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| author | Gertjan van den Burg <gertjanvandenburg@gmail.com> | 2020-03-16 14:46:20 +0000 |
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| committer | Gertjan van den Burg <gertjanvandenburg@gmail.com> | 2020-03-16 14:46:20 +0000 |
| commit | ade351efd7799ccd4e1d313a166986730012bbfa (patch) | |
| tree | f7d32cc97f3d7404aa826c5add3936c6e93e3ea3 /README.md | |
| parent | Update readme (diff) | |
| download | TCPDBench-ade351efd7799ccd4e1d313a166986730012bbfa.tar.gz TCPDBench-ade351efd7799ccd4e1d313a166986730012bbfa.zip | |
Readme fixes
Diffstat (limited to 'README.md')
| -rw-r--r-- | README.md | 4 |
1 files changed, 2 insertions, 2 deletions
@@ -18,11 +18,11 @@ Dataset](https://github.com/alan-turing-institute/TCPD) (TCPD). Change point detection focuses on accurately detecting moments of abrupt change in the behavior of a time series. While many methods for change point -detection exists, past research has paid little attention to the evaluation of +detection exist, past research has paid little attention to the evaluation of existing algorithms on real-world data. This work introduces a benchmark study and a dataset ([TCPD](https://github.com/alan-turing-institute/TCPD)) that are explicitly designed for the evaluation of change point detection algorithms. -We hope that our work becomes a proving ground for the evaluation and +We hope that our work becomes a proving ground for the comparison and development of change point detection algorithms that work well in practice. This repository contains the code necessary to evaluate and analyze a |