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
Sara del Río, Victoria López, José Manuel Benítez, Francisco Herrera
Sara del Río
Available Online 1 June 2015.
- https://doi.org/10.1080/18756891.2015.1017377How to use a DOI?
- Fuzzy rule based classification systems, Big data, MapReduce, Hadoop, Rules fusion
- 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.
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 -