Title | Selecting Models from Data [electronic resource] : Artificial Intelligence and Statistics IV / edited by P. Cheeseman, R. W. Oldford |
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Imprint | New York, NY : Springer New York, 1994 |
Connect to | http://dx.doi.org/10.1007/978-1-4612-2660-4 |
Descript | X, 487 p. 6 illus. online resource |
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