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CASE-BASED PREDICTIONS: AN AXIOMATIC APPROACH TO PREDICTION, CLASSIFICATION AND STATISTICAL LEARNING: 3 (World Scientific Series In Economic Theory) - Hardcover
Synopsis
This 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.
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About the Author
Itzhak Gilboa is Professor of Economics and Decision Sciences at HEC (Ecole des Hautes Etudes Commerciales), Paris, and Professor of Economics at Berglas School of Economics, Tel Aviv University. He is the coauthor (with David Schmeidler) of "Theory of Case-Based Decisions" and the author of "Theory of Decision under Uncertainty".
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- PublisherWorld Scientific Publishing Company
- Publication date2012
- ISBN 10 981436617X
- ISBN 13 9789814366175
- BindingHardcover
- Number of pages348
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