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Clustering of huge datasets using Machine Intelligence Techniques

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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Year of Publication: 2018
Authors:
Shyam Mohan J. S., Shanmugapriya P.
10.5120/ijca2018917856

Shyam Mohan J S. and Shanmugapriya P.. Clustering of huge datasets using Machine Intelligence Techniques. International Journal of Computer Applications 181(18):8-14, September 2018. BibTeX

@article{10.5120/ijca2018917856,
	author = {Shyam Mohan J. S. and Shanmugapriya P.},
	title = {Clustering of huge datasets using Machine Intelligence Techniques},
	journal = {International Journal of Computer Applications},
	issue_date = {September 2018},
	volume = {181},
	number = {18},
	month = {Sep},
	year = {2018},
	issn = {0975-8887},
	pages = {8-14},
	numpages = {7},
	url = {http://www.ijcaonline.org/archives/volume181/number18/29961-2018917856},
	doi = {10.5120/ijca2018917856},
	publisher = {Foundation of Computer Science (FCS), NY, USA},
	address = {New York, USA}
}

Abstract

Cluster identification is useful for finding insights into the huge datasets for finding out the attributes, characteristics of a particular dataset. Today, many organizations have started to use their own data analytic tools for finding clusters.

This paper focuses on various algorithms for finding clusters for huge and different datasets. We have used different datasets and applied MapReduce algorithms for achieving the results. The experimental results obtained in substantial algorithmic computations provide clusters that are used for quick decision making. We present the results performed over various datasets that scales well with respect to both data set size and data set dimensionality.

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Keywords

Machine Intelligence, Dimensionality reduction.