Advances in Intelligent Data Analysis

Inhaltsverzeichnis

• 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.
• Reasoning about Input-Output Modeling of Dynamical Systems.
• Undoing Statistical Advice.
• A Method for Temporal Knowledge Conversion.
• Applications.
• Intrusion Detection through Behavioral Data.
• Bayesian Neural Network Learning for Prediction in the Australian Dairy Industry.
• Exploiting Sample-Data Distributions to Reduce the Cost of Nearest-Neighbor Searches with Kd-Trees.
• Pump Failure Detection Using Support Vector Data Descriptions.
• Data Mining for the Detection of Turning Points in Financial Time Series.
• Computer-Assisted Classification of Legal Abstracts.
• Sequential Control Logic Inferring Method from Observed Plant I/O Data.
• Evaluating an Eye Screening Test.
• Application of Rough Sets Algorithms to Prediction of Aircraft Component Failure.
• Media Mining.
• Exploiting Structural Information for Text Classification on the WWW.
• Multi-agent Web Information Retrieval: Neural Network Based Approach.
• Adaptive Information Filtering Algorithms.
• A Conceptual Graph Approach for Video Data Representation and Retrieval.