Showing 8 open source projects for "genetic algorithm php"

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  • 1
    Soma-direct

    Soma-direct

    System Omnichannel Marketing Analysis

    Soma - System Omnichannel Marketing Analysis is an open-source solution for simplifying the processes of analyzing and predicting consumer behavior. With Soma, you can combine data from multiple systems and channels in the profile joining process. Interactions and behaviors registered as a part of a unique user create and show what a Customer Journey looks like. The data is subjected to an analysis process which enables the examination of the significance of individual touchpoints for the...
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  • 2
    Darwin 2: Java Framework for Evolutionary Computation (genetic algorithm, GA). A true framework with out-of-the-box functionality and extensibility of all classes. Interface-based pattern with dependency-injection to configure components.
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  • 3
    PyPedal is a Python module that provides tools for the manipulation of pedigrees, simple visualization of pedigrees, and the calculation of measures of genetic diversity from pedigrees.
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  • 4

    MultiRank

    A customisable Elo-based ranking algorithm suitable for all situations

    I am sick of people saying Elo-based rankings sytems are difficult to implement, particularly in the case of more than two competitors. MultiRank is a fully-customisable Elo-based ranking solution suitable for any situation or number of competitors. Whilst it is written in PHP, it can easily be ported to other languages. A file is included with examples of usage for many situations.
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  • 5
    PHP Business Rules is an open source application layer for PHP. The logic is defined in rules and facts. Like most Business Rule Engines (BRE) it uses the Rete algorithm.
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  • 6
    Ex-Crawler
    Ex-Crawler is divided into 3 subprojects (Crawler Daemon, distributed gui Client, (web) search engine) which together provide a flexible and powerful search engine supporting distributed computing. More informations: http://ex-crawler.sourceforge.net
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  • 7
    Java port and extension of MLC++ 2.0 by Kohavi et al. Currently contains ID3, C4.5, Naive (aka Simple) Bayes, and FSS and CHC (genetic algorithm) wrappers for feature selection. WEKA 3 interfaces are in development.
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  • 8
    R based genetic algorithm for optimization, variable selection and other machine learning and statistical analysis approaches.
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