stolcke_results.txt

上载文件为Matlab环境下的高斯以马尔科夫模型例程

stolcke_entropic_demo
seeds = 1:5, ueda cooling schedule

rnd starting point
baum welch
entropic
trim
trim states
annealed entropic
annealed entropic and trim
annealed entropic and trim states

loglik_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  -48.9323

mean(loglik_train,2)
ans =
  -61.0205
  -31.3395
  -33.0411
  -32.9596
  -32.9567
  -47.8273
  -52.0903
  -52.0794

loglik_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  -35.6196

mean(loglik_test(:,2:end),2)
ans =
  -43.3683
  -49.8707
  -56.2651
  -39.2165
  -38.5826
  -37.5476
  -40.1808
  -40.4241

Entropic, 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    10
nparseable_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     2

niter =
     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