2012/6/17 Fred Mailhot <[email protected]>:
> 1) I'd like to compute the class probs; are the probs for the individual OvR
> classifiers (easily) accessible? My intuition is that I can compute these
> from the returned vals from decision_function(), then do the normalization
> afterward...
When loss == "log" and len(self.classes_) == 2, predict_proba returns
1.0 / (1.0 + np.exp(-self.decision_function(X)))
i.e. the logistic function of decision_function's output, which can be
generalized to the softmax function in the obvious way.
--
Lars Buitinck
Scientific programmer, ILPS
University of Amsterdam
------------------------------------------------------------------------------
Live Security Virtual Conference
Exclusive live event will cover all the ways today's security and
threat landscape has changed and how IT managers can respond. Discussions
will include endpoint security, mobile security and the latest in malware
threats. http://www.accelacomm.com/jaw/sfrnl04242012/114/50122263/
_______________________________________________
Scikit-learn-general mailing list
[email protected]
https://lists.sourceforge.net/lists/listinfo/scikit-learn-general
