Associative Classification in R: arc, arulesCBA, and rCBA
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21240%2F19%3A00337444" target="_blank" >RIV/68407700:21240/19:00337444 - isvavai.cz</a>
Alternative codes found
RIV/61384399:31140/19:00054581
Result on the web
<a href="https://doi.org/10.32614/RJ-2019-048" target="_blank" >https://doi.org/10.32614/RJ-2019-048</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.32614/RJ-2019-048" target="_blank" >10.32614/RJ-2019-048</a>
Alternative languages
Result language
angličtina
Original language name
Associative Classification in R: arc, arulesCBA, and rCBA
Original language description
Several methods for creating classifiers based on rules discovered via association rule mining have been proposed in the literature. These classifiers are called associative classifiers and the best-known algorithm is Classification Based on Associations (CBA). Interestingly, only very few implementations are available and, until recently, no implementation was available for R. Now, three packages provide CBA. This paper introduces associative classification, the CBA algorithm, and how it can be used in R. A comparison of the three packages is provided to give the potential user an idea about the advantages of each of the implementations. We also show how the packages are related to the existing infrastructure for association rule mining already available in R.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
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Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2019
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
The R Journal
ISSN
2073-4859
e-ISSN
2073-4859
Volume of the periodical
11
Issue of the periodical within the volume
2
Country of publishing house
AT - AUSTRIA
Number of pages
14
Pages from-to
254-267
UT code for WoS article
000522733900018
EID of the result in the Scopus database
2-s2.0-85087025613