KNN Algorithm Based on Weighted Entropy of Attribute Value

Abstract:

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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 et al., "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:

$35.00

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