The book presents an axiomatic approach to the problems of prediction, classification, and statistical learning. Using methodologies from axiomatic decision theory, and, in particular, the authors' case-based decision theory, the present studies attempt to ask what inductive conclusions can be derived from existing databases. It is shown that simple consistency rules lead to similarity-weighted aggregation, akin to kernel-based methods. It is suggested that the similarity function be estimated from the data. The incorporation of rule-based reasoning is discussed.

Book Information
ISBN 9789814366175
Author Itzhak Gilboa
Format Hardback
Page Count 348
Imprint World Scientific Publishing Co Pte Ltd
Publisher World Scientific Publishing Co Pte Ltd