Bayesian Networks: With Examples in R 2nd 版本

Scutari, Marco, Denis, Jean-Baptiste

  • 出版商: CRC
  • 出版日期: 2021-07-29
  • 售價: $3,600
  • 貴賓價: 9.5$3,420
  • 語言: 英文
  • 頁數: 272
  • 裝訂: Hardcover - also called cloth, retail trade, or trade
  • ISBN: 0367366517
  • ISBN-13: 9780367366513
  • 相關分類: 機率統計學 Probability-and-statistics
  • 立即出貨 (庫存 < 4)

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商品描述

 

Bayesian Networks: With Examples in R, Second Edition introduces Bayesian networks using a hands-on approach. Simple yet meaningful examples illustrate each step of the modelling process and discuss side-by-side the underlying theory and its application using R code. The examples start from the simplest notions and gradually increase in complexity. In particular, this new edition contains significant new material on topics from modern machine learning practice: dynamic networks, networks with heterogeneous variables, and model validation.

 

The first three chapters explain the whole process of Bayesian network modelling, from structure learning to parameter learning to inference. These chapters cover discrete, Gaussian, and conditional Gaussian Bayesian networks. The following two chapters delve into dynamic networks (to model temporal data) and into networks including arbitrary random variables (using Stan). The book then gives a concise but rigorous treatment of the fundamentals of Bayesian networks and offers an introduction to causal Bayesian networks. It also presents an overview of R packages and other software implementing Bayesian networks. The final chapter evaluates two real-world examples: a landmark causal protein-signaling network published in Science and a probabilistic graphical model for predicting the composition of different body parts.

 

Covering theoretical and practical aspects of Bayesian networks, this book provides you with an introductory overview of the field. It gives you a clear, practical understanding of the key points behind this modelling approach and, at the same time, it makes you familiar with the most relevant packages used to implement real-world analyses in R. The examples covered in the book span several application fields, data-driven models and expert systems, probabilistic and causal perspectives, thus giving you a starting point to work in a variety of scenarios.

 

Online supplementary materials include the data sets and the code used in the book, which will all be made available from https: //www.bnlearn.com/book-crc-2ed/

 

商品描述(中文翻譯)

「Bayesian Networks: With Examples in R, Second Edition」是一本以實例為基礎介紹貝葉斯網絡的書籍。這本書使用R程式碼進行實際應用,並以簡單而有意義的例子來說明建模過程的每一步,並且同時討論底層理論及其應用。這些例子從最簡單的概念開始,逐漸增加複雜度。特別是這本新版書籍在現代機器學習實踐的主題上增加了重要的新內容:動態網絡、包含異質變量的網絡和模型驗證。

前三章解釋了貝葉斯網絡建模的整個過程,從結構學習到參數學習再到推理。這些章節涵蓋了離散、高斯和條件高斯貝葉斯網絡。接下來的兩章深入探討了動態網絡(用於建模時間數據)和包含任意隨機變量的網絡(使用Stan)。本書還對貝葉斯網絡的基礎知識進行了簡潔但嚴謹的介紹,並介紹了因果貝葉斯網絡。它還概述了實現貝葉斯網絡的R套件和其他軟體。最後一章評估了兩個真實世界的例子:一個發表在《科學》雜誌上的具有里程碑意義的蛋白質信號網絡和一個用於預測不同身體部位組成的概率圖模型。

本書涵蓋了貝葉斯網絡的理論和實踐方面,為您提供了該領域的入門概述。它使您清楚地理解了這種建模方法背後的關鍵點,同時讓您熟悉在R中實現實際分析所使用的最相關的套件。本書涵蓋的例子涉及多個應用領域、數據驅動模型和專家系統、概率和因果觀點,因此為您在各種情境下工作提供了一個起點。

網上補充材料包括本書中使用的數據集和程式碼,將全部提供在https://www.bnlearn.com/book-crc-2ed/。

作者簡介

Marco Scutari is a Senior Lecturer at Istituto Dalle Molle di Studisull'Intelligenza Artificiale (IDSIA), Switzerland. He has held positions in Statistics, Statistical Genetics and Machine Learning in the UK and Switzerland since completing his Ph.D. in Statistics in 2011. His research focuses on the theory of Bayesian networks and their applications to biological and clinical data, as well as statistical computing and software engineering.

 

Jean-Baptiste Denis was formerly appointed as a statistician and modeller at the "Mathematics and Applied Informatics from Genome to Environment" unit of the French National Research Institute for Agriculture, Food and Environment. His main research interests were the modelling of two-way tables and Bayesian approaches, especially applied to genotype-by-environment interactions and microbiological food safety.

作者簡介(中文翻譯)

Marco Scutari是瑞士Istituto Dalle Molle di Studisull'Intelligenza Artificiale (IDSIA)的高級講師。自2011年獲得統計學博士學位以來,他在英國和瑞士的統計學、統計遺傳學和機器學習領域擔任過職位。他的研究主要集中在貝葉斯網絡的理論及其在生物和臨床數據中的應用,以及統計計算和軟件工程。

Jean-Baptiste Denis曾任法國國家農業、食品和環境研究所的“從基因組到環境的數學和應用信息學”單位的統計學家和建模師。他的主要研究興趣是二維表格建模和貝葉斯方法,尤其應用於基因型與環境互作和微生物食品安全。