Mastering Predictive Analytics with R

Hidden Markov models

A Hidden Markov model, often abbreviated to HMM, which we will use here, is a Bayesian network with a repeating structure that is commonly used to model and predict sequences. In this section, we'll see two applications of this model: one to model DNA gene sequences, and another to model the sequences of letters that make up English text. The basic diagram for an HMM is shown here:

As we can see in the diagram, the sequence flows from left to right and we have a pair of nodes for every entry in the sequence that we are trying to model. Nodes labeled C_i are known as latent states, hidden states, or merely states, as they are typically ...