In real-world concept learning problems, the representation of data often uses many
features, only a few of which may be related to the target concept. In this situation, feature
selection is important both to speed up learning and to improve concept quality. A new
feature selection algorithm Relief uses a statistical method and avoids heuristic search.
Relief requires linear time in the number of given features and the number of training
instances regardless of the target concept to be learned. Although the algorithm does not …