Utility-Based Learning from Data
1st Edition
Published on 19. April 2016
417 pages
978-1-000-73814-8 (ISBN)
Description
Utility-Based Learning from Data provides a pedagogical, self-contained discussion of probability estimation methods via a coherent approach from the viewpoint of a decision maker who acts in an uncertain environment. This approach is motivated by the idea that probabilistic models are usually not learned for their own sake; rather, they are used t
More details
Series
Edition
1. Auflage
Language
English
Place of publication
London
United Kingdom
Publishing group
Taylor & Francis Ltd
Target group
College/higher education
File size
7,39 MB
ISBN-13
978-1-000-73814-8 (9781000738148)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Other editions
Additional editions
Craig Friedman | Sven Sandow
Utility-Based Learning from Data
Book
11/2019
1st Edition
Chapman & Hall/CRC
€51.98
Shipment within 15-20 days
Craig Friedman | Sven Sandow
Utility-Based Learning from Data
Book
08/2010
1st Edition
Chapman & Hall/CRC
€155.99
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Persons
Craig Friedman is a managing director and head of research in the Quantitative Analytics group at Standard & Poor's in New York. Dr. Friedman is also a fellow of New York University's Courant Institute of Mathematical Sciences. He is an associate editor of both the International Journal of Theoretical and Applied Finance and the Journal of Credit Risk.
Sven Sandow is an executive director in risk management at Morgan Stanley in New York. Dr. Sandow is also a fellow of New York University's Courant Institute of Mathematical Sciences. He holds a Ph.D. in physics and has published articles in scientific journals on various topics in physics, finance, statistics, and machine learning.
The contents of this book are Dr. Sandow's opinions and do not represent Morgan Stanley.
Sven Sandow is an executive director in risk management at Morgan Stanley in New York. Dr. Sandow is also a fellow of New York University's Courant Institute of Mathematical Sciences. He holds a Ph.D. in physics and has published articles in scientific journals on various topics in physics, finance, statistics, and machine learning.
The contents of this book are Dr. Sandow's opinions and do not represent Morgan Stanley.
Content
Introduction. Mathematical Preliminaries. The Horse Race. Elements of Utility Theory. The Horse Race and Utility. Select Methods for Measuring Model Performance. A Utility-Based Approach to Information Theory. Utility-Based Model Performance Measurement. Select Methods for Estimating Probabilistic Models. A Utility-Based Approach to Probability Estimation. Extensions. Select Applications. References. Index.
