use column names instead of indices

[tiemvanderdeure]

This package currently uses indices throughout, which can lead to unexpected errors and confusing results. I think we should switch to use keys instead.

For instance

N = 1000
X = (x1 = rand(Float32, N), x2 = randn(Float32, N), x3 = categorical(rand('a':'c', N)))
y = categorical(bitrand(N))

model = MLJFlux.NeuralNetworkBinaryClassifier(epochs = 10, builder=MLJFlux.MLP(; hidden=(5,4)), batch_size = 100)
mach = machine(model, X, y)
fit!(mach)

# this errors
predict(mach, (x3 = X.x3, x1 = X.x1, x2 = X.x2))

# this is false!
all(predict(mach, (x2 = X.x2, x1 = X.x1, x3 = X.x3)) .≈ predict(mach, X))

[ablaom]

Mmm. I think this kind of implicit assumption - that the columns of tables are ordered, and that they be presented in a consistent order, is everywhere in MLJ, and probably elsewhere. [Transferring this issue to MLJ].

One could either try to allow tables to be presented in any column order, or throw a warning when the original order is violated. Personally, I think the latter would be sufficient. If MLJ had a generic data-front end for dealing with tables, apart from Tables.matrix which dumps the feature names, this could be an easy fix either way. But a lot of interfaces just don't save the feature names.

I'd support some kind of resolution, but it's a big ask to fix everywhere.

Thanks @tiemvanderdeure for flagging this issue.

[ablaom]

[Transferring this issue to MLJ].

Okay, can't do that in the usual way, this is a different org. Will create a new issue at MLJ and close here.

[ablaom]

Closing in favor of JuliaAI/MLJ.jl#1144