actableai.bayesian_regression package

Submodules

actableai.bayesian_regression.utils module

actableai.bayesian_regression.utils.expand_polynomial_categorical(feature_data: pandas.core.frame.DataFrame, polynomial_degree: int, normalize: bool) → Tuple[pandas.core.frame.DataFrame, List[str]]

Generates a new DataFrame with extra features :

• Exponent of numerical features
• Cross Intersection of variables
• OneHot encoded values for categorical features

Parameters

• feature_data (pd.DataFrame) – DataFrame with the original features. Handles only numerical and categorical features
• polynomial_degree (int) – Maximum polynomial degree to generate cross intersection and exponent
• normalize (bool) – If we want the Data to be normalized

Returns

• pd.DataFrame: New DataFrame with generated features
• List[str]: Names of OneHotEncoded variables

Return type

Tuple

Module contents