Title Algorithmic learning in a random world / Vladimir Vovk, Alexander Gammerman, Glenn Shafer

Published New York : Springer, ©2005

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Description 1 online resource (xiv, 324 pages) : illustrations Contents Introduction; 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 Summary This scientific monograph develops significant new algorithmic foundations in machine learning theory. Researchers and postgraduates in CS, statistics, and A.I. should find the book an authoritative and formal presentation of some of the most promising theoretical developments in machine learning Bibliography Includes bibliographical references (pages 303-316) and index Notes Print version record In Springer e-books Subject Prediction theory. Algorithms. Stochastic processes. Algorithms Stochastic Processes algorithms. Informatique. Algorithms Prediction theory Stochastic processes Form Electronic book Author Gammerman, A. (Alexander) Shafer, Glenn, 1946- ISBN 9780387001524 0387001522 9780387250618 0387250611 661023521X 9786610235216

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