A method that learns from labels and separates groups with the widest gap.
SVM is like a gym teacher drawing a chalk line between two dodgeball teams. It keeps the widest empty space, and the closest kids matter most.
You meet it in small classification tasks, often with small data. With a tweak, it can predict numbers too.
Classification
SVM is best known for classification tasks.
Regression
A changed SVM can also do regression.
Kernel Method
Kernel Method helps SVM split data with curved borders.
SLT
SLT gives SVM its ideas about wide gaps and new data.