rounakbanik / fa_transformer

A Python package with custom Factor Analyzer pipelines

Factor Analysis Transformers

fa_transformer is a small Python package which makes available two Factor Analyzer Transformers that are ideal for use in scikit-learn pipelines

Possible Use Cases

• Dimensionality reduction: The package can be used to convert n features with underlying factors into a single feature.
• Composite Score generation: The package also facilitates creation of Composite scores that are either a 1-factor score or a dot product of transformed factor scores and their respective eigenvalues.

Classes

class FATransformerInPlace(BaseEstimator, TransformerMixin):

This class takes a DataFrame and converts a subet of features into a single feature using 1-Factor Analysis.

Attributes

• feature_names (list): A list of features that need to be condensed
• composite_feature_name (str): Name of the new feature column
• rotation (str): The rotation to be used by the Factor Analyzer
• method (str): The method to be used by the Factor Analyzer

class CompositeFATransformer(BaseEstimator, TransformerMixin):

This class takes a DataFrame and performs n-factor analysis, producing a weighted composite score as well as n-factors.

Attributes

• num_factors (int): The number of factors to be used for Factor Analysis
• rotation (str): The rotation to be used by the Factor Analyzer
• method (str): The method to be used by the Factor Analyzer