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)
“The woman’s world ... is shown as a series of limited spaces, with the woman struggling to get free of them. The struggle is what the film is about; what is struggled against is the limited space itself. Consequently, to make its point, the film has to deny itself and suggest it was the struggle that was wrong, not the space.”
—Jeanine Basinger (b. 1936)