% 
% Written by:
% -- 
% John L. Weatherwax                2007-07-05
% 
% email: wax@alum.mit.edu
% 
% Please send comments and especially bug reports to the
% above email address.
% 
%-----

randn('seed',0); rand('seed',0); 

addpath( fullfile(pwd,'AdaBoost') ); 

% the dimension of the training data: 
dim = 10; 

[patterns_train,labels_train] = gen_data_pt_b(2000,dim);
% the code below expects class labels of 0's and 1's (and a column):
indsm1 = find( labels_train==-1 ); labels_train( indsm1 ) = 0; labels_train = labels_train(:); 

[patterns_test, labels_test ] = gen_data_pt_b(10000,dim);
% the code below expects class labels of 0's and 1's (and a column):
indsm1 = find( labels_test==-1 ); labels_test( indsm1 ) = 0; labels_test = labels_test(:); clear indsm1; 

%%---------------------------------------------------
%FIXED TREE DEPTH, VARYING NUMBER OF WEAK LEARNERS:

%Choose the DEPTH of tree to boost with (1=stumps)
depth = 1;

%Choose the NUMBER of weak learners (trees)
%T_array = [ 1, 10:10:30 ];
%T_array = [ 1, 10:10:400 ];
T_array = [ 1, 10:10:800 ];

err = zeros(length(T_array),2); 
tms = zeros(length(T_array),1); 
for ii = 1:length(T_array)
  T = T_array(ii);
  fprintf('boosting T=%d trees',T);
  if( ii>1 )
    fprintf('; previous round took=(%10.3f sec,%10.3f min,%10.3f hrs)...\n',tms(ii-1),tms(ii-1)/60,tms(ii-1)/3600); 
  else
    fprintf('...\n'); 
  end

  tic;
  [classes, B_t, e_t] = k_adaboost_training(patterns_train, labels_train, depth, T);

  [final_class_train] = k_adaboost_evaluate(patterns_train, classes, B_t);
  error_train = 1-mean(final_class_train==labels_train);

  [final_class_test] = k_adaboost_evaluate(patterns_test, classes, B_t);
  error_test = 1-mean(final_class_test==labels_test);
  
  tms(ii) = toc; 
  err(ii,1) = error_train;
  err(ii,2) = error_test;
end

h_train = plot(T_array,err(:,1),'-gx');
hold on
h_test = plot(T_array,err(:,2),'-bo');
legend( [ h_train, h_test ], { 'training err', 'testing err' } ); 
xlabel( 'number of weak learner boosts' ); ylabel( 'classification error' ); 
axis( [ 0, max(T_array), 0.0, 0.6 ] ); 

%%---------------------------------------------------