Information Theoretic Stepwise Selection of Discriminating Discrete Variables.
Abstract
Often the scientist is faced with a large number of categorical variates which are of potential use in discriminating between two pregiven groups of objects. For example, an investor may wish to assign a particular firm to one of two possible risk groups based upon certain known characteristics of the firm (liquid to fixed asset ratio, etc.), or an engineer might wish to determine which of two models best describes a particular situation based upon the observed characteristics of situation. This is the general problem of variable selection in discriminant analysis. When obtaining and processing the numerous variables is expensive, one must select a best subset of variables which incorporates as much information for discriminating as possible. If time is also a factor, a stepwise procedure is mandated. We propose such a stepwise procedure here based upon information theoretic considerations. (Author)
Document Details
- Document Type
- Technical Report
- Publication Date
- May 01, 1979
- Accession Number
- ADA074520
Entities
People
- A. Levine
- P. Brockett
- P. Haaland
Organizations
- University of Texas at Austin