hmm-0.1: Hidden Markov Model algorithms Source code Contents Index

Data.HMM

Synopsis

type Prob = Lognum Double data HMM state observation train :: (Ord observation, Ord state) => [(observation, state)] -> HMM state observation bestSequence :: Ord observation => HMM state observation -> [observation] -> [state] sequenceProb :: Ord observation => HMM state observation -> [observation] -> Prob

Documentation

type Prob = Lognum Double Source

data HMM state observation Source

The type of Hidden Markov Models.

train :: (Ord observation, Ord state) => [(observation, state)] -> HMM state observation Source

Calculate the parameters of an HMM from a list of observations and the corresponding states.

bestSequence :: Ord observation => HMM state observation -> [observation] -> [state] Source

Calculate the most likely sequence of states for a given sequence of observations using Viterbi's algorithm

sequenceProb :: Ord observation => HMM state observation -> [observation] -> Prob Source

Calculate the probability of a given sequence of observations using the forward algorithm.

Produced by Haddock version 2.1.0