hmma: 'hmma': A package for the contruction of asymmetric hidden...

Description Details


The hmma package is able to construct asymmetric hidden Markov models (HMM-As) from data. HMM-As are similar to regular HMMs, but use Bayesian Networks (BNs) in their emission distribution.


HMMs have successfully been used in “speech recognition systems, in numerous applications incomputational molecular biology, in data compression, and in other areas of artificial intelligenceand pattern recognition”.

When limited data is available, HMMs may be unable to correctly capture these distributions.Bueno et al. show that HMMs can be enriched by employing state-specific Bayesian networks(BNs), i.e. BNs that may be different from state to state. This enables the model to better capturecertain independencies, depending on the state. The resulting models are called asymmetrichidden Markov models (HMM-As). (see: for more information)

hmma documentation built on July 2, 2020, 12:10 a.m.