[scikit-learn] custom loss function in RandomForestRegressor

[Andreas Mueller]

I wonder whether this (together with the caveat about it being slow if 
doing python) should go into the FAQ.

On 02/15/2018 12:50 PM, Guillaume Lemaître wrote:
> The ClassificationCriterion and RegressionCriterion are now exposed in 
> the _criterion.pxd. It will allow you to create your own criterion.
> So you can write your own Criterion with a given loss by implementing 
> the methods which are required in the trees.
> Then you can pass an instance of this criterion to the tree and it 
> should work.
>
> On 15 February 2018 at 18:37, Thomas Evangelidis <tevang3 at gmail.com 
> <mailto:tevang3 at gmail.com>> wrote:
>
>     Greetings,
>
>     The feature importance calculated by the RandomForest
>     implementation is a very useful feature. I personally use it to
>     select the best features because it is simple and fast, and then I
>     train MLPRegressors. The limitation of this approach is that
>     although I can control the loss function of the MLPRegressor (I
>     have modified scikit-learn's implementation to accept an arbitrary
>     loss function), I cannot do the same with RandomForestRegressor,
>     and hence I have to rely on 'mse' which is not in accordance with
>     the loss functions I use in MLPs. Today I was looking at the
>     _criterion.pyx file:
>
>     https://github.com/scikit-learn/scikit-learn/blob/master/sklearn/tree/_criterion.pyx
>     <https://github.com/scikit-learn/scikit-learn/blob/master/sklearn/tree/_criterion.pyx>
>
>     However, the code is in Cython and I find it hard to follow. I
>     know that for Regression the relevant class are Criterion(),
>     RegressionCriterion(Criterion), and MSE(RegressionCriterion). My
>     question is: is it possible to write a class that takes an
>     arbitrary function "loss(predictions, targets)" to calculate the
>     loss and impurity of the nodes?
>
>     thanks,
>     Thomas
>
>
>     -- 
>
>     ======================================================================
>
>     Dr Thomas Evangelidis
>
>     Post-doctoral Researcher
>
>     CEITEC - Central European Institute of Technology
>     Masaryk University
>     Kamenice 5/A35/2S049,
>     62500 Brno, Czech Republic
>
>     email: tevang at pharm.uoa.gr <mailto:tevang at pharm.uoa.gr>
>
>     tevang3 at gmail.com <mailto:tevang3 at gmail.com>
>
>
>     website: https://sites.google.com/site/thomasevangelidishomepage/
>     <https://sites.google.com/site/thomasevangelidishomepage/>
>
>
>
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>
>
>
> -- 
> Guillaume Lemaitre
> INRIA Saclay - Parietal team
> Center for Data Science Paris-Saclay
> https://glemaitre.github.io/
>
>
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