GMMBayes Toolbox - Gaussian mixture model learning and classification Version 1.0 Class learning interface gmmb_create - Construct new classifier with GMM PDFs Calls gmmb_em, gmmb_fj or gmmb_gem. Classification interface gmmb_pdf - multiclass and -variate (complex) GMM PDF gmmb_weightprior - multiply PDF values with constant priors gmmb_normalize - scale all row sums to one (useful in Bayesian classifier) gmmb_decide - make the classification decisions gmmb_fracthresh - threshold PDF values according to given distribution density quantile, i.e., find outliers Legacy Classification interface gmmb_classify - Run the classifier with bayesS struct. (Legacy interface) Estimation functions gmmb_em - The basic EM algorithm. gmmb_fj - The Figueiredo-Jain algorithm. gmmb_gem - Wrapper for the Vlassis code, Greedy EM algorithm. EM initializer functions gmmb_em_init_cmeans1 - c-means clustering, uniform weight and covariance gmmb_em_init_cmeans2 - c-means clustering, cluster weight and covariance gmmb_em_init_fcm1 - Fuzzy c-means clustering, the Toolbox v0.1 method Helper functions gmmb_cmvnpdf - (Real and complex range) multivariate Gaussian pdf gmmb_covfixer - Force matrix to a valid covariance matrix. gmmb_cmeans - Simple c-means clustering gmmb_mkcplx - generate complex data with Gaussian distribution gmmb_hist - Create histS structure from user supplied data. gmmb_generatehist - Create histS structure from generated data, based on bayesS struct. gmmb_lhood2frac - map PDF values to density quantiles gmmb_frac2lhood - map density quantiles to PDF threshold values General functions gmmb_version - Return version string. getargs - Parse variable argument list into a struct. warning_wrap - Wrapper to allow Matlab R13 style warning calls in Matlab R12 Vlassis code gmmbvl_demo1d gmmbvl_demo2d gmmbvl_ellipse gmmbvl_em gmmbvl_em_gauss gmmbvl_em_init_km gmmbvl_em_step gmmbvl_em_step_partial gmmbvl_kmeans gmmbvl_mixgen gmmbvl_plot2 gmmbvl_rand_split gmmbvl_sqdist Demos gmmb_demo01 - A simple demo presenting FJ-learning and Bayesian classification References: [1] Duda, R.O., Hart, P.E, Stork, D.G, Pattern Classification, 2nd ed., John Wiley & Sons, Inc., 2001. [2] Bilmes, J.A., A Gentle Tutorial of the EM Algorithm and its Application to Parameter Estimation for Gaussian Mixture and Hidden Markov Models International Computer Science Institute, 1998 [3] Figueiredo, M.A.T., Jain, A.K., Unsupervised Learning on Finite Mixture Models, IEEE transactions of pattern analysis and machine intelligence, vol.24, no3, March 2002 [4] Vlassis, N., Likas, A., A Greedy EM Algorithm for Gaussian Mixture Learning, Neural Processing Letters 15, Kluwer Academic Publishers, 2002. http://carol.wins.uva.nl/~vlassis/research/learning/index_en.html [5] Paalanen, P., Kamarainen, J.-K., Ilonen, J., Kälviäinen, H., Feature Representation and Discrimination Based on Gaussian Mixture Model Probability Densities - Practices and Algorithms, Research Report 95, Lappeenranta University of Technology, Department of Information Technology, 2005. Authors: Joni Kamarainen <Joni.Kamarainen@lut.fi> Pekka Paalanen <pekka.paalanen@lut.fi> Acknowledgements: All the gmmbvl_* functions and files are not written by the authors of the Toolbox. They are written by Dr. Nikos Vlassis and Sjaak Verbeek unless otherwise noted in each file and are intellectual property of their writers. The code is included "as is" [4], except the file and function names are changed. The Figueiredo-Jain algorithm implementation is partly based on the code published in http://www.lx.it.pt/~mtf/ Copyright: The GMMBayes Toolbox is Copyright (C) 2003, 2004 by Joni Kamarainen and Pekka Paalanen except the gmmbvl_*.m files which are copyrighted by their respective authors. The software package is free software; you can redistribute it and/or modify it under terms of GNU General Public License as published by the Free Software Foundation; either version 2 of the license, or any later version. For more details see licenses at http://www.gnu.org The software package is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. As stated in the GNU General Public License it is not possible to include this software library or even parts of it in a proprietary program without written permission from the owners of the copyright. If you wish to obtain such permission, you can reach us by mail: Department of Information Processing Lappeenranta University of Technology P.O. Box 20 FIN-53851 Lappeenranta FINLAND and by e-mail: joni.kamarainen@lut.fi pekka.paalanen@lut.fi Please, if you find any bugs contact authors. Project home page: http://www.it.lut.fi/project/gmmbayes/ $Name: $ $Revision: 1.4 $ $Date: 2005/04/14 10:33:34 $