Oversampling: Revision history

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    4 November 2024

    • curprev 16:4716:47, 4 November 2024‎ 핵톤 talk contribs‎ 5,524 bytes +5,524‎ Created page with "Oversampling is a technique used in data science and machine learning to address class imbalance by increasing the number of samples in the minority class. In classification tasks with imbalanced datasets, oversampling helps to balance the distribution of classes, allowing the model to learn patterns from both majority and minority classes. Oversampling is commonly used in applications such as fraud detection, medical diagnosis, and other areas where certain classes are..." Tag: Visual edit
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