Random Balance ensembles for multiclass imbalance learning

Random Balance strategy (RandBal) has been recently proposed for constructing classifier ensembles for imbalanced, two-class data sets. In RandBal, each base classifier is trained with a sample of the data with a random class prevalence, independent of the a priori distribution. Hence, for each samp...

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Veröffentlicht in:	Knowledge-based systems 2020-04, Vol.193, p.105434, Article 105434
Hauptverfasser:	Rodríguez, Juan J., Díez-Pastor, José-Francisco, Arnaiz-González, Álvar, Kuncheva, Ludmila I.
Format:	Artikel
Sprache:	eng
Schlagworte:	Classifier ensembles Classifiers Datasets Imbalanced data Multiclass classification
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