Showing 6 open source projects for "easy gui"

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  • 1
    Java Neural Network Framework Neuroph
    Neuroph is lightweight Java Neural Network Framework which can be used to develop common neural network architectures. Small number of basic classes which correspond to basic NN concepts, and GUI editor makes it easy to learn and use.
    Downloads: 59 This Week
    Last Update:
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  • 2
    GUAJE FUZZY

    GUAJE FUZZY

    Free software for generating understandable and accurate fuzzy systems

    GUAJE stands for Generating Understandable and Accurate fuzzy models in a Java Environment. Thus, it is a free software tool (licensed under GPL-v3) with the aim of supporting the design of interpretable and accurate fuzzy systems by means of combining several preexisting open source tools, taking profit from the main advantages of all of them. It is a user-friendly portable tool designed and developed in order to make easier knowledge extraction and representation for fuzzy systems, paying...
    Downloads: 0 This Week
    Last Update:
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  • 3
    Carrot2
    Project moved to GitHub! https://github.com/carrot2/carrot2 Carrot2 is an Open Source Search Results Clustering Engine. It can automatically organize small collections of documents, e.g. search results, into thematic categories. Carrot2 integrates very well with both Open Source and proprietary search engines.
    Downloads: 0 This Week
    Last Update:
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  • 4
    GPalta is a genetic programming toolbox that aims for simplicity and speed. It features tree-based genetic programming, optional strong typing, a GUI to control an evolution process (allows to save and continue later) and easy interoperability with Matlab
    Downloads: 0 This Week
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  • 5
    ORE (Ontology Rule Editor) is a platform-independent application to manage the use of inference rules defined on a model represented by an ontology. ORE offers a easy, well-guided and intiutive GUI to define and test these inference rules.
    Downloads: 0 This Week
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  • 6
    Program to performing the complete cycle of neural networks analysis: preparing data, choosing neural network (CasCor, MP, LogRegression, PNN), learning of network, monitoring learning state, ROC-analysis, optimization of network parameters using GA.
    Downloads: 0 This Week
    Last Update:
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