Number of the records: 1  

Search Techniques for Automated Proposal of Data Mining Schemes

  1. 1.
    0470347 - ÚI 2017 RIV CH eng C - Conference Paper (international conference)
    Neruda, Roman
    Search Techniques for Automated Proposal of Data Mining Schemes.
    Applied Computer Sciences in Engineering. Cham: Springer, 2016 - (Figueroa-García, J.; López-Santana, E.; Ferro-Escobar, R.), s. 84-90. Communications in Computer and Information Science, 657. ISBN 978-3-319-50879-5. ISSN 1865-0929.
    [WEA 2016. Workshop on Engineering Applications /3./. Bogota (CO), 21.09.2016-23.09.2016]
    R&D Projects: GA ČR GA15-19877S
    Institutional support: RVO:67985807
    Keywords : computational intelligence * machine learning * meta-learning
    OECD category: Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

    Data mining schemes, or workflows, are collections of interconnected machine learning models, including preprocessing procedures, and ensembles methods combinations. The proposal of data mining schemes for a task at hand has always been a task for experienced data scientists. We will study generating and testing workflows by automated procedures. Two representations of data mining schemes are used in this paper - a linear one, and a one based on direct acyclic graphs. Efficient procedures for generating schemes are presented and evaluated by testing the generated schemes on real data.
    Permanent Link: http://hdl.handle.net/11104/0268011

     
    FileDownloadSizeCommentaryVersionAccess
    a0470347.pdf1604.7 KBPublisher’s postprintrequire
     
Number of the records: 1  

  This site uses cookies to make them easier to browse. Learn more about how we use cookies.