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.

• Type: Conference
• Year: 2004
• Where: ICPR
• Authors: Guillaume Tremblay, Robert Sabourin, Patrick Maupin
• Keywords: Computer Vision, ICPR 2004, Millions Ensembles, Random Subspaces Paradigms