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Book 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.

Book details

Book category Books in English Economics, finance, business & management Economics Economic theory & philosophy

• Full title: Case-based Predictions: An Axiomatic Approach To Prediction, Classification And Statistical Learning
• Author: Itzhak Gilboa
• Language: English
• Binding: Hardback
• Number of pages: 348
• EAN: 9789814366175
• ISBN: 981436617X
• ID: 04430080
• Publisher: World Scientific Publishing Co Pte Ltd
• Weight: 628 g
• Dimensions: 233 × 161 × 24 mm
• Date of publishing: 27. April 2012

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