[scikit-learn] Scikit-learn porting strategy

[Andreas Mueller]

There's some stuff already:
https://github.com/SciRuby/

And in terms of strategy:
No, you can go estimator by estimator and at some point implement 
cross-validation and grid-search and pipelines and metrics pretty 
independently.

It looks like daru is written in ruby which I expect to be too slow.
nmatrix is written in C++, so I guess you'd have to write many of the 
algorithms in C++.

At that point it might be easier to wrap an existing C++ library like 
mlpack or shogun.

On 2/5/19 6:12 AM, Joel Nothman wrote:
> If you count things in Scipy and NumPy (and Joblib and Cython?) that 
> Scikit-learn depends on and which may be lacking or hard to find 
> in SciRuby, it's much much more than 39 years. PyCall, and potentially 
> some Scikit-learn-specific wrappers around it, seems a much more 
> sensible approach.
>
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