coursera 吴恩达作业第六次提交

gaussianKernel.m

sim=sim+exp(-(x1-x2)'*(x1-x2)/2/sigma^2);

dataset3Params.m

err=10000;
temp=[0.01,0.03,0.1,0.3,1,3,10,30];
for i=1:length(temp)
    for j=1:length(temp)
        model= svmTrain(X, y, temp(i), @(x1, x2) gaussianKernel(x1, x2,temp(j)));
        predictions = svmPredict(model, Xval);        
        if(err>mean(double(predictions ~= yval)))
            err=mean(double(predictions ~= yval));
            C=temp(i);
            sigma=temp(j);
        end
    end
end 

 processEmail.m

for i=1:length(vocabList)
   if(strcmp(vocabList(i),str))
      word_indices=[word_indices;i];
   end
end

emailFeatures.m

for i=1:length(word_indices)
    x(word_indices(i))=1;
end