add constructor for binary classifiers

[tiemvanderdeure]

This PR adds a separate constructor NeuralNetworkBinaryClassifier for binary classification.

Unlike for the existing NeuralNetworkClassifier constructor, in the final layer always has size 1. By default, a sigmoid function is used to transform this layer. This is a pretty common thing to use neural networks for, and as far as I can tell it's not possible with the existing constructors.

I'll add tests and documentation if this PR gets some support.

PR Checklist

• Tests are added
• Documentation, if applicable

[tiemvanderdeure]

I think the test failures are unrelated to this PR?

[ablaom]

@tiemvanderdeure Thanks for this PR, which looks like a valuable contribution. I'll try to investigate the fail soon and get back you.

[ablaom]

@tiemvanderdeure The source of your fail is sorted. Do you mind rebasing onto dev?

[ablaom]

Thanks @tiemvanderdeure for this contribution and taking the time to wrap your head around the code base.

I can see attention to detail in the PR, which is much appreciated. I couldn't spot any flaws in your implementation. Are you happy to add some tests?

[tiemvanderdeure]

Thanks for reviewing. I'll add some tests and documentation later this week!

[ablaom]

@tiemvanderdeure I'm tweaking the tests a bit at #251. I suggest you wait till I finish that before writing your tests. Sorry for any inconvenience.

[ablaom]

Regarding tests: I don't think it is nessary to run testoptimiser or to compare predictions b/w CPU/GPU, as we do for the other classifier. The basictest should suffice.

[ablaom]

Re documentation. In view of #252 just merged, you just need to update the table at https://github.com/FluxML/MLJFlux.jl/blob/dev/docs/src/interface/Summary.md and write a model doc-string, modelled on the existing classifier.