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Advances in Intelligent Data Analysis
Third International Symposium, IDA-99 Amsterdam, The Netherlands, August 9-11, 1999 Proceedings
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Beschreibung
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.
Spezifikationen
Sprache
- Englisch
Autor
- Joost N. Kok
- Michael R. Berthold
- David J Hand
Thema
- Datenbanken: Allgemein, Data Warehousing, Information Retrieval
- Künstliche Intelligenz: Allgemein, Maschinelles Sehen
Kollektion
- Lecture Notes in Computer Science
Erscheinungsjahr
- 1999
Erscheinungsland
- Deutschland
Format
- Buch (Softcover)
Anzahl Seiten
- 544
