Statistical and Inductive Inference by Minimum Message Length

C. S. Wallace - Collection Information Science and Statistics

430 pages, parution le 01/07/2005

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Résumé

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.

L'auteur - C. S. Wallace

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.

Sommaire

Preface
Inductive Inference
Information
Strict Minimum Message Length (SMML)
Approximations to SMML
MML: Quadratic Approximations to SMML
MML Details in Some Interesting Cases
Structural Models
The Feathers on the Arrow of Time
MML as a Descriptive Theory
Related Work
Bibliography
Index

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Caractéristiques techniques

	PAPIER
Éditeur(s)	Springer
Auteur(s)	C. S. Wallace
Collection	Information Science and Statistics
Parution	01/07/2005
Nb. de pages	430
Format	16 x 24
Couverture	Relié
Poids	741g
Intérieur	Noir et Blanc
EAN13	9780387237954
ISBN13	978-0-387-23795-4