hdda_demo.m

来自「高维数据判别分析程序！数据挖掘及图像分析利器！matlab版！」· M 代码 · 共 26 行

% High Dimensionality Discriminant Analysis (demonstration)
%
% Authors: C. Bouveyron <[e-mail]> - 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);