| dc.contributor.author | Cordeiro De Amorim, Renato | |
| dc.date.accessioned | 2016-04-04T11:47:13Z | |
| dc.date.available | 2016-04-04T11:47:13Z | |
| dc.date.issued | 2013 | |
| dc.identifier.citation | Cordeiro 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 . https://doi.org/10.1007/978-3-642-37807-2_2 | |
| dc.identifier.citation | conference | |
| dc.identifier.isbn | 978-3-642-37806-5 | |
| dc.identifier.isbn | 978-3-642-37807-2 | |
| dc.identifier.other | PURE: 9822506 | |
| dc.identifier.other | PURE UUID: d5482480-ae55-401c-950e-21b879196797 | |
| dc.identifier.other | Scopus: 84875823166 | |
| dc.identifier.uri | http://hdl.handle.net/2299/16913 | |
| dc.description.abstract | This 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 datasets | en |
| dc.language.iso | eng | |
| dc.publisher | Springer Nature | |
| dc.relation.ispartof | Advances in Artificial Intelligence | |
| dc.relation.ispartofseries | Lecture Notes in Computer Science | |
| dc.title | An Empirical Evaluation of Different Initializations on the Number of K-Means Iterations | en |
| dc.contributor.institution | School of Computer Science | |
| rioxxterms.versionofrecord | https://doi.org/10.1007/978-3-642-37807-2_2 | |
| rioxxterms.type | Other | |
| herts.preservation.rarelyaccessed | true | |
