Accession Number : ADA292575

Title :   Selection of Relevant Features in Machine Learning.

Descriptive Note : Interim rept. 1 Aug 94-31 Oct 94,

Corporate Author : INSTITUTE FOR THE STUDY OF LEARNING AND EXPERTISE PALO ALTO CA

Personal Author(s) : Langley, Pat

PDF Url : ADA292575

Report Date : 01 NOV 1994

Pagination or Media Count : 8

Abstract : In this paper, we review the problem of selecting relevant features for use in machine learning. We describe this problem in terms of heuristic search through a space of feature sets, and we identify four dimensions along which approaches to the problem can vary. We consider recent work on feature selection in terms of this framework, then close with some challenges for future work in the area.

Descriptors :   *HEURISTIC METHODS, LEARNING MACHINES, PROBLEM SOLVING, SEARCHING, SELECTION.

Subject Categories : Cybernetics

Distribution Statement : APPROVED FOR PUBLIC RELEASE