DocumentCode
327814
Title
The labelled cell classifier: a fast approximation to k nearest neighbors
Author
Palau, Alessandro M. ; Snapp, Robert R.
Author_Institution
Dept. of Comput. Sci., Vermont Univ., Burlington, VT, USA
Volume
1
fYear
1998
fDate
16-20 Aug 1998
Firstpage
823
Abstract
A k-nearest-neighbor classifier is approximated by a labeled cell classifier that recursively labels the nodes of a hierarchically organized reference sample (e.g., a k-d tree) if a local estimate of the conditional Bayes risk is sufficiently small. Simulations suggest that the labeled cell classifier is significantly faster than k-d tree implementations for problems with small Bayes risk, and may be more accurate as a larger reference sample can be examined in a fixed amount of time
Keywords
Bayes methods; approximation theory; pattern classification; trees (mathematics); Bayes risk; fast approximation; feature space; labelled cell classifier; nearest-neighbor classifier; pattern classification; trees; Acceleration; Algorithm design and analysis; Binary search trees; Classification tree analysis; Computational efficiency; Computer science; Data structures; Multidimensional systems; Nearest neighbor searches; Pattern recognition;
fLanguage
English
Publisher
ieee
Conference_Titel
Pattern Recognition, 1998. Proceedings. Fourteenth International Conference on
Conference_Location
Brisbane, Qld.
ISSN
1051-4651
Print_ISBN
0-8186-8512-3
Type
conf
DOI
10.1109/ICPR.1998.711276
Filename
711276
Link To Document