[scikit-learn] implementing regularized random forest

[Nicolas Hug]

Mickael,

You probably don't need to ship an entire fork, but all the tree 
internals that you are using (splitter etc.) are part of a private API 
so yes, you would need to duplicate these into your own implementation.

Nicolas

On 11/3/20 4:38 PM, Mick Men wrote:
> Hello,
>
> I am trying to implement my own regularized random forest (RRF) which 
> grows trees in series and selects new features only if they are better 
> than the features used in previous splits.
>
> This is for a research project and I will need to ship the code with 
> the publication. So far I have a working proof of concept where I 
> modified the scikit-learn forest, tree, and splitter modules. But this 
> mean that I need to ship my fork version of scikit-learn.
>
> Ideally, I am looking for a way to build my own RRF that uses 
> scikit-learn API instead of modifying it.
> Is it possible?
>
> Thanks.
>
> Mickael
>
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