Advances in Intelligent Data Analysis: Third International Symposium, IDA-99 Amsterdam, The Netherlands, August 9-11, 1999 Proceedings [Paperback]

Learning.- From Theoretical Learnability to Statistical Measures of the Learnable.- ALM: A Methodology for Designing Accurate Linguistic Models for Intelligent Data Analysis.- A Top-Down and Prune Induction Scheme for Constrained Decision Committees.- Mining Clusters with Association Rules.- Evolutionary Computation to Search for Strongly Correlated Variables in High-Dimensional Time-Series.- The Biases of Decision Tree Pruning Strategies.- Feature Selection as Retrospective Pruning in Hierarchical Clustering.- Discriminative Power of Input Features in a Fuzzy Model.- Learning Elements of Representations for Redescribing Robot Experiences.- Seeing Objects in Spatial Datasets.- Intelligent Monitoring Method Using Time Varying Binomial Distribution Models for Pseudo-Periodic Communication Traffic.- Visualization.- Monitoring Human Information Processing via Intelligent Data Analysis of EEG Recordings.- Knowledge-Based Visualization to Support Spatial Data Mining.- Probabilistic Topic Maps: Navigating through Large Text Collections.- 3D Grand Tour for Multidimensional Data and Clusters.- Classification and Clustering.- A Decision Tree Algorithm for Ordinal Classification.- Discovering Dynamics Using Bayesian Clustering.- Integrating Declarative Knowledge in Hierarchical Clustering Tasks.- Nonparametric Linear Discriminant Analysis by Recursive Optimization with Random Initialization.- Supervised Classification Problems: How to Be Both Judge and Jury.- Temporal Pattern Generation Using Hidden Markov Model Based Unsupervised Classification.- Exploiting Similarity for Supporting Data Analysis and Problem Solving.- Multiple Prototype Model for Fuzzy Clustering.- A Comparison of Genetic Programming Variants for Data Classification.- Fuzzy Clustering Based onModified Distance Measures.- Building Classes in Object-Based Languages by Automatic Clustering.- Integration.- Adjusted Estimation for the Combination of Classifiers.- Data-Driven Theory Refinement Using KBDistAl.- l“9