intRVFL

[denkle]

Created the first draft for intRVFL model that uses 'Abalone' and all other datasets from the collection that would eventually have to be included.
I have left comments starting with "DK:" in multiple places to indicate my doubts.
Hope we will figure them through the interaction.

[mikeheddes]

Great work! It will be very helpful to have an example of using the newly added datasets

[mikeheddes]

This is looking pretty good. I think, however, that the implementation right now is a bit too specific, i.e., it does not allow a lot of flexibility of training and testing setups from the user. So I would suggest to think a bit about how to modularize the code such that users can only use the parts that work for their setup and code the rest themselves. Look at some of my comments for suggestions. Once those are improved we can do another round of feedback to see how we can improve the modularity further.
Thanks again for your hard work!

[mikeheddes]

For the first version of the benchmark I think it is important to not make it too complicated because it will just limit the number of people that are going to use it. I suggested an api from the user perspective. If you want help with how this would be coded up from the library perspective let me know, I'm happy to help.

[denkle]

@mikeheddes, I tried my best to implement your suggestions from the previous review. As usually, happy to continue iterating. It should be admitted that I have not paid detailed attention to the documentation. This would have to be double-checked once we settle down with the structure for the benchmark and its primitives

[mikeheddes]

I think we are getting close to finishing this PR, it's looking very good. Great work!

[mikeheddes]

It looks great! Thank you for the amazing work :)

I will test the code locally this weekend and maybe make some minor refactoring changes and then merge it.

[denkle]

It looks great! Thank you for the amazing work :)

I will test the code locally this weekend and maybe make some minor refactoring changes and then merge it.

Sounds great!

[mikeheddes]

@denkle your code works like a charm! Very good work.

I decided to remove the classification module for now and just add the ridge regression function to the example. We can in a follow up PR try to extract the IntRVFL model to the models module which I think can also include the ridge regression function.
I also made the EncodingDensityClipped a bit more general so it supports other VSA models and renamed it to just Density.
Other than that I added some python typing and mostly made some small modifications.