xLearn
A high-performance, easy-to-use, and scalable machine learning package for linear models, factorization machines, and field-aware factorization machines.
What is xLearn?
xLearn is a high-performance machine learning package that implements linear models, factorization machines, and field-aware factorization machines. It is specifically designed to handle large-scale sparse data, such as in recommendation systems, where feature dimensions can reach millions. The package offers significant speed improvements and scalability while maintaining ease of use through Python and CLI interfaces.
Data scientists and machine learning engineers working with large-scale sparse datasets, particularly in domains like recommendation systems, advertising, and high-dimensional classification/regression tasks.
Developers choose xLearn for its exceptional performance (5x-13x faster than alternatives), scalability to terabyte-scale datasets, and straightforward integration without third-party dependencies. It serves as a direct open-source replacement for liblinear, libfm, and libffm with enhanced features.
Overview
High performance, easy-to-use, and scalable machine learning (ML) package, including linear model (LR), factorization machines (FM), and field-aware factorization machines (FFM) for Python and CLI interface.
Use Cases
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