Training and testing the data

Question

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    I got a code from net for SVM classifier 
    clc
    clear all
    load fisheriris                              %# load iris dataset
    groups = ismember(species,'setosa');         %# create a two-class problem
    %# number of cross-validation folds:
    %# If you have 50 samples, divide them into 10 groups of 5 samples each,
    %# then train with 9 groups (45 samples) and test with 1 group (5 samples).
    %# This is repeated ten times, with each group used exactly once as a test set.
    %# Finally the 10 results from the folds are averaged to produce a single
    %# performance estimation.
    k=10;
    cvFolds = crossvalind('Kfold', groups, k);   %# get indices of 10-fold CV
    cp = classperf(groups);                      %# init performance tracker
    for i = 1:k                                  %# for each fold
        testIdx = (cvFolds == i);                %# get indices of test instances
        trainIdx = ~testIdx;                     %# get indices training instances
        %# train an SVM model over training instances
        svmModel = svmtrain(meas(trainIdx,:), groups(trainIdx), ...
            'Autoscale',true, 'Showplot',false, 'Method','QP', ...
            'BoxConstraint',2e-1, 'Kernel_Function','rbf', 'RBF_Sigma',1);
        %# test using test instances
        pred = svmclassify(svmModel, meas(testIdx,:), 'Showplot',false);
        %# evaluate and update performance object
        cp = classperf(cp, pred, testIdx);
    end
    %# get accuracy
    cp.CorrectRate
    %# get confusion matrix
    %# columns:actual, rows:predicted, last-row: unclassified instances
    cp.CountingMatrix
In comment 
%If you have 50 samples, divide them into 10 groups of 5 samples each,
  %# then train with 9 groups (45 samples) and test with 1 group (5 samples).
I have 5x6 samples
have divided 5x4 to training and 5x2 for testing
now please tell how to process above mentioned step