Predicted confidence of DenseSVMPredictor

Aster
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Predicted confidence of DenseSVMPredictor

Hi,

 

How is the "predicted_confidence" of classification determined for a prediction from the Aster DenseSVMPredictor function? And can the predicted_confidence be interpreted as a probability of the classification? We already searched in the paper that is referred to in the Aster Analytics Foundation Userguide (Hash-SVM: Scalable Kernel Machines for Large-Scale Visual Classification” by Yadong Mu,Gang Hua, Wei Fan, and Shih-Fu Chang ). We cannot find the answer to our question in this paper. Normally, probabilities from SVM are determined as in: "Probabilistic Outputs for Support Vector Machines and Comparisons to Regularized Likelihood Methods, Platt (1999)".  

 

Tnx!

 

3 REPLIES
Teradata Employee

Re: Predicted confidence of DenseSVMPredictor

The predict_confidence is a fraction between 0 and 1, which estimates the quality of the predict result. It is given by the following formula: 1/(1 + exp(-v)), where v is the internal predicted value.
If the predict_confidence is larger, the corresponding result will be more dependable.

Re: Predicted confidence of DenseSVMPredictor

Thanks for your reply. We still have some questions, hopefully you will be able to answer them as wel.

 

So the predict_confidence is not done by Platt scaling ( p(y|X) = 1 / (1 + exp(A * f(X) + B)) ) as done in the aforementioned paper?
Is there a way to extract the internal prediction?
And is the internal prediction equal to the signed distance of a sample from the hyperplane?

 

Thanks!

Teradata Employee

Re: Predicted confidence of DenseSVMPredictor

I am sorry. I do not have these details. In case you are a Teradata or Aster customer, you can open an incident. Customer support will try reaching out to engineering to gather these details. I am not sure whether all answers can be provided but it is worth a try.