Feature: pipeline spark k-sigma anomaly filtering #13
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Signed-off-by: Felipe Trost <[email protected]>
Signed-off-by: Felipe Trost <[email protected]>
Signed-off-by: Felipe Trost <[email protected]>
FelipeTrost
changed the title
Signed-off-by: Dominik Hoffmann <[email protected]>
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lftm. Merge |
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Test pipeline fails when naming the test file according to conventions (test_....) . Also happened in other PR. |
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Uses dependency that is only available in a later pyspark version: Our tests with older pyspark versions fail. The pipeline beforehand ran through because the test file wasn't recognized as it was missing the (test_...) name. |
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Summary
Anomaly detection with the k-sigma method for spark.
This method either computes the mean and standard deviation, or the median and the median absolute deviation (MAD) of the data. The k-sigma method then filters out all data points that are k times the standard deviation away from the mean, or k times the MAD away from the median.
A future improvement could be to support multiple columns of the data.