A MapReduce Approach to Address Big Data Classification Problems Based on the Fusion of Linguistic Fuzzy Rules
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...
Main Authors: | , , , |
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Format: | Article |
Language: | English |
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Springer
2015-06-01
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Series: | International Journal of Computational Intelligence Systems |
Subjects: | |
Online Access: | https://www.atlantis-press.com/article/25868606.pdf |
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author | Sara del Río Victoria López José Manuel Benítez Francisco Herrera |
author_facet | Sara del Río Victoria López José Manuel Benítez Francisco Herrera |
author_sort | Sara del Río |
collection | DOAJ |
description | 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. |
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format | Article |
id | doaj.art-242dc903934b4675bfdcda35da76f0f3 |
institution | Directory Open Access Journal |
issn | 1875-6883 |
language | English |
last_indexed | 2024-12-10T07:36:02Z |
publishDate | 2015-06-01 |
publisher | Springer |
record_format | Article |
series | International Journal of Computational Intelligence Systems |
spelling | doaj.art-242dc903934b4675bfdcda35da76f0f32022-12-22T01:57:25ZengSpringerInternational Journal of Computational Intelligence Systems1875-68832015-06-018310.1080/18756891.2015.1017377A MapReduce Approach to Address Big Data Classification Problems Based on the Fusion of Linguistic Fuzzy RulesSara del RíoVictoria LópezJosé Manuel BenítezFrancisco HerreraThe 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.https://www.atlantis-press.com/article/25868606.pdfFuzzy rule based classification systemsBig dataMapReduceHadoopRules fusion |
spellingShingle | Sara del Río Victoria López José Manuel Benítez Francisco Herrera A MapReduce Approach to Address Big Data Classification Problems Based on the Fusion of Linguistic Fuzzy Rules International Journal of Computational Intelligence Systems Fuzzy rule based classification systems Big data MapReduce Hadoop Rules fusion |
title | A MapReduce Approach to Address Big Data Classification Problems Based on the Fusion of Linguistic Fuzzy Rules |
title_full | A MapReduce Approach to Address Big Data Classification Problems Based on the Fusion of Linguistic Fuzzy Rules |
title_fullStr | A MapReduce Approach to Address Big Data Classification Problems Based on the Fusion of Linguistic Fuzzy Rules |
title_full_unstemmed | A MapReduce Approach to Address Big Data Classification Problems Based on the Fusion of Linguistic Fuzzy Rules |
title_short | A MapReduce Approach to Address Big Data Classification Problems Based on the Fusion of Linguistic Fuzzy Rules |
title_sort | mapreduce approach to address big data classification problems based on the fusion of linguistic fuzzy rules |
topic | Fuzzy rule based classification systems Big data MapReduce Hadoop Rules fusion |
url | https://www.atlantis-press.com/article/25868606.pdf |
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