# Demo entry 6781024

**v**

Submitted by **anonymous**
on Dec 31, 2018 at 07:01

Language: Matlab. Code size: 620 Bytes.

CArr = [0.01, 0.03, 0.1, 0.3, 1, 3, 10, 30]; sigmaArr = [0.01, 0.03, 0.1, 0.3, 1, 3, 10, 30]; C_Temp = 1; sigma_Temp = 0.3; err = Inf; for i = 1:length(CArr) for j = 1:length(sigmaArr) C_Temp = CArr(i); sigma_Temp = sigmaArr(j); model = svmTrain(X, y,C_Temp, @(x1, x2) gaussianKernel(x1, x2, sigma_Temp)); predictions = svmPredict(model, Xval); if(mean(double(predictions ~= yval)) < err) C = C_Temp; sigma = sigma_Temp; err = mean(double(predictions ~= yval)); end end end

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