1 Solutions to Exercises for Module 4 – Bayesian Networks Exercise 1: Mr. Dupont is a professional wine taster. When given a French wine, he will identify it 90% of the time correctly as French, and will mistake it for a Californian wine 10% of the time. When given a Californian wine, he will identify […]
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1 Solutions to Exercises for Module 5 – Defining Bayesian Network Structure Exercise 1: Create a Bayesian network with two Boolean nodes A and B. Make B the child of A and define the NPTs respectively as: NPT for node A: NPT for node B: Construct an ‘equivalent’ version of the model in which A
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Supervised Learning – Classification Supervised Learning – Classification COMP9417 Machine Learning and Data Mining Last revision: 14 March 2018 COMP9417 ML & DM Classification Semester 1, 2018 1 / 132 Acknowledgements Material derived from slides for the book “Elements of Statistical Learning (2nd Ed.)” by T. Hastie, R. Tibshirani & J. Friedman. Springer (2009) http://statweb.stanford.edu/~tibs/ElemStatLearn/
1 Solutions to Exercises for Module 6 – Defining Bayesian Network Probabilities Discrete Nodes Exercise 1: Suppose A is a ranked node with 5 states and that it has 3 parent nodes each with 5 states. How many cells are there in the NPT of A? What kind of problems would you expect to encounter
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3. Flower Breeding Solution: The Bayesian network： NPT for Plant_1_Genotype、Plant_2_Genotype、Plant_3_Genotype node（the same values of these）: NPT for Flower_Colour（the same values of all plants）: NPT for Offspring_1_Flower_Colour、Offspring_2_Flower_Colour（the same values of all plants）: Inserting the evidence into the Bayesian network: Result:P(red flowers|the second generation offspring) = 66.7% 4. Horse Stud Solution: Because the frequency of occurrence of
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Machine Learning Objectives of the Course And Preliminaries * * * Instructor: Dr. Nathalie Japkowicz Office: DMTI-112B Phone Number: (202) 885-6486 (don’t rely on it too much!) E-mail: japkowic@american.edu (best way to contact me!) Office Hours: Thursdays, 2:30pm-4pm By arrangement, on Skype Malfunctioning gearboxes have been the cause for CH-46 US Navy helicopters to crash.
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Artificial Intelligence: A Modern Approach (3rd Edition) This page intentionally left blank crazy-readers.blogspot.com Artificial Intelligence A Modern Approach Third Edition crazy-readers.blogspot.com PRENTICE HALL SERIES IN ARTIFICIAL INTELLIGENCE Stuart Russell and Peter Norvig, Editors FORSYTH & PONCE Computer Vision: A Modern Approach GRAHAM ANSI Common Lisp JURAFSKY & MARTIN Speech and Language Processing, 2nd ed. NEAPOLITAN
第 41 卷第 6 期 2011 年 11 月 东 南 大 学 学 报 ( 自 然 科 学 版 ) JOURNAL OF SOUTHEAST UNIVERSITY ( Natural Science Edition) Vol． 41 No． 6 Nov． 2011 doi: 10． 3969 / j． issn． 1001 － 0505． 2011． 06． 032 基于贝叶斯网络的城市道路交通事故分析 赵金宝 邓 卫 王 建 (
Microsoft Word – IJBIDM090203 WANG_no downsample.doc Stock price direction prediction by directly using prices data: an empirical study on the KOSPI and HSI Yanshan Wang School of Industrial Management Engineering, Korea University, Seoul, 136-713, Korea E-mail: yansh.wang@gmail.com Abstract: The prediction of a stock market direction may serve as an early recommendation system for short-term investors
PART 1 PART 2 PART 3 PART 4 PART 5 Contents Preface v Introduction 1 1 Introduction 2 Logic and Search 17 2 Logic 18 3 Search 46 4 Automating Logical Reasoning 72 Uncertainty 103 5 Bayesian Networks I 104 6 Bayesian Networks II 133 7 Other Approaches to Uncertainty 154 Deciding on Actions 173