Insights module and SHAPInsight

[Alex6022]

Dear @Scienfitz and @AdrianSosic,

As you previously offered in PR #335, I have taken a shot at integrating SHAP analysis amongst other explainers provided by the SHAP package. Similar to the Polars integration, it is provided as an optional dependency. As suggested, I have included tests, ensured it works with hybrid spaces and molecular encodings, implemented it as another utility and decoupled the computation and plotting methods. It also uses the exposed surrogate implemented in PR #355.

The Explanation object provided by the SHAP package can be created through
shap_kern = explanation(campaign)

This object can then be passed to the plotting functions wrapped from the SHAP package:
plot_beeswarm(shap_kern)

Additionally, this implementation allows users to selected whether to use the computational or experimental representation of the search space. E.g., while the experimental representation can give a good overview of the important parameters:

, the computational representation can give more advanced users the option to understand which encodings specifically predict the target:

Please let me know if you have any further input for improving this. Looking forward to it!

[AdrianSosic]

Hi @Alex6022, awesome that you gave it a shot 🎖️ I just returned from my vacation on the weekend. Let me have a thorough look at the code, exchange with @Scienfitz, and then we'll share with you our consolidated thoughts 👍🏼

[Scienfitz]

sorry for taking long, busy days :) but we see your contribution 👍
I'm leaving some initial comments here (and theres also something for you in #357), as I took a first look now, I'll discuss the structure question with the others, some more requests especially regarding the main file will definitely come later

[AVHopp]

Gave it a very brief additional check, LGTM so here is my approve :)

In case anything comes up where you need an additional opinion, just summon me again, otherwise I have nothing left to say other than thanks for the contribution!

[AdrianSosic]

Hi @Alex6022, for my part, the PR is good to go (except for the remaining open threads that I leave to @Scienfitz). Again, many thanks for this great piece of work, and also for your perseverance! 🥇

[Scienfitz]

@Alex6022 many thanks also from my side, super cool contribution, please let us know if you need any reference or endorsement in the future :). This will be part of the next LinkedIn shoutout for the version release, I assume your fine with being explicitly mentioned? If not let me know in any form or way