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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有本科的概率知识基本就可以读懂这本书了。当然，相应地有些地方也不可能给出深入的论证。
评分有本科的概率知识基本就可以读懂这本书了。当然，相应地有些地方也不可能给出深入的论证。
评分有点啰嗦就是了
评分有点啰嗦就是了
评分有本科的概率知识基本就可以读懂这本书了。当然，相应地有些地方也不可能给出深入的论证。
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