[BUG] detect fake anomalies when the buckets are not completely full

[MCdeamon7]

I have generated fake data with a gauss function, the data are generated from ~8AM to ~6PM for 30 days with the related timestamp.
When the data starts or ends, I frequently get spikes that trigger the anomaly detection algorithm.

Observing the data in "visualize" that depending on the bucket size the algorithm (avg) actually show random spikes:

But zooming, the data are actually as expected.

To reproduce the bug, you can try to import data generated with my python script:
https://github.com/MCdeamon7/data-generator
import the data and then try to make an anomaly detection job on it

I imagine that is something about bucket size because by adjusting it from 5 to 10 or to 15 the spikes disappear in some places and reappear in other places.

I'm using it on a docker container on Linux recompiled by me from version 2.11.0 (i modified just the max features from 5 to 10)

Sorry for my English and thanks to everyone that can help me.

[minalsha]

@kaituo thoughts?

[kaituo]

@MCdeamon7 Can you list steps on how to generate data using https://github.com/MCdeamon7/data-generator ?

Also, what do you mean by bucket size/ What's your detector configuration?