neub

01-17-2008, 07:12 AM

Hello,

I've trained a SVM classifier with two classes that works correctly but the problem is that my output is binary, and not between [0-1].

This is okay if it was for a classification but i want the ouput of the SVM to be the input of probabilistic classification schema (BayesNetwork), therefore it would be great to have value between [0-1] depending on the distance from the support vectors.

I've read in Witten2005 (Chap.10 - p.410):

Logistic regression models can be fitted to the support

vector machine output to obtain probability estimates.

But i don't really know how to do this?

PS: a simple feature to include in Weka should be to have confusion matrix in percent for a better visualisation.

I've trained a SVM classifier with two classes that works correctly but the problem is that my output is binary, and not between [0-1].

This is okay if it was for a classification but i want the ouput of the SVM to be the input of probabilistic classification schema (BayesNetwork), therefore it would be great to have value between [0-1] depending on the distance from the support vectors.

I've read in Witten2005 (Chap.10 - p.410):

Logistic regression models can be fitted to the support

vector machine output to obtain probability estimates.

But i don't really know how to do this?

PS: a simple feature to include in Weka should be to have confusion matrix in percent for a better visualisation.