Undersampling: Revision history

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21 March 2023

  • curprev 22:2922:29, 21 March 2023‎ Walle talk contribs‎ 3,452 bytes +3,452‎ Created page with "{{see also|Machine learning terms}} ==Overview== Undersampling is a technique used in machine learning to address the issue of imbalanced datasets. In this context, an imbalanced dataset refers to a dataset where the classes are not represented equally. This can lead to poor performance for certain machine learning algorithms, as they may be biased towards the majority class. Undersampling involves reducing the number of instances in the majority class, with the goal..."
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