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| Homogenous Distribution http://poker-ai.org/phpbb/viewtopic.php?f=24&t=2644 |
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| Author: | cantina [ Sat Nov 16, 2013 6:16 pm ] |
| Post subject: | Homogenous Distribution |
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? |
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| Author: | algonoob [ Sat Nov 16, 2013 7:54 pm ] |
| Post subject: | Re: Homogenous Distribution |
i believe they are random, i remember reading their code for dealing cards and modifying it to deal x games |
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| Author: | cantina [ Sat Nov 16, 2013 8:00 pm ] |
| Post subject: | Re: Homogenous Distribution |
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? |
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| Author: | flopnflush [ Mon Nov 18, 2013 8:13 pm ] |
| Post subject: | Re: Homogenous Distribution |
Are you looking for something like this? https://en.wikipedia.org/wiki/Sobol_sequence |
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| Author: | cantina [ Fri Nov 22, 2013 5:19 pm ] |
| Post subject: | Re: Homogenous Distribution |
I don't think so. |
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| Author: | cantina [ Wed Nov 27, 2013 6:30 am ] |
| Post subject: | Re: Homogenous Distribution |
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. |
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| Author: | spears [ Wed Nov 27, 2013 9:43 am ] |
| Post subject: | Re: Homogenous Distribution |
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? |
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| Author: | cantina [ Wed Nov 27, 2013 7:37 pm ] |
| Post subject: | Re: Homogenous Distribution |
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. |
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| Author: | spears [ Wed Nov 27, 2013 9:52 pm ] |
| Post subject: | Re: Homogenous Distribution |
"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. |
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| Author: | cantina [ Wed Nov 27, 2013 10:14 pm ] |
| Post subject: | Re: Homogenous Distribution |
You're not really "homogenising" the data, you're picking homogenous points in the game space to sample your data. |
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