The reviewed record of science sign in
Pith

arxiv: 2203.04676 · v1 · pith:SQ24R66C · submitted 2022-03-09 · stat.ML · cs.LG

SparseChem: Fast and accurate machine learning model for small molecules

Reviewed by Pith T0 review T1 audit T2 compute T3 formal T4 kernel pith:SQ24R66Crecord.jsonopen to challenge →

classification stat.ML cs.LG
keywords accuratefastlearningmachinemillionsmodelsregressionsparsechem
0
0 comments X
read the original 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.

This paper has not been read by Pith yet.

discussion (0)

Sign in with ORCID, Apple, or X to comment. Anyone can read and Pith papers without signing in.