For courses in Bayesian Networks or Advanced Networking focusing on Bayesian networks found in departments of Computer Science, Computer Engineering and Electrical Engineering. Also appropriate as a supplementary text in courses on Expert Systems, Machine Learning, and Artificial Intelligence where the topic of Bayesian Networks is covered. This book provides an accessible and unified discussion of Bayesian networks. It includes discussions of topics related to the areas of artificial intelligence, expert systems and decision analysis, the fields in which Bayesian networks are frequently applied. The author discusses both methods for doing inference in Bayesian networks and influence diagrams. The book also covers the Bayesian method for learning the values of discrete and continuous parameters. Both the Bayesian and constraint-based methods for learning structure are discussed in detail.
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有點囉嗦就是瞭
评分有本科的概率知識基本就可以讀懂這本書瞭。當然，相應地有些地方也不可能給齣深入的論證。
评分有本科的概率知識基本就可以讀懂這本書瞭。當然，相應地有些地方也不可能給齣深入的論證。
评分有本科的概率知識基本就可以讀懂這本書瞭。當然，相應地有些地方也不可能給齣深入的論證。
评分有本科的概率知識基本就可以讀懂這本書瞭。當然，相應地有些地方也不可能給齣深入的論證。
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