Poker-AI.org

Re: Homogenous Distribution

2013-11-27T22:14:17+00:00

You're not really "homogenising" the data, you're picking homogenous points in the game space to sample your data.

Statistics: Posted by cantina — Wed Nov 27, 2013 10:14 pm

Re: Homogenous Distribution

2013-11-27T21:52:59+00:00

"homogenising" the data will invalidate any regression. The only thing I think you can do is increase the resolution of the regression. ie increase the number of neurons, support vectors. Or maybe use random forests.
I'd like to see a toy problem exhibiting this behaviour so I can do some experiments.

Statistics: Posted by spears — Wed Nov 27, 2013 9:52 pm

Re: Homogenous Distribution

2013-11-27T19:37:30+00:00

It actually applies to two different problems I'm working on. One is regression, the other is as mentioned above where I'm just trying to represent the entire game space.

Statistics: Posted by cantina — Wed Nov 27, 2013 7:37 pm

Re: Homogenous Distribution

2013-11-27T09:43:17+00:00

http://en.wikipedia.org/wiki/Multivaria ... estimation

I think the answer to this question depends on the "training" you are trying to do. Is it for density estimation, regression, classification or something else?

Statistics: Posted by spears — Wed Nov 27, 2013 9:43 am

Re: Homogenous Distribution

2013-11-27T06:30:20+00:00

Another way of approaching this, and applicable to other areas, would be: say you have a ton of data samples that you want to use to train a model. How do you make those samples homogenous as possible across all point dimensions (attributes) as to prevent a biased model (one that favors the most abundant data)? For example, in poker, if you represent your hands via HS/HP metrics, the majority of those sampled will be towards the center of a bell curve.

I guess the obvious answer is clustering. Are there any other ways? I'm trying a reduction method, where I look at the least abundant data and make all the other sample counts equal to that. However, it's only based on a couple attributes.

Statistics: Posted by cantina — Wed Nov 27, 2013 6:30 am

Re: Homogenous Distribution

2013-11-22T17:19:23+00:00

I don't think so.

Statistics: Posted by cantina — Fri Nov 22, 2013 5:19 pm

Re: Homogenous Distribution

2013-11-18T20:13:19+00:00

Are you looking for something like this? https://en.wikipedia.org/wiki/Sobol_sequence

Statistics: Posted by flopnflush — Mon Nov 18, 2013 8:13 pm

Re: Homogenous Distribution

2013-11-16T20:00:07+00:00

Hmm, I could have sworn they weren't completely random after looking at the HS/HP of the hands. But, that was years ago, maybe I was mistaken. Regardless, any suggestions on generating 1000 hands that represent points evenly distributed throughout the game space?

Statistics: Posted by cantina — Sat Nov 16, 2013 8:00 pm

Re: Homogenous Distribution

2013-11-16T19:54:32+00:00

i believe they are random, i remember reading their code for dealing cards and modifying it to deal x games

Statistics: Posted by algonoob — Sat Nov 16, 2013 7:54 pm

Homogenous Distribution

2013-11-16T18:16:50+00:00

As part of a sampling method when comparing strategies, I need about 1000 hands that will represent the entire game space. So, I'd like them to be as homogenous as possible. The 6000 hands used by the U of A during their ACPC(s) looked pretty evenly distributed. Anybody know how they come up with those each year?

Statistics: Posted by cantina — Sat Nov 16, 2013 6:16 pm