Evolving ensemble of classifiers in random subspace
Proceedings of the 8th annual conference on Genetic and evolutionary computation
Pairwise fusion matrix for combining classifiers
Pattern Recognition
From dynamic classifier selection to dynamic ensemble selection
Pattern Recognition
From dynamic classifier selection to dynamic ensemble selection
Pattern Recognition
Using the RRT algorithm to optimize classification systems for handwritten digits and letters
Proceedings of the 2008 ACM symposium on Applied computing
Pareto analysis for the selection of classifier ensembles
Proceedings of the 10th annual conference on Genetic and evolutionary computation
Boosting k-nearest neighbor classifier by means of input space projection
Expert Systems with Applications: An International Journal
A new dynamic ensemble selection method for numeral recognition
MCS'07 Proceedings of the 7th international conference on Multiple classifier systems
A survey of multiple classifier systems as hybrid systems
Information Fusion
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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.