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 <teva...@gmail.com
<mailto:teva...@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: tev...@pharm.uoa.gr <mailto:tev...@pharm.uoa.gr>
teva...@gmail.com <mailto:teva...@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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