run classify svmΒΆ

Matlab output: run_classify_svm

%% Classification using svm
%
% #   For CoSMoMVPA's copyright information and license terms,   #
% #   see the COPYING file distributed with CoSMoMVPA.           #

if ~cosmo_check_external('svm',false)
    fprintf('No SVM implementation is available, skipping\n');
    return
end

%% Define data
config=cosmo_config();
data_path=fullfile(config.tutorial_data_path,'ak6','s01');

data_fn=fullfile(data_path,'glm_T_stats_perrun.nii');
mask_fn=fullfile(data_path,'vt_mask.nii');
ds=cosmo_fmri_dataset(data_fn,'mask',mask_fn,...
                        'targets',repmat(1:6,1,10)',...
                        'chunks',floor(((1:60)-1)/6)+1)';


% remove constant features
ds=cosmo_remove_useless_data(ds);

%% Two class classification
ds_2class=cosmo_slice(ds, ds.sa.targets==2 | ds.sa.targets==5);
ds_2class_train=cosmo_slice(ds_2class,ds_2class.sa.chunks<=5);
ds_2class_test=cosmo_slice(ds_2class,ds_2class.sa.chunks>5);

pred2=cosmo_classify_svm(ds_2class_train.samples,...
                                ds_2class_train.sa.targets,...
                                ds_2class_test.samples);

fprintf('2-class accuracy %.3f\n', sum(pred2==ds_2class_test.sa.targets)/numel(pred2));
mx=cosmo_confusion_matrix(ds_2class_test.sa.targets,pred2);
imagesc(mx);
colorbar();


%% Four class classification
ds_4class=cosmo_slice(ds, ds.sa.targets>=2 & ds.sa.targets<=5);
ds_4class_train=cosmo_slice(ds_4class,ds_4class.sa.chunks<=5);
ds_4class_test=cosmo_slice(ds_4class,ds_4class.sa.chunks>5);

pred4=cosmo_classify_svm(ds_4class_train.samples,...
                        ds_4class_train.sa.targets,...
                        ds_4class_test.samples);

fprintf('4-class: accuracy %.3f\n', sum(pred4==ds_4class_test.sa.targets)/numel(pred4));

mx=cosmo_confusion_matrix(ds_4class_test.sa.targets,pred4);
imagesc(mx);
colorbar();