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Case-Based Predictions: An Axiomatic Approach to Prediction, Classification and Statistical Learning
     

Case-Based Predictions: An Axiomatic Approach to Prediction, Classification and Statistical Learning

by Itzhak Gilboa, David Schmeidler
 

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

Overview

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.

Product Details

ISBN-13:
9789814366175
Publisher:
World Scientific Publishing Company, Incorporated
Publication date:
05/01/2012
Series:
World Scientific Series in Economic Theory
Pages:
309
Product dimensions:
6.20(w) x 8.90(h) x 1.20(d)

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