boniolp/ADecimo

[ICDE 2024] a Web-app for Evaluation of Model selection for Anomaly Detection in Time Series

33
/ 100
Emerging

This tool helps data analysts and domain experts quickly identify unusual patterns or events in time series data. You input a time series dataset, and it automatically selects the most effective anomaly detection method for your specific data, then outputs the detected anomalies. It's designed for anyone working with fluctuating data, like system logs, sensor readings, or financial metrics, who needs to spot critical deviations without deep expertise in anomaly detection algorithms.

No commits in the last 6 months.

Use this if you have diverse time series datasets and need a reliable way to find anomalies without manually testing multiple detection algorithms for each dataset.

Not ideal if you require a very simple, single-method anomaly detector or need to integrate a custom anomaly detection algorithm not supported by the platform.

time-series-analysis operations-monitoring fraud-detection predictive-maintenance healthcare-analytics
Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 5 / 25
Maturity 16 / 25
Community 12 / 25

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Stars

11

Forks

2

Language

Python

License

MIT

Last pushed

Oct 03, 2024

Commits (30d)

0

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