| 期刊全称 | Bayesian Networks and Decision Graphs | | 影响因子2023 | Finn V. Jensen | | 视频video | | | 发行地址 | Gives a well-founded practical introduction to Bayesian networks.Includes presentation of the most efficient algorithm for solving influence diagrams | | 学科分类 | Information Science and Statistics | | 图书封面 |  | | 影响因子 | Bayesian networks and decision graphs are formal graphical languages for representation and communication of decision scenarios requiring reasoning under uncertainty. Their strengths are two-sided. It is easy for humans to construct and to understand them, and when communicated to a computer, they can easily be compiled. Furthermore, handy algorithms are developed for analyses of the models and for providing responses to a wide range of requests such as belief updating, determining optimal strategies, conflict analyses of evidence, and most probable explanation. The book emphasizes both the human and the computer sides. Part I gives a thorough introduction to Bayesian networks as well as decision trees and infulence diagrams, and through examples and exercises, the reader is instructed in building graphical models from domain knowledge. This part is self-contained and it does not require other background than standard secondary school mathematics. Part II is devoted to the presentation of algorithms and complexity issues. This part is also self-contained, but it requires that the reader is familiar with working with texts in the mathematical language. The author also:.- provides a | | Pindex | Textbook 20011st edition |
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发表于 2025-3-21 19:58:16
