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. __________________________________________________ Do You Yahoo!? Tired of spam? Yahoo! Mail has the best spam protection around http://mail.yahoo.com -- Unsubscribe mailto:[EMAIL PROTECTED] Help mailto:[EMAIL PROTECTED] Archive http://lists.ee.ethz.ch/rrd-users WebAdmin http://lists.ee.ethz.ch/lsg2.cgi
