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Uncertainty-Based Clustering Algorithms for Large Data Sets

Uncertainty-Based Clustering Algorithms for Large Data Sets

B. K. Tripathy, Hari Seetha, M. N. Murty
Copyright: © 2018 |Pages: 33
ISBN13: 9781522528050|ISBN10: 1522528059|EISBN13: 9781522528067
DOI: 10.4018/978-1-5225-2805-0.ch001
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MLA

Tripathy, B. K., et al. "Uncertainty-Based Clustering Algorithms for Large Data Sets." Modern Technologies for Big Data Classification and Clustering, edited by Hari Seetha, et al., IGI Global, 2018, pp. 1-33. https://doi.org/10.4018/978-1-5225-2805-0.ch001

APA

Tripathy, B. K., Seetha, H., & Murty, M. N. (2018). Uncertainty-Based Clustering Algorithms for Large Data Sets. In H. Seetha, M. Murty, & B. Tripathy (Eds.), Modern Technologies for Big Data Classification and Clustering (pp. 1-33). IGI Global. https://doi.org/10.4018/978-1-5225-2805-0.ch001

Chicago

Tripathy, B. K., Hari Seetha, and M. N. Murty. "Uncertainty-Based Clustering Algorithms for Large Data Sets." In Modern Technologies for Big Data Classification and Clustering, edited by Hari Seetha, M. Narasimha Murty, and B. K. Tripathy, 1-33. Hershey, PA: IGI Global, 2018. https://doi.org/10.4018/978-1-5225-2805-0.ch001

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Abstract

Data clustering plays a very important role in Data mining, machine learning and Image processing areas. As modern day databases have inherent uncertainties, many uncertainty-based data clustering algorithms have been developed in this direction. These algorithms are fuzzy c-means, rough c-means, intuitionistic fuzzy c-means and the means like rough fuzzy c-means, rough intuitionistic fuzzy c-means which base on hybrid models. Also, we find many variants of these algorithms which improve them in different directions like their Kernelised versions, possibilistic versions, and possibilistic Kernelised versions. However, all the above algorithms are not effective on big data for various reasons. So, researchers have been trying for the past few years to improve these algorithms in order they can be applied to cluster big data. The algorithms are relatively few in comparison to those for datasets of reasonable size. It is our aim in this chapter to present the uncertainty based clustering algorithms developed so far and proposes a few new algorithms which can be developed further.

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