GMMB_HIST Create histS structure from data for PDF-value - density quantile mapping histS = GMMB_HIST(data, type, bayesS) data, type are the training data used to create the bayesS. This function creates ordered lists of training sample PDF-values for PDF-value - density quantile mapping. See gmmb_generatehist, gmmb_lhood2frac, gmmb_frac2lhood, gmmb_fracthresh References: [1] 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. Author(s): Pekka Paalanen <pekka.paalanen@lut.fi> Jarmo Ilonen <jarmo.ilonen@lut.fi> Joni Kamarainen <Joni.Kamarainen@lut.fi> Copyright: Bayesian Classifier with Gaussian Mixture Model Pdf functionality is Copyright (C) 2004 by Pekka Paalanen and Joni-Kristian Kamarainen. $Name: $ $Revision: 1.2 $ $Date: 2005/04/14 10:33:34 $
0001 %GMMB_HIST Create histS structure from data for PDF-value - density quantile mapping 0002 % 0003 % histS = GMMB_HIST(data, type, bayesS) 0004 % 0005 % data, type are the training data used to create the bayesS. 0006 % 0007 % This function creates ordered lists of training sample 0008 % PDF-values for PDF-value - density quantile mapping. 0009 % 0010 % See gmmb_generatehist, gmmb_lhood2frac, gmmb_frac2lhood, gmmb_fracthresh 0011 % 0012 % References: 0013 % [1] Paalanen, P., Kamarainen, J.-K., Ilonen, J., Kälviäinen, H., 0014 % Feature Representation and Discrimination Based on Gaussian Mixture Model 0015 % Probability Densities - Practices and Algorithms, Research Report 95, 0016 % Lappeenranta University of Technology, Department of Information 0017 % Technology, 2005. 0018 % 0019 % Author(s): 0020 % Pekka Paalanen <pekka.paalanen@lut.fi> 0021 % Jarmo Ilonen <jarmo.ilonen@lut.fi> 0022 % Joni Kamarainen <Joni.Kamarainen@lut.fi> 0023 % 0024 % Copyright: 0025 % 0026 % Bayesian Classifier with Gaussian Mixture Model Pdf 0027 % functionality is Copyright (C) 2004 by Pekka Paalanen and 0028 % Joni-Kristian Kamarainen. 0029 % 0030 % $Name: $ $Revision: 1.2 $ $Date: 2005/04/14 10:33:34 $ 0031 % 0032 0033 function histS = gmmb_hist(data_, type_, bayesS); 0034 0035 K = size(bayesS,2); 0036 0037 histS = {}; 0038 0039 for k = 1:K 0040 samples = data_(type_==k, :); 0041 dens = gmmb_pdf( samples, bayesS(k) ); 0042 histS(k) = {sort(dens)}; 0043 end