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International Journal of Innovation and Scientific Research
ISSN: 2351-8014
 
 
Tuesday 02 June 2020

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  Call for Papers (June 2020)  
 
 
 

EFFICIENT AND EFFECTIVE SUBSET SELECTION PROCESS BASED ON CLUSTERING ALGORITHM


Volume 6, Issue 1, August 2014, Pages 75–81

 EFFICIENT AND EFFECTIVE SUBSET SELECTION PROCESS BASED ON CLUSTERING ALGORITHM

K. Revathi and T. Kalai Selvi

Original language: English

Received 5 May 2014

Copyright © 2014 ISSR Journals. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract


Process with high dimensional data is enormous issue in data mining and machine learning applications. Feature selection is the mode of recognize the good number of features that produce well-suited outcome as the unique entire set of features. Feature selection process constructs a pathway to reduce the dimensionality and time complexity and also improve the accuracy level of classifier. In this paper, we use an alternative approach, called affinity propagation algorithm for effective and efficient feature selection and clustering process. The endeavor is to improve the performance in terms accuracy and time complexity.

Author Keywords: Classification, Data mining, Feature selection, Feature clustering.


How to Cite this Article


K. Revathi and T. Kalai Selvi, “EFFICIENT AND EFFECTIVE SUBSET SELECTION PROCESS BASED ON CLUSTERING ALGORITHM,” International Journal of Innovation and Scientific Research, vol. 6, no. 1, pp. 75–81, August 2014.