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Danger
You are looking at the documentation for an older version of the SDV! We are no longer supporting or maintaining this version of the software
Click here to go to the new docs pages.
sdv.metrics.tabular.
SVCDetection
ScikitLearnClassifierDetectionMetric based on a SVC.
This metric builds a SVC Classifier that learns to tell the synthetic data apart from the real data, which later on is evaluated using Cross Validation.
The output of the metric is one minus the average ROC AUC score obtained.
__init__
Initialize self. See help(type(self)) for accurate signature.
Methods
__init__()
Initialize self.
compute(real_data, synthetic_data[, metadata])
compute
Compute this metric.
compute_breakdown(real_data, synthetic_data)
compute_breakdown
Compute this metric breakdown.
get_subclasses([include_parents])
get_subclasses
Recursively find subclasses of this metric.
normalize(raw_score)
normalize
Return the raw_score as is, since it is already normalized.
Attributes
goal
max_value
min_value
name