Add data validations to SDK defined cohorts

[gaugup]

Description

The following validations need to be performed for cohort filter with
test data:-

High level validations

1. Validate if the filter column is present in the test data.
2. Validate if the filter column is present in the special column
   list.

"Index" Filter validations

1. The Index filter only takes integer arguments.
2. The Index filter doesn't take CohortFilterMethods.EXCLUDES
   filter method.

"Classification Outcome" Filter validations

1. Validate that "Classification Outcome" filter is not configure for
   multiclass classification and regression.
2. The "Classification Outcome" filter only contains values from set
   ClassificationOutcomes.
3. The "Classification Outcome" filter only takes
   CohortFilterMethods.INCLUDES filter method.

"Error" Filter validations

1. Validate that "Error" filter is not configure for
   multiclass classification and binary classification.
2. Only integer or floating points can be configured as arguments.
3. The CohortFilterMethods.INCLUDES and CohortFilterMethods.EXCLUDES
   filter methods cannot be configured for this filter.

"Predicted Y/True Y" Filter validations

1. The set of classes configured in case of classification is a
   superset of the classes available in the test data.
2. The CohortFilterMethods.INCLUDES is only allowed to be
   configured for "Predicted Y" filter in case of classification.
3. The CohortFilterMethods.INCLUDES and CohortFilterMethods.EXCLUDES
   filter methods cannot be configured for this filter for regression.

"Dataset" Filter validations

1. TODO:- For continuous features the allowed values that be configured
   should be within the range of minimum and maximum values available
   within the continuous feature column in the test data.
2. For categorical features only CohortFilterMethods.INCLUDES can be
   configured.
3. For categorical features the values allowed are a subset of the
   the values available in the categorical column in the test data.

Areas changed

npm packages changed:

• responsibleai/causality
• responsibleai/core-ui
• responsibleai/counterfactuals
• responsibleai/dataset-explorer
• responsibleai/fairness
• responsibleai/interpret
• responsibleai/localization
• responsibleai/mlchartlib
• responsibleai/model-assessment

Python packages changed:

• raiwidgets
• responsibleai
• erroranalysis
• rai_core_flask

Tests

• No new tests required.
• New tests for the added feature are part of this PR.
• I validated the changes manually.

Screenshots (if appropriate):

Documentation:

• My change requires a change to the documentation.
• I have updated the documentation accordingly.

[codecov-commenter]

Codecov Report

Merging #1227 (7df90a2) into main (11ee5ca) will decrease coverage by 1.20%.
The diff coverage is 0.00%.

@@            Coverage Diff             @@
##             main    #1227      +/-   ##
==========================================
- Coverage   67.19%   65.99%   -1.21%     
==========================================
  Files          91       91              
  Lines        4393     4473      +80     
==========================================
  Hits         2952     2952              
- Misses       1441     1521      +80     

Flag	Coverage Δ
unittests	65.99% <0.00%> (-1.21%)	⬇️

Flags with carried forward coverage won't be shown. Click here to find out more.

Impacted Files	Coverage Δ
raiwidgets/raiwidgets/_cohort.py	0.00% <0.00%> (ø)

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[github-actions]

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