A Comprehensive and Scalable Python Library for Outlier Detection (Anomaly Detection)
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Updated
May 10, 2024 - Python
A Comprehensive and Scalable Python Library for Outlier Detection (Anomaly Detection)
I created this automated anomaly detection preprocessing pipeline during my master thesis. It can be used to automatically preprocess tabular data for anomaly detection methods.
This library, designed for visualizing trees of the Isolation Forest, is available as an npm package. The project was created for my Bachelor's Thesis at TBU in Zlín, Czech Republic.
Algorithms for outlier, adversarial and drift detection
Quick and Easy Time Series Outlier Detection
CoRA Docs
This tool parses log data and allows to define analysis pipelines for anomaly detection. It was designed to run the analysis with limited resources and lowest possible permissions to make it suitable for production server use.
This repository is showcasing our Anomaly Detection System, developed as our final project in the software engineering course, utilizing basic statistical techniques like mean, variance, and covariance to detects anomalies
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