I can not use libsvm!!!

download it from ( http://www.csie.ntu.edu.tw/~cjlin/libsvm/#download)
add the svmtrain, svmpredict, libsvmwrite & libscmread .mex Files to your matlab path (probably you just put them in the working folder...)

then let me provide you my sample code - note: I use precompiled kernel data.

Here, I would like to find the optimal parameter c for my SVM.

    clear all; close all; 
 %%load datasets
    [lvtest,  test]  = libsvmread('test.krnl');
    [lvtrain, train] = libsvmread('train.krnl');
    [lvvalid, valid] = libsvmread('valid.krnl');
 %%optimize parameter c on validation set
    n = -17:17;
    accuracy = nan(size(n));
    for i=1:numel(n);   % n = {-17,...,17}
        c=2^n(i);       
        % create model
        model = svmtrain(lvtrain, train,['-q -t 4 -c ' num2str(c)]); 
            % option: -t 4 -> precomputed kernel
        [lbl, acc, dec] = svmpredict(lvvalid, valid, model);
        accuracy(i) = acc(1);
    end
    % output the accuracy vs the chosen parameter c
    plot(accuracy);
    xlabel('c'), ylabel('Accuracy'); title('Accuracy vs. c');
 %%test optimal c on the test set
    [~, i] = max(accuracy); % find the best value
    c = 2^n(i);             % this is the optimal c
    % create model
    model = svmtrain(lvtrain, train,['-q -t 4 -c ' num2str(c)]); 
    % test on the testset
    [lbl, acc, dec] = svmpredict(lvtest, test, model, []);
    % show accuracy
    disp(['Accuracy with optimized c (' ...
          num2str(c) ') on Testset: ' num2str(acc(1)) '%']);

hope this helps...?

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judy frost 2013-9-23

Can you please explain the example further by showing how to find optimal cost and gamma values from validation data that are used for k-fold cross validation. Furthermore is it possible to plot the graph of classified data at the end of validation,training and test stages. I will appreciate any further explanation regarding the topic. Thank you.

Najiyah Valappil 2020-3-16