SVM to return probabilistic output

Re: SVM to return probabilistic output
Yes, the usual one used for SVMs is proposed by Platt:
http://citeseerx.ist.psu.edu/viewdoc...10.1.1.41.1639 which is of the form and estimates and by a logisticregression like optimization problem. An improved implementation for calculating and can be found in HsuanTien Lin, ChihJen Lin, and Ruby C. Weng. A Note on Platt's Probabilistic Outputs for Support Vector Machines. Machine Learning, 68(3), 267276, 2007. http://www.csie.ntu.edu.tw/~htlin/pa.../plattprob.pdf Hope this helps. 
Re: SVM to return probabilistic output
Thanks!

Re: SVM to return probabilistic output
Yes. Thank you. Very interesting. I read both papers (well, skimmed some parts) and basically followed but I do have a general question.
I can understand A as a saturation factor or gain, but at first glance B is a little confusing. If B is nonzero, then the probability at the decision boundary will not be 1/2. Is the reason for needing nonzero B that the mapping from Y>T no longer just maps +1 to 1, and 1 to 0, but rather to two values in (0,1) based on the relative number of +1s to 1s? 
Re: SVM to return probabilistic output
And just out of curiosity  as an extension to the original question:
Can SVMs be used for regression? If so, do they perform better than the regression methods we have learned about in the course? Thanks. Samir 
Re: SVM to return probabilistic output
Quote:
Hope this helps. 
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