comparison toolboxes/FullBNT-1.0.7/netlab3.3/demknn1.m @ 0:e9a9cd732c1e tip

first hg version after svn

+%DEMKNN1 Demonstrate nearest neighbour classifier.
+%
+%	Description
+%	The problem consists of data in a two-dimensional space.  The data is
+%	drawn from three spherical Gaussian distributions with priors 0.3,
+%	0.5 and 0.2; centres (2, 3.5), (0, 0) and (0,2); and standard
+%	deviations 0.2, 0.5 and 1.0. The first figure contains a scatter plot
+%	of the data.  The data is the same as in DEMGMM1.
+%
+%	The second figure shows the data labelled with the corresponding
+%	class given by the classifier.
+%
+%	See also
+%	DEM2DDAT, DEMGMM1, KNN
+%
+
+%	Copyright (c) Ian T Nabney (1996-2001)
+
+clc
+disp('This program demonstrates the use of the K nearest neighbour algorithm.')
+disp(' ')
+disp('Press any key to continue.')
+pause
+% Generate the test data
+ndata = 250;
+randn('state', 42);
+rand('state', 42);
+
+[data, c] = dem2ddat(ndata);
+
+% Randomise data order
+data = data(randperm(ndata),:);
+
+clc
+disp('We generate the data in two-dimensional space from a mixture of')
+disp('three spherical Gaussians. The centres are shown as black crosses')
+disp('in the plot.')
+disp(' ')
+disp('Press any key to continue.')
+pause
+fh1 = figure;
+plot(data(:, 1), data(:, 2), 'o')
+set(gca, 'Box', 'on')
+hold on
+title('Data')
+hp1 = plot(c(:, 1), c(:,2), 'k+')
+% Increase size of crosses
+set(hp1, 'MarkerSize', 8);
+set(hp1, 'LineWidth', 2);
+hold off
+
+clc
+disp('We next use the centres as training examplars for the K nearest')
+disp('neighbour algorithm.')
+disp(' ')
+disp('Press any key to continue.')
+pause
+
+% Use centres as training data
+train_labels = [1, 0, 0; 0, 1, 0; 0, 0, 1];
+
+% Label the test data up to kmax neighbours
+kmax = 1;
+net = knn(2, 3, kmax, c, train_labels);
+[y, l] = knnfwd(net, data);
+
+clc
+disp('We now plot each data point coloured according to its classification.')
+disp(' ')
+disp('Press any key to continue.')
+pause
+% Plot the result
+fh2 = figure;
+colors = ['b.'; 'r.'; 'g.'];
+for i = 1:3
+  thisX = data(l == i,1);
+  thisY = data(l == i,2);
+  hp(i) = plot(thisX, thisY, colors(i,:));
+  set(hp(i), 'MarkerSize', 12);
+  if i == 1
+    hold on
+  end
+end
+set(gca, 'Box', 'on');
+legend('Class 1', 'Class 2', 'Class 3', 2)
+hold on
+labels = ['1', '2', '3'];
+hp2 = plot(c(:, 1), c(:,2), 'k+');
+% Increase size of crosses
+set(hp2, 'MarkerSize', 8);
+set(hp2, 'LineWidth', 2);
+
+test_labels = labels(l(:,1));
+
+title('Training data and data labels')
+hold off
+
+disp('The demonstration is now complete: press any key to exit.')
+pause
+close(fh1);
+close(fh2);
+clear all; 
+