scikit-mdr
A scikit-learn-compatible Python implementation of Multifactor Dimensionality Reduction (MDR) for feature construction.
What is scikit-mdr?
scikit-mdr is a Python library that implements Multifactor Dimensionality Reduction (MDR), a feature construction algorithm for machine learning. It creates new features by modeling higher-order interactions between variables, particularly useful for capturing complex patterns in datasets with categorical features. The library provides scikit-learn-compatible estimators for both classification and regression problems.
Data scientists and researchers working with categorical data who need to model feature interactions, particularly in domains like bioinformatics and genetics where detecting epistasis (gene-gene interactions) is important.
Developers choose scikit-mdr because it provides a well-tested, scikit-learn-compatible implementation of the MDR algorithm that seamlessly integrates into existing machine learning workflows. Unlike generic feature engineering approaches, it specifically targets higher-order interaction detection in categorical data.
Overview
A sklearn-compatible Python implementation of Multifactor Dimensionality Reduction (MDR) for feature construction.
Use Cases
Best For
- Detecting gene-gene interactions (epistasis) in genetic association studies
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