tods
timebasedcv
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tods | timebasedcv | |
---|---|---|
3 | 1 | |
1,292 | 7 | |
3.4% | - | |
3.1 | 7.1 | |
8 months ago | 26 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
timebasedcv
What are some alternatives?
pyod - A Comprehensive and Scalable Python Library for Outlier Detection (Anomaly Detection)
sktime - A unified framework for machine learning with time series
luminaire - Luminaire is a python package that provides ML driven solutions for monitoring time series data.
aeon - A toolkit for conducting machine learning tasks with time series data
OpenOOD - Benchmarking Generalized Out-of-Distribution Detection
tslearn - The machine learning toolkit for time series analysis in Python
anomaly-detection-resources - Anomaly detection related books, papers, videos, and toolboxes
iterative-stratification - scikit-learn cross validators for iterative stratification of multilabel data
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.
TSCV - Time Series Cross-Validation -- an extension for scikit-learn
Merlion - Merlion: A Machine Learning Framework for Time Series Intelligence
flow-forecast - Deep learning PyTorch library for time series forecasting, classification, and anomaly detection (originally for flood forecasting).