Machine Learning: ECML 2000

1. Front Matter

   Pages I-XII

   PDF

2. Invited Papers

   1. Beyond Occam’s Razor: Process-Oriented Evaluation

      • Pedro Domingos

      Pages 3-3

   2. The Representation Race — Preprocessing for Handling Time Phenomena

      • Katharina Morik

      Pages 4-19

3. Contributed Papers

   1. Short-Term Profiling for a Case-Based Reasoning Recommendation System

      • Esma Aimeur, Mathieu Vézeau

      Pages 23-30

   2. K-SVCR. A Multi-class Support Vector Machine

      • Cecilio Angulo, Andreu Català

      Pages 31-38

   3. Learning Trading Rules with Inductive Logic Programming

      • Liviu Badea

      Pages 39-46

   4. Improving Knowledge Discovery Using Domain Knowledge in Unsupervised Learning

      • Javier Béjar

      Pages 47-54

   5. Exploiting Classifier Combination for Early Melanoma Diagnosis Support

      • E. Blanzieri, C. Eccher, S. Forti, A. Sboner

      Pages 55-62

   6. A Comparison of Ranking Methods for Classification Algorithm Selection

      • Pavel B. Brazdil, Carlos Soares

      Pages 63-75

   7. Hidden Markov Models with Patterns and Their Application to Integrated Circuit Testing

      • Laurent Bréhélin, Olivier Gascuel, Gilles Caraux

      Pages 75-87

   8. Comparing Complete and Partial Classification for Identifying Latently Dissatisfied Customers

      • Tom Brijs, Gilbert Swinnen, Koen Vanhoof, Geert Wets

      Pages 88-95

   9. Wrapper Generation via Grammar Induction

      • Boris Chidlovskii, Jon Ragetli, Maarten de Rijke

      Pages 96-108

   10. Diversity versus Quality in Classification Ensembles Based on Feature Selection

       • Pádraig Cunningham, John Carney

       Pages 109-116

   11. Minimax TD-Learning with Neural Nets in a Markov Game

       • Fredrik A. Dahl, Ole Martin Halck

       Pages 117-128

   12. Boosting Applied to Word Sense Disambiguation

       • Gerard Escudero, Lluís Màrquez, German Rigau

       Pages 129-141

   13. A Multiple Model Cost-Sensitive Approach for Intrusion Detection

       • Wei Fan, Wenke Lee, Salvatore J. Stolfo, Matthew Miller

       Pages 142-154

   14. Value Miner: A Data Mining Environment for the Calculation of the Customer Lifetime Value with Application to the Automotive Industry

       • Katja Gelbrich, Reza Nakhaeizadeh

       Pages 154-161

   15. Investigation and Reduction of Discretization Variance in Decision Tree Induction

       • Pierre Geurts, Louis Wehenkel

       Pages 162-170

   16. Asymmetric Co-evolution for Imperfect-Information Zero-Sum Games

       • Ole Martin Halck, Fredrik A. Dahl

       Pages 171-182

   17. A Machine Learning Approach to Workflow Management

       • Joachim Herbst

       Pages 183-194

The biennial European Conference on Machine Learning (ECML) series is intended to provide an international forum for the discussion of the latest high quality research results in machine learning and is the major European scienti?c event in the ?eld. The eleventh conference (ECML 2000) held in Barcelona, Catalonia, Spain from May 31 to June 2, 2000, has continued this tradition by attracting high quality papers from around the world. Scientists from 21 countries submitted 100 papers to ECML 2000, from which 20 were selected for long oral presentations and 23 for short oral presentations. This selection was based on the recommendations of at least two reviewers for each submitted paper. It is worth noticing that the number of papers reporting applications of machine learning has increased in comparison to past ECML conferences. We believe this fact shows the growing maturity of the ?eld. This volume contains the 43 accepted papers as well as the invited talks by Katharina Morik from theUniversity of Dortmund and Pedro Domingos from the University of Washington at Seattle. In addition, three workshops were jointly organized by ECML 2000 and the European Network of Excellence - net: “Dealing with Structured Data in Machine Learning and Statistics W- stites”, “Machine Learning in the New Information Age” , and “Meta-Learning: Building Automatic Advice Strategies for Model Selection and Method Com- nation”.

• Algorithmic Learning
• Classification
• Data Mining
• Decision Diagrams
• Inductive Learning
• Inductive Logic Programming
• Inference
• algorithms
• cognition
• complexity
• genetic algorithms
• knowledge discovery
• learning
• machine learning
• proving
• algorithm analysis and problem complexity

• Institut d’Investigació en Intelligència Artificial, IIIA, Spanish Council for Scientific Research, CSIC, Bellaterra, Catalonia, Spain

  Ramon López de Mántaras, Enric Plaza

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