sdv.constraints.OneHotEncoding

class sdv.constraints.OneHotEncoding(column_names)

Ensure the appropriate columns are one hot encoded.

This constraint allows the user to specify a list of columns where each row is a one hot vector. During the reverse transform, the output of the model is transformed so that the column with the largest value is set to 1 while all other columns are set to 0.

Parameters

column_names (list[str]) – Names of the columns containing one hot rows.

__init__(column_names)

Initialize self. See help(type(self)) for accurate signature.

Methods

__init__(column_names)	Initialize self.
filter_valid(table_data)	Get only the rows that are valid.
fit(table_data)	Fit Constraint class to data.
fit_transform(table_data)	Fit this Constraint to the data and then transform it.
from_dict(constraint_dict)	Build a Constraint object from a dict.
is_valid(table_data)	Check whether the data satisfies the one-hot constraint.
reverse_transform(table_data)	Handle logic around reverse transforming constraints.
to_dict()	Return a dict representation of this Constraint.
transform(table_data)	Perform necessary transformations needed by constraint.

Attributes

constraint_columns

sdv.constraints.ScalarRange.to_dict sdv.constraints.OneHotEncoding.fit