Show HN: Kentro – a fast Rust library for K-Means clustering
a year ago
- #Rust
- #K-Means
- #Clustering
- High-performance Rust implementation of K-Means clustering algorithms.
- Supports standard K-Means, Spherical K-Means, Balanced K-Means, and K-Medoids.
- Parallel processing support using Rayon for multi-threaded execution.
- Flexible API with builder pattern for easy configuration.
- Memory efficient and optimized for large datasets.
- Comprehensive error handling with detailed error types and messages.
- Includes examples for basic, balanced, medoids, and text clustering.
- Automatically uses all available CPU cores for cluster assignment.
- Designed for high performance with minimal memory allocations.
- Licensed under the Apache 2.0 License.