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open-source feature selection repository in python
Featuretools is a Python data science library and automated feature engineering framework designed to create predictive features from multiple related datasets. It automates the data preparation and transformation steps required for machine learning models through deep feature synthesis. The library enables the automatic generation of comprehensive feature tables by applying recursive transformations to relational data. It supports the transformation of unstructured text into structured numeric features and allows users to define custom primitives to extend the synthesis process with specific
A scikit-learn-compatible Python implementation of ReBATE, a suite of Relief-based feature selection algorithms for Machine Learning.
A set of tools for creating and testing machine learning features, with a scikit-learn compatible API
Data search & enrichment library for Machine Learning → Easily find and add relevant features to your ML & AI pipeline from hundreds of public and premium external data sources, including open & commercial LLMs
The main features of upgini/upgini are: General Machine Learning, Data Enrichment, Data Loading Extraction, Feature Engineering.
Projects with overlapping indexed features include: scikit-image/scikit-image — scikit-image is a Python image processing library and scientific image analysis toolkit. It provides a framework for… machinalis/featureforge — A set of tools for creating and testing machine learning features, with a scikit-learn compatible API. featuretools/featuretools — Featuretools is a Python data science library and automated feature engineering framework designed to create… epistasislab/scikit-rebate — A scikit-learn-compatible Python implementation of ReBATE, a suite of Relief-based feature selection algorithms for… jundongl/scikit-feature — open-source feature selection repository in python. snorkel-team/snorkel — Snorkel is a weak supervision system that enables users to programmatically generate training labels for machine…