The General Hidden Markov Model library (GHMM) is a freely available LGPL-ed C library implementing efficient data structures and algorithms for basic and extended HMMs. The development is hosted at Sourceforge http://sourceforge.net/projects/ghmm/, where you have access to the Subversion repository, mailing lists and forums.



The GHMM is developed by the Algorithmics group at the Max Planck Institute for Molecular Genetics.

Features



* Discrete and continous emissions

* Mixtures of PDFs for continous emissions

* Non-homogenous Markov chains

* Pair HMMs (contributed by Genoscope )

* Clustering and mixture modelling for HMMs

* Graphical Editor HMMEd

* Python bindings

* XML-based file format

* Portable (autoconf, automake, Windows)

* C++ API (NOT under active development, unsupported) -The General Hidden Markov Model library (GHMM) is a freely available LGPL-ed C library implementing efficient data structures and algorithms for basic and extended HMMs. The development is hosted at Sourceforge http://sourceforge.net/projects/ghmm/, where you have access to the Subversion repository, mailing lists and forums.



The GHMM is developed by the Algorithmics group at the Max Planck Institute for Molecular Genetics.

Features



　　* Discrete and continous emissions

　　* Mixtures of PDFs for continous emissions

　　* Non-homogenous Markov chains

　　* Pair HMMs (contributed by Genoscope )

　　* Clustering and mixture modelling for HMMs

　　* Graphical Editor HMMEd

　　* Python bindings

　　* XML-based file format

　　* Portable (autoconf, automake, Windows)

　　* C++ API (NOT under active development, unsupported)