measuring uncertainty in matlabs svmclassify

Posted by Mark on Stack Overflow See other posts from Stack Overflow or by Mark
Published on 2013-03-22T21:14:10Z Indexed on 2013/11/03 9:54 UTC
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I'm doing contextual object recognition and I need a prior for my observations. e.g. this space was labeled "dog", what's the probability that it was labeled correctly? Do you know if matlabs svmclassify has an argument to return this level of certainty with it's classification?

If not, matlabs svm has the following structures in it:

SVM = 
      SupportVectors: [11x124 single]
               Alpha: [11x1 double]
                Bias: 0.0915
      KernelFunction: @linear_kernel
  KernelFunctionArgs: {}
          GroupNames: {11x1 cell}
SupportVectorIndices: [11x1 double]
           ScaleData: [1x1 struct]
       FigureHandles: []

Can you think of any ways to compute a good measure of uncertainty from these? (Which support vector to use?) Papers/articles explaining uncertainty in SVMs welcome. More in depth explanations of matlabs SVM are also welcome.

If you can't do it this way, can you think of any other libraries with SVMs that have this measure of uncertainty?

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