dc.contributor.advisor | Heisterkamp, Douglas R. | |
dc.contributor.author | Muralla, Sumakwel R. | |
dc.date.accessioned | 2014-04-15T18:33:03Z | |
dc.date.available | 2014-04-15T18:33:03Z | |
dc.date.issued | 2006-07-01 | |
dc.identifier.uri | https://hdl.handle.net/11244/8207 | |
dc.description.abstract | K-Means clustering algorithm is a simple and yet very powerful technique of partitioning data sets. This paper presents a method of decreasing the total iterations needed to run K-Means. This is done by adding perturbations to the cluster centroids and using the perturbed centroids as the seed values to compute the next codevectors. The use of this method significantly improved the performance of K-Means while preserving the quality of final cluster centroids. | |
dc.format | application/pdf | |
dc.language | en_US | |
dc.publisher | Oklahoma State University | |
dc.rights | Copyright is held by the author who has granted the Oklahoma State University Library the non-exclusive right to share this material in its institutional repository. Contact Digital Library Services at lib-dls@okstate.edu or 405-744-9161 for the permission policy on the use, reproduction or distribution of this material. | |
dc.title | Method of Accelerating K-means by Directed Perturbation of the Codevectors | |
dc.type | text | |
dc.contributor.committeeMember | Chandler, John P. | |
dc.contributor.committeeMember | Dai, H. K. | |
osu.filename | Muralla_okstate_0664M_1882.pdf | |
osu.college | Arts and Sciences | |
osu.accesstype | Open Access | |
dc.description.department | Computer Science Department | |
dc.type.genre | Thesis | |