Library for Nearest Shrunken Centroids
LibNSC is a mathematical framework for creating advanced, LLM-free, and highly-accurate classification models based on natural language. It fuses Snell's Prototypical Networks with Mahalanobis distance, built on a Linux-native semantic substrate specifically written for high-signal Physics and ML vector-based data ingestion and geometric research.
LibNSC is useful to everyone from psychologists to biblical scholars to physicists, as well as trust & safety professionals and quality assurance engineers.
- LLM-free, highly-accurate natural-language classification
- Fusion of Snell's Prototypical Networks with Mahalanobis distance
- Linux-native semantic substrate
- High-signal ingestion for Physics and ML vector data
- Geometric research oriented
LibNSC is released under a mix of the Apache 2.0 and MIT software licenses, with clear delineation in file headers. See the LICENSE-APACHE and LICENSE-MIT files for full terms.
Please see CONTRIBUTING.md.
Please see SECURITY.md.
Please see CODE_OF_CONDUCT.md.