On the independence of the individual predictions in parallel randomized ensembles
Entity
UAM. Departamento de Ingeniería InformáticaPublisher
Université catholique de LouvainDate
2012Citation
ESSAN 2012: European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning. Bruges, 2012. 233-238ISBN
978-2-87419-049-0Subjects
InformáticaNote
This is an electronic version of the paper presented at the European Symposium on Artificial Neural Networks, held in Bruges on 2012Abstract
In randomized parallel ensembles the class label predictions
for a particular instance by different ensemble classifiers are independent
random variables. Taking advantage of this independence we design a
statistical test to identify instances near the decision borders, which are
difficult to classify because of their proximity to these borders. For these
instances, the performance of the ensemble is poor and approaches random
guessing. The validity of this analysis and the usefulness of the proposed
statistical test are illustrated in several real-world classification problems.
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Google Scholar:Hernández Lobato, Daniel
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Martínez Muñoz, Gonzalo
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Suárez González, Alberto
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