Showing 6 open source projects for "java machine learning library"

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    DSTK - Data Science TooKit 3

    DSTK - Data Science TooKit 3

    Data and Text Mining Software for Everyone

    DSTK - Data Science Toolkit 3 is a set of data and text mining softwares, following the CRISP DM model. DSTK offers data understanding using statistical and text analysis, data preparation using normalization and text processing, modeling and evaluation for machine learning and algorithms. It is based on the old version DSTK at https://sourceforge.net/projects/dstk2/ DSTK Engine is like R. DSTK ScriptWriter offers GUI to write DSTK script. DSTK Studio offers SPSS Statistics like GUI...
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  • 2
    DSTK - DataScience ToolKit

    DSTK - DataScience ToolKit

    DSTK - DataScience ToolKit for All of Us

    DSTK - DataScience ToolKit is an opensource free software for statistical analysis, data visualization, text analysis, and predictive analytics. Newer version and smaller file size can be found at: https://sourceforge.net/projects/dstk3/ It is designed to be straight forward and easy to use, and familar to SPSS user. While JASP offers more statistical features, DSTK tends to be a broad solution workbench, including text analysis and predictive analytics features. Of course you may specify...
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  • 3
    Cenobi

    Cenobi

    cost estimation and management accounting, using neural networks

    Cenobi is designed for management accountants, not (only) for statisticians and data mining experts. Carefully arranged default settings make sure you can concentrate on Cenobi's many accounting features rather than worrying about setting up artificial neural networks or genetic algorithms, which are the main machine learning tools under Cenobi's hood. Cenobi's main benefits are: - ease of use - Utilizing artificial neural networks to estimate cost relationships, Cenobi is able to...
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  • 4
    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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  • 5
    ICT-Alive
    The aim of ALIVE is to develop new approaches to the engineering of flexible, adaptable distributed service-oriented systems based on the adaptation of social coordination and organisation mechanisms.
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  • 6
    weka outlier is an implementation of outlier detection algorithms for WEKA. CODB (Class Outliers: Distance-Based) Algorithm is the first algorithm developed using WEKA framework.
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