Sowiks commented on code in PR #126: URL: https://github.com/apache/otava/pull/126#discussion_r2839101704
########## docs/MATH.md: ########## @@ -0,0 +1,79 @@ +# Change Point Detection +## Overview +Otava implements a nonparametric change point detection algorithm designed to identify statistically significant distribution changes in time-ordered data. The method is primarily based on the **E-Divisive family of algorithms** for multivariate change point detection, with some practical adaptations. + +At a high level, the algorithm: +- Measures statistical divergence between segments of a time series +- Searches for change points using hierarchical segmentation +- Evaluates significance of candidate splits using statistical hypothesis testing + +The current implementation prioritizes: +- Robustness to noisy real-world signals +- Deterministic behavior +- Practical runtime for production workloads + +A representative example of algorithm application: + + + +Here the algorithm detected 4 change points with statistical test showing that behavior of the time series changes at them. In other words, data have different distribution to the left and to the right of each change point. Review Comment: Selected a different example + included parameters in the figure. -- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. To unsubscribe, e-mail: [email protected] For queries about this service, please contact Infrastructure at: [email protected]
