%PREX_COST PRTools example on cost matrices and rejection%% Prtools example code to show the use of cost matrices and how% to introduce a reject class.help prex_costecho on                % Generate a three class problem  randn('state',1);  rand('state',1);  n = 30;  class_labels = char('apple','pear','banana');  a = [gendatb([n,n]);  gauss(n,[-2 6])];  laba = genlab([n n n],class_labels);  a = setlabels(a,laba);                % Compute a simple ldc  w = ldc(a);                % Scatterplot and classifier  figure;  gridsize(30);  scatterd(a,'legend');  plotc(w);                % Define a classifier with a new cost matrix,					 % which puts a high cost on misclassifying					 % pears to apples  cost = [0.0  1.0  1.0;          9.0  0.0  1.0;		    1.0  1.0  0.0];  wc = w*classc*costm([],cost,class_labels);  plotc(wc,'b');                % Define a classifier with a cost matrix where					 % an outlier class is introduced. For this an					 % extra column in the cost matrix has to be defined.					 % Furthermore, the class labels have to be supplied					 % to give the new class a name.  cost = [0.0  1.0  1.0  0.2;          9.0  0.0  1.0  0.2;          1.0  1.0  0.0  0.2];  class_labels = char('apple','pear','banana','reject');  wr = w*classc*costm([],cost,class_labels);  plotc(wr,'--')echo offdisp(' ')disp('   The black decision boundary shows the standard ldc classifier');disp('   for this data. When the misclassification cost of a pear to an');disp('   apple is increased, we obtain the blue classifier. When on top');disp('   of that a rejection class is introduced, we get the blue dashed');disp('   classifier. In that case, all objects between the dashed lines');disp('   are rejected.');fprintf('\n');fprintf('  Cost of basic classifier  =  %4.2f\n',...             a*w*testcost([],cost,class_labels));fprintf('  Cost of cost classifier   =  %4.2f\n',...             a*wc*testcost([],cost,class_labels));fprintf('  Cost of reject classifier =  %4.2f\n',...             a*wr*testcost([],cost,class_labels));