Algorithms for clustering data
Algorithms for clustering data
An introduction to genetic algorithms
An introduction to genetic algorithms
Pattern Recognition and Image Preprocessing
Pattern Recognition and Image Preprocessing
Fuzzy Clustering Models and Applications
Fuzzy Clustering Models and Applications
Digital Image Processing
Self-Adaptive Genetic Algorithm for Clustering
Journal of Heuristics
Refining Initial Points for K-Means Clustering
ICML '98 Proceedings of the Fifteenth International Conference on Machine Learning
Survey of Text Mining
Pattern Classification (2nd Edition)
Pattern Classification (2nd Edition)
Genetic Programming Theory And Practice Ii (Genetic Programming)
Genetic Programming Theory And Practice Ii (Genetic Programming)
Knowledge-Based Clustering: From Data to Information Granules
Knowledge-Based Clustering: From Data to Information Granules
EDA-USL: unsupervised clustering algorithm based on estimation of distribution algorithm
International Journal of Wireless and Mobile Computing
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Clustering techniques have obtained adequate results when are applied to data mining problems. However, different runs of the same clustering technique on a specific dataset may result in different solutions. The cause of this difference is the choice of the initial cluster setting and the values of the parameters associated with the technique. A definition of good initial settings and optimal parameters values is not an easy task, particularly because both vary largely from one dataset to another. In this paper the authors investigate the use of Genetic Algorithms to determine the best initialization of clusters, as well as the optimization of the initial parameters. The experimental results show the great potential of the Genetic Algorithms for the improvement of the clusters, since they do not only optimize the clusters, but resolve the problem of the number K cluster, which had been giving it form a priori. The techniques of clustering are most used in the analysis of information or Data Mining, this method was applied to Data Set at mining.