Big Data Classification using Fuzzy K-Nearest Neighbor
Malak El, Soha Safwat, Osman Hegazy · International Journal of Computer Applications · 2015
Because of the massive increase in the size of the data it becomes troublesome to perform effective analysis using the current traditional techniques.Big data put forward a lot of challenges due to its several characteristics like volume, velocity, variety, variability, value and complexity.Today there is not only a necessity for efficient data mining techniques to process large volume of data but in addition a need for a means to meet the computational requirements to process such huge volume of data.The objective of this paper is to classify big data using Fuzzy K-Nearest Neighbor classifier, and to provide a comparative study between the results of the proposed systems and the method reviewed in the literature.In this paper we implemented the Fuzzy K-Nearest Neighbor method using the MapReduce paradigm to process on big data.Results on different data sets show that the proposed Fuzzy K-Nearest Neighbor method outperforms a better performance than the method reviewed in the literature.