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Support Vector Machine (SVM) is a supervised machine learning algorithm primarily used for classification, aiming to find the optimal hyperplane that separates data points in different classes. It utilizes support vectors, which are the closest points to the hyperplane, to maximize the margin between classes. SVM can be classified into linear and non-linear types, with various kernel functions available to transform input data for better separation in higher dimensions.

Author

93 75 98 Mehadi

Language

EN