DocumentCode
2734912
Title
On clusterings-good, bad and spectral
Author
Kannan, Ravi ; Vempala, Santosh ; Veta, A.
Author_Institution
Dept. of Comput. Sci., Yale Univ., New Haven, CT, USA
fYear
2000
fDate
2000
Firstpage
367
Lastpage
377
Abstract
We propose a new measure for assessing the quality of a clustering. A simple heuristic is shown to give worst-case guarantees under the new measure. Then we present two results regarding the quality of the clustering found by a popular spectral algorithm. One proffers worst case guarantees whilst the other shows that if there exists a “good” clustering then the spectral algorithm will find one close to it
Keywords
computational complexity; heuristic programming; pattern clustering; randomised algorithms; clustering quality assessment measure; heuristic; polynomial time algorithms; randomized algorithm; spectral algorithm; spectral clustering; worst-case guarantees; Algorithm design and analysis; Clustering algorithms; Computer science; Engineering profession; Mathematics; Partitioning algorithms; Performance analysis; Spectral analysis;
fLanguage
English
Publisher
ieee
Conference_Titel
Foundations of Computer Science, 2000. Proceedings. 41st Annual Symposium on
Conference_Location
Redondo Beach, CA
ISSN
0272-5428
Print_ISBN
0-7695-0850-2
Type
conf
DOI
10.1109/SFCS.2000.892125
Filename
892125
Link To Document