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Optimizing Nearest Neighbour in Random Subspaces using a Multi-Objective Genetic Algorithm

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Optimizing Nearest Neighbour in Random Subspaces using a Multi-Objective Genetic Algorithm
In this work, the authors have evaluated almost 20 millions ensembles of classifiers generated by several methods. Trying to optimize those ensembles based on the nearest neighbours and the random subspaces paradigms, we found that the use of a diversity metric called "ambiguity" had no better positive impact than plain stochastic search.
Guillaume Tremblay, Robert Sabourin, Patrick Maupi
Added 09 Nov 2009
Updated 09 Nov 2009
Type Conference
Year 2004
Where ICPR
Authors Guillaume Tremblay, Robert Sabourin, Patrick Maupin
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