One-hot encoding: Revision history

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18 March 2023

  • curprev 13:2513:25, 18 March 2023‎ Walle talk contribs‎ 3,145 bytes +3,145‎ Created page with "{{see also|Machine learning terms}} ==One-Hot Encoding== One-hot encoding is a widely used technique in the field of machine learning and data preprocessing. It is employed to convert categorical variables into a numerical format that is suitable for machine learning algorithms to process. This method involves transforming a categorical variable into a binary vector, where each category is represented by a unique combination of zeros and ones. ===Background=== C..."
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