carlg/alternative-metrics #950
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carl-offerfit
commented
Jan 29, 2025
carl-offerfit
commented
- Adds an optional scoring argument to _OrthoLearner.score so that the score can be viewed according to several other sklearn metrics. Currently supported are: mean_absolute_error, mean_squared_error, r2_score.
- The original default behavior of using MSE for the model fitting is preserved, now calculated in sklearn mean_square_error function instead of written out in code.
- Adds a new public method score_nuisances to _OrthoLearner.score so that the first stage models can be evaluated by other sklearn metrics. If sample weights are not used, any metric supported by sklearn get_scoring can be used. If sample weights are used, f1_score, log_loss, roc_auc_score are supported for binary outcomes/treatments; and for real valued outcome treatments it will be the same as _OrthoLearner.score for the final model mean_absolute_error, mean_squared_error, r2_score.
Fix names of scoring methods in wrappers (don't end in "score")
Add Log Loss as a weighted option Fixes calling the ModelFinal.wrap_scoring function
for more information, see https://pre-commit.ci
for more information, see https://pre-commit.ci
Add pearsonr as a score and test
…nds on the _rlearner _ModelNuisance implementation of score
…scoring is used without an _rlearner._ModelFinal Test that logic in the _otho_learner test
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