Compute this metric.
This denormalizes the parent-child relationships from the dataset and then
applies 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, either a foreign_keys list
containing the relationships between the tables or a metadata that can be
used to create such list must be passed.
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, foreign keys must be
foreign_keys (list[tuple[str, str, str, str]]) – List of foreign key relationships specified as tuples
that contain (parent_table, parent_key, child_table, child_key).
Ignored if metada is given.
Average of the scores obtained by the single table metric.