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Please use this identifier to cite or link to this item: http://hdl.handle.net/10481/49779

Title: Why Linguistic Fuzzy Rule Based Classification Systems perform well in Big Data Applications?
Authors: Fernández Hilario, Alberto
Altalhi, Abdulrahman
Alshomrani, Saleh
Herrera, Francisco
Issue Date: 2017
Abstract: The significance of addressing Big Data applications is beyond all doubt. The current ability of extracting interesting knowledge from large volumes of information provides great advantages to both corporations and academia. Therefore, researchers and practitioners must deal with the problem of scalability so that Machine Learning and Data Mining algorithms can address Big Data properly. With this end, the MapReduce programming framework is by far the most widely used mechanism to implement fault-tolerant distributed applications. This novel framework implies the design of a divide-and-conquer mechanism in which local models are learned separately in one stage (Map tasks) whereas a second stage (Reduce) is devoted to aggregate all sub-models into a single solution. In this paper, we focus on the analysis of the behavior of Linguistic Fuzzy Rule Based Classification Systems when embedded into a MapReduce working procedure. By retrieving different information regarding the rules learned throughout the MapReduce process, we will be able to identify some of the capabilities of this particular paradigm that allowed them to provide a good performance when addressing Big Data problems. In summary, we will show that linguistic fuzzy classifiers are a robust approach in case of scalability requirements.
Sponsorship: This work have been partially supported by the Spanish Ministry of Science and Technology under projects TIN2014-57251-P and TIN2015-68454-R.
Publisher: Atlantis Press
Keywords: Big data
Fuzzy rule based classification systems
URI: http://hdl.handle.net/10481/49779
ISSN: 1875-6883
Rights : Creative Commons Attribution-NonCommercial-NoDerivs 3.0 License
Citation: Fernández Hilario, A.; et al. Why Linguistic Fuzzy Rule Based Classification Systems perform well in Big Data Applications?. International Journal of Computational Intelligence Systems, 10: 1211-1225 (2017). [http://hdl.handle.net/10481/49779]
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