Some decision network designs for pattern classification

摘要

This article is concerned with the problem of labelling an unidentified parameter vector as belonging to one of a number of given classes. A cluster-analytic approach to the design of binary decision trees is discussed, but the major part of the paper is devoted to the construction of binary features and the creation of a binary feature vector as a means of pattern classification. Complete algorithms are described and some worked examples are also presented.