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A Logarithmic-Complexity Algorithm for Nearest Neighbor Classification Using Layered Range Trees
Laboratory for Analysis and Architecture of Systems (LAAS-CNRS), Universitt’e de Toulouse, Toulouse, France
Department of Computer Science, University of Sharjah, Sharjah, UAE
- 1 Laboratory for Analysis and Architecture of Systems (LAAS-CNRS), Universitt’e de Toulouse, Toulouse, France
- 2 Department of Computer Science, University of Sharjah, Sharjah, UAE
Intelligent Information Management·Volume 04 (2012)·Pages 39–43·Published 28 March 2012·DOI10.4236/iim.2012.42006
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Abstract
Finding Nearest Neighbors efficiently is crucial to the design of any nearest neighbor classifier. This paper shows how Layered Range Trees (LRT) could be utilized for efficient nearest neighbor classification. The presented algorithm is robust and finds the nearest neighbor in a logarithmic order. The proposed algorithm reports the nearest neighbor in , where k is a very small constant when compared with the dataset size n and d is the number of dimensions. Experimental results demonstrate the efficiency of the proposed algorithm.
KeywordsNearest Neighbor ClassifierRange TreesLogarithmic Order
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