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Search Techniques for Automated Proposal of Data Mining Schemes

Result description

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.

Keywords

computational intelligencemachine learningmeta-learning

The result's identifiers

Alternative languages

  • Result language

    angličtina

  • Original language name

    Search Techniques for Automated Proposal of Data Mining Schemes

  • Original language description

    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.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

    IN - Informatics

  • OECD FORD branch

Result continuities

Others

  • Publication year

    2016

  • Confidentiality

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

Data specific for result type

  • Article name in the collection

    Applied Computer Sciences in Engineering

  • ISBN

    978-3-319-50879-5

  • ISSN

    1865-0929

  • e-ISSN

  • Number of pages

    7

  • Pages from-to

    84-90

  • Publisher name

    Springer

  • Place of publication

    Cham

  • Event location

    Bogota

  • Event date

    Sep 21, 2016

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article