Showing 5 open source projects for "outlier detection"

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  • 1
    MOA - Massive Online Analysis

    MOA - Massive Online Analysis

    Big Data Stream Analytics Framework.

    A framework for learning from a continuous supply of examples, a data stream. Includes classification, regression, clustering, outlier detection and recommender systems. Related to the WEKA project, also written in Java, while scaling to adaptive large scale machine learning.
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    Downloads: 124 This Week
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  • 2
    JPIV

    JPIV

    Particle Image Velocimetry

    JPIV is a platform independent, graphical stand-alone application for Particle Image Velocimetry (PIV) written in Java. PIV is an optical technique for measuring fluid flow velocities. JPIV moved to GitHub. Please visit us at: https://eguvep.github.io/jpiv/
    Downloads: 0 This Week
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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...
    Downloads: 0 This Week
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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
    Downloads: 0 This Week
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  • 5
    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.
    Downloads: 0 This Week
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