A/B testing: Revision history

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17 March 2023

27 February 2023

  • curprev 14:3314:33, 27 February 2023‎ Alpha5 talk contribs‎ 3,281 bytes +3,281‎ Created page with "{{see also|Machine learning terms}} ==Introduction== A/B testing is a statistical method employed in machine learning research to compare two versions of a product and determine which version is more successful. It involves randomly dividing a population into two groups, "A" and "B," then exposing each group to one version of the tested product. After analyzing the results of this experiment, one version will be determined as having higher click-through rates or conversi..."
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