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1 function [data, ndata1, ndata2, targets]=gen_data(ndata, seed)
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2 % Generate data from three classes in 2d
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3 % Setting 'seed' for reproducible results
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4 % OUTPUT
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5 % data : data set
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6 % ndata1, ndata2: separator
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7
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8 if nargin<1,
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9 error('Missing data size');
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10 end
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11
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12 input_dim = 2;
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13 num_classes = 3;
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14
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15 if nargin==2,
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16 % Fix seeds for reproducible results
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17 randn('state', seed);
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18 rand('state', seed);
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19 end
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20
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21 % Generate mixture of three Gaussians in two dimensional space
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22 data = randn(ndata, input_dim);
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23 targets = zeros(ndata, 3);
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24
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25 % Priors for the clusters
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26 prior(1) = 0.4;
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27 prior(2) = 0.3;
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28 prior(3) = 0.3;
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29
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30 % Cluster centres
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31 c = [2.0, 2.0; 0.0, 0.0; 1, -1];
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32
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33 ndata1 = round(prior(1)*ndata);
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34 ndata2 = round((prior(1) + prior(2))*ndata);
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35 % Put first cluster at (2, 2)
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36 data(1:ndata1, 1) = data(1:ndata1, 1) * 0.5 + c(1,1);
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37 data(1:ndata1, 2) = data(1:ndata1, 2) * 0.5 + c(1,2);
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38 targets(1:ndata1, 1) = 1;
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39
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40 % Leave second cluster at (0,0)
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41 data((ndata1 + 1):ndata2, :) = data((ndata1 + 1):ndata2, :);
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42 targets((ndata1+1):ndata2, 2) = 1;
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43
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44 data((ndata2+1):ndata, 1) = data((ndata2+1):ndata,1) *0.6 + c(3, 1);
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45 data((ndata2+1):ndata, 2) = data((ndata2+1):ndata,2) *0.6 + c(3, 2);
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46 targets((ndata2+1):ndata, 3) = 1;
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47
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48 if 0
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49 ndata = 1;
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50 data = x;
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51 targets = [1 0 0];
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52 end
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