Mathematical Problems in Engineering / 2017 / Article / Tab 4

Research Article

Efficient and Effective Learning of HMMs Based on Identification of Hidden States

Table 4

Identification results on identifiable HMMs.

TypeMethod# Iters.Time (s) selectPara. Dist.Conv. (%)Identi. (%)

Pers.BW151054Min. AIC1.670.0280.1545.5688.89
Correct 0.000.0580.0216.1166.67

Tran.BW221276Min. AIC1.000.0140.08100100
Correct 0.000.0120.0175.56100

Hybr.BW19891Min. AIC1.750.0080.1988100
Correct 0.000.0070.0036.50100

Iters.: average number of iterations; Conv. : rate of convergence; Identi. : percentage of identification; : unit log-likelihood difference between the true models and the learned model on test-sets; Para. Dist.: parameter distance; Pers.: Persistent; Tran.: Transient-cyclic; Hybr.: Hybrid. Note that, for the BW, when calculating , , and Para. Dist., the learned model is the best one selected from the repeated random models.

We are committed to sharing findings related to COVID-19 as quickly as possible. We will be providing unlimited waivers of publication charges for accepted research articles as well as case reports and case series related to COVID-19. Review articles are excluded from this waiver policy. Sign up here as a reviewer to help fast-track new submissions.