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).

tfma.metrics.default_regression_specs

Args