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Click here to go to the new docs pages.
sdv.metrics.tabular.
MultiSingleColumnMetric
SingleTableMetric subclass that applies a SingleColumnMetric on each column.
This class can either be used by creating a subclass that inherits from it and sets the SingleColumn Metric as the single_column_metric attribute, or by creating an instance of this class passing the underlying SingleColumn metric as an argument.
single_column_metric
name
Name to use when reports about this metric are printed.
str
goal
The goal of this metric.
sdmetrics.goal.Goal
min_value
Minimum value or values that this metric can take.
Union[float, tuple[float]]
max_value
Maximum value or values that this metric can take.
SingleColumn metric to apply.
sdmetrics.single_column.base.SingleColumnMetric
field_types
Field types to which the SingleColumn metric will be applied.
dict
__init__
Initialize self. See help(type(self)) for accurate signature.
Methods
__init__([single_column_metric])
Initialize self.
compute(real_data, synthetic_data[, metadata])
compute
Compute this metric.
compute_breakdown(real_data, synthetic_data)
compute_breakdown
Compute this metric broken down by column.
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
single_column_metric_kwargs