SVM (Support Vector Machine)

Support Vector Machine (SVM) is a machine learning technique used for classifying data points into different categories. Imagine plotting data on a graph; SVM finds the best possible straight line (or boundary) that separates these categories with the widest gap, ensuring accurate classification. The points closest to this boundary are called support vectors because they influence its position. SVM aims to maximize this margin to improve the model's ability to classify new data accurately. It works well with complex data by transforming it into higher dimensions to find an optimal separating boundary.