Support Vector Machines (SVM)

Support Vector Machines (SVM) are a type of machine learning algorithm used for classifying data into different groups. They work by finding the best boundary, called a hyperplane, that separates data points of different classes with the widest possible margin. Think of it like drawing a line (or a plane) that best divides two sets of points on a graph, ensuring the closest points from each side are as far from the line as possible. This approach helps SVMs make accurate predictions even with complex data, by effectively distinguishing patterns and similarities.