ENH add from_cv_results in RocCurveDisplay (list of displays) #30370
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lucyleeow
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Nov 29, 2024
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| # Ideally we would use `_validate_plot_params` but that is a instance | ||
| # method | ||
| check_matplotlib_support(f"{cls.__class__.__name__}.plot") | ||
| import matplotlib.pyplot as plt |
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The _BinaryClassifierCurveDisplayMixin method _validate_plot_params, is an instance method which uses self, which means we can't use it here.
Not sure how much of a problem this is.
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Reference Issues/PRs
Supercedes #25939
This is part of a group of draft PRs to determine best API for adding plots for cv results to our displays.
from_cv_resultsinRocCurveDisplay(Multi-display) #30359)from_cv_resultsinRocCurveDisplay(singleRocCurveDisplay) #30399)For all 3 options we take the output of
cross_validate, and use the fitted estimator and test indicies. No fitting is done in the display.We do recalculate the predictions (which would have already been done in
cross_validate), which could be avoided if we decided to changecross_validateto optionally return the predictions as well (note this would makecross_val_predictredundant).See more thread: #25939 (comment)). I think should be outside of the scope of this body of work though.
What does this implement/fix? Explain your changes.
Adds
from_cv_resultswhich returns a list ofRocCurveDisplay's, one for each fold.I like this implementation. There is one small problem I'll detail in a review comment.
Any other comments?
Plot looks like (should be the same as the other PRs):