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cog-imperial / OMLT

Represent trained machine learning models as Pyomo optimization formulations
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Add GBT base score to block output #81

Closed ThebTron closed 2 years ago

ThebTron commented 2 years ago

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This PR addresses #80. GBT models imported from scikit-learn have an additional constant base score that is added to the prediction of the model. This doesn't apply for lightgbm and the base score defaults to zero. I also added a note to the jupyter notebook that only lightgbm and scikit-learn tree model inputs are officially supported.

codecov[bot] commented 2 years ago

Codecov Report

Merging #81 (8aac10f) into main (3e2f9e4) will increase coverage by 0.00%. The diff coverage is 100.00%.

@@           Coverage Diff           @@
##             main      #81   +/-   ##
=======================================
  Coverage   94.18%   94.19%           
=======================================
  Files          24       24           
  Lines        1239     1240    +1     
  Branches      192      192           
=======================================
+ Hits         1167     1168    +1     
  Misses         42       42           
  Partials       30       30
Impacted Files Coverage Δ
src/omlt/gbt/gbt_formulation.py 93.65% <100.00%> (+0.05%) :arrow_up:

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