tfma.metrics.default_multi_class_classification_specs
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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.
|
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Last updated 2024-04-26 UTC.
[[["Easy to understand","easyToUnderstand","thumb-up"],["Solved my problem","solvedMyProblem","thumb-up"],["Other","otherUp","thumb-up"]],[["Missing the information I need","missingTheInformationINeed","thumb-down"],["Too complicated / too many steps","tooComplicatedTooManySteps","thumb-down"],["Out of date","outOfDate","thumb-down"],["Samples / code issue","samplesCodeIssue","thumb-down"],["Other","otherDown","thumb-down"]],["Last updated 2024-04-26 UTC."],[],[]]