lantonov and Stéphane Nicolet
44f79bdf5a
Tuned nullmove search
...
Tuning was done with Bayesian optimisation and sequential use of gaussian process
regressor and gaussian process classifier. The latter is used in lieu of ordinal
categorical modelling. Details will be given in Fishcooking forum topic: https://groups.google.com/forum/?fromgroups=#!topic/fishcooking/b3uhBBJcJG4
STC:
LLR: 2.96 (-2.94,2.94) {-1.00,3.00}
Total: 10248 W: 2361 L: 2233 D: 5654
Ptnml(0-2): 191, 1153, 2303, 1276, 194
http://tests.stockfishchess.org/tests/view/5e0ba4159d3fbe26f672d4e6
LTC:
LLR: 2.94 (-2.94,2.94) {0.00,2.00}
Total: 16003 W: 2648 L: 2458 D: 10897
Ptnml(0-2): 121, 1595, 4394, 1718, 153
http://tests.stockfishchess.org/tests/view/5e0bb8519d3fbe26f672d4fd
Closes https://github.com/official-stockfish/Stockfish/pull/2468
Bench 4747984
2020-01-07 11:47:39 +01:00
lantonov and Stéphane Nicolet
443787b0d1
Tuned razor and futility margins
...
Tuning was done with Bayesian optimisation with the following parameters:
Acquisition function: Expected Improvement
alpha: 0.05
xi: 1e-4
TC: 60+0.6
Number of iterations: 100
Initial points: 5
Batch size: 20 games
STC
http://tests.stockfishchess.org/tests/view/5dee291e3cff9a249bb9e470
LLR: 2.97 (-2.94,2.94) [-1.50,4.50]
Total: 19586 W: 4382 L: 4214 D: 10990
LTC
http://tests.stockfishchess.org/tests/view/5dee4e273cff9a249bb9e473
LLR: 2.95 (-2.94,2.94) [0.00,3.50]
Total: 38840 W: 6315 L: 6036 D: 26489
Bench: 5033242
2019-12-10 01:10:19 +01:00
