Add input validation to auuc_score for missing model columns (#858)#881
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Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
auuc_score (and the underlying get_cumlift) treats every DataFrame
column not in {outcome_col, treatment_col, treatment_effect_col} as
a model prediction column. When users pass a DataFrame without any
model columns, the function fails with a confusing error. Now raises
a clear ValueError explaining the expected DataFrame format.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
jeongyoonlee
requested review from
alexander-pv,
huigangchen,
paullo0106,
ppstacy,
ras44,
t-tte,
vincewu51 and
zhenyuz0500
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Summary
auuc_scoretreats every DataFrame column not in{outcome_col, treatment_col, treatment_effect_col}as a model prediction columnValueErrorexplaining the expected DataFrame formatTest plan
pytest tests/test_visualize.py— 2 passed🤖 Generated with Claude Code