[scikit-learn] custom estimator with more than two arguments to fit()

[Gregory, Matthew]

Hi Nicolas,

Nicolas Hug wrote:
> We do have CCA and other PLS-related transformers / regressors in
> scikit-learn. They are able to do dimensionality reduction on both
> X and Y (which I believe correspond to spp and env), so you might
> want to have a look at these. However, they're not fully
> compatible with the whole ecosystem unfortunately: for example our
> Pipeline objects assume that only X can be transformed, not Y.

Just to clarify, I'm only seeing canonical *correlation* analysis and not canonical *correspondence* analysis (ter Braak) in scikit-learn?

https://scikit-learn.org/stable/modules/generated/sklearn.cross_decomposition.CCA.html

But your point is taken - I can use this for inspiration because it has both X and Y matrices.  But if I'm understanding correctly, there is no way to couple this with a further step of NearestNeighbors into a pipeline?  I will only need the transformed scores coming out of CCA to feed into the NearestNeighbors step.  Sorry if I'm not understanding this correctly.

matt