Statistical and Inductive Inference by Minimum Message Length

2005. Auflage 2005
ISBN: 978-0-387-23795-4
Verlag: Springer

Buch, Englisch, 432 Seiten, Format (B × H): 156 mm x 243 mm, Gewicht: 1770 g

Reihe: Information Science and Statistics

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.

Zielgruppe

Research

Autoren/Hrsg.

Wallace, C S

Fachgebiete

• Mathematik | Informatik EDV | Informatik Daten / Datenbanken Informationstheorie, Kodierungstheorie
• Mathematik | Informatik Mathematik Stochastik Wahrscheinlichkeitsrechnung
• Mathematik | Informatik Mathematik Stochastik Mathematische Statistik
• Interdisziplinäres Wissenschaften Wissenschaften: Forschung und Information Informationstheorie, Kodierungstheorie
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Wissensbasierte Systeme, Expertensysteme
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Maschinelles Lernen

Inhaltsverzeichnis

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.

Über Autor(innen)

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.