BSD-3-Clause licensed by Henning Thielemann
This version can be pinned in stack with:hmm-lapack-0.5.0.1@sha256:3e11ca51c3fd2b45430c1ccc970b4d4bb342b3f396c0d5b2cd68289511cd153f,4114
Module documentation for 0.5.0.1
- Math
- Math.HiddenMarkovModel
- Math.HiddenMarkovModel.Distribution
- Math.HiddenMarkovModel.Example
- Math.HiddenMarkovModel.Example.Circle
- Math.HiddenMarkovModel.Example.SineWave
- Math.HiddenMarkovModel.Example.TrafficLight
- Math.HiddenMarkovModel.Named
- Math.HiddenMarkovModel.Pattern
Depends on 16 packages
(full list with versions):
base,
comfort-array,
comfort-array-shape,
containers,
deepseq,
explicit-exception,
fixed-length,
hmm-lapack,
lapack,
lazy-csv,
netlib-ffi,
non-empty,
semigroups,
tfp,
transformers,
utility-ht Hidden Markov Models implemented using LAPACK data types and operations.
http://en.wikipedia.org/wiki/Hidden_Markov_Model
It implements:
generation of samples of emission sequences,
computation of the likelihood of an observed sequence of emissions,
construction of most likely state sequence
that produces an observed sequence of emissions,
supervised and unsupervised training of the model by Baum-Welch algorithm.
It supports any kind of emission distribution,
where discrete and multivariate Gaussian distributions
are implemented as examples.
For an introduction please refer to the examples:
Math.HiddenMarkovModel.Example.TrafficLight
Math.HiddenMarkovModel.Example.SineWave
Math.HiddenMarkovModel.Example.Circle
An alternative package without foreign calls is hmm.
0.4
Distribution: Make type-classes single parameter using data families.
0.3
- Move to new packages
comfort-array and lapack.
0.1
Distribution.Estimate turned into a multi-parameter type class.
