In pattern recognition a feature space is an abstract space where each pattern sample is represented as a point in n-dimensional space. Its dimension is determined by the number of features used to describe the patterns. Similar samples are grouped together, which allows the use of density estimation for finding patterns.
The concept is a most used one in classification techniques like k nearest neighbors or support vector machines.
Famous quotes containing the words feature and/or space:
“When delicate and feeling souls are separated, there is not a feature in the sky, not a movement of the elements, not an aspiration of the breeze, but hints some cause for a lover’s apprehension.”
—Richard Brinsley Sheridan (1751–1816)
“In bourgeois society, the French and the industrial revolution transformed the authorization of political space. The political revolution put an end to the formalized hierarchy of the ancien regimé.... Concurrently, the industrial revolution subverted the social hierarchy upon which the old political space was based. It transformed the experience of society from one of vertical hierarchy to one of horizontal class stratification.”
—Donald M. Lowe, U.S. historian, educator. History of Bourgeois Perception, ch. 4, University of Chicago Press (1982)