tfma.metrics.default_regression_specs
Returns default metric specs for for regression problems.
tfma.metrics.default_regression_specs(
model_names: Optional[List[str]] = None,
output_names: Optional[List[str]] = None,
output_weights: Optional[Dict[str, float]] = None,
loss_functions: Optional[List[Union[tf_keras.metrics.Metric, tf_keras.losses.Loss]]] = None,
min_value: Optional[float] = None,
max_value: Optional[float] = None
) -> 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).
|
loss_functions
|
Loss functions to use (if None MSE is used).
|
min_value
|
Min value for calibration plot (if None no plot will be created).
|
max_value
|
Max value for calibration plot (if None no plot will be created).
|
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Last updated 2024-04-26 UTC.
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