nuggets: Data Pattern Extraction Framework in R

Kód výsledku v 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>

Výsledek na webu

<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>

Jazyk výsledku

angličtina

Název v původním jazyce

nuggets: Data Pattern Extraction Framework in R

Popis výsledku v původním jazyce

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.

Název v anglickém jazyce

nuggets: Data Pattern Extraction Framework in R

Popis výsledku anglicky

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.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

10200 - Computer and information sciences

Projekt

<a href="/cs/project/EH22_008%2F0004583" target="_blank" >EH22_008/0004583: Excelentní výzkum v oblasti digitálních technologií a wellbeingu</a><br>

Návaznosti

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

Rok uplatnění

2024

Kód důvěrnosti údajů

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

Název statě ve sborníku

Modeling Decisions for Artificial Intelligence

ISBN

978-3-031-68208-7

ISSN

—

e-ISSN

—

Počet stran výsledku

12

Strana od-do

115-126

Název nakladatele

Springer Nature Switzerland

Místo vydání

Cham

Místo konání akce

Tokyo

Datum konání akce

27. 8. 2024

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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