Paper Title:
KNN Algorithm Based on Weighted Entropy of Attribute Value
  Abstract

The traditional KNN algorithm usually adopts European distance formula to measure the distance between two samples. Since each attribute functions differently in the actual sample data collection, the accuracy of the classification will be reduced consequently, this article proposes one method to measure the attribute value and entropy weight, namely KNN algorithm based on weighted entropy of attribute value. The experiment indicated that, compared with the traditional KNN algorithm, the algorithm proposed in this article can not only guarantee the efficiency of classification but also enhance the accuracy of classification.

  Info
Periodical
Advanced Materials Research (Volumes 179-180)
Edited by
Garry Zhu
Pages
1000-1004
DOI
10.4028/www.scientific.net/AMR.179-180.1000
Citation
X. J. Xiao, W. Q. Wang, H. F. Ding, L. Cao, "KNN Algorithm Based on Weighted Entropy of Attribute Value", Advanced Materials Research, Vols. 179-180, pp. 1000-1004, 2011
Online since
January 2011
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Price
$32.00
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