Publication Type |
pre-print |
School or College |
College of Engineering |
Department |
Computing, School of |
Creator |
Venkatasubramanian, Suresh |
Other Author |
Raman, Parasaran |
Title |
Power to the points: validating data memberships in clusterings |
Date |
2013-01-01 |
Description |
In this paper, we present a method to attach affinity scores to the implicit labels of individual points in a clustering. The affinity scores capture the confidence level of the cluster that claims to "own" the point. We demonstrate that these scores accurately capture the quality of the label assigned to the point. We also show further applications of these scores to estimate global measures of clustering quality, as well as accelerate clustering algorithms by orders of magnitude using active selection based on affinity. This method is very general and applies to clusterings derived from any geometric source. It lends itself to easy visualization and can prove useful as part of an interactive visual analytics framework. It is also efficient: assigning an affinity score to a point depends only polynomially on the number of clusters and is independent both of the size and dimensionality of the data. It is based on techniques from the theory of interpolation, coupled with sampling and estimation algorithms from high dimensional computational geometry. |
Type |
Text |
Publisher |
Institute of Electrical and Electronics Engineers (IEEE) |
First Page |
617 |
Last Page |
626 |
Language |
eng |
Bibliographic Citation |
Raman, P., & Venkatasubramanian, S. (2013). Power to the points: validating data memberships in clusterings. Proceedings - IEEE International Conference on Data Mining, ICDM, 6729546, 617-26. |
Rights Management |
(c) 2013 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE. |
Format Medium |
application/pdf |
Format Extent |
948,810 bytes |
Identifier |
uspace,18494 |
ARK |
ark:/87278/s6jq490z |
Setname |
ir_uspace |
ID |
712047 |
Reference URL |
https://collections.lib.utah.edu/ark:/87278/s6jq490z |