A hyperplane is a boundary that divides a mathematical space into subspaces. In machine learning, it often represents a decision boundary separating classes in a feature space, including high-dimensional spaces used by support vector machines.
A decision boundary in machine learning classifiers that partitions the input space into two or more sections, with each section corresponding to a unique class label.
A boundary that separates a space into two subspaces. For example, a line is a hyperplane in two dimensions and a plane is a hyperplane in three dimensions. More typically in machine learning, a hyperplane is the boundary separating a high-dimensional space. Kernel Support Vector Machines use hyperplanes to separate positive classes from negative classes, often in a very high-dimensional space.