mlgauge
A simple library to benchmark the performance of machine learning methods across different datasets. (by SuryaThiru)
pyod
A Comprehensive and Scalable Python Library for Outlier Detection (Anomaly Detection) (by yzhao062)
mlgauge | pyod | |
---|---|---|
1 | 7 | |
23 | 7,962 | |
- | - | |
0.0 | 7.5 | |
about 3 years ago | 1 day ago | |
Python | Python | |
MIT License | 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.
mlgauge
Posts with mentions or reviews of mlgauge.
We have used some of these posts to build our list of alternatives
and similar projects.
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[P] Simple wrapper for benchmarking tabular datasets
GitHub: https://github.com/SuryaThiru/mlgauge Documentation: https://mlgauge.readthedocs.io/
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.
-
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.