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Post subject: Re: tuning for the uninformed - Poisson?    Posted: Sun Dec 03, 2017 10:09 am

 jdart wrote: It is has occurred me that the correct model here might be Poisson regression (https://en.wikipedia.org/wiki/Poisson_regression). If we ran for each position a match of n games, and if the probability of a win is some value p, then the distribution of game results (x2) would be integers that could be modeled as a Poisson distribution and the parameters could be tuned using that method to model the outcomes. I don't know if this is completely valid but it seems plausible. Texel tuning as initially described is the special case of n=1. --Jon

This is only mildly related to the topic, but Jon, I think you said that Arasan used a closed-form equation for the derivatives of your eval. Would you mind going over how you calculated those? It confuses me a lot.

For example, even if I take a stupid material only tapered eval with mean-squared error, I get this:

 Code: Let count_p_w, count_n_w etc be the count of pawns, knights etc for white. Let count_p_b, count_n_b etc be the count of pawns, knights etc for black. Let phase_p, phase_n etc be the phase weight of pawns, knights, etc for tapered eval. Let value_p_o, value_n_o etc be the material value of pawns, knights, etc in the opening. Let value_p_e, value_n_e etc be the material value of pawns, knights, etc in the endgame value_o = (count_p_w - count_p_b) * value_p_o + (count_n_w - count_n_b) * value_n_o + ... value_e = (count_p_w - count_p_b) * value_p_e + (count_n_w - count_n_b) * value_n_e + ... total_phase = 16 * phase_p + 4 * phase_n + ... phase = (count_p_w + count_p_b) * phase_p + (count_n_w + count_n_b) * phase_n + ... value = ((phase * value_o) + ((total_phase - phase) * value_e)) / total_phase sigmoid = 1 / (1 + 10 ** (-K*value)) error = (result - sigmoid) * (result - sigmoid)

And I have no idea how to then differentiate that, because that's a lot of variables.
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Folkert van Heusden Thu Nov 23, 2017 10:37 am
Henk van den Belt Thu Nov 23, 2017 11:49 am
Mehdi Amini Thu Nov 23, 2017 11:49 am
Henk van den Belt Thu Nov 23, 2017 11:53 am
Folkert van Heusden Thu Nov 23, 2017 12:26 pm
Henk van den Belt Thu Nov 23, 2017 12:44 pm
Alexandru Mosoi Thu Nov 23, 2017 2:07 pm
Folkert van Heusden Thu Nov 23, 2017 2:16 pm
Folkert van Heusden Thu Nov 23, 2017 5:34 pm
Sander Maassen vd Brink Thu Nov 23, 2017 6:47 pm
Henk van den Belt Thu Nov 23, 2017 7:21 pm
Sander Maassen vd Brink Thu Nov 23, 2017 7:26 pm
Henk van den Belt Thu Nov 23, 2017 7:36 pm
Sander Maassen vd Brink Thu Nov 23, 2017 7:43 pm
Martin Fierz Tue Dec 12, 2017 9:17 pm
Álvaro Begué Tue Dec 12, 2017 10:47 pm
Folkert van Heusden Fri Nov 24, 2017 9:15 am
Sander Maassen vd Brink Fri Nov 24, 2017 9:30 am
Robin Messemer Fri Nov 24, 2017 11:04 pm
Henk van den Belt Sat Nov 25, 2017 11:30 am
Robin Messemer Sat Nov 25, 2017 1:58 pm
Henk van den Belt Sat Nov 25, 2017 2:48 pm
Robert Pope Mon Nov 27, 2017 5:38 pm
Álvaro Begué Mon Nov 27, 2017 5:52 pm
Alexandru Mosoi Mon Nov 27, 2017 9:56 pm
Robert Pope Tue Nov 28, 2017 4:41 pm
Robin Messemer Tue Nov 28, 2017 7:23 pm
Álvaro Begué Tue Nov 28, 2017 7:37 pm
Jon Dart Thu Dec 14, 2017 3:09 pm
Álvaro Begué Thu Dec 14, 2017 3:15 pm
Jon Dart Sat Dec 02, 2017 3:02 pm
Jon Dart Sat Dec 02, 2017 2:58 pm
Erin Dame Sat Dec 02, 2017 10:50 am
Jon Dart Sat Dec 02, 2017 2:54 pm
Erin Dame Sat Dec 02, 2017 5:14 pm
Jon Dart Sat Dec 02, 2017 5:56 pm
Jon Dart Sat Dec 02, 2017 8:09 pm
Re: tuning for the uninformed - Poisson? Matthew R. Brades Sun Dec 03, 2017 10:09 am
Álvaro Begué Sun Dec 03, 2017 1:03 pm
Jon Dart Sun Dec 03, 2017 3:47 pm

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