TODS¶
Focuses on multivariate outlier detection for time series data. It builds on project:yzao062/pyod and support three scenarios: individual point detection, pattern detection, and system-wise detection (comparing sets of time series).
Logo |
![]() |
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Website |
N/A |
Repository |
|
Byline |
An Automated Time-series Outlier Detection System |
License |
Apache 2.0 |
Project age |
1 years 7 months |
Backers |
Rice DATA Lab (Creator and maintainer) |
Size score (1 to 10, higher is better) |
2.5 |
Trend score (1 to 10, higher is better) |
4.0 |
Education Resources¶
URL |
Resource Type |
Description |
---|---|---|
Documentation |
Official project documentation. |
|
Paper |
Paper from AAAI conference describing TODS |
Git Commit Statistics¶
Statistics computed using Git data through March 31, 2022.
Statistic |
Lifetime |
Last 12 Months |
---|---|---|
Commits |
301 |
78 |
Lines committed |
2,166,670 |
106,350 |
Unique committers |
13 |
5 |
Core committers |
5 |
2 |

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