tods
TODS: An Automated Time-series Outlier Detection System (by datamllab)
pyod
A Comprehensive and Scalable Python Library for Outlier Detection (Anomaly Detection) (by yzhao062)
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| tods | pyod | |
|---|---|---|
| 3 | 7 | |
| 1,292 | 7,941 | |
| 3.4% | - | |
| 3.1 | 7.7 | |
| 8 months ago | 5 days ago | |
| Python | Python | |
| Apache License 2.0 | BSD 2-clause "Simplified" License |
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
tods
Posts with mentions or reviews of tods.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2022-05-27.
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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
pyod
Posts with mentions or reviews of pyod.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2023-09-13.
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A Comprehensive Guide for Building Rag-Based LLM Applications
This is a feature in many commercial products already, as well as open source libraries like PyOD. https://github.com/yzhao062/pyod
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Analyze defects and errors in the created images
PyOD
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Multivariate Outlier Detection in Python
Check out the algorithms and documentation in this toolkit. It’ll give you a list of methods to read up on to understand their mechanisms. https://github.com/yzhao062/pyod
- Pyod – A Comprehensive and Scalable Python Library for Outlier Detection
- Predictive Maintenance and Anomaly Detection Resources
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[D] Unsupervised Outlier Detection - Advise Requested
The source code and documentaion of PyOD is the best survey about OOD. Besides, the normalized flow and VQVAE are also feasible.
- PyOD: ~50 anomaly detection algorithms in one framework.
What are some alternatives?
When comparing tods and pyod you can also consider the following projects:
luminaire - Luminaire is a python package that provides ML driven solutions for monitoring time series data.
isolation-forest - A Spark/Scala implementation of the isolation forest unsupervised outlier detection algorithm.