Machine Learning - ECML '94: Proceedings of the European Conference on Machine Learning, Heraclion, Crete, Greece, April 1995

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Product Details

  • ISBN-13: 9780387592862
  • Publisher: Springer-Verlag New York, LLC
  • Publication date: 4/1/1995
  • Series: Lecture Notes in Computer Science
  • Pages: 370
  • Product dimensions: 62.50 (w) x 95.00 (h) x 7.50 (d)

Table of Contents

Reasoning and Learning in Probabilistic and Possibilistic Networks: An Overview 3
Problem Decomposition and the Learning of Skills 17
Machine Learning in the World Wide Web 32
Abstract Computer Models: Towards a New Method for Theorizing About Adaptive Agents 33
Learning Abstract Planning Cases 55
The Role of Prototypicality in Exemplar-Based Learning 77
Specialization of Recursive Predicates 92
A Distributed Genetic Algorithm Improving the Generalization Behavior of Neural Networks 107
Learning Non-Monotonic Logic Programs: Learning Exceptions 122
A Comparative Utility Analysis of Case-Based Reasoning and Control-Rule Learning Systems 138
A Minimization Approach to Propositional Inductive Learning 151
On Concept Space and Hypothesis Space in Case-Based Learning Algorithms 161
The Power of Decision Tables 174
Pruning Multivariate Decision Trees by Hyperplane Merging 190
Multiple-Knowledge Representations in Concept Learning 200
The Effect of Numeric Features on the Scalability of Inductive Learning Programs 218
Analogical Logic Program Synthesis from Examples 232
A Guided Tour Through Hypothesis Spaces in ILP 245
JIGSAW: Puzzling Together RUTH and SPECTRE 263
Discovery of Constraints and Data Dependencies in Relational Databases 267
Learning Disjunctive Normal Forms in a Dual Classifier System 271
The Effects of Noise on Efficient Incremental Induction 275
Analysis of Rachmaninoff's Piano Performances Using Inductive Logic Programming 279
Handling Real Numbers in Inductive Logic Programming: A Step Towards Better Behavioural Clones 283
Simplifying Decision Trees by Pruning and Grafting: New Results 287
A Tight Integration of Pruning and Learning 291
Decision-Tree Based Neural Network 295
Learning Recursion with Iterative Bootstrap Induction 299
Patching Proofs for Reuse 303
Adapting to Drift in Continuous Domains 307
Parallel Recombinative Reinforcement Learning 311
Learning to Solve Complex Tasks for Reactive Systems 315
Co-operative Reinforcement Learning by Payoff Filters 319
Automatic Synthesis of Control Programs by Combination of Learning and Problem Solving Methods 323
Analytical Learning Guided by Empirical Technology: An Approach to Integration 327
A New MDL Measure for Robust Rule Induction 331
Class-Driven Statistical Discretization of Continuous Attributes 335
Generating Neural Networks Through the Induction of Threshold Logic Unit Trees 339
Learning Classification Rules Using Lattices 343
Hybrid Classification: Using Axis-Parallel and Oblique Subdivisions of the Attribute Space 347
An Induction-based Control for Genetic Algorithms 351
FENDER: An Approach to Theory Restructuring 356
Language Series Revisited: The Complexity of Hypothesis Spaces in ILP 360
Prototype, Nearest Neighbor and Hybrid Algorithms for Time Series Classification 364
Author Index 369
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