Algorithmic Learning in a Random World

Algorithmic Learning in a Random World by Vladimir Vovk, Alex Gammerman, Glenn Shafer.

Conformal prediction is a valuable new method of machine learning. Conformal predictors are among the most accurate methods of machine learning, and unlike other state-of-the-art methods, they provide information about their own accuracy and reliability. This new monograph integrates mathematical th...

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Bibliographic Details
Main Authors: Vovk, Vladimir (Author), Gammerman, Alex (Author), Shafer, Glenn (Author)
Corporate Author: SpringerLink (Online service)
Format: eBook
Language:English
Published: New York, NY : Springer US : Imprint: Springer, 2005.
Edition:1st ed. 2005.
Series:Springer eBook Collection.
Subjects:
Artificial intelligence.
Statistics .
Data structures (Computer science).
Electronic resources (E-books)
Online Access:Click to view e-book
Holy Cross Note:Loaded electronically.
Electronic access restricted to members of the Holy Cross Community.
Table of Contents:
  • Conformal prediction
  • Classification with conformal predictors
  • Modifications of conformal predictors
  • Probabilistic prediction I: impossibility results
  • Probabilistic prediction II: Venn predictors
  • Beyond exchangeability
  • On-line compression modeling I: conformal prediction
  • On-line compression modeling II: Venn prediction
  • Perspectives and contrasts.

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