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

Itzhak Gilboa, David Schmeidler

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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.

Produktfakta

Språk Engelsk Engelsk Utgitt 2012
Forfatter David Schmeidler, Itzhak Gilboa Forlag
World Scientific Publishing UK
ISBN 9789814366175 Antall sider 250
Dimensjoner 15,7cm x 22,9cm x 2,3cm Vekt 612 gram
Leverandør Bertram Trading Ltd Emner og form Economic theory & philosophy