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nuggets: Data Pattern Extraction Framework in R

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61988987%3A17610%2F24%3AA2502O4M" target="_blank" >RIV/61988987:17610/24:A2502O4M - isvavai.cz</a>

  • Result on the web

    <a href="https://link.springer.com/chapter/10.1007/978-3-031-68208-7_10" target="_blank" >https://link.springer.com/chapter/10.1007/978-3-031-68208-7_10</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1007/978-3-031-68208-7_10" target="_blank" >10.1007/978-3-031-68208-7_10</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    nuggets: Data Pattern Extraction Framework in R

  • Original language description

    nuggets is a framework for subgroup discovery, contrast and emerging patterns, association rules, and more. Developed as a package for the R statistical environment, nuggets provides a novel and extensible toolkit for performing rule-based analyses. Both crisp (Boolean) and fuzzy data are supported. The package generates conditions in the form of elementary conjunctions, evaluates them on a dataset, and checks the induced sub-data for interesting statistical properties. A user defined function may be evaluated on generated sub-dataset, which provides a novel generality. The aim of this paper is to present that free software to the soft computing community, as the tool could be useful to both researchers and analysts in the domain of pattern mining, as, besides searching for various existing pattern types, brand new ideas may be easily implemented and evaluated within that framework.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

  • OECD FORD branch

    10200 - Computer and information sciences

Result continuities

  • Project

    <a href="/en/project/EH22_008%2F0004583" target="_blank" >EH22_008/0004583: Research of Excellence on Digital Technologies and Wellbeing</a><br>

  • Continuities

    P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Others

  • Publication year

    2024

  • Confidentiality

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

Data specific for result type

  • Article name in the collection

    Modeling Decisions for Artificial Intelligence

  • ISBN

    978-3-031-68208-7

  • ISSN

  • e-ISSN

  • Number of pages

    12

  • Pages from-to

    115-126

  • Publisher name

    Springer Nature Switzerland

  • Place of publication

    Cham

  • Event location

    Tokyo

  • Event date

    Aug 27, 2024

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article