This monograph is a contribution to the study of the identification
problem: the problem of identifying an item from a known class us
ing positive and negative examples. This problem is considered to
be an important component of the process of inductive learning, and
as such has been studied extensively. In the overview we shall
explain the objectives of this work and its place in the overall
fabric of learning research. Context. Learning occurs in many
forms; the only form we are treat ing here is inductive learning,
roughly characterized as the process of forming general concepts
from specific examples. Computer Science has found three basic
approaches to this problem: * Select a specific learning task,
possibly part of a larger task, and construct a computer program to
solve that task . * Study cognitive models of learning in humans
and extrapolate from them general principles to explain learning
behavior. Then construct machine programs to test and illustrate
these models. xi Xll PREFACE * Formulate a mathematical theory to
capture key features of the induction process. This work belongs to
the third category. The various studies of learning utilize
training examples (data) in different ways. The three principal
ones are: * Similarity-based (or empirical) learning, in which a
collection of examples is used to select an explanation from a
class of possible rules.
General
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