Enhancement: Add explicit UserWarning for NaN classes in macro-averaged metrics#558
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karttikjangid wants to merge 4 commits intoJdeRobot:masterfrom
Open
Enhancement: Add explicit UserWarning for NaN classes in macro-averaged metrics#558karttikjangid wants to merge 4 commits intoJdeRobot:masterfrom
karttikjangid wants to merge 4 commits intoJdeRobot:masterfrom
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Hi team, the CI is failing on LiDAR tests due to an isinstance check against a mocked Open3D class in the headless runner. My changes are limited to metrics; would you like me to include a small guard to fix this CI bottleneck? |
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I have reinstated the original poetry files for reference in the last commit |
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Fixes #546
Following up on the discussion in #546, this PR adds a UserWarning during macro-averaged metric calculation.
When per-class metric values are NaN (for example, denominator-zero cases such as classes missing from the confusion matrix), they are ignored by np.nanmean as intended. This PR now surfaces a warning indicating how many classes were dropped for that metric so researchers are explicitly aware of the macro-average context.
All existing metric formulas and public APIs are unchanged. Feedback on the warning text format is welcome.