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1 function [count total] = gen_classify(W, visB, hidB,mW,test_file,test_label);
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2 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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3 % RBM for generative classification %
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4 % conf: training setting %
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5 % WW = [W visB hidB] %
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6 % mW: mask of connections %
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7 % -*-sontran2012-*- %
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8 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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9 %% Loading data & label
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10 vars = whos('-file', test_file);
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11 A = load(test_file,vars(1).name);
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12 data = A.(vars(1).name);
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13 vars = whos('-file', test_label);
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14 A = load(test_label,vars(1).name);
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15 label = A.(vars(1).name);
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16 assert(size(data,1) == size(label,1),'[KRBM-GEN] Number of data and label mismatch');
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17 Classes = unique(label)';
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18 lNum = size(Classes,2);
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19 %% Loading structure
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20 [total visNum]= size(data);
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21 sNum = 500; % fix
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22 bNum = floor(total/sNum); % divide the testing samples to batches of sNum
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23 %% Classifying
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24 count = 0;
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25 for i=1:bNum
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26 % Find the position of softmax unit which make lowest free energy
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27 L = lowest_fenergy(data((i-1)*sNum + 1:i*sNum,:),W, visB, hidB,Classes);
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28 count = count + sum(L==label((i-1)*sNum + 1:i*sNum));
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29 end
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30 L = lowest_fenergy(data(bNum*sNum + 1:total,:),W, visB, hidB,Classes);
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31 count = count + sum(L==label(bNum*sNum + 1:total));
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32 fprintf('Correct rate: %f (%d/%d)\n',count/total,count,total);
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33 clear A vars data lNum sNum bNum out;
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34 end
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35
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