In this work, a new method for the creation of classifier ensembles is introduced. The patterns are partitioned into clusters to group together similar patterns, a training set is built using the patterns that belong to a cluster. Each of the new sets is used to train a classifier. We show that the approach here presented, called FuzzyBagging, obtains performance better than Bagging.
A. Lumini, L. Nanni (2006). FuzzyBagging: a novel ensemble of classifiers. PATTERN RECOGNITION, 39, 488-490 [10.1016/j.patcog.2005.10.002].
FuzzyBagging: a novel ensemble of classifiers
LUMINI, ALESSANDRA;NANNI, LORIS
2006
Abstract
In this work, a new method for the creation of classifier ensembles is introduced. The patterns are partitioned into clusters to group together similar patterns, a training set is built using the patterns that belong to a cluster. Each of the new sets is used to train a classifier. We show that the approach here presented, called FuzzyBagging, obtains performance better than Bagging.File in questo prodotto:
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