Showing 268 open source projects for "gnu linux"

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  • 1
    Blunder is an automated tool for analyzing chained exceptions in Java. It's usefull for classify, generate a customized error message and a list for possible solutions.
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  • 2
    {IBA}Miner is an expert system, being developed at the AI-Lab at IBA. The purpose of this software is to provide businesses an easy to use system in which the analysts can easily create and test models and the end-users get predictions for new instances.
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  • 3
    This is implementation of parallel genetic algorithm with "ring" insular topology. Algorithm provides a dynamic choice of genetic operators in the evolution of. The library supports the 26 genetic operators. This is cross-platform GA written in С++.
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  • 4
    ANT is a lightweight implementation in C of a kind of artificial neural net called Multilayer Perceptron, which uses the backpropagation algorithm as learning method. The package includes an introductory example to start using artificial neural nets.
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  • 5
    This is C++ application code that implements Gene Expression Programming, or GEP - a form of genetic algorithm.
    Downloads: 2 This Week
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  • 6
    Linear Time Invariant (LTI) system identification using particle swarm optimization (PSO) algorithm. Creators : Vahid Kiani, Hadi Sadoghi Yazdi
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  • 7
    TrimGA is a lightweight genetic algorithm library written in pure Java 6.0 that can be quickly applied to most optimization problems.
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  • 8

    TimeSleuth - Temporal Rule Discovery

    Temporal and Causal Decision Rules

    TimeSleuth discovers temporal decision rules. It also judges the (a)causality of the rules. TimeSleuth can discover rules that involve time: {if (rainy_yesterday = true) then rainy_today = true}, or {if (rainy_tomorrow = true) then rainy_today = true}.
    Downloads: 0 This Week
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  • 9

    Betelgeuse

    Powerful machine learning modeling software suitable for industry use.

    Betelgeuse is a machine learning modeling package designed to meet the requirements of heavy-duty industry use. It was designed to be efficient, reliable, and highly modular; it is developed primarily in Python to promote maintainability and rapid development, but uses Cython and C in critical bottlenecks for efficiency. It focuses on high-quality implementations of a diverse set of the most widely used machine learning algorithms. An important goal of Betelgeuse is to have a clean,...
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  • 10
    pySPACE

    pySPACE

    Signal Processing and Classification Environment in Python using YAML

    pySPACE is a modular software for processing of large data streams that has been specifically designed to enable distributed execution and empirical evaluation of signal processing chains. Various signal processing algorithms (so called nodes) are available within the software, from finite impulse response filters over data-dependent spatial filters (e.g. CSP, xDAWN) to established classifiers (e.g. SVM, LDA). pySPACE incorporates the concept of node and node chains of the MDP framework. Due...
    Downloads: 0 This Week
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  • 11
    lstm network library
    Downloads: 0 This Week
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  • 12

    AraRooter

    Find Arabic Root Word

    Using Machine Learning, AraRooter finds the three-lettered root of any Arabic lemma with around 84% accuracy.
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  • 13
    Spec is a voice control based on the libraries of Sphinx-4.
    Downloads: 0 This Week
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  • 14
    UnBFuzzy is an API for fuzzy-logic and learning algorithms for fuzzy systems.
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  • 15
    qMaZda

    qMaZda

    Image analysis software

    The open source project to port image analysis MaZda program to Linux and OS X platforms. See: http://www.eletel.p.lodz.pl/programy/mazda/
    Downloads: 0 This Week
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  • 16
    The goal of the project it to learn how to use Neural Networks, and teach one how to play tic tac toe, and get to the never losing ability that most people can play at.
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  • 17

    Supertagger

    Software for assigning supertags.

    Supertagging is a process of statistical lexical disambiguation, preprocessing step to parsing, which assigns LTAG tree categories to the lexical items present in the input sentence. Thus, if the input sentence is in the form of a dependency tree, the task of the supertagger is to assign the most probable TAG family to each node and edge in the dependency tree.
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  • 18
    a distributed engine for abstract neural network development via natural-language programming
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