Abstract: Class imbalanced classification presents a considerable difficulty in machine learning, as conventional algorithms typically exhibit bias towards the majority class, compromising minority ...

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Abstract: The work's objective is to assess how well the classification techniques of logistic regression and support vector machine predict handwritten digits. A Digit dataset with 985 records is ...

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The classification models built on class imbalanced data sets tend to prioritize the accuracy of the majority class, and thus, the minority class generally has a higher misclassification rate.