| 书目名称 | Coding Ockham‘s Razor | | 编辑 | Lloyd Allison | | 视频video | | | 概述 | 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 | | 图书封面 |  | | 描述 | .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 documentedin 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 n | | 出版日期 | Book 2018 | | 关键词 | artificial intelligence; Bayesian; data science; inference; information; machine learning; minimum message | | 版次 | 1 | | doi | https://doi.org/10.1007/978-3-319-76433-7 | | isbn_softcover | 978-3-030-09488-1 | | isbn_ebook | 978-3-319-76433-7 | | copyright | Springer International Publishing AG, part of Springer Nature 2018 |
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发表于 2025-3-21 19:53:27
