Mining association rules in R using the package RKEEL

The discovery of fuzzy associations comprises a collection of data mining methods used to extract knowledge from large data sets. Although there is an extensive catalog of specialized algorithms that cover different aspects of the problem, the most recent approaches are not yet packaged in mainstrea...

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Bibliographic Details
Main Authors: Sanchez, Oliver, Moyano, Jose M., Sanchez, Luciano, Alcala-Fadez, Jesus
Format: Conference Proceeding
Language:English
Subjects:
Computer science
Data mining
Electronic mail
Measurement
Open source software
Software algorithms
Online Access:Request full text
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Summary:The discovery of fuzzy associations comprises a collection of data mining methods used to extract knowledge from large data sets. Although there is an extensive catalog of specialized algorithms that cover different aspects of the problem, the most recent approaches are not yet packaged in mainstream software environments. This makes it difficult to incorporate novel association rules methods to the data mining workflow. In this paper an extension of the RKEEL package is described that allows calling from the programming language R to those association rules methods contained in KEEL, which is one of the most comprehensive open source software suites. The potential of the proposed tool is illustrated through a case study comprising seven real-world datasets.
ISSN:1558-4739
DOI:10.1109/FUZZ-IEEE.2017.8015572