Coding Ockham's Razor

Authors: Allison, Lloyd

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  • "Gathers together the minimum necessary MML theory in one place"Implemented models and estimators include those for discrete, continuous and multivariate data, mixture models (clustering), regressions, classification trees, models of vectors and directions, linear regression, models of graphs (networks)All models are taken from the maths through to computer code and to useAn accompanying library of software includes standard probability distributions, statistical models and estimatorsThe e-book contains internet links to the software, documentation, and interactive (javascript) examples

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eBook 80,24 €
price for Spain (gross)
  • ISBN 978-3-319-76433-7
  • Digitally watermarked, DRM-free
  • Included format: EPUB, PDF
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Hardcover 103,99 €
price for Spain (gross)
  • ISBN 978-3-319-76432-0
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
  • The final prices may differ from the prices shown due to specifics of VAT rules
Softcover 98,79 €
price for Spain (gross)
  • ISBN 978-3-030-09488-1
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
  • The final prices may differ from the prices shown due to specifics of VAT rules
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.

Reviews

“The GNU GPL licensed library is well documented and can be easily used and extended to the user’s needs. A lot of instructive examples for problem solving with this software are presented in the book and even have been coded for the reader’s convenience.” (Rainer Horsch, zbMATH 1409.68001, 2019)

Table of contents (13 chapters)

Table of contents (13 chapters)

Buy this book

eBook 80,24 €
price for Spain (gross)
  • ISBN 978-3-319-76433-7
  • Digitally watermarked, DRM-free
  • Included format: EPUB, PDF
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Hardcover 103,99 €
price for Spain (gross)
  • ISBN 978-3-319-76432-0
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
  • The final prices may differ from the prices shown due to specifics of VAT rules
Softcover 98,79 €
price for Spain (gross)
  • ISBN 978-3-030-09488-1
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
  • The final prices may differ from the prices shown due to specifics of VAT rules
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Bibliographic Information

Bibliographic Information
Book Title
Coding Ockham's Razor
Authors
Copyright
2018
Publisher
Springer International Publishing
Copyright Holder
Springer International Publishing AG, part of Springer Nature
eBook ISBN
978-3-319-76433-7
DOI
10.1007/978-3-319-76433-7
Hardcover ISBN
978-3-319-76432-0
Softcover ISBN
978-3-030-09488-1
Edition Number
1
Number of Pages
XIV, 175
Number of Illustrations
46 b/w illustrations
Topics