Sampling bias: Revision history

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21 March 2023

  • curprev 01:1401:14, 21 March 2023‎ Walle talk contribs‎ 4,091 bytes +4,091‎ Created page with "{{see also|Machine learning terms}} ==Introduction== Sampling bias in machine learning is a type of bias that occurs when the data used for training and testing a model does not accurately represent the underlying population. This can lead to a model that performs poorly in real-world applications, as it is not able to generalize well to the broader population. In this article, we will discuss the various causes and types of sampling bias, the consequences of samplin..."
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