DocumentCode :
2873714
Title :
Genetic algorithms for clustering: a preliminary investigation
Author :
Krovi, Ravindra
Author_Institution :
Dept. of MIS/DS, Memphis State Univ., TN, USA
Volume :
iv
fYear :
1992
fDate :
7-10 Jan 1992
Firstpage :
540
Abstract :
Cluster analysis is a technique which is used to discover patterns and associations within data. More specifically, it is a multivariate statistical procedure that starts with a data set containing information on some variables and attempts to reorganize these data cases into relatively homogeneous groups. One of the major problems encountered by researchers, with regard to cluster analysis that different clustering methods can and do generate different solutions for the same data set. What is needed, is a technique that has discovered the most `natural´ groups in a data set. Genetic algorithms belong to a class of `artificially intelligent´ techniques, that are founded on principles of natural selection and natural genetics. The primary goal of this research effort is to investigate the potential feasibility of using genetic algorithms for the purpose of clustering
Keywords :
data handling; genetic algorithms; artificially intelligent; cluster analysis; data set; genetic algorithms; homogeneous groups; multivariate statistical procedure; natural genetics; natural selection; Algorithm design and analysis; Artificial intelligence; Clustering algorithms; Clustering methods; Couplings; Educational institutions; Euclidean distance; Genetic algorithms; Information analysis; Pattern analysis;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
System Sciences, 1992. Proceedings of the Twenty-Fifth Hawaii International Conference on
Conference_Location :
Kauai, HI
Print_ISBN :
0-8186-2420-5
Type :
conf
DOI :
10.1109/HICSS.1992.183445
Filename :
183445
Link To Document :
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