diff reproduce_AES53rd/rerun_table3.m @ 0:e9a9cd732c1e tip

first hg version after svn

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+% ---
+% This script trains similarity measures and shows the
+% results regarding RBM of table 3
+%
+% Feature Preprocessing with RBMs for Music Similarity Learning
+% Son N. Tran, Daniel Wolff, Tillman Weyde, Artur Garcez, AES53rd
+% conference 
+% 
+% please note that the RBM training is a probabilistic process, and 
+% thus the papers' results can only be reproduced approximately with 
+% large numbers of iterations of this script, and selection of RBMs according to
+% their training set performance.
+% Here, training is done on 20 random initialisations of RBM features ,
+% the test results corresponding to the RBM with the best training result are then
+% returned.
+%
+% The train and test performances are output in the console
+%
+% For convenicence, The precomputed RBM features are stored in the files
+% accompaining this script.
+% In order to compute new SVM features, delete these files.
+% ---
+
+% ---
+% get svm results for RBM
+% ---
+svm_table3
+% svm_test_performance
+%fprintf('SVM Original Test Result (Wolff etal. 2012)=71.20 / 83.54\n');
+
+% ---
+% get gradient results for RBM
+% ---
+gradient_table3
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