wolffd@0: function [mod] = new_rbm(hidNum,type)
wolffd@0: % computes a new RBM that can be used instead of the saved ones
wolffd@0: 
wolffd@0: conf.hidNum = hidNum;
wolffd@0: conf.eNum   = 150;
wolffd@0: conf.bNum   = 1;
wolffd@0: conf.gNum   = 1;
wolffd@0: conf.N    = 80;
wolffd@0: conf.MAX_INC = 10;
wolffd@0:  
wolffd@0: % use the specific parameters from the paper
wolffd@0: switch type
wolffd@0: 
wolffd@0:     case 'svm' 
wolffd@0:         conf.params = [0.7 0.7 0.1 2.0e-5];
wolffd@0:     case 'grad'
wolffd@0:         conf.params = [0.05 0.1 0.1 2.0e-5];
wolffd@0:     otherwise 
wolffd@0: end
wolffd@0: 
wolffd@0: % load data
wolffd@0: feature_file = 'rel_music_raw_features+simdata_ISMIR12';
wolffd@0: vars = whos('-file', feature_file);
wolffd@0: A = load(feature_file,vars(1).name,vars(2).name,vars(3).name,vars(4).name);
wolffd@0: data = A.(vars(1).name);
wolffd@0: conf.sNum   = size(data,1);
wolffd@0: 
wolffd@0: mod = struct();
wolffd@0: [mod.W_max{1} mod.vB_max{1} mod.hB_max{1}] = training_rbm(conf,zeros(0,0),feature_file);
wolffd@0: