tods
OpenOOD
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| tods | OpenOOD | |
|---|---|---|
| 3 | 2 | |
| 1,292 | 749 | |
| 3.4% | - | |
| 3.1 | 8.1 | |
| 8 months ago | 11 days ago | |
| Python | Python | |
| Apache License 2.0 | MIT License |
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tods
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Anomaly detection Algorithms
Sounds that OP is looking for time series anomaly detection, not multivariate. Perhaps https://github.com/datamllab/tods is an option,
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Unsupervised Anomaly Detection with Multivariate Time series
I suggest you try some AutoML library for anomaly detection, e.g.: https://github.com/datamllab/tods
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[P] [R] Luminaire: A hands-off Anomaly Detection Library
TODS
OpenOOD
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[Online Leaderboard | Easy Evaluation] OpenOOD v1.5: Enhanced Benchmark for Out-of-Distribution Detection
Open-sourced implementations of 40+ advanced methods (see our repo);
- Large OOD Detection Library with Multiple Papers Implemented
What are some alternatives?
pyod - A Comprehensive and Scalable Python Library for Outlier Detection (Anomaly Detection)
luminaire - Luminaire is a python package that provides ML driven solutions for monitoring time series data.
DGFraud - A Deep Graph-based Toolbox for Fraud Detection
anomaly-detection-resources - Anomaly detection related books, papers, videos, and toolboxes
cleanlab - The standard data-centric AI package for data quality and machine learning with messy, real-world data and labels.
PyPOTS - A Python toolbox/library for reality-centric machine/deep learning and data mining on partially-observed time series with PyTorch, including SOTA neural network models for science tasks of imputation, classification, clustering, and forecasting on incomplete (irregularly-sampled) multivariate time series with NaN missing values/data.
timebasedcv - Time based splits for cross validation
Merlion - Merlion: A Machine Learning Framework for Time Series Intelligence