Showing 31 open source projects for "java machine learning library"

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  • 1
    jStates is a java library for easy state machine design and implementation.It uses XML to define states and state transitions. jStates is aimed at easy integration with desktop J2SE applications, Struts, Commons Validator, Web and other J2EE technologies
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  • 2
    Conrad is both a high performance Conditional Random Field engine which can be applied to a variety of machine learning problems and a specific set of models for gene prediction using semi-Markov CRFs.
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  • 3
    KNN-WEKA provides a implementation of the K-nearest neighbour algorithm for Weka. Weka is a collection of machine learning algorithms for data mining tasks. For more information on Weka, see http://www.cs.waikato.ac.nz/ml/weka/.
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  • 4
    MultiBoost is a C++ implementation of the multi-class AdaBoost algorithm. AdaBoost is a powerful meta-learning algorithm commonly used in machine learning. The code is well documented and easy to extend, especially for adding new weak learners.
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  • 5
    The OS561 operating system based around FORTH/Java. The OS is to run on a VHDL chip OpenHardware design called the Minon, but could become available for other platforms. The unique point of the design is a revolutionary data compression technology.
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  • 6
    Weka++ is a collection of machine learning and data mining algorithm implementations ported from Weka (http://www.cs.waikato.ac.nz/ml/weka/) from Java to C++, with enhancements for usability as embedded components.
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