Add zero_division parameter to F1 metric #722
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Adds zero_division parameter to F1._compute() to match sklearn.metrics.f1_score interface. Controls behavior when precision/recall denominators are zero. Default value is 0 for backward compatibility.
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Add zero_division parameter to F1 metric
Fixes TypeError when passing zero_division argument to F1.compute().
sklearn.metrics.f1_score raises UndefinedMetricWarning suggesting use
of zero_division parameter, but evaluate.load("f1") did not accept it.
Changes:
This change adds the zero_division parameter that directly passes through to sklearn.metrics.f1_score, which already has comprehensive tests for this parameter
Resolves crashes when computing F1 with classes that have neither
predictions nor ground truth labels.
Fixes #699