SparseChem: Fast and accurate machine learning model for small molecules
This provides a tool for biochemical applications, but it appears incremental as it focuses on implementation and accessibility rather than novel breakthroughs.
SparseChem introduces a fast and accurate machine learning model for small molecules, supporting high-dimensional sparse inputs with millions of features and compounds, and is available as an open-source package under MIT License.
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.