hmm-lapack-0.3.0.3: Hidden Markov Models using LAPACK primitives
Math.HiddenMarkovModel.Example.SineWave
Description
Warning: do not import that module, it is only intended for demonstration
Example of an HMM with continuous emissions. We train a model to accept sine waves of a certain frequency.
There are four hidden states: Rising, High, Falling, Low.
Rising
High
Falling
Low
data State Source #
Constructors
Defined in Math.HiddenMarkovModel.Example.SineWave
Methods
minBound :: State #
maxBound :: State #
succ :: State -> State #
pred :: State -> State #
toEnum :: Int -> State #
fromEnum :: State -> Int #
enumFrom :: State -> [State] #
enumFromThen :: State -> State -> [State] #
enumFromTo :: State -> State -> [State] #
enumFromThenTo :: State -> State -> State -> [State] #
(==) :: State -> State -> Bool #
(/=) :: State -> State -> Bool #
compare :: State -> State -> Ordering #
(<) :: State -> State -> Bool #
(<=) :: State -> State -> Bool #
(>) :: State -> State -> Bool #
(>=) :: State -> State -> Bool #
max :: State -> State -> State #
min :: State -> State -> State #
type StateSet = Enumeration State Source #
stateSet :: StateSet Source #
type HMM = Gaussian () StateSet Double Source #
hmm :: HMM Source #
stateVector :: Double -> Double -> Double -> Double -> Vector StateSet Double Source #
sineWaveLabeled :: T [] (State, Double) Source #
sineWave :: T [] Double Source #
revealed :: T [] State Source #
hmmTrainedSupervised :: HMM Source #
hmmTrainedUnsupervised :: HMM Source #
hmmIterativelyTrained :: HMM Source #