%% adaboost_ex 
% Adaboost 2D examples based on perceptrons and decision stumps
%
% <http://37steps.com/software/prtools/ PRTools> should be in the path.
% <http://37steps.com/exam/adaboost_ex/adaboost_ex.m Download the m-file from here,>
%
% See http://37steps.com/prtools for more. 

%% Generate simple 2D examples
randreset; % for reproducability
a = prdataset([gencirc(100);gencirc(100)*0.5],genlab([100 100]));
a = setprior(a,0);
delfigs

%% Run adaboost, 200 iterations, linear peceptron as weak classifier
figure; w = adaboostc(a,perlc([],1),200,[],1);
title('200 base classifiers: single epoch linear perceptron');
fontsize(14);
figure; scatterd(a); plotc(w)
title('Result adaboost, 200 weak classifiers combined');
fontsize(14);

%% Run adaboost, 200 iterations, decision stump as weak classifier
figure; w = adaboostc(a,stumpc,200,[],3);
title('200 base classifiers: single epoch decision stump');
fontsize(14);
figure; scatterd(a); plotc(w)
title('Result adaboost, 200 weak classifiers combined');
fontsize(14);
%showfigs