References
- Bouguila, N., Almakadmeh, K. and Boutemedjet, S. (2012). A finite mixture model for simultaneous high-dimensional clustering, localized feature selection and outlier rejection, Expert Systems with Applica-tions, 39, 6641-6656. https://doi.org/10.1016/j.eswa.2011.12.038
- Bouguila, N. and Ziou, D. (2006). A hybrid SEM algorithm for high-dimensional unsupervised learning using a finite generalized Dirichlet mixture, IEEE Transactions on Image Processing, 15, 2657-2668. https://doi.org/10.1109/TIP.2006.877379
- Boutemedjet, S., Bouguila, N. and Ziou, D. (2009). A hybrid feature extraction selection approach for high-dimensional non-Gaussian data clustering, IEEE Transactions on Pattern Analysis and Machine Intelligence, 31, 1429-1443. https://doi.org/10.1109/TPAMI.2008.155
- Elguebaly, T. and Bouguila, N. (2013). Simultaneous Bayesian clustering and features election using RJMCMC-based learning of finite generalized Dirichlet mixture models, Signal Processing, 93, 1531-1546. https://doi.org/10.1016/j.sigpro.2012.07.037
- 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. and Bloomfield, C. D. (1999). Molecular classification of cancer: Class discovery and class prediction by gene expression monitoring, Science, 286, 531-537. https://doi.org/10.1126/science.286.5439.531
- Graham, M. W. and Miller, D. J. (2006). Unsupervised learning of parsimonious mixtures on large spaces with integrated feature and component selection, IEEE Transactions on Signal Processing, 54, 1289-1303. https://doi.org/10.1109/TSP.2006.870586
- Kim, S. G. (2011). Variable selection in normal mixture model based clustering under heteroscedasticity, The Korean Journal of Applied Statistics, 24, 1-12. https://doi.org/10.5351/KJAS.2011.24.1.001
- 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. https://doi.org/10.1109/TPAMI.2004.71
- Li, M. D. Y. and Hua, J. (2008). Localized feature selection for clustering, Pattern Recognition Letters, 29, 10-18. https://doi.org/10.1016/j.patrec.2007.08.012
- Li, Y., Dong, M. and Hua, J. (2009). Simultaneous localized feature selection and model detection for Gaussian mixtures, IEEE Transactions on Pattern Analysis and Machine Intelligence, 31, 953-960. https://doi.org/10.1109/TPAMI.2008.261
- McLachlan, G. J. and Peel, D. (2000). Finite Mixture Models, Wiley, New York.
- Pan, W. and Shen, X. (2006). Penalized model-based clustering with application to variable selection. Journal of Machine Learning Research, 8, 1145-1164.
- Schwarz, G. (1978). Estimating the dimension of a model, Annals of Statistics, 6, 461-464. https://doi.org/10.1214/aos/1176344136
- Wang, S. and Zhu, J. (2008). Variable selection for model-based high-dimensional clustering and its application to microarray data, Bioinformatics, 64, 440-448.
- Xie, B., Pan, W. and Shen, X. (2008). Variable selection in penalized model-based clustering via regularization on grouped parameters, Biometrics, 64, 921-930. https://doi.org/10.1111/j.1541-0420.2007.00955.x