Anilkumar Panda

Open a PR for this issue #40

It works with both numerical and categorical variables. Refer this [example](https://skope-rules.readthedocs.io/en/latest/auto_examples/plot_credit_default.html).

I would be happy to make the changes, if you agree.

Generally the number of features and performance would form an convex curve. With the performance to be lower with all features, increasing(or staying constant) with the removal of certain features...

We also have the Features to keep update in SHAPRFECV #50

This [blogpost](https://gsarantitis.wordpress.com/2020/04/16/data-shift-in-machine-learning-what-is-it-and-how-to-detect-it/) identifies different types of datashift and provides some ways of tackling it. TL;DR: There are 3 types of data shifts possible : 1. Co-variate shift : * The...

I agree with the above points. The feature is a large one and needs to be separated. I will create a separate issues for this one. Linking them to this...

Hey @orchardbirds @satya-pattnaik do you still plan to work on this issue ? Let me know how we can help you.

Hi @rishabsinghh thanks for picking this up.