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C++, Matlab and Python library for Hidden-state ConditionalRandom Fields. Implements 3 algorithms: LDCRF, HCRF and CRF. For Windows and Linux, 32- and 64-bits. Optimized for multi-threading. Works with sparse or dense input features.
ConditionalRandomField(CRF) is a probabilistic model used in labeling or parsing sequential data. We provide a COM wrapper for CrfPP,which makes it easier to use for clients implemented in different languaes like C#,VB,C++ and script languages.
...It allows you to create simple static networks as well as complex temporal models with changing structure.
It can handle highly non-linear dependencies between multivariate random variables. The particle based inference can answer arbitrary questions given the provided evidence and can even cope with multimodal densities. The library supports the most common types of densities and conditional densities, like uniform or normal densities and facilitates user defined density functions.
To enable easy use the library is taking account of modern development techniques like policy based design and template programming.
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