Showing 12 open source projects for "parallel"

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    TRAK for Visio

    TRAK for Visio

    Simple Visio stencil to help create TRAK architecture views

    A Visio stencil that provides the elements and connectors from the TRAK metamodel for you to create TRAK architecture views with. With thanks to Nic Plum for the latest revision. TRAK is an ISO/IEC 42010:2011-compliant open-source architecture framework for enterprise architecture modelling / architecture description in all domains. TRAK is specified in three parts and is available at: * http://trak.sourceforge.net [overview] * http://trakmetamodels.sourceforge.net...
    Downloads: 0 This Week
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  • 2
    FreeMat
    Freemat is an interpreted, matrix-oriented development environment for engineering and scientific applications, similar to the commercial package MATLAB. Freemat provides visualization, image manipulation, and plotting as well as parallel programming.
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    Downloads: 192 This Week
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  • 3

    jAgg

    jAgg - Java Aggregation Operations

    jAgg is a Java 5.0 API that supports “group by” operations on Lists of Java objects: aggregate operations such as count, sum, max, min, avg, and many more. It supports Super Aggregation: Rollups, Cube, and Grouping Sets. It supports analytic operations such as lag/lead and row number and more. It also allows custom aggregate and analytic operations.
    Downloads: 0 This Week
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  • 4
    CRFSharp

    CRFSharp

    CRFSharp is a .NET(C#) implementation of Conditional Random Field

    ...CRF#'s mainly algorithm is the same as CRF++ written by Taku Kudo. It encodes model parameters by L-BFGS. Moreover, it has many significant improvement than CRF++, such as totally parallel encoding, optimizing memory usage and so on. Currently, when training corpus, compared with CRF++, CRF# can make full use of multi-core CPUs and only uses very low memory, and memory grow is very smoothly and slowly while amount of training corpus, tags increase. with multi-threads process, CRF# is more suitable for large data and tags training than CRF++ now. ...
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  • 5
    A Machine Learning and Data Retrieval Framework
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  • 6
    Cloudster is a generic and parallel implementation of the k-means algorithm. It is written in C# and uses the Windows Azure environment.
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  • 7
    Simple console program intended for factor or principal components analysis. It calculates the optimal number of factors using the Horn's parallel analysis, computes the Kaiser-Meyer-Olkin and a few other measures of sampling adequacy.
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  • 8
    Parallel IBDWS is an upgrade from IBDWS that utilizes parallel processing. Also, the incorporation of DNA sequence data has been added since the last code release
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  • 9
    FlexCRFs: A Flexible Conditional Random Fields Toolkit for Labeling and Segmenting Sequence Data (this includes a parallel implementation of CRFs called PCRFs to support training CRF models on massively parallel computer systems).
    Downloads: 0 This Week
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  • 10
    WebDip is a platform for the tracking of information search in a psychological decision making experiment. It enables to run parallel experiments, with different search modes and comfortabel user management.
    Downloads: 1 This Week
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  • 11
    Weka-Parallel is a modification to Weka, created with the intention of being able to harness the power of Weka and the speed of parallel processing to be able to run a number of data mining and machine learning algorithms quickly.
    Downloads: 0 This Week
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  • 12
    ExoPlanet

    ExoPlanet

    GUI based toolkit for running common Machine Learning algorithms.

    ExoPlanet provides a graphical interface for the construction, evaluation and application of a Machine Learning model in predictive analysis. With the back-end built using the numpy and scikit-learn libraries, as a toolkit, ExoPlanet couples fast and well tested algorithms, a UI designed over the Qt4 framework, and graphs rendered using Matplotlib to provide the user with a rich interface, rapid analytics and interactive visuals. ExoPlanet is designed to have a minimal learning curve,...
    Downloads: 0 This Week
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