[rrd-users] Aberrant Behavior Detection tuning

[Praveen P]

Hi,

Can someone please explain how to tune the seasonal
coefficient adaptation and seasonal deviation
adaptation parameters for aberrant behavior detection
?

By default, gamma is set to the same value as alpha. I
understand that the Alpha value is derived based on
the "% weight given to the last n number of samples".
So does this mean that gamma is also a weight for a
set of seasonal co-efficients or does it have a one to
one correspondence between the current prediction and
a single value one seasonal period in the past ?

I was trying to see if the algorithm can 'learn' about
the deviations in the pattern that occurs at a fixed
point in every seasonal cycle. For example, if we were
monitoring web tv traffic, we would like the algorithm
to learn the fact that every monday there will be a
sudden increase in the traffic at the time of the
football telecast (assuming the seasonal period to be
one week). Is this possible currently ?

Thanks, Praveen.

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