AD model performance benchmark (#729) #734
Merged
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Description
This PR adds an AD model performance benchmark so that we can compare model performance across versions.
Regarding benchmark data, we randomly generated synthetic data with known anomalies inserted throughout the signal. In particular, these are one/two/four dimensional data where each dimension is a noisy cosine wave. Anomalies are inserted into one dimension with 0.003 probability. Anomalies across each dimension can be independent or dependent. We have approximately 5000 observations per data set. The data set is generated using the same random seed so the result is comparable across versions.
We also backported #600 so that we can capture the performance data in CI output.
Testing done:
Signed-off-by: Kaituo Li [email protected]
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