%PREX_COMBINING PRTools example on classifier combining
%
% Presents the use of various fixed combiners for some
% classifiers on the 'difficult data'.
%
help prex_combining
echo on
% Generate 10-dimensional data
A = gendatd([100,100],10);
% Select the training set of 40 = 2x20 objects
% and the test set of 160 = 2x80 objects
[B,C] = gendat(A,0.2);
% Define 5 untrained classifiers, (re)set their names
% w1 is a linear discriminant (LDC) in the space reduced by PCA
w1 = klm([],0.95)*ldc;
w1 = setname(w1,'klm - ldc');
% w2 is an LDC on the best (1-NN leave-one-out error) 3 features
w2 = featself([],'NN',3)*ldc;
w2 = setname(w2,'NN-FFS - ldc');
% w3 is an LDC on the best (LDC leave-one-out error) 3 features
w3 = featself([],ldc,3)*ldc;
w3 = setname(w3,'LDC-FFS - ldc');
% w4 is an LDC
w4 = ldc;
w4 = setname(w4,'ldc');
% w5 is a 1-NN
w5 = knnc([],1);
w5 = setname(w5,'1-NN');
% Store classifiers in a cell
W = {w1,w2,w3,w4,w5};
% Train them all
V = B*W;
% Test them all
disp([newline 'Errors for individual classifiers'])
testc(C,V);
% Construct combined classifier
VALL = [V{:}];
% Define combiners
WC = {prodc,meanc,medianc,maxc,minc,votec};
% Combine (result is cell array of combined classifiers)
VC = VALL * WC;
% Test them all
disp([newline 'Errors for combining rules'])
testc(C,VC)
echo off