SparseChem: Fast and accurate machine learning model for small molecules

• URL: http://arxiv.org/abs/2203.04676v1
• Date: Wed, 9 Mar 2022 12:40:35 GMT
• Title: SparseChem: Fast and accurate machine learning model for small molecules
• Authors: Adam Arany, Jaak Simm, Martijn Oldenhof and Yves Moreau
• Abstract summary: SparseChem provides fast and accurate machine learning models for biochemical applications. It is possible to train classification, regression and censored regression models, or combination of them from command line. Source code and documentation is freely available under MIT License on GitHub.
• Score: 6.88204255655161
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: SparseChem provides fast and accurate machine learning models for biochemical applications. Especially, the package supports very high-dimensional sparse inputs, e.g., millions of features and millions of compounds. It is possible to train classification, regression and censored regression models, or combination of them from command line. Additionally, the library can be accessed directly from Python. Source code and documentation is freely available under MIT License on GitHub.

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