Walle
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..."
