Not surprised. It is still roughly an O(n^3) algorithm (n = number of users).
A lower number will increase speed. You might want something far lower like 0.05. One other way to speed this up is to use a different metric for cluster similarity, like computing a centroid for the cluster and comparing that rather than the O(n^2) comparison done now. This sort of approach, I haven't followed up on much, to be honest. There are some areas for improvement to be sure. On Fri, Oct 31, 2008 at 7:21 PM, Otis Gospodnetic <[EMAIL PROTECTED]> wrote: > Quick report that, sadly, TreeClusteringRecommender > (TreeClusteringRecommender2 actually!) is a no go, too. It's been running > for well over an hour over the same amount of data, and this is where its > been spending its time:
