A FAST K-MEANS TYPE CLUSTERING ALGORITHM

Simple item page
dc.contributor.authorWu, Xiaolineng
dc.contributor.authorWitten, Ian H.eng
dc.date.accessioned2008-02-27T22:25:41Z
dc.date.available2008-02-27T22:25:41Z
dc.date.computerscience1999-05-27eng
dc.date.issued1985-06-01eng
dc.description.abstractThis paper describes a new $k$-means type clustering algorithm which gives excellent results for a moderate computational cost. It is particularly suitable for partitioning large data sets into a number of clusters where the conventional $k$-means algorithm becomes computationally unmanageable. While it does not guarantee to reach a global optimum, its performance in practice is very good indeed, as demonstrated by theoretical analysis and experiments on color image data.eng
dc.description.notesWe are currently acquiring citations for the work deposited into this collection. We recognize the distribution rights of this item may have been assigned to another entity, other than the author(s) of the work.If you can provide the citation for this work or you think you own the distribution rights to this work please contact the Institutional Repository Administrator at digitize@ucalgary.caeng
dc.identifier.department1985-197-10eng
dc.identifier.doihttp://dx.doi.org/10.11575/PRISM/31135
dc.identifier.urihttp://hdl.handle.net/1880/46139
dc.language.isoEngeng
dc.publisher.corporateUniversity of Calgaryeng
dc.publisher.facultyScienceeng
dc.subjectComputer Scienceeng
dc.titleA FAST K-MEANS TYPE CLUSTERING ALGORITHMeng
dc.typeunknown
thesis.degree.disciplineComputer Scienceeng
Files
Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
1985-197-10.pdf
Size:
1.97 MB
Format:
Adobe Portable Document Format
Description:
Download
License bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
license.txt
Size:
1.86 KB
Format:
Plain Text
Description:
Download
Collections
Science Research & Publications