📄 hdda_demo.m
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% High Dimensionality Discriminant Analysis (demonstration)%% Authors: C. Bouveyron <charles.bouveyron@inrialpes.fr> - 2004-2006% % Reference: C. Bouveyron, S. Girard and C. Schmid, "High Dimensional Discriminant Analysis",% Communications in Statistics, Theory and methods, in press, 2007.fprintf('\n- Loading of simulated high-dimensional data\n')fprintf('load(''hd_data.mat'');\n')load('hd_data.mat' );fprintf('\n- Press the keyboard to continue ...\n\n'), pause()fprintf('- Looking for the model with the smallest BIC value\n')fprintf('prms =hdda_learn(X,''model'',''best'',''seuil'',0.2);\n')prms = hdda_learn(X,'model','best','seuil',0.2);fprintf('\n- Press the keyboard to continue ...\n\n'), pause()fprintf('- Learning parameters of a specific model\n')fprintf('prms = hdda_learn(X,''model'',''AiBQiDi'',''seuil'',0.2)\n');prms = hdda_learn(X,'model','AiBQiDi','seuil',0.2);fprintf('\n- Press the keyboard to continue ...\n\n'), pause()fprintf('- Classification of the test data using the learned model\n')fprintf('[cls,P] = hdda_classif(prms,Y)\n');[cls,P] = hdda_classif(prms,Y);
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