A New Measure For Clustering Model Selection
| dc.contributor.author | McCrosky, Jesse | |
| dc.date.accessioned | 2008-05-20 14:42:24 (GMT) | |
| dc.date.available | 2008-05-20 14:42:24 (GMT) | |
| dc.date.issued | 2008-05-20T14:42:24Z | |
| dc.date.submitted | 2008 | |
| dc.identifier.uri | http://hdl.handle.net/10012/3697 | |
| dc.description.abstract | A new method for determining the number of k-means clusters in a given data set is presented. The algorithm is developed from a theoretical perspective and then its implementation is examined and compared to existing solutions. | en |
| dc.language.iso | en | en |
| dc.publisher | University of Waterloo | en |
| dc.subject | Clustering | en |
| dc.subject | Model Selection | en |
| dc.title | A New Measure For Clustering Model Selection | en |
| dc.type | Master Thesis | en |
| dc.pending | false | en |
| dc.subject.program | Computer Science | en |
| uws-etd.degree.department | School of Computer Science | en |
| uws-etd.degree | Master of Mathematics | en |
| uws.typeOfResource | Text | en |
| uws.peerReviewStatus | Unreviewed | en |
| uws.scholarLevel | Graduate | en |
