The Community for Technology Leaders
RSS Icon
Subscribe
Issue No.06 - June (1996 vol.18)
pp: 663-668
ABSTRACT
<p><b>Abstract</b>—In this paper we present cost estimates for finding the <it>k</it>-nearest neighbors to a test pattern according to a Minkowski <it>p</it>-metric, as a function of the size of the buckets in partitioning searching algorithms. The asymptotic expected number of operations to find the nearest neighbor is presented as a function of the average number of patterns per bucket <it>n</it> and is shown to contain a global minimum.</p>
INDEX TERMS
k nearest-neighbor search, nearest-neighbor search, complexity analysis, cost analysis, Minkowski p-metric, k-d tree partitioning, ordered partitioning, product partitioning.
CITATION
Pierre Zakarauskas, John M. Ozard, "Complexity Analysis for Partitioning Nearest Neighbor Searching Algorithms", IEEE Transactions on Pattern Analysis & Machine Intelligence, vol.18, no. 6, pp. 663-668, June 1996, doi:10.1109/34.506419
22 ms
(Ver 2.0)

Marketing Automation Platform Marketing Automation Tool