A Multiple Resampling Method for Learning from Imbalanced Data Sets

Resampling methods are commonly used for dealing with the class‐imbalance problem. Their advantage over other methods is that they are external and thus, easily transportable. Although such approaches can be very simple to implement, tuning them most effectively is not an easy task. In particular, i...

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Veröffentlicht in:	Computational intelligence 2004-02, Vol.20 (1), p.18-36
Hauptverfasser:	Estabrooks, Andrew, Jo, Taeho, Japkowicz, Nathalie
Format:	Artikel
Sprache:	eng
Schlagworte:	class imbalance problem decision trees Experiments inductive learning multiple resampling Organizational learning Sampling techniques Studies text classification
Online-Zugang:	Volltext
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