%% sspca 
% Semi-supervised classification by PCA, Sonar example, 250 repitions
%
% <http://37steps.com/software/prtools/ PRTools> and
% <http://37steps.com/software/prdatasets/ PRDataSets> should be in the path
%
% <http://37steps.com/exam/sspca/sspca.m Download the m-file from here>.
% see http://37steps.com/prtools for more. 

%% Get data
a = sonar;
a = setprior(a,getprior(a)); % set priors equal to class frequencies
c = getsize(a,3);            % get number of classes
delfigs                      % delete figures

%% Initialization
itermax = 250;               % run over itermax repititions
classf  = setname(qdc,'QDA');% define classifier and its name
T = [2 3 4 5:2:11 15:5:40];  % training set sizes for learnig curves
S = [4 5 7];                 % desired PCA dimensions

n = itermax*numel(T)*numel(S);
q = sprintf('running over %i experiments: ',n);
prwaitbar(n,q);
es = zeros(numel(T),numel(S),itermax); % space for supervised results
eu = zeros(numel(T),numel(S),itermax); % space for semisupervised results

%% Process
r = 0;
for iter = 1:itermax
  for j=1:numel(T)                        % run over training set sizes
    randreset(100*iter+j);                % take care of reproducability
    [X,Y] = gendat(a,T(j)*ones(1,c));     % trainset and testset
    for i=1:numel(S)                      % run over all dims
      r = r+1; prwaitbar(n,r,[q num2str(r)]); % report progress
      es(j,i,iter) = Y*(X*(pcam(+X,S(i))*classf))*testc; % supervised
      eu(j,i,iter) = Y*(X*(pcam(+a,S(i))*classf))*testc; % semisupervised
    end 
  end
end
prwaitbar(0)

%% Present results
semilogx(T,mean(es,3));
hold on; semilogx(T,mean(eu,3),'--');
linewidth(1.5);
legendpar = cell(1,numel(S));
for j=1:numel(S)
  legendpar{j} = ['super dim = ' num2str(S(j))];
end
for j=1:numel(S)
  legendpar{j+numel(S)} = [' semi dim = ' num2str(S(j))];
end
legend(legendpar{:},'Location','SouthWest');
title([getname(classf) ', Learning curves ' getname(a) ' dataset'])
xlabel('# training objects per class')
ylabel(['Averaged class. error (' num2str(itermax) ' exp.)']);
fontsize(14)

%% Adapt to this problem
set(gcf,'Position',[23    57   847   468]);
axis([2 40 0.2 0.51])
set(gca,'xtick',[2 4 10 20 40])