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Combining Parameter Space Search and Meta-learning for Data-Dependent Computational Agent Recommendation

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F12%3A10127163" target="_blank" >RIV/00216208:11320/12:10127163 - isvavai.cz</a>

  • Alternative codes found

    RIV/67985807:_____/12:00384944

  • Result on the web

    <a href="http://dx.doi.org/10.1109/ICMLA.2012.137" target="_blank" >http://dx.doi.org/10.1109/ICMLA.2012.137</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1109/ICMLA.2012.137" target="_blank" >10.1109/ICMLA.2012.137</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Combining Parameter Space Search and Meta-learning for Data-Dependent Computational Agent Recommendation

  • Original language description

    The goal of our data-mining multi-agent system is to facilitate data-mining experiments without the necessary knowledge of the most suitable machine learning method and its parameters to the data. In order to replace the expert's knowledge, the meta-learning subsystems are proposed including the parameter-space search and method recommendation based on previous experiments. In this paper we show the results of the parameter-space search with several search algorithms - tabulation, random search, simmulated annealing, and genetic algorithm.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

    IN - Informatics

  • OECD FORD branch

Result continuities

  • Project

    Result was created during the realization of more than one project. More information in the Projects tab.

  • Continuities

    P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach

Others

  • Publication year

    2012

  • Confidentiality

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

Data specific for result type

  • Article name in the collection

    11th International Conference on Machine Learning and Applications (ICMLA)

  • ISBN

    978-1-4673-4651-1

  • ISSN

  • e-ISSN

  • Number of pages

    6

  • Pages from-to

    36-41

  • Publisher name

    IEEE Computer Society

  • Place of publication

    Neuveden

  • Event location

    Boca Raton, Florida, USA

  • Event date

    Dec 12, 2012

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article