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One-hot encoding is a crucial technique in data preprocessing that transforms categorical data into a binary format, enabling the application of mathematical and statistical analyses like correlation on these categories. This process is essential for incorporating categorical variables into machine learning and statistical models, enhancing their capacity to uncover valuable insights and patterns in the data.
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