.
   Web of Science ®Google Scholar
• Friedman, J., and Meulman, J. J. (2004), “Clustering Objects on Subsets of Attributes,” Journal of the Royal Statistical Society, Series B, 66, 815–849.
   Web of Science ®Google Scholar
• Guo, J., Levina, E., Michailidis, G., and Zhu, J. (2010), “Pairwise Variable Selection for High-Dimensional Model-Based Clustering,” Biometrics, 66(3), 793–804.
   PubMed Web of Science ®Google Scholar
• Guyon, I., and Elisseeff, A. (2003), “An Introduction to Variable and Feature Selection,” Journal of Machine Learning Research, 3, 1157–1182.
   Google Scholar
• Law, M. H. C., Figueiredo, M. A. T., and Jain, A. K. (2004), “Simultaneous Feature Selection and Clustering Using Mixture Models,” IEEE Transactions on Pattern Analysis and Machine Intelligence, 26, 1154–1166.
   PubMed Web of Science ®Google Scholar
• Li, J., Ray, S., and Lindsay, B. G. (2007), “A Nonparametric Statistical Approach to Clustering via Mode Identification,” Journal of Machine Learning Research, 8, 1687–1723.
   Web of Science ®Google Scholar
• Liu, H., and Setiono, R. (1996), “Dimension Reduction via Discretization,” Knowledge-Based Systems, 9, 67–72.
   Web of Science ®Google Scholar
• Liu, Y., and Wu, Y. (2007), “Variable Selection via a Combination of the L0 and L1 Penalties,” Journal of Computational and Graphical Statistics, 16, 782–798.
   Web of Science ®Google Scholar
• Maugis, C., Celeux, G., and Martin-Magniette, M.-L. (2009), “Variable Selection for Clustering With Gaussian Mixture Models,” Biometrics, 65, 701–709.
   PubMed Web of Science ®Google Scholar
• McLachlan, G., and Peel, D. (2000), Finite Mixture Models, New York: Wiley.
   Google Scholar
• Mitra, P., Murthy, C. A., and Pal, S. K. (2002), “Unsupervised Feature Selection Using Feature Similarity,” IEEE Transactions on Pattern Analysis and Machine Intelligence, 24, 301–312.
   Web of Science ®Google Scholar
• Narendra, P. M., and Fukunaga, K. (1977), “A Branch and Bound Algorithm for Feature Subset Selection,” IEEE Transactions of Computers, C-26, 917–922.
   Web of Science ®Google Scholar
• Pan, W., and Shen, X. (2007), “Penalized Model-Based Clustering With Application to Variable Selection,” Journal of Machine Learning Research, 8, 1145–1164.
   Web of Science ®Google Scholar
• Raftery, A., and Dean, N. (2006), “Variable Selection for Model-Based Clustering,” Journal of the American Statistical Association, 101, 168–178.
   Web of Science ®Google Scholar
• Ray, S., and Lindsay, B. G. (2005), “The Topography of Multivariate Normal Mixtures,” The Annals of Statistics, 33, 2042–2065.
   Web of Science ®Google Scholar
• Tadesse, M. G., Sha, N., and Vannucci, M. (2005), “Bayesian Variable Selection in Clustering High-Dimensional Data,” Journal of the American Statistical Association, 100, 602–617.
   Web of Science ®Google Scholar
• Wang, L., and Shen, X. (2006), “Multicategory Support Vector Machines, Feature Selection and Solution Path,” Statistics Sinica, 16, 617–634.
   Web of Science ®Google Scholar
• Wang, S., and Zhu, J. (2008), “Variable Selection for Model-Based High-Dimensional Clustering and Its Application to Microarray Data,” Biometrics, 64, 440–448.
   PubMed Web of Science ®Google Scholar
• Witten, D. M., and Tibshirani, R. (2010), “A Framework for Feature Selection in Clustering,” Journal of the American Statistical Association, 105, 713–726.
   PubMed Web of Science ®Google Scholar
• Xie, B., Pan, W., and Shen, X. (2008), “Penalized Model-Based Clustering With Cluster-Specific Diagonal Covariance Matrices and Grouped Variables,” Electronic Journal of Statistics, 2, 168–212.
   PubMed Web of Science ®Google Scholar
• Yuan, M., Joseph, V. R., and Zou, H. (2009), “Structured Variable Selection and Estimation,” Annals of Applied Statistics, 3, 1738–1757.
   Web of Science ®Google Scholar
• Zhang, H. H., Liu, Y., Wu, Y., and Zhu, J. (2008), “Variable Selection for Multicategory SVM via Sup-Norm Regularization,” Electronic Journal of Statics, 2, 149–167.
   Web of Science ®Google Scholar
• Zou, H. (2006), “The Adaptive Lasso and Its Oracle Properties,” Journal of the American Statistical Association, 101, 1418–1429.
   Web of Science ®Google Scholar