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.constraints.OneHotEncoding

class sdv.constraints.OneHotEncoding(column_names)[source]

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