PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

A tabular pruning rule in tree-based pruning rule fast nearest neighbour search algorithms
Jose Oncina, Franck Thollard, Eva Gomez-Ballester, Luisa Mico and Francisco Moreno-Seco
In: Third Iberian Conference, IbPRIA 2007, 6-8 June 2007, Girona, Spain.

Abstract

Some fast nearest neighbor search (NNS) algorithms using metric properties have appeared in the last years for reducing computational cost. Depending on the structure used to store the training set, different strategies to speed up the search have been defined. For instance, pruning rules avoid the search of some branches of a tree in a tree-based search algorithm. In this paper, we propose a new and simple pruning rule that can be used in most of the tree-based search algorithms. All the information needed by the rule can be stored in a table (at preprocessing time). Moreover, the rule can be computed in constant time. This approach is evaluated through real and artificial data experiments. In order to test its performance, the rule is compared to and combined with other previously defined rules.

EPrint Type:Conference or Workshop Item (Poster)
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Learning/Statistics & Optimisation
ID Code:3375
Deposited By:Luisa Mico
Deposited On:09 February 2008