"Reference to non-existent field 'tutorial_data_path'", this error appears each time I run the code of my gradution project and I don't know how I can solved I tried a lot ..

Christine Zarief

2018 2 13

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Hi,I need help! "Reference to non-existent field 'tutorial_data_path'", this error appears each time I run the code of my gradution project and I don't know how I can solved it I tried a lot .. Thanks in advance

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Christine Zarief 2018-2-13

编辑：Stephen23 2018-2-14

在 MATLAB Online 中打开

%%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();