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dc.contributor.authorCordeiro De Amorim, Renato
dc.identifier.citationCordeiro De Amorim , R 2013 , An Empirical Evaluation of Different Initializations on the Number of K-Means Iterations . in Advances in Artificial Intelligence : 11th Mexican International Conference on Artificial Intelligence - revised selected papers . Lecture Notes in Computer Science , vol. 7629 , Springer Nature , pp. 15-26 , 11th Mexican Int Conf on Artificial Intelligence - MICAI 2012 , San Luis Potosi , Mexico , 27/10/12 .
dc.description.abstractThis paper presents an analysis of the number of iterations K-Means takes to converge under different initializations. We have experimented with seven initialization algorithms in a total of 37 real and synthetic datasets. We have found that hierarchical-based initializations tend to be most effective at reducing the number of iterations, especially a divisive algorithm using the Ward criterion when applied to real datasetsen
dc.publisherSpringer Nature
dc.relation.ispartofAdvances in Artificial Intelligence
dc.relation.ispartofseriesLecture Notes in Computer Science
dc.titleAn Empirical Evaluation of Different Initializations on the Number of K-Means Iterationsen
dc.contributor.institutionSchool of Computer Science

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