stolcke_results.txt

来自「上载文件为Matlab环境下的高斯以马尔科夫模型例程」· 文本 代码 · 共 90 行

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stolcke_entropic_demoseeds = 1:5, ueda cooling schedulernd starting pointbaum welchentropictrimtrim statesannealed entropicannealed entropic and trimannealed entropic and trim statesloglik_train =  -63.6481  -61.4752  -58.0153  -58.8626  -63.1011  -31.0097  -30.8240  -32.0260  -30.8067  -32.0312  -31.5363  -32.4862  -34.2353  -34.4488  -32.4988  -32.8257  -32.3337  -32.4947  -34.6412  -32.5027  -32.8063  -32.3301  -32.4954  -34.6409  -32.5106  -49.2446  -45.7072  -45.7025  -49.2379  -49.2444  -48.9148  -56.8079  -56.8079  -49.0068  -48.9141  -48.9316  -56.8019  -56.8019  -48.9290  -48.9323mean(loglik_train,2)ans =  -61.0205  -31.3395  -33.0411  -32.9596  -32.9567  -47.8273  -52.0903  -52.0794loglik_test =  -43.9145  -42.6181  -43.1069  -45.2779  -42.4704  -49.8674  -51.4637  -35.6700  -74.2182  -38.1308      -Inf  -97.4110  -35.9379  -50.1834  -41.5282  -43.8075  -49.2715  -37.8409  -27.7367  -42.0170  -43.5852  -45.2563  -37.8412  -27.7361  -43.4969  -35.0114  -40.0737  -39.9606  -35.1394  -35.0169  -35.4081  -45.3011  -45.3011  -34.7649  -35.3560  -35.6153  -45.2985  -45.2985  -35.4798  -35.6196mean(loglik_test(:,2:end),2)ans =  -43.3683  -49.8707  -56.2651  -39.2165  -38.5826  -37.5476  -40.1808  -40.4241Entropic, trim and BW are similar on training (BW is usually best).Trim is better (more robust) than entropic on test.Trim is sometimes better, but never much worse, than BW on test.Annealed is always worse on train, but often best on test.Annealed no-trim seems to be better than annealed+trim, and is probably the best overall.nparseable_by_learned =    10    10    10    10    10    10    10    10    10    10     8    10    10    10    10    10    10    10    10    10    10    10    10    10    10    10    10    10    10    10    10    10    10    10    10    10    10    10    10    10nparseable_by_true =     0     0     0     0     0     1     3     4     1     1     4     4     2     2     3     3     2     3     1     6     1     1     1     3     0     0     2     0     0     1     0     0     0     1     3     5     0     0     4     2niter =     0     0     0     0     0    29    43    41    50    48    34    33    25    20    17    30    16    14    16    19    30    14    14    16    20    48    92    74    54    55    58    82    63    57    65    58    71    52    61    64

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