Title | Learning from Data [electronic resource] : Artificial Intelligence and Statistics V / edited by Doug Fisher, Hans-J. Lenz |
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Imprint | New York, NY : Springer New York, 1996 |
Connect to | http://dx.doi.org/10.1007/978-1-4612-2404-4 |
Descript | 450p. online resource |
I Causality -- 1 Two Algorithms for Inducing Structural Equation Models from Data -- 2 Using Causal Knowledge to Learn More Useful Decision Rules from Data -- 3 A Causal Calculus for Statistical Research -- 4 Likelihood-based Causal Inference -- II Inference and Decision Making -- 5 Ploxoma: Testbed for Uncertain Inference -- 6 Solving Influence Diagrams Using Gibbs Sampling -- 7 Modeling and Monitoring Dynamic Systems by Chain Graphs -- 8 Propagation of Gaussian Belief Functions -- 9 On Test Selection Strategies for Belief Networks -- 10 Representing and Solving Asymmetric Decision Problems Using Valuation Networks -- 11 A Hill-Climbing Approach for Optimizing Classification Trees -- III Search Control in Model Hunting -- 12 Learning Bayesian Networks is NP-Complete -- 13 Heuristic Search for Model Structure: The Benefits of Restraining Greed -- 14 Learning Possibilistic Networks from Data -- 15 Detecting Imperfect Patterns in Event Streams Using Local Search -- 16 Structure Learning of Bayesian Networks by Hybrid Genetic Algorithms -- 17 An Axiomatization of Loglinear Models with an Application to the Model-Search Problem -- 18 Detecting Complex Dependencies in Categorical Data -- IV Classification -- 19 A Comparative Evaluation of Sequential Feature Selection Algorithms -- 20 Classification Using Bayes Averaging of Multiple, Relational Rule-Based Models -- 21 Picking the Best Expert from a Sequence -- 22 Hierarchical Clustering of Composite Objects with a Variable Number of Components -- 23 Searching for Dependencies in Bayesian Classifiers -- V General Learning Issues -- 24 Statistical Analysis fo Complex Systems in Biomedicine -- 25 Learning in Hybrid Noise Environments Using Statistical Queries -- 26 On the Statistical Comparison of Inductive Learning Methods -- 27 Dynamical Selection of Learning Algorithms -- 28 Learning Bayesian Networks Using Feature Selection -- 29 Data Representations in Learning -- VI EDA: Tools and Methods -- 30 Rule Induction as Exploratory Data Analysis -- 31 Non-Linear Dimensionality Reduction: A Comparative Performance Analysis -- 32 Omega-Stat: An Environment for Implementing Intelligent Modeling Strategies -- 33 Framework for a Generic Knowledge Discovery Toolkit -- 34 Control Representation in an EDA Assistant -- VII Decision and Regression Tree Induction -- 35 A Further Comparison of Simplification Methods for Decision-Tree Induction -- 36 Robust Linear Discriminant Trees -- 37 Tree Structured Interpretable Regression -- 38 An Exact Probability Metric for Decision Tree Splitting -- VIII Natural Language Processing -- 39 Two Applications of Statistical Modelling to Natural Language Processing -- 40 A Model for Part-of-Speech Prediction -- 41 Viewpoint-Based Measurement of Semantic Similarity Between Words -- 42 Part-of-Speech Tagging from โSmallโ Data Sets