On Apr 2, 2013, at 4:08 PM, Don Dailey <[email protected]> wrote: > I like that paper a lot, but I really had a difficult time swallowing the > assumption that a team could be rating by summing together each individual > member. The paper of course makes a disclaimer that it may not be a good > assumption "all the time" but in my view it's rarely a good assumption - > unless you are playing tug of war. > > It may be a reasonable however if the number of features in the pattern you > are comparing is the same. Then summing the ELO's of the features is exactly > the same as taking the average. I don't remember if that was the case here.
It's been a while since I read the paper, but I do believe the number of features per point is constant for the data set Remi used. He had independent grouping of features, and each group would have one member for each point on the board. I logically treat "absent" as an extra level with a gamma of 1.0. With such exhaustive partitioning, one member of a group must have a gamma of 1.0 or there won't be a unique result. For example, all gammas in the "MC Owner" category could be multiplied by 1000 and it'd still yield the same probability distribution. _______________________________________________ Computer-go mailing list [email protected] http://dvandva.org/cgi-bin/mailman/listinfo/computer-go
