An improved K-means clustering algorithm

That traditional K-mean algorithm is a widely used clustering algorithm, with a wide application. In light of the disadvantage of K-mean algorithm, improvement is made to the traditional K-mean algorithm, a k value learning algorithm is proposed. Using genetic algorithm to optimize the K value, and...

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Bibliographic Details
Published in2010 2nd IEEE International Conference on Information Management and Engineering pp. 190 - 192
Main Authors Jian Zhu, Hanshi Wang
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.04.2010
Subjects
Application software
Clustering algorithm
Clustering algorithms
Computer science
Data compression
Data mining
Euclidean distance
genetic algorithm
Genetic algorithms
K-mean value
Modeling
Neural networks
Radial basis function networks
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ISBN9781424452637
1424452635
DOI10.1109/ICIME.2010.5478087

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Summary:That traditional K-mean algorithm is a widely used clustering algorithm, with a wide application. In light of the disadvantage of K-mean algorithm, improvement is made to the traditional K-mean algorithm, a k value learning algorithm is proposed. Using genetic algorithm to optimize the K value, and improve clustering performance.
ISBN:9781424452637
1424452635
DOI:10.1109/ICIME.2010.5478087