A Fast k Nearest Neighbor Finding Algorithm Based on the Ordered Partition
IEEE Transactions on Pattern Analysis and Machine Intelligence
An algorithm for finding nearest neighbours in (approximately) constant average time
Pattern Recognition Letters
An efficient branch-and-bound nearest neighbour classifier
Pattern Recognition Letters
Introduction to statistical pattern recognition (2nd ed.)
Introduction to statistical pattern recognition (2nd ed.)
Pattern Recognition Letters
Reducing the overhead of the AESA metric-space nearest neighbour searching algorithm
Information Processing Letters
A fast branch & bound nearest neighbour classifier in metric spaces
Pattern Recognition Letters
A Fast Nearest-Neighbor Algorithm Based on a Principal Axis Search Tree
IEEE Transactions on Pattern Analysis and Machine Intelligence
Fast Nearest-Neighbor Search in Dissimilarity Spaces
IEEE Transactions on Pattern Analysis and Machine Intelligence
ICPR '98 Proceedings of the 14th International Conference on Pattern Recognition-Volume 1 - Volume 1
Some approaches to improve tree-based nearest neighbour search algorithms
Pattern Recognition
Fast k most similar neighbor classifier for mixed data (tree k-MSN)
Pattern Recognition
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In this paper, the efficiency of branch and bound search algorithms for the computation of K nearest neighbors is studied. The most important aspects that influence the efficiency of the search algorithm are: (1) the decomposition method, (2) the elimination rule, (3) the traversal order and (4) the level of decomposition. First, a theoretical derivation of an efficient decomposition method based on principal component analysis is given. Then, different elimination rules and traversal orders are combined resulting in ten different search algorithms. Since the efficiency is strongly dependent on the level of decomposition, this user specified parameter is optimized first. This optimization is realized by a probabilistic model that expresses the total computation time in function of the node traversal cost and the distance computation cost. All comparisons are based on the total computation time for the optimal level of decomposition.