diff reproduce_AES53rd/rerun_figure2.m @ 0:e9a9cd732c1e tip

first hg version after svn

--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/reproduce_AES53rd/rerun_figure2.m	Tue Feb 10 15:05:51 2015 +0000
@@ -0,0 +1,39 @@
+% ---
+% This script plots 50-dimensional RBM features as in figure 2 of 
+% 
+% Feature Preprocessing with RBMs for Music Similarity Learning
+% Son N. Tran, Daniel Wolff, Tillman Weyde, Artur Garcez, AES53rd
+% conference 
+% ---
+
+% cr_: training correct
+% cr : testing correct
+feature_file = 'rel_music_raw_features+simdata_ISMIR12';
+vars = whos('-file', feature_file);
+A = load(feature_file,vars(1).name,vars(2).name,vars(3).name,vars(4).name);
+raw_features = A.(vars(1).name);
+indices      = A.(vars(2).name);
+tst_inx      = A.(vars(3).name);
+trn_inx      = A.(vars(4).name);
+% 
+figure(1); imagesc(raw_features);colorbar;
+title 'Original Features';
+
+% load pregenerated RBM features
+mod = load('rbm_50');
+
+% ---
+% uncomment the following line to use newly calculated RBM features
+% mod = new_rbm(50,'grad');
+% ---
+
+features = logistic(raw_features*mod.W_max{1} + repmat(mod.hB_max{1},size(raw_features,1),1));
+figure(2); imagesc(features);colorbar;
+title 'RBM Features';
+
+num_case = size(trn_inx,1); 
+[trnd_12 trnd_13] = subspace_distances(trn_inx,features,indices,1,1);
+[tstd_12 tstd_13] = subspace_distances(tst_inx,features,indices,1,1);
+cr_ = 0;   % correct rate for training
+cr  = 0;   % correct rate for testing
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%