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Implementation of parameter space search for meta learning in a data-mining multi-agent system

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985807%3A_____%2F11%3A00375575" target="_blank" >RIV/67985807:_____/11:00375575 - isvavai.cz</a>

  • Alternative codes found

    RIV/00216208:11320/11:10103692

  • Result on the web

    <a href="http://dx.doi.org/10.1109/ICMLA.2011.161" target="_blank" >http://dx.doi.org/10.1109/ICMLA.2011.161</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1109/ICMLA.2011.161" target="_blank" >10.1109/ICMLA.2011.161</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Implementation of parameter space search for meta learning in a data-mining multi-agent system

  • Original language description

    In this paper an implementation of a multi-agent system designed for solving complex data mining tasks is presented. The system is based on ontologically sound AGR (agents, groups, roles) model and encapsulates Weka library methods in JADE agents. We emphasize the unique intelligent features of the system - its ability to search the parameter space of the data mining methods to find the optimal configuration, and meta learning - finding the best possible method for the given data based on the ontological compatibility of datasets.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

    IN - Informatics

  • OECD FORD branch

Result continuities

  • Project

    <a href="/en/project/GAP202%2F11%2F1368" target="_blank" >GAP202/11/1368: Learning of functional relationships from high-dimensional data</a><br>

  • Continuities

    Z - Vyzkumny zamer (s odkazem do CEZ)

Others

  • Publication year

    2011

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Article name in the collection

    Proceedings of the The 10th International Conference on Machine Learning and Applications

  • ISBN

    978-0-7695-4607-0

  • ISSN

  • e-ISSN

  • Number of pages

    4

  • Pages from-to

    366-369

  • Publisher name

    IEEE Computer Society

  • Place of publication

    Piscataway

  • Event location

    Honolulu

  • Event date

    Dec 18, 2011

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article