I recently (yesterday) switched from scikit 0.9 to scikit 0.11 (dev) so
as to get latest code. I use scikit for multiclass classification from
which I retrieve probability estimates. Untli now, I was very satisfied
using LogisticRegression classifier.
Apparently, the LogisticRegression doesn't implement multiclass
classificaiton in a native way anymore? Since I switched, I get very
very poor results (as was the case for SVM previously).
My classification problem is quite high dimensional and very sparse (45K
features * 1M samples). I was suspecting OvA was rather unefficient for
that kind of problem. Could you confirm you moved LogisticRegression
from native multiclass classification to OvA approach ? Or are there any
other changes from 0.9 to 0.11 that may explain this degradation of
performances ?
Regards,
Damien
--
[email protected]
GSM: +33 (0)6 63 56 27 17
------------------------------------------------------------------------------
Keep Your Developer Skills Current with LearnDevNow!
The most comprehensive online learning library for Microsoft developers
is just $99.99! Visual Studio, SharePoint, SQL - plus HTML5, CSS3, MVC3,
Metro Style Apps, more. Free future releases when you subscribe now!
http://p.sf.net/sfu/learndevnow-d2d
_______________________________________________
Scikit-learn-general mailing list
[email protected]
https://lists.sourceforge.net/lists/listinfo/scikit-learn-general
