Clustering Algorithm for Mixed Attributes Data Based on Restricted Particle Swarm Optimization
作者单位：Department of Computer Science Harbin Engineering University Department of Computer Science Northeast Agricultural University
会议名称：《2011 International Conference on Computer Science and Information Technology(ICCSIT 2011)》
会议日期：2011年
学科分类：12[管理学] 1201[管理学-管理科学与工程(可授管理学、工学学位)] 081104[工学-模式识别与智能系统] 08[工学] 0835[工学-软件工程] 0811[工学-控制科学与工程] 0812[工学-计算机科学与技术（可授工学、理学学位）]
关 键 词：numerical and categorical values potential field restriction particle swarm
摘 要：When the data mixed with numerical and categorical values is processed at present, it is very common to convert the categorical values into numerical ones and then cluster them according to a certain weight. Obviously such clustering results rely heavily on the weight given by experts. Hence in this paper a categorical attribute is proposed as a potential field restriction to limit the searching directions of particle swarm, which consequently improves the speed and effectiveness of the clustering algorithms.