anomaly-detection-resources
MemStream
anomaly-detection-resources | MemStream | |
---|---|---|
98 | 1 | |
7,887 | 81 | |
- | - | |
4.6 | 3.5 | |
13 days ago | 4 months ago | |
Python | Python | |
GNU Affero General Public License v3.0 | Apache License 2.0 |
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.
anomaly-detection-resources
- anomaly-detection-resources: NEW Extended Research - star count:7507.0
- anomaly-detection-resources: NEW Extended Research - star count:7323.0
- anomaly-detection-resources: NEW Extended Research - star count:7109.0
-
Time-based splitting performing significantly worse than random splitting
https://github.com/yzhao062/anomaly-detection-resources https://search.brave.com/search?q=imbalanced+dataset+machine+learning+github&source=desktop
MemStream
What are some alternatives?
anomalib - An anomaly detection library comprising state-of-the-art algorithms and features such as experiment management, hyper-parameter optimization, and edge inference.
alibi-detect - Algorithms for outlier, adversarial and drift detection
pygod - A Python Library for Graph Outlier Detection (Anomaly Detection)
MStream - Anomaly Detection on Time-Evolving Streams in Real-time. Detecting intrusions (DoS and DDoS attacks), frauds, fake rating anomalies.
loglizer - A machine learning toolkit for log-based anomaly detection [ISSRE'16]
pycaret - An open-source, low-code machine learning library in Python
pyod - A Comprehensive and Scalable Python Library for Outlier Detection (Anomaly Detection)
DGFraud - A Deep Graph-based Toolbox for Fraud Detection
UGFraud - An Unsupervised Graph-based Toolbox for Fraud Detection
sktime - A unified framework for machine learning with time series
TranAD - [VLDB'22] Anomaly Detection using Transformers, self-conditioning and adversarial training.
tods - TODS: An Automated Time-series Outlier Detection System