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Utility-Based Learning from Data book cover

1st Edition

Utility-Based Learning from Data

By Craig Friedman, Sven Sandow Copyright 2011
417 Pages
by Chapman & Hall

418 Pages
by Chapman & Hall

417 Pages
by Chapman & Hall
Also available as eBook on:
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 to make decisions. Specifically, the authors... Read more

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.

Biography

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.

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