The Potential of Prototype Styles of Generalization
D.R. Wilson, Tony R. Martinez · 1993
. There are many ways for a learning system to generalize from training set data. This paper presents several generalization styles using prototypes in an attempt to provide accurate generalization on training set data for a wide variety of applications. These generalization styles are efficient in terms of time and space, and lend themselves well to massively parallel architectures. Empirical results of generalizing on several real-world applications are given, and these results indicate that the prototype styles of generalization presented have potential to provide accurate generalization for many applications. 1. Introduction There are many ways for a learning system to generalize from training set data. This paper proposes several generalization styles using prototypes in an attempt to provide accurate generalization on training set data for a wide variety of applications. These generalization styles are efficient in terms of time and space, and lend themselves well to massively ...