Caesar AI Atlas

Kernel Support Vector Machines

Also known as: Kernel Support Vector Machines (KSVMs) Β· KSVMs Β· Kernel Support Vector Machines KSVMs

Caesar AI Atlas Definition

Kernel support vector machines, or KSVMs, are support vector machines that use kernel functions to create nonlinear decision boundaries. They separate classes by finding a maximum-margin boundary in an implicit higher-dimensional feature space.

Other Definitions

Kernel Support Vector Machines [KSVMs] Source

A classification algorithm that seeks to maximize the margin between positive and negative classes by mapping input data vectors to a higher dimensional space. For example, consider a classification problem in which the input dataset has a hundred features. To maximize the margin between positive and negative classes, a KSVM could internally map those features into a million-dimension space. KSVMs uses a loss function called hinge loss.

Related Terms

VectorNonlinearFeatureKernel MethodSupport Vector MachineHyperplane