Showing 37 open source projects for "graphical data"

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  • 1
    DocCO

    DocCO

    Non-disjoint groupping of Documents based on word sequence approach

    This is a GUI for learning non disjoint groups of documents based on Weka machine learning framework. It offers the possibility to make non disjoint clustering of documents using both vectorial and sequential representation (word sequence approach based on WSK kernel). All data format supported by WEKA could be used in DocCO. Data could be loaded from files, from databases or from specified URL. All the preprocessing techniques implemented in WEKA could be used before performing the learning.
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  • 2
    feed4weka is an open library that enriches weka (http://www.cs.waikato.ac.nz/ml/weka/), an open source project for data analysis. It integrates new classification and clustering algorithms, and adds the coclustering and outlier detection frameworks
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  • 3
    TreeLiker

    TreeLiker

    TreeLiker is a collection of fast algorithms for working with complex

    TreeLiker is a collection of fast algorithms for working with complex structured data in relational form. The data can, for example, describe large organic molecules such as proteins or groups of individuals such as social networks or predator-prey networks etc. The algorithms included in TreeLiker are unique in that, in principle, they are able to search given sets of relational patterns exhaustively, thus guaranteeing that if some good pattern capturing an important feature of the problem...
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  • 4
    pyIRDG

    pyIRDG

    IMDb Relational Dataset Generator

    pyIRDG is a program written in Python to generate relational datasets in Prolog format. It uses data from the Internet Movie Database in combination with IMDbPY as backend. A graphical user interface written in pyQt allows the user to link multiple entities together as model for the generation process. The big four entities are Title, Person, Company and Character. Many attributes can be chosen for adding to the output .pl file.
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  • 5
    RapidMiner Feature Selection Extension
    This RapidMiner-plugin consists of operators for feature selection and classification - mainly on high-dimensional (microarray-) data - and some helper-classes/operators.
    Downloads: 2 This Week
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  • 6
    BIL++
    BIL++ is a set of standalone C++ packages for data processing in Bioinformatics (Graph mining, Bayesian networks, Genetic algorithm, Discretization, Gene expression data analysis, Hypothesis testing).
    Downloads: 0 This Week
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  • 7
    KeplerWeka adds the functionality of the open-source machine learning and data mining workbench WEKA to the free and open-source, scientific workflow application, Kepler.
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  • 8
    SAIM allows to interlink knowledge bases in the Semantic Web. It focuses on instance matching of very large knowledge bases available as SPARQL endpoints. SAIM uses machine learning techniques and is compatible with SILK.
    Downloads: 0 This Week
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  • 9
    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
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  • 10
    Sanchay
    Sanchay is a collection of tools and APIs for language researchers. It has some implementations of NLP algorithms, some flexible APIs, several user friendly annotation interfaces and Sanchay Query Language for language resources.
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  • 11
    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.
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  • 12

    Cinefile

    A category-based approach to exploring film data.

    ...It allows the user to identify abstract categories of films by providing examples of category members, learns to classify films as belonging or not belonging to those categories, and provides a graphical interface for exploring and comparing categories. Cinefile is designed to work with data retrieved from the Internet Movie Database (imdb.com). This data is used for classification and is the subject of the category-based analysis. Cinefile was developed by the University of Mary Washington's Computer Science department (http://cas.umw.edu/computerscience).
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