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Table of contents

  1. Front Matter
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  2. FOIL: A midterm report
    J. R. Quinlan, R. M. Cameron-Jones
    Pages 1-20
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  3. Inductive logic programming: Derivations, successes and shortcomings
    Stephen Muggleton
    Pages 21-37
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  4. Two methods for improving inductive logic programming systems
    Irene Stahl, Birgit Tausend, Rüdiger Wirth
    Pages 39-55
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  5. Generalization under implication by using or-introduction
    Peter Idestam-Almquist
    Pages 56-64
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  6. On the proper definition of minimality in specialization and theory revision
    Stefan Wrobel
    Pages 65-82
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  7. Predicate invention in inductive data engineering
    Peter A. Flach
    Pages 83-94
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  8. Subsumption and refinement in model inference
    Patrick R. J. van der Laag, Shan-Hwei Nienhuys-Cheng
    Pages 95-114
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  9. Some lower bounds for the computational complexity of inductive logic programming
    Jörg-Uwe Kietz
    Pages 115-123
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  10. Improving example-guided unfolding
    Henrik Boström
    Pages 124-135
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  11. Bayes and pseudo-Bayes estimates of conditional probabilities and their reliability
    James Cussens
    Pages 136-152
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  12. Induction of recursive Bayesian classifiers
    Pat Langley
    Pages 153-164
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  13. Decision tree pruning as a search in the state space
    Floriana Esposito, Donate Malerba, Giovanni Semeraro
    Pages 165-184
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  14. Controlled redundancy in incremental rule learning
    Luis Torgo
    Pages 185-195
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  15. Getting order independence in incremental learning
    Antoine Cornuéjols
    Pages 196-212
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  16. Feature selection using rough sets theory
    Maciej Modrzejewski
    Pages 213-226
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  17. Effective learning in dynamic environments by explicit context tracking
    Gerhard Widmer, Miroslav Kubat
    Pages 227-243
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  18. COBBIT—A control procedure for COBWEB in the presence of concept drift
    Fredrik Kilander, Carl Gustaf Jansson
    Pages 244-261
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  19. Genetic algorithms for protein tertiary structure prediction
    Steffen Schulze-Kremer
    Pages 262-279
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  20. SIA: A supervised inductive algorithm with genetic search for learning attributes based concepts
    Gilles Venturini
    Pages 280-296
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  21. SAMIA: A bottom-up learning method using a simulated annealing algorithm
    Pierre Brézellec, Henri Soldano
    Pages 297-309
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  22. Predicate invention in ILP — an overview
    Irene Stahl
    Pages 311-322
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  23. Functional inductive logic programming with queries to the user
    F. Bergadano, D. Gunetti
    Pages 323-328
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  24. A note on refinement operators
    Tim Niblett
    Pages 329-335
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  25. An iterative and bottom-up procedure for proving-by-example
    Masami Hagiya
    Pages 336-341
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  26. Learnability of constrained logic programs
    Sašo Džeroski, Stephen Muggleton, Stuart Russell
    Pages 342-347
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  27. Complexity dimensions and learnability
    S. H. Nienhuys-Cheng, M. Polman
    Pages 348-353
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  28. Can complexity theory benefit from Learning Theory?
    Tibor Hegedüs
    Pages 354-359
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  29. Learning domain theories using abstract background knowledge
    Peter Clark, Stan Matwin
    Pages 360-365
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  30. Discovering patterns in EEG-signals: Comparative study of a few methods
    Miroslav Kubat, Doris Flotzinger, Gert Pfurtscheller
    Pages 366-371
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  31. Learning to control dynamic systems with automatic quantization
    Charles X. Ling, Ralph Buchal
    Pages 372-377
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  32. Refinement of rule sets with JoJo
    Dieter Fensel, Markus Wiese
    Pages 378-383
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  33. Rule combination in inductive learning
    Luis Torgo
    Pages 384-389
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  34. Using heuristics to speed up induction on continuous-valued attributes
    Günter Seidelmann
    Pages 390-395
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  35. Integrating models of knowledge and Machine Learning
    Jean-Gabriel Ganascia, Jérôme Thomas, Philippe Laublet
    Pages 396-401
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  36. Exploiting context when learning to classify
    Peter D. Turney
    Pages 402-407
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  37. IDDD: An inductive, domain dependent decision algorithm
    L. Gaga, V. Moustakis, G. Charissis, S. Orphanoudakis
    Pages 408-413
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  38. An application of machine learning in the domain of loan analysis
    José Ferreira, Joaquim Correia, Thomas Jamet, Ernesto Costa
    Pages 414-419
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  39. Extraction of knowledge from data using constrained neural networks
    Raqui Kane, Irina Tchoumatchenko, Maurice Milgram
    Pages 420-425
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  40. Integrated learning architectures
    E. Plaza, A. Aamodt, A. Ram, W. van de Velde, M. van Someren
    Pages 427-441
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  41. An overview of evolutionary computation
    William M. Spears, Kenneth A. De Jong, Thomas Bäck, David B. Fogel, Hugo de Garis
    Pages 442-459
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  42. ML techniques and text analysis
    Pieter Adriaans
    Pages 460-469
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  43. Back Matter
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About these proceedings

Introduction

This volume contains the proceedings of the Eurpoean Conference on Machine Learning (ECML-93), continuing the tradition of the five earlier EWSLs (European Working Sessions on Learning). The aim of these conferences is to provide a platform for presenting the latest results in the area of machine learning. The ECML-93 programme included invited talks, selected papers, and the presentation of ongoing work in poster sessions. The programme was completed by several workshops on specific topics. The volume contains papers related to all these activities. The first chapter of the proceedings contains two invited papers, one by Ross Quinlan and one by Stephen Muggleton on inductive logic programming. The second chapter contains 18 scientific papers accepted for the main sessions of the conference. The third chapter contains 18 shorter position papers. The final chapter includes three overview papers related to the ECML-93 workshops.

Keywords

Genetic Algorithms Genetische Algorithmen Inductive Learning Inductive Loigic Induktives Lernen Induktives Logisches Programmieren Learnability Lernbarkeit complexity complexity theory heuristics learning machine learning programming proving

Bibliographic information

  • DOI https://doi.org/10.1007/3-540-56602-3
  • Copyright Information Springer-Verlag Berlin Heidelberg 1993
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Springer Book Archive
  • Print ISBN 978-3-540-56602-1
  • Online ISBN 978-3-540-47597-2
  • Series Print ISSN 0302-9743
  • Series Online ISSN 1611-3349
  • Buy this book on publisher's site