10 Hidden Markov Models
The hidden Markov model (HMM) is a useful tool for computing probabilities of sequences. Since there are different types of sequences, there are different variations of the HMM. This chapter will review the basics of some of the most popular instantiations.
A typical HMM is a set of connected nodes, as shown in Figure 10-1. The information flows through the network from left to right. Each node computes the probability of emitting a given state, and each connection contains the probability of a transition from one node to the next. Commonly, the HMM uses only the emission or transition probabilities, but not both. Therefore, different HMMs are presented here using only one of these options.
10.1 The Emission HMM
The emission ...
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