function [projected_features, preserved, model] = reductor(n_p_features,dimension_changer,selected_features,label_set)

%testar com pca
disp('pca/lda')
size(selected_features)
n_p_features
if strcmp(dimension_changer,'pca')
    modelpca = pca(selected_features',n_p_features);
    projected_features = linproj(selected_features',modelpca);
    preserved = sum(modelpca.eigval(1:n_p_features).^2)/sum(modelpca.eigval(1:end).^2);
    model=modelpca;
end




%testar com lda
if strcmp(dimension_changer,'lda')
    disp('project_features')
    size(selected_features)
    size(label_set)
    pf.X=selected_features';
    pf.y=label_set+1; %classes de 1 a nclasses
    model=lda(pf,n_p_features);
    projected_features = linproj(selected_features',model);
    preserved = sum(model.eigval(1:n_p_features).^2)/sum(model.eigval(1:end).^2);
end