SVM classification weight fitcsvm

Hi,

I am training a linear SVM classifier:

cvFolds = crossvalind('Kfold', labels, nrFolds);

for i = 1:nrFolds                            % iteratre through each fold
    testIdx = (cvFolds == i);                % indices of test instances
    trainIdx = ~testIdx;                     % indices training instances

      % train the SVM
      % 'OptimizeHyperparameters','auto'
      cl = fitcsvm(features(trainIdx,:), labels(trainIdx),'KernelFunction',kernel,'Standardize',true,...
      'BoxConstraint',C,'ClassNames',[0,1], 'Solver', solver);

      [labelPred,scores] =  predict(cl, features(testIdx,:));
      eq = sum(labelPred==labels(testIdx));
      accuracy(i) = eq/numel(labels(testIdx));

end

As is obvious, the trained SVM model is stored in cl. Checking the model parameters in cl I do not see which parameters correspond to classifier weight - feedback much appreciated.

[Ramya k]

how to find Sensitivity of above code?

Answer 1

[Prashant Lawhatre]

weight_vector=c1.Beta;

bais_vector=c1.Bias;