Hi Andreas,
IMHO the only reasonable thing to do is to ignore samples for which
there is no oob estimation.
building a forest with less than 5 trees makes no sense in the first place,
so I would not worry if sklearn doesn't provide any warning for that
specific
problem (too "few" oob estimates).
I'd rather document that the reasonable number of trees should be > 20/30.
Paolo
On Wed, Jan 25, 2012 at 2:20 PM, Andreas <[email protected]> wrote:
> Hi everybody.
> My pull request for oob estimates got merge a couple of days ago.
> Now I noticed a behavior that I am not completely happy with.
> If the number of estimator in the ensemble is small (say 1)
> then the won't be a prediction for all of the samples.
> The way it is currently implemented, there will be NaNs in the
> prediction.
> It is possible to compute the oob accuracies for each estimator
> on it's own but that is not really what one wants, I guess.
>
> Any ideas how to best handle this?
>
> I feel like this estimate only makes sense with n_estimators >> 5
> but even then it is not impossible that one sample will never
> get left out and random NaNs might appear.
>
> Cheers,
> Andy
>
>
> ------------------------------------------------------------------------------
> 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
>
--
Paolo Losi
e-mail: [email protected]
mob: +39 348 7705261
ENUAN Srl
Via XX Settembre, 12 - 29100 Piacenza
------------------------------------------------------------------------------
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
