tfma.metrics.default_multi_class_classification_specs

Returns default metric specs for multi-class classification problems.

tfma.metrics.default_multi_class_classification_specs(
    model_names: Optional[List[str]] = None,
    output_names: Optional[List[str]] = None,
    output_weights: Optional[Dict[str, float]] = None,
    binarize: Optional[tfma.BinarizationOptions] = None,
    aggregate: Optional[tfma.AggregationOptions] = None,
    sparse: bool = True
) -> List[tfma.MetricsSpec]

Args
`model_names`	Optional model names if multi-model evaluation.
`output_names`	Optional list of output names (if multi-output model).
`output_weights`	Optional output weights for creating overall metric aggregated across outputs (if multi-output model). If a weight is not provided for an output, it's weight defaults to 0.0 (i.e. output ignored).
`binarize`	Optional settings for binarizing multi-class/multi-label metrics.
`aggregate`	Optional settings for aggregating multi-class/multi-label metrics.
`sparse`	True if the labels are sparse.

tfma.metrics.default_multi_class_classification_specs

Args