support-vector-machine

A supervised learning algorithm used for classification and regression tasks.

Support vector machines (SVMs) work by finding the optimal hyperplane that separates different classes in the feature space. They are effective in high-dimensional spaces and can handle both linear and non-linear classification through the use of kernel functions. SVMs are known for their robustness against overfitting.