Richard E. Neapolitan | Akateeminen Kirjakauppa

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LEARNING BAYESIAN NETWORKS

Richard E. Neapolitan
(2003)
Pehmeäkantinen kirja

165,10 €

DATA MINING: KNOW IT ALL

Soumen Chakrabarti; Richard E. Neapolitan; Dorian Pyle; Mamdouh Refaat; Markus Schneider; Toby J. Teorey; Ian H. Witten
Elsevier Science & Technology (2008)
Kovakantinen kirja

68,90 €

PROBABILISTIC METHODS FOR BIOINFORMATICS - WITH AN INTRODUCTION TO BAYESIAN NETWORKS

Richard E. Neapolitan
Elsevier Science & Technology (2009)
Kovakantinen kirja

62,60 €

FOUNDATIONS OF ALGORITHMS USING JAVA PSEUDOCODE

Richard E. Neapolitan; Kumarss Naimipour
Jones and Bartlett Publishers, Inc (2004)
Kovakantinen kirja

131,20 €

PROBABILISTIC METHODS FOR FINANCIAL AND MARKETING INFORMATICS

Richard E. Neapolitan; Xia Jiang
Elsevier Science & Technology (2007)
Kovakantinen kirja

73,00 €

FOUNDATIONS OF ALGORITHMS USING C++ P

Richard E. Neapolitan
Jones and Bartlett Publishers, Inc (2008)
Pehmeäkantinen kirja

124,10 €

CONTEMPORARY ARTIFICIAL INTELLIGENCE

Richard E. Neapolitan
Taylor & Francis Ltd (2012)
Kovakantinen kirja

76,10 €

ARTIFICIAL INTELLIGENCE - WITH AN INTRODUCTION TO MACHINE LEARNING, SECOND EDITION

Richard E. Neapolitan; Xia Jiang
Taylor & Francis Ltd (2018)
Kovakantinen kirja

141,00 €

ARTIFICIAL INTELLIGENCE - WITH AN INTRODUCTION TO MACHINE LEARNING, SECOND EDITION

Richard E. Neapolitan; Xia Jiang
Taylor & Francis Ltd (2020)
Pehmeäkantinen kirja

54,10 €

Learning Bayesian Networks

Richard E. Neapolitan

165,10 €

Sivumäärä: 696 sivua
Asu: Pehmeäkantinen kirja
Julkaisuvuosi: 2003, 27.03.2003 (lisätietoa)
Kieli: Englanti

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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