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Conformal Prediction for Reliable Machine Learning : Theory, Adaptations and Applications by Shen-Shyang Ho (2014, Trade Paperback)

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Binding: Paperback, Paperback. Weight: 1.47 lbs. Publication Date: 2014-04-29. Publisher: Morgan Kaufmann Publishers.

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Product Information

The conformal predictions framework is a recent development in machine learning that can associate a reliable measure of confidence with a prediction in any real-world pattern recognition application, including risk-sensitive applications such as medical diagnosis, face recognition, and financial risk prediction. Conformal Predictions for Reliable Machine Learning: Theory, Adaptations and Applications captures the basic theory of the framework, demonstrates how to apply it to real-world problems, and presents several adaptations, including active learning, change detection, and anomaly detection. As practitioners and researchers around the world apply and adapt the framework, this edited volume brings together these bodies of work, providing a springboard for further research as well as a handbook for application in real-world problems.

Product Identifiers

Publisher
Elsevier Science & Technology
ISBN-10
0123985374
ISBN-13
9780123985378
eBay Product ID (ePID)
202616349

Product Key Features

Author
Shen-Shyang HO
Publication Name
Conformal Prediction for Reliable Machine Learning : Theory, Adaptations and Applications
Format
Trade Paperback
Language
English
Publication Year
2014
Type
Textbook
Number of Pages
334 Pages

Dimensions

Item Length
9.2in
Item Width
7.5in

Additional Product Features

Lc Classification Number
Q325.5c668 2014
Reviews
"...captures the basic theory of the framework, demonstrates how to apply it to real-world problems, and presents several adaptations, including active learning, change detection, and anomaly detection." -- Zentralblatt MATH, Sep-14 "...the book is highly recommended for people looking for formal machine learning techniques that can guarantee theoretical soundness and reliability." --Computing Reviews,December 4,2014 "This book captures the basic theory of the framework, demonstrates how the framework can be applied to real-world problems, and also presents several adaptations of the framework..." --HPCMagazine.com, August 2014, "This book captures the basic theory of the framework, demonstrates how the framework can be applied to real-world problems, and also presents several adaptations of the framework." - HPCMagazine.com, August 2014, "...captures the basic theory of the framework, demonstrates how to apply it to real-world problems, and presents several adaptations, including active learning, change detection, and anomaly detection."-- Zentralblatt MATH, Sep-14 "...the book is highly recommended for people looking for formal machine learning techniques that can guarantee theoretical soundness and reliability." --Computing Reviews, December 4,2014 "This book captures the basic theory of the framework, demonstrates how the framework can be applied to real-world problems, and also presents several adaptations of the framework..." - HPCMagazine.com, August 2014
Table of Content
Section I: Theory 1. The Basic Conformal Prediction Framework 2. Beyond the Basic Conformal Prediction Framework Section II: Adaptations 3. Active Learning using Conformal Prediction 4. Anomaly Detection 5. Online Change Detection by Testing Exchangeability 6. Feature Selection and Conformal Predictors 7. Model Selection 8. Quality Assessment 9. Other Adaptations Section III: Applications 10. Biometrics 11. Diagnostics and Prognostics by Conformal Predictors 12. Biomedical Applications using Conformal Predictors 13. Reliable Network Traffic Classification and Demand Prediction 14. Other Applications
Copyright Date
2014
Target Audience
Scholarly & Professional
Topic
Intelligence (Ai) & Semantics
Lccn
2014-003894
Dewey Decimal
006.3/1
Dewey Edition
23
Genre
Computers

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Conformal Prediction for Reliable Machine Learning : Theory, Adaptations and Applications by Shen-Shyang Ho (2014, Trade Paperback)

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item 1 Conformal Prediction for Reliable Machine Learning: Theory, Adaptati - VERY GOOD

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item 4 Conformal Prediction for Reliable Machine Learn, Balasubramanian, Ho, Vovk.=

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