tfma.metrics.CalibrationPlot

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Calibration plot.

Inherits From: Metric

tfma.metrics.CalibrationPlot(
    num_buckets: int = DEFAULT_NUM_BUCKETS,
    left: Optional[float] = None,
    right: Optional[float] = None,
    name: str = CALIBRATION_PLOT_NAME
)

Args
num_buckets	Number of buckets to use when creating the plot. Defaults to 1000.
left	Left boundary of plot. Defaults to 0.0 when a schema is not provided.
right	Right boundary of plot. Defaults to 1.0 when a schema is not provided.
name	Plot name.

Attributes
compute_confidence_interval	Whether to compute confidence intervals for this metric. Note that this may not completely remove the computational overhead involved in computing a given metric. This is only respected by the jackknife confidence interval method.

Methods

computations

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computations(
    eval_config: Optional[tfma.EvalConfig] = None,
    schema: Optional[schema_pb2.Schema] = None,
    model_names: Optional[List[str]] = None,
    output_names: Optional[List[str]] = None,
    sub_keys: Optional[List[Optional[SubKey]]] = None,
    aggregation_type: Optional[AggregationType] = None,
    class_weights: Optional[Dict[int, float]] = None,
    example_weighted: bool = False,
    query_key: Optional[str] = None
) -> tfma.metrics.MetricComputations

Creates computations associated with metric.

get_config

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get_config() -> Dict[str, Any]

Returns serializable config.