Feature Engine
A Python library for feature engineering and selection with scikit-learn compatible transformers.
What is Feature Engine?
Feature-engine is an open-source Python library that provides a wide array of transformers for feature engineering and feature selection in machine learning workflows. It solves the problem of fragmented feature preprocessing by offering a unified, scikit-learn-compatible toolkit that includes imputation, encoding, discretization, outlier handling, transformation, and selection methods. The library is designed to integrate seamlessly into existing scikit-learn pipelines, making feature engineering more efficient and reproducible.
Data scientists, machine learning engineers, and researchers who build machine learning models in Python and need robust, scalable tools for feature preprocessing and selection. It is particularly useful for professionals working on tabular data, time series, or text data within scikit-learn ecosystems.
Developers choose Feature-engine because it consolidates numerous feature engineering techniques into a single, well-documented library with a consistent scikit-learn API, reducing the need for custom code and third-party dependencies. Its comprehensive coverage of methods, active maintenance, and integration with popular ML workflows provide a reliable, production-ready solution for feature preprocessing.
Overview
Feature engineering and selection open-source Python library compatible with sklearn.
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