comparison toolboxes/FullBNT-1.0.7/bnt/examples/static/HME/gen_data.m @ 0:e9a9cd732c1e tip

first hg version after svn

+function [data, ndata1, ndata2, targets]=gen_data(ndata, seed)
+% Generate data from three classes in 2d
+% Setting 'seed' for reproducible results
+% OUTPUT
+% data : data set
+% ndata1, ndata2: separator
+
+if nargin<1,
+   error('Missing data size');
+end
+
+input_dim = 2;
+num_classes = 3;
+
+if nargin==2,
+   % Fix seeds for reproducible results
+   randn('state', seed);
+   rand('state', seed);
+end
+
+% Generate mixture of three Gaussians in two dimensional space
+data = randn(ndata, input_dim);
+targets = zeros(ndata, 3);
+
+% Priors for the clusters
+prior(1) = 0.4;
+prior(2) = 0.3;
+prior(3) = 0.3;
+
+% Cluster centres
+c = [2.0, 2.0; 0.0, 0.0; 1, -1];
+
+ndata1 = round(prior(1)*ndata);
+ndata2 = round((prior(1) + prior(2))*ndata);
+% Put first cluster at (2, 2)
+data(1:ndata1, 1) = data(1:ndata1, 1) * 0.5 + c(1,1);
+data(1:ndata1, 2) = data(1:ndata1, 2) * 0.5 + c(1,2);
+targets(1:ndata1, 1) = 1;
+
+% Leave second cluster at (0,0)
+data((ndata1 + 1):ndata2, :) = data((ndata1 + 1):ndata2, :);
+targets((ndata1+1):ndata2, 2) = 1;
+
+data((ndata2+1):ndata, 1) = data((ndata2+1):ndata,1) *0.6 + c(3, 1);
+data((ndata2+1):ndata, 2) = data((ndata2+1):ndata,2) *0.6 + c(3, 2);
+targets((ndata2+1):ndata, 3) = 1;
+
+if 0
+  ndata = 1;
+  data = x;
+  targets = [1 0 0];
+end