Showing 8 open source projects for "algorithms framework"

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  • 1
    Oryx

    Oryx

    Lambda architecture on Apache Spark, Apache Kafka for real-time

    Oryx 2 is a realization of the lambda architecture built on Apache Spark and Apache Kafka, but with specialization for real-time large-scale machine learning. It is a framework for building applications but also includes packaged, end-to-end applications for collaborative filtering, classification, regression and clustering. The application is written in Java, using Apache Spark, Hadoop, Tomcat, Kafka, Zookeeper and more. Configuration uses a single Typesafe Config config file, wherein...
    Downloads: 0 This Week
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  • 2
    Scene
    Scene is a computer vision framework that performs background subtraction and object tracking, using two traditional algorithms and three more recent algorithms based on neural networks and fuzzy classification rules. For each detected object, Scene sends TUIO messages to one or several client applications. The present release features GPU accelerated versions of all the background subtraction methods and morphological post processing of the object blobs with dilation and erosion filters, implemented in OpenCL. ...
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    Downloads: 12 This Week
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  • 3

    Java Library for Machine Learning

    A pure Java library for machine learning

    JML is a machine learning library in Java, it is a pure Java package, and thus is cross-platform. The goal of JML is to make machine learning methods very easy to use and speed up code conversion from MATLAB to Java. Please be noted that JML has been replaced by LAML.
    Downloads: 0 This Week
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  • 4

    JCLALtext

    Text processing module for JCLAL

    JCLALtext is a class library designed to extend the framework JCLAL text tasks. JCLALtext is free, open source and developed with the Java programming language. JCLALtext is distributed under the GNU license. The researcher can use the class library by adding it to your project.
    Downloads: 0 This Week
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  • 5
    The Edlin toolkit provides a machine learning framework for linear models, designed to be easy to read and understand. The main goal is to provide an architecture and easy to edit working examples of implementations for popular learning algorithms.
    Downloads: 0 This Week
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  • 6
    Weka4OC GUI for Overlapping clustering

    Weka4OC GUI for Overlapping clustering

    Weka4OC: Weka for Overlapping Clustering is a GUI extending WEKA

    This is a GUI application for learning non disjoint groups based on Weka machine learning framework. It offers a variety of learning methods, based on k-means, able to produce overlapping clusters. The application also contains an evaluation framework that calculates several external validation measures. The application offers a visualization tool to discover overlapping groups.
    Downloads: 0 This Week
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  • 7
    Ms. Pac-Man Framework

    Ms. Pac-Man Framework

    Using reinforcement learning with relative input to train Ms. Pac-Man

    This Java-application contains all required components to simulate a game of Ms. Pac-Man and let an agent learn intelligent playing behaviour using reinforcement learning and either Q-Learning or SARSA. The framework was developed by Luuk Bom and Ruud Henken, under supervision of Marco Wiering, Department of Artificial Intelligence, University of Groningen. It formed the basis of a bachelor's thesis titled "Using reinforcement learning with relative input to train Ms. Pac-Man", L.A.M. Bom (2012).
    Downloads: 0 This Week
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  • 8
    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: 1 This Week
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