decisionintelligence/TAB
[PVLDB 2025] TAB: Unified Benchmarking of Time Series Anomaly Detection Methods
This is a benchmarking library for evaluating time series anomaly detection models. It takes in various time series datasets and different anomaly detection algorithms, then outputs comprehensive performance comparisons based on various metrics and strategies. This tool is designed for researchers in time series anomaly detection who need to rigorously compare and validate different methods.
117 stars.
Use this if you are a researcher needing a standardized and reproducible way to evaluate and compare the performance of different time series anomaly detection models.
Not ideal if you are a practitioner looking for a ready-to-use anomaly detection solution for your specific business data.
Stars
117
Forks
13
Language
Jupyter Notebook
License
—
Category
Last pushed
Nov 26, 2025
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/decisionintelligence/TAB"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
yzhao062/pyod
A Python Library for Outlier and Anomaly Detection, Integrating Classical and Deep Learning Techniques
unit8co/darts
A python library for user-friendly forecasting and anomaly detection on time series.
elki-project/elki
ELKI Data Mining Toolkit
raphaelvallat/antropy
AntroPy: entropy and complexity of (EEG) time-series in Python
Minqi824/ADBench
Official Implement of "ADBench: Anomaly Detection Benchmark", NeurIPS 2022.