function errorStruct = computeClassificationPerformanceTrainTest(numFeatures, sizeTest, ftrain_all, ftest_all, TrnLabels, TestLabels, stepPrint, numCoresKnn, fidLogs, param)

%1-NN classifier (Nearest Neighbor)

fprintf_pers(fidLogs, '\t\tClassification... \n');

%display

fprintf_pers(fidLogs, ['\t\tNumber of features: ' num2str(numFeatures) '\n']);

fprintf_pers(fidLogs, ['\t\tNumber of samples: ' num2str(sizeTest) '\n']);

%time

tic

% [TestOutput, distMatrixTest] = computekNNClassificationPerformance(ftest_all, TestLabels, sizeTest, stepPrint, numCoresKnn, param);

[TestOutput, distMatrixTest] = computekNNClassificationPerformanceTrainTest(ftrain_all, ftest_all, TrnLabels, TestLabels, sizeTest, stepPrint, numCoresKnn, param);

%Time for feature extraction

timeClass = toc;

fprintf_pers(fidLogs, ['\t\tTime for classification: ' num2str(timeClass) ' s\n']);

%Confusion matrix

C_knn = confusionmat(TestLabels, TestOutput);

%pause

%Error metrics

errorStruct = computeErrorsFromCM(C_knn);

errorStruct.distMatrixTest = distMatrixTest;

errorStruct.rank5 = [];