Utility-based learning from data
Statistical learning, particularly probabilistic model learning, has become increasingly important in recent years. Probabilistic models, however, are not usually studied for their own sake but for decision-making purposes. Written by authorities in the field, ""Utility-Based Learning from Data"" approaches the probabilistic modeling problem from the point of view of decision makers who operate in an uncertain environment, base their decisions on a probabilistic model, and build and assess this…
Read More ↓Title Statements
- Full title :Utility-based learning from data / authors, Craig Friedman, Sven Sandow.
Summary
Statistical learning, particularly probabilistic model learning, has become increasingly important in recent years. Probabilistic models, however, are not usually studied for their own sake but for decision-making purposes. Written by authorities in the field, ""Utility-Based Learning from Data"" approaches the probabilistic modeling problem from the point of view of decision makers who operate in an uncertain environment, base their decisions on a probabilistic model, and build and assess this model accordingly. After reviewing utility theory, the book surveys and extends popular statistical.
Read More ↓Edition Statements
- Publication Date:2010.
Publication Statements
- Publisher(s):Chapman & Hall/CRC
- Place of Publication:Boca Raton
- Language:eng
- Publication Date:2010.
Notes
Description based upon print version of record.
Back cover.
The Physical Object
- Description:1 online resource (412 p.).
Edition Identifiers
- ISBN:1000738140, 9781000738148, 0367452324, 9780367452322, 0429141920, 9780429141928, 1420011286, 9781420011289
- DOI:10.1201/9781420011289
- oclc:on1328436951
- LC Classification:Q325.5
- Dewey Decimal:006.3/1
Table of Contents
Front cover; Contents; Preface; Acknowledgments; Disclaimer; Chapter 1: Introduction; Chapter 2: Mathematical Preliminaries; Chapter 3: The Horse Race; Chapter 4: Elements of Utility Theory; Chapter 5: The Horse Race and Utility; Chapter 6: Select Methods for Measuring Model Performance; Chapter 7: A Utility-Based Approach toInformation Theory; Chapter 8: Utility-Based Model Performance Measurement; Chapter 9: Select Methods for Estimating Probabilistic Models; Chapter 10: A Utility-Based Approach to Probability Estimation; Chapter 11: Extensions; Chapter 12: Select Applications; References
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