
yhat = svmPredict(SVMmodel, Xtest);
svmNerrors = sum(yhat ~= ytest) <span class="comment">%0</span>
</pre><pre class="codeoutput">svmNerrors =
     0
</pre><h2>LR L1<a name="3"></a></h2><pre class="codeinput">lambdaL1 = 1e-3; SigmaL1 = 0.5;
args.lambda = lambdaL1;
args.preproc.kernelFn = @(X1, X2)kernelRbfSigma(X1, X2, SigmaL1);
args.preproc.rescaleX = true;
args.regType = <span class="string">'L1'</span>;
LRL1model = logregFit(Xtrain, ytrain, args);
yhat = logregPredict(LRL1model, Xtest);
lrL1Nerrors = su