The Accord.NET Framework is a .NET machine learning framework combined with audio and image processing libraries completely written in C#. It is a complete framework for building production-grade computer vision, computer audition, signal processing and statistics applications. A comprehensive set
... [More] of sample applications provide a fast start to get up and running quickly, and an extensive online documentation helps fill in the details. [Less]
MALLET (A Machine Learning for Language Toolkit) is an integrated collection of Java code useful for statistical natural language processing, document classification, clustering, information extraction, and other machine learning applications to text
Citar is a C++ free software part of speech tagger using a trigram Hidden Markov Model (HMM), with linear interpolation smoothing of trigrams and suffix-based unknown word handling.
Features
Citar has the following major features:
* High accuracy tagging through a trigram Hidden Markov
... [More] Model with Viterbi decoding.
* Handling of unknown words through suffix analysis.
* Licensed under the GNU Lesser General Public License version 2.1 (LGPLv2.1), which only imposes restrictions on redistribution of Citar itself.
* Written in C++ for performance. [Less]
A framework for learning finite automatons that perform goal-directed interaction with entities which exhibit deterministic or stochastic behavior. The learning process can be carried out in real time together with the interaction process. A basic building block for supporting state models of finite
... [More] automatons is adaptive probabilistic mapping, which for an argument from its domain returns more often results that maximize or minimize values of one or more objective functions. Finite automatons can be represented by assembler programs with user-defined instructions that perform effective work. To assist in the learning of a finite automaton, a template for its state model can be provided as an assembler program with probabilistic jump instructions. [Less]
JitarJitar is an open source part of speech tagger using a trigram Hidden Markov Model (HMM).
FeaturesJitar has the following major features:
High accuracy tagging through a trigram Hidden Markov Model with Viterbi decoding. Handling of unknown words through suffix analysis. Licensed under
... [More] the GNU Lesser General Public License version 3 (LGPLv3), which only imposes restrictions on redistribution of Jitar itself. Written in Java, allowing for easy integration with other programs that are built upon the excellent JDK platform. AvailabilityJitar 0.0.2 is now available, and can be obtained in source or compiled form from the Downloads page. You can also use Subversion to retrieve this version of Jitar:
svn checkout http://jitar.googlecode.com/svn/tags/jitar-0.0.2After checking out or dow [Less]
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