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
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;
Conference_Titel :
Pattern Recognition, 1998. Proceedings. Fourteenth International Conference on
Conference_Location :
Brisbane, Qld.
Print_ISBN :
0-8186-8512-3
DOI :
10.1109/ICPR.1998.711276