Random Forests for Change Point Detection
A crate for implementing various flavors of random forests and decision trees.
Simple, fast random forests.
Systematic Error Removal using Random Forests (SERRF) normalization for metabolomics data
Fast Random Forest library.
Generic library to build Random Forest implementations
Streaming anomaly detection toolkit — Random Cut Forest, per-feature drift, streaming sketches, SOC triage, hot-path ingress. Facade re-export of anomstream-core / anomstream-triage / anomstream-hotpath.
Ensemble methods for sklears: Random Forest, Gradient Boosting, AdaBoost
Core streaming anomaly detectors + companion primitives (Random Cut Forest, per-feature EWMA / CUSUM, drift detectors, streaming stats) — part of the anomstream toolkit
Blazingly fast implementation of Random Forest with apache arrow support
Ensemble methods for imbalanced learning in Rust - Balanced Random Forest and more
Classical ML algorithms for GhostFlow