dsgibbons / shap

A game theoretic approach to explain the output of any machine learning model.
https://shap-community.readthedocs.io/en/latest/
MIT License
25 stars 5 forks source link

docs: fix several doc issues and missing API documentation #102

Closed thatlittleboy closed 1 year ago

thatlittleboy commented 1 year ago

Port of #2020, with some notable changes:

codecov[bot] commented 1 year ago

Codecov Report

Merging #102 (02df738) into master (b1252d9) will not change coverage. The diff coverage is 100.00%.

@@           Coverage Diff           @@
##           master     #102   +/-   ##
=======================================
  Coverage   53.58%   53.58%           
=======================================
  Files          90       90           
  Lines       12893    12893           
=======================================
  Hits         6909     6909           
  Misses       5984     5984           
Impacted Files Coverage Δ
shap/explainers/__init__.py 100.00% <100.00%> (ø)
shap/utils/__init__.py 100.00% <100.00%> (ø)

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