Add Maximum Relevance Minimum Redundancy as feature selection algorithm

[konst-int-i]

Is your feature request related to a problem? Please describe.
Feature is not directly related to a problem, but is rather an enhancement of existing functionality. As suggested by Julian King on the facet Slack channel, we could add Maximum Relevance Minimum Redundancy (MRMR) as a feature selection algorithm.

The algorithm is explained in the following papers:
https://arxiv.org/pdf/1908.05376.pdf
https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-016-1423-9

Describe the solution you'd like
Implement MrmrDF in a similar fashion to BorutaDF such that it can be passed into the sklearndf pipeline.

Describe alternatives you've considered
The paper also suggests using a redundancy matrix in to shine some light on the feature selection as shown below. While this is for discussion, I would not use this output to avoid confusion with the shap value redundancy calculated as part of the feature selection.