Hi Mathieu.
From my point of view, producing sensible probabilities is even harder
than producing
the correct class labels - so I don't think there is a great solution.
For binary classification, you could use LogisticRegression, but I'm not
sure that it really gives
you good estimates.
Maybe I'd go with the RandomForestClassfier?
Cheers,
Andy
On 04/10/2013 07:21 PM, mathieu lacage wrote:
hi,
I wonder if someone could suggest which classifiers are the most
useful to produce probabilities associated with their predictions. In
my case, I am trying to perform a binary classification and I am
trying to obtain an estimate of the probability that the output
classification is correct. I initially started from an SVC but it
seems that producing probability estimates is not one of their biggest
strength. I then turned to bayes classifiers but the sklearn
documentation is pretty clear about the fact that the estimates
produced by these classifiers are "not good". Is there an well known
alternative to do this or am I stuck with trying every possible option
until I find one that appears to work ?
Mathieu
--
Mathieu Lacage <[email protected]
<mailto:[email protected]>>
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