Hi,

note first there are 2 implementations of random forests now available in
OTB since release 5.8. One from openCV and the other one from the shark
machine learning library (which allows parallel training). Both
implementations are wrappers around those libraries and you generally have
to dig into libraries documentation to find out such information.

Regarding the criteria, I think that both opencv and shark implementations
use the Gini criterion (for shark I'm quite sure). Would be glad if someone
who know a bit more those implementations can confirm this.

Note also that I don't think that we have a way in otb to change this
criteria with shark implementation even if there is a way to do this in
shark base class. Perhaps something that could be added to the
SharkMachineLearningModel in the future.

Regards,


2017-03-27 9:46 GMT+02:00 Nafissa Sfaksi <[email protected]>:

> Hi,
> With the tool TrainClassifier we can put several parameters but is it
> possible to see which criteria is used for the method?
> I mean the tool use Gini criterion or entropy criterion?
> Thanks for reply
> Nafissa
>
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-- 
Manuel Grizonnet

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