Support Vector Machine (SVM)

Support Vector Machine is a type of supervised learning algorithm that finds the optimal hyperplane to separate classes in a dataset. It works by identifying support vectors, which are the data points closest to the hyperplane, and maximizing the margin between these points and the hyperplane. SVMs are effective in high-dimensional spaces and are commonly used in classification tasks.