A Systematic Data Mining Method for Clustering of Data using Map-Reduce Model

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Abstract

Data mining is an important research concept that has a vast scope in future. Data mining is used to find the unseen information from the data. In cluster, main half is feature choice. It involves recognition of a set of options of a set, because feature choice is taken into account as a necessary method. They additionally produce the approximate and according requests with the initial set of options employed in this kind of approach. The most construct on the far side this paper is to relinquish the end result of the bunch options. This paper conveys the cluster and the clustering process. The processing of large datasets the nature of clustering where some more concepts are more helpful and important in a clustering process. In clustering methodology many concepts are very useful. The feature selection algorithm which affects the entire process of clustering is the map-reduce concept. Here time needed to seek out the effective options, options of quality subsets is capable of providing effectiveness. The paper discussed map-reduce feature selection approach, its algorithm and framework of implementation.

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Lekha*, Dr. J. … Nithyan, L. (2020). A Systematic Data Mining Method for Clustering of Data using Map-Reduce Model. International Journal of Innovative Technology and Exploring Engineering, 9(3), 716–720. https://doi.org/10.35940/ijitee.b7026.019320

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