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sdv.metrics.relational.SVCDetection.compute

classmethod SVCDetection.compute(real_data, synthetic_data, metadata=None, **kwargs)

Compute this metric.

This applies the underlying single table metric to all the tables found in the dataset and then returns the average score obtained.

Parameters

  • real_data (dict[str, pandas.DataFrame]) – The tables from the real dataset.

  • synthetic_data (dict[str, pandas.DataFrame]) – The tables from the synthetic dataset.

  • metadata (dict) – Multi-table metadata dict. If not passed, it is build based on the real_data fields and dtypes.

  • **kwargs – Any additional keyword arguments will be passed down to the single table metric

Returns

Metric output.

Return type

Union[float, tuple[float]]

sdv.metrics.relational.SVCDetection.get_subclasses sdv.metrics.relational.ParentChildDetectionMetric