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Table 3 Improvements of cBW + model selection, cBW alone vs Scheffer et al. in cases of correct initial transition matrix for synthetic data with Viterbi algorithm

From: A new algorithm to train hidden Markov models for biological sequences with partial labels

State #/training sample Average improvements of cBW + model selection in setting 1/2 Average p value of cBW + model selection in setting 1/2 Average improvements of cBW alone in setting 1/2
3/1600 8.07/8.57% 2.3E−04/4.7E−07 8.11/8.56%
3/2000 8.58/9.05% 1.9E−06/6.5E−09 8.63/9.03%
3/2400 8.93/9.24% 1.6E−07/1.0E−09 8.97/9.20%
3/2800 8.87/9.31% 1.3E−08/1.5E−09 8.94/9.26%
5/1600 11.99/13.24% 1.7E−02/4.5E−06 11.76/13.08%
5/2000 13.07/14.20% 4.1E−02/3.4E−06 12.87/14.11%
5/2400 13.22/14.59% 2.0E−02/1.2E−05 12.94/14.35%
5/2800 13.89/15.20% 4.1E−02/1.6E−07 13.85/15.16%
7/1600 7.85/9.37% 6.7E−02/3.5E−02 6.04/7.34%
7/2000 9.75/11.28% 5.6E−03/4.1E−03 7.93/9.32%
7/2400 10.50/12.10% 1.8E−02/1.9E−02 8.99/10.53%
7/2800 11.39/12.95% 1.4E−03/1.9E−04 9.75/11.29%