L0Learn: A Scalable Package for Sparse Learning using L0 Regularization

02/10/2022

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by   Hussein Hazimeh, et al.

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Google

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MIT

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We introduce L0Learn: an open-source package for sparse regression and classification using L0 regularization. L0Learn implements scalable, approximate algorithms, based on coordinate descent and local combinatorial optimization. The package is built using C++ and has a user-friendly R interface. Our experiments indicate that L0Learn can scale to problems with millions of features, achieving competitive run times with state-of-the-art sparse learning packages. L0Learn is available on both CRAN and GitHub.