Format:
1 online resource (xii, 394 Seiten)
ISBN:
9780511546921
Content:
This important text and reference for researchers and students in machine learning, game theory, statistics and information theory offers a comprehensive treatment of the problem of predicting individual sequences. Unlike standard statistical approaches to forecasting, prediction of individual sequences does not impose any probabilistic assumption on the data-generating mechanism. Yet, prediction algorithms can be constructed that work well for all possible sequences, in the sense that their performance is always nearly as good as the best forecasting strategy in a given reference class. The central theme is the model of prediction using expert advice, a general framework within which many related problems can be cast and discussed. Repeated game playing, adaptive data compression, sequential investment in the stock market, sequential pattern analysis, and several other problems are viewed as instances of the experts' framework and analyzed from a common nonstochastic standpoint that often reveals new and intriguing connections
Note:
Title from publisher's bibliographic system (viewed on 05 Oct 2015)
Additional Edition:
Erscheint auch als Druck-Ausgabe ISBN 978-0-521-84108-5
Additional Edition:
Erscheint auch als Druckausgabe ISBN 978-0-521-84108-5
Language:
English
Subjects:
Computer Science
,
Economics
,
Mathematics
Keywords:
Spieltheorie
;
Vorhersagetheorie
;
Maschinelles Lernen
DOI:
10.1017/CBO9780511546921
URL:
Volltext
(URL des Erstveröffentlichers)
Author information:
Cesa-Bianchi, Nicolò 1963-
Author information:
Lugosi, Gábor 1964-
