English
 
Help Privacy Policy Disclaimer
  Advanced SearchBrowse

Item

ITEM ACTIONSEXPORT
 
 
DownloadE-Mail
  Cluster Identification in Nearest-Neighbor Graphs

Maier, M., Hein, M., & von Luxburg, U.(2007). Cluster Identification in Nearest-Neighbor Graphs (163).

Item is

Files

show Files

Locators

show

Creators

show
hide
 Creators:
Maier, M1, Author           
Hein, M, Author
von Luxburg, U1, Author           
Affiliations:
1Department Empirical Inference, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497795              

Content

show
hide
Free keywords: -
 Abstract: Assume we are given a sample of points from some underlying distribution which contains several distinct clusters. Our goal is to construct a neighborhood graph on the sample points such that clusters are ``identifiedlsquo;lsquo;: that is, the subgraph induced by points from the same cluster is connected, while subgraphs corresponding to different clusters are not connected to each other. We derive bounds on the probability that cluster identification is successful, and use them to predict ``optimallsquo;lsquo; values of k for the mutual and symmetric k-nearest-neighbor graphs. We point out different properties of the mutual and symmetric nearest-neighbor graphs related to the cluster identification problem.

Details

show
hide
Language(s):
 Dates: 2007-05
 Publication Status: Issued
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: -
 Identifiers: Report Nr.: 163
BibTex Citekey: 4587
 Degree: -

Event

show

Legal Case

show

Project information

show

Source

show