Bagging: Revision history

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18 March 2023

  • curprev 19:0119:01, 18 March 2023‎ Walle talk contribs‎ 3,720 bytes +3,720‎ Created page with "{{see also|Machine learning terms}} ==Bagging in Machine Learning== Bagging, or '''Bootstrap Aggregating''', is a popular ensemble learning technique in machine learning that aims to improve the stability and accuracy of a base learning algorithm by training multiple instances of the same model on different subsamples of the training data. The predictions from the individual models are then combined, usually by means of a majority vote, to produce the final output. This..."
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