A New Hybrid Under-sampling Approach to Imbalanced Classification Problems

Among many machine learning applications, classification is one of the important tasks. Most classification algorithms have been designed under the assumption that the number of samples for each class is approximately balanced. However, if the conventional classification approaches are applied to a...

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Veröffentlicht in:	Applied artificial intelligence 2022-12, Vol.36 (1)
Hauptverfasser:	Peng, Chun-Yang, Park, You-Jin
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Classification Clustering Data analysis Datasets Machine learning Noise factor Outliers (statistics) Resampling Sampling
Online-Zugang:	Volltext
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