feat: [DistributionBalanceMeasure] Add implementation + unit tests for custom reference distribution

[ms-kashyap]

Related Issues/PRs

Original PR for distribution balance measures - #1218

What changes are proposed in this pull request?

Context

Distribution balance measures are distance measures that can be computed between two distributions, typically between a reference and observed distribution.

These measures can help us create responsible AI products, i.e., seeing if a column (such as Gender or Ethnicity or any col) doesn't have a large skew towards one value which may lead to a biased model.

This PR

Until now, these distance measures were computed using a uniform reference distribution, meaning we expect to see each unique value in a column the same amount.

This PR allows users to specify a custom reference distribution in the form of a <string, double> map that contains <feature value, feature probability> pairs.

This will particularly be helpful for measuring data drift, where the custom reference distribution is the distribution of a baseline dataset column and the observed distribution is the distribution of the latest-versioned dataset column.

How is this patch tested?

• I have written tests (not required for typo or doc fix) and confirmed the proposed feature/bug-fix/change works.

Does this PR change any dependencies?

• No. You can skip this section.
• Yes. Make sure the dependencies are resolved correctly, and list changes here.

Does this PR add a new feature? If so, have you added samples on website?

• No. You can skip this section.
• Yes. Make sure you have added samples following below steps.

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   Make sure you choose the correct class estimators/transformers and namespace.
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3. Make sure the DocTable points to correct API link.
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5. Don't forget to add <!--pytest-codeblocks:cont--> before each python code blocks to enable auto-tests for python samples.
6. Make sure the WebsiteSamplesTests job pass in the pipeline.

[github-actions]

Hey @ms-kashyap 👋!
Thank you so much for contributing to our repository 🙌.
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[ms-kashyap]

/azp run

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[codecov-commenter]

Codecov Report

Merging #1885 (f9f2486) into master (412620a) will decrease coverage by 5.98%.
The diff coverage is 89.65%.

@@            Coverage Diff             @@
##           master    #1885      +/-   ##
==========================================
- Coverage   86.95%   80.98%   -5.98%     
==========================================
  Files         301      301              
  Lines       15565    15586      +21     
  Branches      797      805       +8     
==========================================
- Hits        13535    12622     -913     
- Misses       2030     2964     +934     

Impacted Files	Coverage Δ
...se/ml/exploratory/DistributionBalanceMeasure.scala	96.33% <89.65%> (-2.54%)	⬇️

... and 20 files with indirect coverage changes

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[ms-kashyap]

/azp run

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Azure Pipelines successfully started running 1 pipeline(s).