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Item Details
| Title:
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CASE-BASED PREDICTIONS: AN AXIOMATIC APPROACH TO PREDICTION, CLASSIFICATION AND STATISTICAL LEARNING
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| By: |
Itzhak Gilboa, David Schmeidler |
| Format: |
Hardback |
| List price:
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£114.00 |
| Our price: |
£102.60 |
| Discount: |
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| You save:
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£11.40 |
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| ISBN 10: |
981436617X |
| ISBN 13: |
9789814366175 |
| Availability: |
Usually dispatched within 1-3 weeks.
 Delivery
rates
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| Stock: |
Currently 0 available |
| Publisher: |
WORLD SCIENTIFIC PUBLISHING CO PTE LTD |
| Pub. date: |
27 April, 2012 |
| Series: |
World Scientific Series In Economic Theory 3 |
| Pages: |
348 |
| Description: |
Presents an axiomatic approach to the problems of prediction, classification, and statistical learning. |
| Synopsis: |
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. |
| Publication: |
Singapore |
| Imprint: |
World Scientific Publishing Co Pte Ltd |
| Returns: |
Returnable |
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