Lleyton-Ariton/oddity
Time series anomaly detection via decomposition and gaussian process regression.
This tool helps you automatically spot unusual patterns or "oddities" in your time-based data, like sensor readings or sales figures. You input your historical time series data, and it identifies and highlights points that deviate significantly from the expected trend and seasonal cycles. Operations managers, data analysts, and anyone monitoring metrics over time can use this to quickly pinpoint anomalies that might indicate problems or opportunities.
No commits in the last 6 months.
Use this if you need to detect subtle or obvious anomalies in datasets that show clear trends and repeating seasonal patterns, whether daily, weekly, or yearly.
Not ideal if you need real-time, continuous anomaly detection on a live data stream, as it's currently designed for analyzing fixed, historical datasets.
Stars
21
Forks
3
Language
Rust
License
GPL-3.0
Category
Last pushed
May 22, 2021
Commits (30d)
0
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