Anthony Blaom, PhD

Model-specific documentation is not currently collated. Part of the GSoD project is to create and organise such a collation. So I'd have to write a script that loads every model...

@ExpandingMan Thank you for spending some substantial time with MLJ's learning networks. And your feedback is very much appreciated. You raise a few interesting issues here, and I don't have...

Oh, by the way, a PR to clarify the status quo in the documentation would be very welcome.

@ExpandingMan Although it's not part of the public API, TableTransforms has the `tablehcat` method: ```julia julia> table1 3×2 DataFrame Row │ x z │ Char Float64 ─────┼─────────────────── 1 │ 𘂯...

> It seems this is the fundamental issue at the core of the matter. It seems to me that for machine learning what is needed is an object with n...

> I can tell there is no standard for what type is returned by a particular machine component So generally, transformers in MLJ that train on a table will transform...

Okay this design won't do because of ambiguity with `models(matching(X, y))`. Also I don't like the fact that `matching` is forcing us to couple model search code with measure search...

Another nice enhancement would be to allow kwargs for searching over trait values, as in `models(package_name="ScikitLearn", is_supervised=true)`. Currently we have the ugly ```julia models() do m m.package_name(m) == ScikitLearn" &&...

cc @boliu-christine

Here's an update on my suggestion for the format of feature importances, as returned by the proposed method `feature_importances(model, report)`. I think allowing models to expose multiple types of feature...