%A JIANG Feng, DU Junwei, LIU Guozhu, SUI Yuefei
%T A weight-based initial centers selection algorithm for *K*-modes clustering
%0 Journal Article
%D 2016
%J Journal of Shandong University(Engineering Science)
%R 10.6040/j.issn.1672-3961.0.2015.101
%P 29-34
%V 46
%N 2
%U {http://gxbwk.njournal.sdu.edu.cn/CN/abstract/article_1437.shtml}
%8 2016-04-20
%X The current initialization methods for *K*-modes clustering do not consider the case in which various attributes have different significances. To solve this problem, a weighted density and weighted overlap distance-based initial center selection algorithm(called Ini_{-}Weight)was proposed. In algorithm Ini_{-}Weight, initial centers were selected by calculating the density of each object and the distance between any two objects. In Ini_{-}Weight, when calculating the density of each object and the distance between any two objects, different weights were assigned to different attributes according to the significance of each attribute. Finally, Ini_{-}Weight was compared with the current methods on UCI data sets. The results showed that Ini_{-}Weight algorithm could effectively distinguish different attributes and improve the accuracy for selecting initial centers.