I Overviews: Model Selection.- 1 Statistical strategy: step 1.- 2 Rational Learning: Finding a Balance Between Utility and Efficiency.- 3 A new criterion for selecting models from partially observed data.- 4 Small-sample and large-sample statistical model selection criteria.- 5 On the choice of penalty term in generalized FPE criterion.- 6 Cross-Validation, Stacking and Bi-Level Stacking: Meta-Methods for Classification Learning.- 7 Probabilistic approach to model selection: comparison with unstructured data set.- 8 Detecting and Explaining Dependencies in Execution Traces.- 9 A method for the dynamic selection of models under time constraints.- II Graphical Models.- 10 Strategies for Graphical Model Selection.- 11 Conditional dependence in probabilistic networks.- 12 Reuse and sharing of graphical belief network components.- 13 Bayesian Graphical Models for Predicting Errors in Databases.- 14 Model Selection for Diagnosis and Treatment Using Temporal Influence Diagrams.- 15 Diagnostic systems by model selection: a case study.- 16 A Survey of Sampling Methods for Inference on Directed Graphs.- 17 Minimizing decision table sizes in influence diagrams: dimension shrinking.- 18 Models from Data for Various Types of Reasoning.- III Causal Models.- 19 Causal inference in artificial intelligence.- 20 Inferring causal structure among unmeasured variables.- 21 When can association graphs admit a causal interpretation?.- 22 Inference, Intervention, and Prediction.- 23 Attitude Formation Models: Insights from TETRAD.- 24 Discovering Probabilistic Causal Relationships: A Comparison Between Two Methods.- 25 Path Analysis Models of an Autonomous Agent in a Complex Environment.- IV Particular Models.- 26 A Parallel Constructor of Markov Networks.- 27 Capturing observations in a nonstationary hidden Markov model.- 28 Extrapolating Definite Integral Information.- 29 The Software Reliability Consultant.- 30 Statistical Reasoning to Enhance User Modelling in Consulting Systems.- 31 Selecting a frailty model for longitudinal breast cancer data.- 32 Optimal design of reflective sensors using probabilistic analysis.- V Similarity-Based Models.- 33 Learning to Catch: Applying Nearest Neighbor Algorithms to Dynamic Control Tasks.- 34 Dynamic Recursive Model Class Selection for Classifier Construction.- 35 Minimizing the expected costs of classifying patterns by sequential costly inspections.- 36 Combining a knowledge-based system and a clustering method for a construction of models in ill-structured domains.- 37 Clustering of Symbolically Described Events for Prediction of Numeric Attributes.- 38 Symbolic Classifiers: Conditions to Have Good Accuracy Performance.- VI Regression and Other Statistical Models.- 39 Statistical and neural network techniques for nonparametric regression.- 40 Multicollinearity: A tale of two nonparametric regressions.- 41 Choice of Order in Regression Strategy.- 42 Modelling response models in software.- 43 Principal components and model selection.- VII Algorithms and Tools.- 44 Algorithmic speedups in growing classification trees by using an additive split criterion.- 45 Markov Chain Monte Carlo Methods for Hierarchical Bayesian Expert Systems.- 46 Simulated annealing in the construction of near-optimal decision trees.- 47 SA/GA: Survival of the Fittest in Alaska.- 48 A Tool for Model Generation and Knowledge Acquisition.- 49 Using knowledge-assisted discriminant analysis to generate new comparative terms.
