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CRFsuite
CRFSuite is an implementation of Conditional Random Fields (CRFs) [Lafferty01, Sha03] for labeling sequential data. Among the various implementations of CRFs, this software provides following features.
FlexCRFs: Flexible Conditional Random Fields
FlexCRFs is a conditional random field toolkit for segmenting and labeling sequence data written in C/C++ using STL library. It was implemented based on the theoretic model presented in (Lafferty et al. 2001) and (Sha and Pereira 2003). The toolkit uses L-BFGS (Liu and Nocedal 1989) - an advanced convex optimization procedure - to train CRF models. FlexCRFs was designed to deal with hundreds of thousand data sequences and millions of features. FlexCRFs supports both first-order and second-order Markov CRFs. We have tested FlexCRFs on Linux (Red Hat, Fedora), Sun Solaris, and MS Windows with MS Visual C++.
PCRFs is a parallel version of FlexCRFs that allows us to train conditional random fields on massively parallel processing systems supporting Message Passing Interface (MPI).
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FlexCRFs is a conditional random field
toolkit for segmenting and labeling sequence data written in C/C++ using STL
library. It was implemented based on the theoretic model presented in (Lafferty et al. 2001)
and (Sha and
Pereira 2003). The toolkit uses L-BFGS (Liu
and Nocedal 1989) - an advanced convex optimization procedure - to train
CRF models. FlexCRFs was designed to deal with hundreds of thousand data
sequences and millions of features. FlexCRFs supports both first-order and
second-order Markov CRFs. We have tested FlexCRFs on Linux (Red Hat, Fedora),
Sun Solaris, and MS Windows with MS Visual C++.PCRFs is a parallel version of FlexCRFs that allows us to
train conditional random fields on massively parallel processing systems
supporting Message Passing Interface (MPI).
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