3. IDA 1999:
Amsterdam, The Netherlands
David J. Hand, Joost N. Kok, Michael R. Berthold (Eds.):
Advances in Intelligent Data Analysis, Third International Symposium, IDA-99, Amsterdam, The Netherlands, August 1999, Proceedings.
Lecture Notes in Computer Science 1642 Springer 1999, ISBN 3-540-66332-0
Section I:
Learning
- Marc Sebban, Gilles Richard:
From Theoretical Learnability to Statistical Measures of the Learnable.
3-14

- Oscar Cordón, Francisco Herrera:
ALM: A Methodology for Designing Accurate Linguistic Models for Intelligent Data Analysis.
15-26

- Richard Nock, Pascal Jappy:
A ``Top-Down and Prune'' Induction Scheme for Constrained Decision Committees.
27-38

- Walter A. Kosters, Elena Marchiori, Ard A. J. Oerlemans:
Mining Clusters with Association Rules.
39-50

- Stephen Swift, Allan Tucker, Xiaohui Liu:
Evolutionary Computation to Search for Strongly Correlated Variables in High-Dimensional Time-Series.
51-62

- Tapio Elomaa:
The Biases of Decision Tree Pruning Strategies.
63-74

- Luis Talavera:
Feature Selection as Retrospective Pruning in Hierarchical Clustering.
75-86

- Rosaria Silipo, Michael R. Berthold:
Discriminative Power of Input Features in a Fuzzy Model.
87-98

- Laura Firoiu, Paul R. Cohen:
Learning Elements of Representations for Redescribing Robot Experiences.
99-110

- Xingang Huang, Feng Zhao:
``Seeing'' Objects in Spatial Datasets.
111-122

- Kazunori Matsumoto, Kazuo Hashimoto:
Intelligent Monitoring Method Using Time Varying Binomial Distribution Models for Pseudo-Periodic Communication Traffic.
123-136

Section II:
Visualization
Section III:
Classification and Clustering
- Rob Potharst, Jan C. Bioch:
A Decision Tree Algorithm for Ordinal Classification.
187-198

- Paola Sebastiani, Marco Ramoni, Paul R. Cohen, John Warwick, James Davis:
Discovering Dynamics Using Bayesian Clustering.
199-210

- Luis Talavera, Javier Béjar:
Integrating Declarative Knowledge in Hierarchical Clustering Tasks.
211-222

- Mayer Aladjem:
Nonparametric Linear Discriminant Analysis by Recursive Optimization with Random Initialization.
223-234

- Mark G. Kelly, David J. Hand, Niall M. Adams:
Supervised Classification Problems: How to Be Both Judge and Jury.
235-244

- Cen Li, Gautam Biswas:
Temporal Pattern Generation Using Hidden Markov Model Based Unsupervised Classification.
245-256

- Eyke Hüllermeier:
Exploiting Similarity for Supporting Data Analysis and Problem Solving.
257-268

- Susana Nascimento, Boris Mirkin, Fernando Moura-Pires:
Multiple Prototype Model for Fuzzy Clustering.
269-280

- Jeroen Eggermont, A. E. Eiben, Jano I. van Hemert:
A Comparison of Genetic Programming Variants for Data Classification.
281-290

- Frank Klawonn, Annette Keller:
Fuzzy Clustering Based on Modified Distance Measures.
291-302

- Petko Valtchev:
Building Classes in Object-Based Languages by Automatic Clustering.
303-316

Section IV:
Integration
Section V:
Applications
- Daniele Gunetti, Giancarlo Ruffo:
Intrusion Detection through Behavioral Data.
383-394

- Paula E. Macrossan, Hussein A. Abbass, Kerrie L. Mengersen, Michael Towsey, Gerard D. Finn:
Bayesian Neural Network Learning for Prediction in the Australian Dairy Industry.
395-406

- Douglas A. Talbert, Douglas H. Fisher:
Exploiting Sample-Data Distributions to Reduce the Cost of Nearest-Neighbor Searches with Kd-Trees.
407-414

- David M. J. Tax, Alexander Ypma, Robert P. W. Duin:
Pump Failure Detection Using Support Vector Data Descriptions.
415-426

- Thorsten Poddig, Claus Huber:
Data Mining for the Detection of Turning Points in Financial Time Series.
427-436

- Bokyung Yang-Stephens, M. Charles Swope, Jeffrey Locke, Isabelle Moulinier:
Computer-Assisted Classification of Legal Abstracts.
437-448

- Yoshitomo Ikkai, Kazuhisa Ikeda, Norihisa Komoda, Akira Yamane, Isao Tone:
Sequential Control Logic Inferring Method from Observed Plant I/O Data.
449-460

- Gongxian Cheng, Kwawen Cho, Xiaohui Liu, George Loizou, John Xingwang Wu:
Evaluating an Eye Screening Test.
461-472

- José Manuel Peña, Sylvain Létourneau, Fazel Famili:
Application of Rough Sets Algorithms to Prediction of Aircraft Component Failure.
473-486

Section VI:
Media Mining
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