Data provided by National Institute of Standards and Technology
Affinis is a tool for assisting in unsupervised structure learning on sparse, binary data. For large (sparse) feature matrices, especially ones with binary-valued entries, techniques to figure out the underlying structure of the feature space are widely varied, and different communities have widely different practices and assumptions for what is an appropriate approach. Affinis provides reference implementations for many of these methods, with a consistent API to enable community adoption and a shared benchmarking environment.
About this Dataset
Updated: 2026-09-04
Metadata Last Updated:
2026-02-17 00:00:00
Date Created:
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| Title | Affinis: tools for inferring relations from co-occurrence data |
|---|---|
| Description | Affinis is a tool for assisting in unsupervised structure learning on sparse, binary data. For large (sparse) feature matrices, especially ones with binary-valued entries, techniques to figure out the underlying structure of the feature space are widely varied, and different communities have widely different practices and assumptions for what is an appropriate approach. Affinis provides reference implementations for many of these methods, with a consistent API to enable community adoption and a shared benchmarking environment. |
| Modified | 2026-02-17 00:00:00 |
| Publisher Name | National Institute of Standards and Technology |
| Contact | mailto:[email protected] |
| Keywords | network analysis , sparse matrix , covariance shrinkage , binary data , structure learning , edge prediction , filtering , feature learning , multi-label , graph theory , scientific-software , tools |
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