Support Vector Machines (SVM)
SVM
Support Vector Machines (SVMs) are supervised machine learning models used for classification and regression. They find the optimal hyperplane that maximizes the margin between different classes in a dataset, aiming to effectively separate data points while minimizing misclassifications. SVMs can also utilize kernel functions to map data into higher dimensions, enabling non-linear decision boundaries.