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* Move all dims under one class.
* Dimension owns anomaly rate RD.
* Remove Dimension::isAnomalous()
* Remove Dimension::trainEvery()
* Rm ml/kmeans
* Remove anomaly detector
The same logic can be implemented by using the host anomaly rate dim.
* Profile plugin.
* Revert "Profile plugin."
This reverts commit e3db37cb49c514502c5216cfe7bca2a003fb90f1.
* Add separate source files for anomaly detection charts.
* Handle training/prediction sync at the dimension level.
* Keep multiple KMeans models in mem.
* Move feature extraction outside KMeans class.
* Use multiple models.
* Add /api/v1/ml_models endpoint.
* Remove Dimension::getID()
* Use just 1 model and fix tests.
* Add detection logic based on rrdr.
* Remove config options related to anomaly detection.
* Make anomaly detection queries configurable.
* Fix ad query duration option.
* Finalize queries in all code paths.
* Check if query was initialized before finalizing it
* Do not leak OWA
* Profile plugin.
* Revert "Profile plugin."
This reverts commit 5c77145d0df7e091d030476c480ab8d9cbceb89e.
* Change context from anomaly_detection to detector_events.
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