Advanced Methodologies for Bayesian Networks

Chapter 1 Efficiently Learning Bayesian Network Structures Based on the B&B Strategy: A Theoretical Analysis

Chapter 2 Constraint-Based Learning Bayesian Networks Using Bayes Factor

Chapter 3 Learning Bayesian Network Parameters from Small Data Set: A Spatially Maximum a Posteriori Method

Chapter 4 Hashing-Based Hybrid Duplicate Detection for Bayesian Network Structure Learning

Chapter 5 A Bayesian Network Approach for Predicting Purchase Behavior via Direct Observation of In-store Behavior

Chapter 6 Statistical Tests for Joint Analysis of Performance Measures

Chapter 7 Extending Naive Bayes Classifier with Hierarchy Feature Level Information for Record Linkage

Chapter 8 Empirical Behavior of Bayesian Network Structure Learning Algorithms

Chapter 9 On Model Selection, Bayesian Networks, and the Fisher Information Integral

Chapter 11 A Fast Clique Maintenance Algorithm for Optimal Triangulation of Bayesian Networks

Chapter 12 Factorization of ZDDs for Representing Bayesian Networks Based on d -Separations

Chapter 13 Missing Data from a Causal Perspective

Chapter 14 Learning Maximal Ancestral Graphs with Robustness for Faithfulness Violations

Chapter 15 Discriminative and Generative Models in Causal and Anticausal Settings

Chapter 16 A Non-Gaussian Approach for Causal Discovery in the Presence of Hidden Common Causes

Chapter 17 Forest Learning Based on the Chow-Liu Algorithm and Its Application to Genome Differential Analysis: A Novel Mutual Information Estimation

Chapter 18 Tips and Tricks for Building Bayesian Networks for Scoring Game-Based Assessments