Analysis of Data using K-Means Clustering Algorithm with Min Max Function

  IJCTT-book-cover
 
International Journal of Computer Trends and Technology (IJCTT)          
 
© 2018 by IJCTT Journal
Volume-58 Number-2
Year of Publication : 2018
Authors : S. Narain Sinha, Ram Lal Yadav
  10.14445/22312803/IJCTT-V58P113

MLA

S. Narain Sinha, Ram Lal Yadav "Analysis of Data using K-Means Clustering Algorithm with Min Max Function". International Journal of Computer Trends and Technology (IJCTT) V58(2):82-84, April 2018. ISSN:2231-2803. www.ijcttjournal.org. Published by Seventh Sense Research Group.

Abstract
The information is currently used for wide range of applications. Data mining is a logical process that is used to search through large amount of data in order to find useful data. Data mining is studied for different databases. For the proper utilization of data the data analytics techniques are applied on the data. Data analytics uses clustering, normalization, etc. Clustering is the process of organizing the objects into groups whose members are similar in some way to others. Lot of work is done in this field by different researchers. In this work the new data analytics technique is proposed. The base technique is modified by the new proposed technique. New technique uses the min max function instead of the scaling. The new technique is proposed, designed, implemented in the R language. The results obtained and analysed. The new proposed technique gives the better and compact clusters.

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Keywords
Data Mining, K-Means Clustering, Data analytics, normalization, Min Max Function.