Details

Title Statistical and Inductive Inference by Minimum Message Length (Information Science and Statistics)
Author Wallace, C.S
Binding Hardback
Edition U. S. EDITION
Condition New
Pages 432
Volumes 1
Language ENG
Publisher Springer, Secaucus, New Jersey, U.S.A.
Publication date 2005-05-26
Illustrated Yes
Features Bibliography, Illustrated, Index
Bookseller's Inventory # Q-038723795X
ISBN 9780387237954 / 038723795X
Weight 1.65 lbs (0.75 kg)
Dimensions 9.56 x 6.16 x 0.99 in (24.28 x 15.65 x 2.51 cm)
Category Mathematics
Library of Congress subjects Induction (Mathematics), Minimum message length (Information theory)
Library of Congress Catalogue Number 2004059195
Dewey Decimal Code 519.5
Quantity available 1

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From the publisher

Since 1965, Prof. Wallace and others have been developing an approach tostatistical estimation, hypothesis testing, model selection and their applications in the Artificial Intelligence field of Machine Learning. The approach is based on Information Theory, using concepts from classical Shannon theory and more recent work on Algorithmic Complexity. The new approach has come to be called the Minimum Message Length principle, since it is based on the idea of constructing a message which concisely encodes the available data. Although a range of journal and conference papers has been published on the principle and its application, and several computer programs applying it have been shown to perform well and have been fairly widely used, there is no text providing a thorough treatment of the principle or giving general guidance for its application.

First line

The best explanation of the facts is the shortest.

From the rear cover

The Minimum Message Length (MML) Principle is an information-theoretic approach to induction, hypothesis testing, model selection, and statistical inference. MML, which provides a formal specification for the implementation of Occam's Razor, asserts that the 'best' explanation of observed data is the shortest. Further, an explanation is acceptable

(i.e. the induction is justified) only if the explanation is shorter than the original data.

This book gives a sound introduction to the Minimum Message Length Principle and its applications, provides the theoretical arguments for the adoption of the principle, and shows the development of certain approximations that assist its practical application. MML appears also to provide both a normative and a descriptive basis for inductive reasoning generally, and scientific induction in particular. The book describes this basis and aims to show its relevance to the Philosophy of Science.

Statistical and Inductive Inference by Minimum Message Length will be of special interest to graduate students and researchers in Machine Learning and Data Mining, scientists and analysts in various disciplines wishing to make use of computer techniques for hypothesis discovery, statisticians and econometricians interested in the underlying theory of their discipline, and persons interested in the Philosophy of Science. The book could also be used in a graduate-level course in Machine Learning and Estimation and Model-selection, Econometrics and Data Mining.

C.S. Wallace was appointed Foundation Chair of Computer Science at Monash University in 1968, at the age of 35, where he worked until his death in 2004. He received an ACM Fellowship in 1995, and was appointed Professor Emeritus in 1996. Professor Wallace made numerous significant contributions to diverse areas of Computer Science, such as Computer Architecture, Simulation and Machine Learning. His final research focusedprimarily on the Minimum Message Length Principle.

About the author

C.S. Wallace was appointed Foundation Chair of Computer Science at Monash University in 1968, at the age of 35, where he worked until his death in 2004. He received an ACM Fellowship in 1995, and was appointed Professor Emeritus in 1996. Professor Wallace made numerous significant contributions to diverse areas of Computer Science, such as Computer Architecture, Simulation and Machine Learning. His final research focused primarily on the Minimum Message Length Principle.

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