[computer-go] 19x19 Study

[Don Dailey]

In other tests I've done,  bayeselo comes out pretty much the same as an
iterative method I use where players are batch rated over and over until
they converge. 

I did a similar thing with the current data and it comes out very
similar to bayeselo, so I have no reason to believe that with a few
hundred samples we have anything to worry about.

- Don


Don Dailey wrote:
> They seem under-rated to me also.   Bayeselo pushes the ratings together
> because that is apparently a valid initial assumption.   With enough
> games I believe that effect goes away.
>
> I could test that theory with some work.    Unless there is a way to
> turn that off in bayelo (I don't see it) I could rate them with my own
> program.
>
> Perhaps I will do that test.
>
> - Don
>
>
> Sylvain Gelly wrote:
>   
>>     but not linearly and you can see a nice gradual curve in the plot.
>>
>>     Now we have something we can argue about for weeks.   Why is it not
>>     mostly linear?   Could it be the memory issue I just mentioned?   
>>
>>
>> Hi Don and all participants to that study, that is very interesting!
>>
>> The memory constrains are certainly a valid hypothesis, especially the
>> default settings of the release are rather conservative on that side,
>> because it seemed better to have a weaker player than begin to make
>> the player's machine swapping... Those settings are rather fitting
>> your memory constrains as well, so it is fine.
>>
>> Reading your email and looking at the curve, I wonder if one possible
>> explanation could be an artifact on how the ratings are computed? My
>> question is: what curve would we see for that study if the involved
>> players were exactly linearly scalable? That seems silly, but I
>> wondered if there were an underestimating of higher levels, because of
>> the way the bayeselo works. I am also looking at the curve after the
>> 5-6th level (~gnugo), as behavior may be different for very low levels.
>>
>> I don't know if my hypothesis makes sense.
>> Sylvain
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