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sdv.metrics.relational.ParentChildDetectionMetric¶

class sdv.metrics.relational.ParentChildDetectionMetric[source]¶

Base class for Multi-table Detection metrics based on parent-child relationships.

These metrics denormalize the parent-child relationships from the dataset and then apply a Single Table Detection metric on the resulting tables.

The output of the metric is one minus the average ROC AUC score obtained.

A part from the real and synthetic data, these metrics need to be passed a list with the foreign key relationships that exist between the tables.

name¶

Name to use when reports about this metric are printed.

Type: str

goal¶

The goal of this metric.

Type: sdmetrics.goal.Goal

min_value¶

Minimum value or values that this metric can take.

Type: Union[float, tuple[float]]

max_value¶

Maximum value or values that this metric can take.

Type: Union[float, tuple[float]]

single_table_metric¶

The single table detection metric to use.

Type: sdmetrics.single_table.detection.base.DetectionMetric

__init__()¶: Initialize self. See help(type(self)) for accurate signature.

Methods

`__init__`()	Initialize self.
`compute`(real_data, synthetic_data[, …])	Compute this metric.
`get_subclasses`([include_parents])	Recursively find subclasses of this metric.
`normalize`(raw_score)	Return the raw_score as is, since it is already normalized.

Attributes

single_table_metric

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