Coding Ockham's Razor

  • Lloyd Allison

Table of contents

  1. Front Matter
    Pages i-xiv
  2. Lloyd Allison
    Pages 1-15
  3. Lloyd Allison
    Pages 17-25
  4. Lloyd Allison
    Pages 27-39
  5. Lloyd Allison
    Pages 41-52
  6. Lloyd Allison
    Pages 53-59
  7. Lloyd Allison
    Pages 61-64
  8. Lloyd Allison
    Pages 65-76
  9. Lloyd Allison
    Pages 77-88
  10. Lloyd Allison
    Pages 89-101
  11. Lloyd Allison
    Pages 103-111
  12. Lloyd Allison
    Pages 113-130
  13. Lloyd Allison
    Pages 131-141
  14. Lloyd Allison
    Pages 143-153
  15. Back Matter
    Pages 155-175

About this book


This book explores inductive inference using the minimum message length (MML) principle, a Bayesian method which is a realisation of Ockham's Razor based on information theory. Accompanied by a library of software, the book can assist an applications programmer, student or researcher in the fields of data analysis and machine learning to write computer programs based upon this principle.

MML inference has been around for 50 years and yet only one highly technical book has been written about the subject.  The majority of research in the field has been backed by specialised one-off programs but this book includes a library of general MML–based software, in Java.  The Java source code is available under the GNU GPL open-source license.  The software library is documented using Javadoc which produces extensive cross referenced HTML manual pages.  Every probability distribution and statistical model that is described in the book is implemented and documented in the software library.  The library may contain a component that directly solves a reader's inference problem, or contain components that can be put together to solve the problem, or provide a standard interface under which a new component can be written to solve the problem.

This book will be of interest to application developers in the fields of machine learning and statistics as well as academics, postdocs, programmers and data scientists. It could also be used by third year or fourth year undergraduate or postgraduate students.


artificial intelligence Bayesian data science inference information machine learning minimum message length, MML model Ockham's razor software statistics

Authors and affiliations

  • Lloyd Allison
    • 1
  1. 1.Faculty of Information TechnologyMonash UniversityMelbourneAustralia

Bibliographic information

  • DOI
  • Copyright Information Springer International Publishing AG, part of Springer Nature 2018
  • Publisher Name Springer, Cham
  • eBook Packages Computer Science
  • Print ISBN 978-3-319-76432-0
  • Online ISBN 978-3-319-76433-7
  • Buy this book on publisher's site