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.
| Identifer | oai:union.ndltd.org:WATERLOO/oai:uwspace.uwaterloo.ca:10012/3697 |
| Date | January 2008 |
| Creators | McCrosky, Jesse |
| Source Sets | University of Waterloo Electronic Theses Repository |
| Language | English |
| Detected Language | English |
| Type | Thesis or Dissertation |
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