International Journal of Computational Intelligence Systems

Volume 8, Issue 3, June 2015, Pages 422 - 437

A MapReduce Approach to Address Big Data Classification Problems Based on the Fusion of Linguistic Fuzzy Rules

Authors
Sara del Río, Victoria López, José Manuel Benítez, Francisco Herrera
Corresponding Author
Sara del Río
Available Online 1 June 2015.
DOI
https://doi.org/10.1080/18756891.2015.1017377How to use a DOI?
Keywords
Fuzzy rule based classification systems, Big data, MapReduce, Hadoop, Rules fusion
Abstract
The big data term is used to describe the exponential data growth that has recently occurred and represents an immense challenge for traditional learning techniques. To deal with big data classification problems we propose the Chi-FRBCS-BigData algorithm, a linguistic fuzzy rule-based classification system that uses the MapReduce framework to learn and fuse rule bases. It has been developed in two versions with different fusion processes. An experimental study is carried out and the results obtained show that the proposal is able to handle these problems providing competitive results.
Open Access
This is an open access article distributed under the CC BY-NC license.

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Journal
International Journal of Computational Intelligence Systems
Volume-Issue
8 - 3
Pages
422 - 437
Publication Date
2015/06
ISSN (Online)
1875-6883
ISSN (Print)
1875-6891
DOI
https://doi.org/10.1080/18756891.2015.1017377How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - JOUR
AU  - Sara del Río
AU  - Victoria López
AU  - José Manuel Benítez
AU  - Francisco Herrera
PY  - 2015
DA  - 2015/06
TI  - A MapReduce Approach to Address Big Data Classification Problems Based on the Fusion of Linguistic Fuzzy Rules
JO  - International Journal of Computational Intelligence Systems
SP  - 422
EP  - 437
VL  - 8
IS  - 3
SN  - 1875-6883
UR  - https://doi.org/10.1080/18756891.2015.1017377
DO  - https://doi.org/10.1080/18756891.2015.1017377
ID  - delRío2015
ER  -