Editing Hyperplane (section)

==Applications==
In [[convex geometry]], two [[disjoint sets|disjoint]] [[convex set]]s in n-dimensional Euclidean space are separated by a hyperplane, a result called the [[hyperplane separation theorem]].

In [[machine learning]], hyperplanes are a key tool to create [[support vector machine]]s for such tasks as [[computer vision]] and [[natural language processing]].

The datapoint and its predicted value via a linear model is a hyperplane.

In [[astronomy]], hyperplanes can be used to calculate shortest distance between star systems, galaxies and celestial bodies with regard of [[general relativity]] and curvature of [[space-time]] as optimized [[geodesic]] or paths influenced by gravitational fields.