A Kind of Fast Clustering Algorithm Based on Probability
Author(s): LI Jing, School of Mathematics, Chongqing Normal University
Pages: 61-65
Year: 2014 Issue: 2
Journal: Journal of Yuzhou University, Natural Sciences Edition
Keyword: clustering; sample; feature; probability;
Abstract: In clustering algorithms,in model samples determined by eigenvector dimensions,every dimension of each sample represents a corresponding feature,based on this,this paper advances a kind of fast clustering algorithm based on probability on the basis of hierarchical algorithm. This algorithm firstly classifies each feature,then according to probability principle,makes each vector become a type,combines the maximum eigenvectors with its corresponding probability to reduce the type number until the requirement is met,and conducts simulation experiment on this algorithm by using Iris and Wine data set in UCI. Experiment data show that better clustering results can be obtained by using this algorithm for clustering,which illustrates that this algorithm has certain validity.
Pages: 61-65
Year: 2014 Issue: 2
Journal: Journal of Yuzhou University, Natural Sciences Edition
Keyword: clustering; sample; feature; probability;
Abstract: In clustering algorithms,in model samples determined by eigenvector dimensions,every dimension of each sample represents a corresponding feature,based on this,this paper advances a kind of fast clustering algorithm based on probability on the basis of hierarchical algorithm. This algorithm firstly classifies each feature,then according to probability principle,makes each vector become a type,combines the maximum eigenvectors with its corresponding probability to reduce the type number until the requirement is met,and conducts simulation experiment on this algorithm by using Iris and Wine data set in UCI. Experiment data show that better clustering results can be obtained by using this algorithm for clustering,which illustrates that this algorithm has certain validity.
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