Support Vector Machines

This collection encompasses research on Support Vector Machines (SVM) and their applications within machine learning. Content includes novel frameworks for credit card fraud detection, bankruptcy prediction, and advanced model comparisons for various classification tasks. Documents highlight the geometric principles of SVM, its use in predictive modeling for taxi-time and network maintenance, and its role in healthcare, particularly in predicting diseases such as cancer and diabetes. Overall, the focus is on enhancing prediction accuracy and addressing challenges in diverse datasets.

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