%PREX_COMBINING   PRTools example on classifier combining%% Presents the use of various fixed combiners for some % classifiers on the 'difficult data'.%help prex_combiningecho 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