Machine Learning: ECML 2001

1. Regular Papers

   1. Using Multiple Clause Constructors in Inductive Logic Programming for Semantic Parsing

      • Lappoon R. Tang, Raymond J. Mooney

      Pages 466-477

   2. Using Domain Knowledge on Population Dynamics Modeling for Equation Discovery

      • 1Ljupčo Todorovski, Sašo DŽeroski

      Pages 478-490

   3. Mining the Web for Synonyms: PMI-IR versus LSA on TOEFL

      • Peter D. Turney

      Pages 491-502

   4. A Unified Framework for Evaluation Metrics in Classification Using Decision Trees

      • Ricardo Vilalta, Mark Brodie, Daniel Oblinger, Irina Rish

      Pages 503-514

   5. Improving Term Extraction by System Combination Using Boosting

      • Jordi Vivaldi, 2Lluís Màrquez, Horacio Rodríguez

      Pages 515-526

   6. Classification on Data with Biased Class Distribution

      • Slobodan Vucetic, Zoran Obradovic

      Pages 527-538

   7. Discovering Admissible Simultaneous Equation Models from Observed Data

      • Takashi Washio, Hiroshi Motoda, Yuji Niwa

      Pages 539-551

   8. Discovering Strong Principles of Expressive Music Performance with the PLCG Rule Learning Strategy

      • Gerhard Widmer

      Pages 552-563

   9. Proportional k-Interval Discretization for Naive-Bayes Classifiers

      • Ying Yang, Geoffrey I. Webb

      Pages 564-575

   10. Using Diversity in Preparing Ensembles of Classifiers Based on Different Feature Subsets to Minimize Generalization Error

       • Gabriele Zenobi, Pádraig Cunningham

       Pages 576-587

   11. Geometric Properties of Naive Bayes in Nominal Domains

       • Huajie Zhang, Charles X. Ling

       Pages 587-599

2. Invited Papers

   1. Support Vectors for Reinforcement Learning

      • Thomas G. Dietterich, Xin Wang

      Pages 600-600

   2. Combining Discrete Algorithmic and Probabilistic Approaches in Data Mining

      • Heikki Mannila

      Pages 601-601

   3. Statistification or Mystification? The Need for Statistical Thought in Visual Data Mining

      • Antony Unwin

      Pages 602-602

   4. The Musical Expression Project: A Challenge for Machine Learning and Knowledge Discovery

      • Gerhard Widmer

      Pages 603-614

   5. Scalability, Search, and Sampling: From Smart Algorithms to Active Discovery

      • Stefan Wrobel

      Pages 615-615

3. Back Matter

   Pages 617-618

   PDF

This book constitutes the refereed proceedings of the 12th European Conference on Machine Learning, ECML 2001, held in Freiburg, Germany, in September 2001.
The 50 revised full papers presented together with four invited contributions were carefully reviewed and selected from a total of 140 submissions. Among the topics covered are classifier systems, naive-Bayes classification, rule learning, decision tree-based classification, Web mining, equation discovery, inductive logic programming, text categorization, agent learning, backpropagation, reinforcement learning, sequence prediction, sequential decisions, classification learning, sampling, and semi-supervised learning.

• Text
• classification
• learning
• logic
• machine learning
• programming
• reinforcement learning
• supervised learning
• web mining
• algorithm analysis and problem complexity

• Department of Computer Science, Albert-Ludwigs University Freiburg, Freiburg, Germany

  Luc Raedt

• Department of Computer Science, University of Bristol, Bristol, UK

  Peter Flach

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