pyod and SUOD
SUOD is a scalable acceleration system designed to efficiently orchestrate and ensemble multiple heterogeneous outlier detection algorithms from PyOD, making them complementary tools that work together rather than competitors.
About pyod
yzhao062/pyod
A Python Library for Outlier and Anomaly Detection, Integrating Classical and Deep Learning Techniques
Provides 45+ detection algorithms unified under a scikit-learn compatible API, combining classical methods (LOF, Isolation Forest) with 12 PyTorch-based neural models. Emphasizes performance through Numba JIT compilation and the SUOD framework for fast training/prediction, plus LLM-guided automated model selection to reduce manual hyperparameter tuning.
About SUOD
yzhao062/SUOD
(MLSys' 21) An Acceleration System for Large-scare Unsupervised Heterogeneous Outlier Detection (Anomaly Detection)
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