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Titlebook: Coding Ockham‘s Razor; Lloyd Allison Book 2018 Springer International Publishing AG, part of Springer Nature 2018 artificial intelligence.

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發(fā)表于 2025-3-21 19:53:27 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
書目名稱Coding Ockham‘s Razor
編輯Lloyd Allison
視頻videohttp://file.papertrans.cn/229/228881/228881.mp4
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
圖書封面Titlebook: Coding Ockham‘s Razor;  Lloyd Allison Book 2018 Springer International Publishing AG, part of Springer Nature 2018 artificial intelligence.
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
關(guān)鍵詞artificial intelligence; Bayesian; data science; inference; information; machine learning; minimum message
版次1
doihttps://doi.org/10.1007/978-3-319-76433-7
isbn_softcover978-3-030-09488-1
isbn_ebook978-3-319-76433-7
copyrightSpringer International Publishing AG, part of Springer Nature 2018
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Leslie A. Dervan,R. Scott WatsonThis chapter concerns models of integers, ., most often of non-negative (.) or positive (.) integers.
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Sedation Considerations for ECMOThe important thing about continuous data—., real, floating point, double—is that each datum has an accuracy of measurement (AoM), ., and hence a negative log AoM (nlAoM), .. A datum . is of the form .. Models of such data are generally defined in terms of a probability density function pdf(.).
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Sedentary Behaviour and MortalityA linear regression is a form of function-model (Chaps. ., .) between continuous variables. An output (dependent) variable . is approximated by a function .(.) of an input (independent) variable . with the error, .???.(.), being modelled by a model of continuous data (Chap. .), most commonly by the Normal distribution (Sect. .).
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Introduction,This book is about inductive inference using the minimum message length (MML) principle and a computer. It is accompanied by a library of software to help an applications programmer, student or researcher in the fields of data analysis or machine learning to write computer programs of this kind.
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