R: Hidden Markov Model (HMM) Viterbi State Prediction

hmm_viterbi {mlpack} | R Documentation

## Hidden Markov Model (HMM) Viterbi State Prediction

### Description

A utility for computing the most probable hidden state sequence for Hidden Markov Models (HMMs). Given a pre-trained HMM and an observed sequence, this uses the Viterbi algorithm to compute and return the most probable hidden state sequence.

### Usage

    hmm_viterbi(input, input_model, verbose = FALSE)

### Arguments

`input` | Matrix containing observations (numeric matrix).
`input_model` | Trained HMM to use (HMMModel).
`verbose` | Display informational messages and the full list of parameters and timers at the end of execution. Default value "FALSE" (logical).

### Details

This utility takes an already-trained HMM, specified as "input_model", and evaluates the most probable hidden state sequence of a given sequence of observations (specified as '"input", using the Viterbi algorithm. The computed state sequence may be saved using the "output" output parameter.

### Value

A list with several components:

`output` | File to save predicted state sequence to (integer matrix).

### Author(s)

mlpack developers

### Examples

    # For example, to predict the state sequence of the observations "obs" using
    # the HMM "hmm", storing the predicted state sequence to "states", the
    # following command could be used:

    ## Not run:
    output <- hmm_viterbi(input=obs, input_model=hmm)
    states <- output$output

    ## End(Not run)

[Package mlpack version 3.4.2.1 Index]