Selection bias: Revision history

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21 March 2023

  • curprev 01:1501:15, 21 March 2023‎ Walle talk contribs‎ 4,400 bytes +4,400‎ Created page with "{{see also|Machine learning terms}} ==Introduction== Selection bias in machine learning refers to the phenomenon where the sample data used to train or evaluate a machine learning model does not accurately represent the underlying population or the target domain. This issue arises when the training data is collected or selected in a way that introduces systematic errors, which can lead to biased predictions or conclusions when the model is applied to real-world scena..."
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