Machine Learning: ECML-95

Table of Contents

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   Book Overview
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   Chapter 45 Reasoning and learning in probabilistic and possibilistic networks: An overview
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   Chapter 46 Problem decomposition and the learning of skills
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   Chapter 47 Machine learning in the world wide web
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   Chapter 48 Abstract computer models: Towards a new method for theorizing about adaptive agents
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   Chapter 49 Learning abstract planning cases
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   Chapter 50 The role of prototypicality in exemplar-based learning
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   Chapter 51 Specialization of recursive predicates
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   Chapter 52 A distributed genetic algorithm improving the generalization behavior of neural networks
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    Chapter 53 Learning non-monotonic logic programs: Learning exceptions
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    Chapter 54 A comparative utility analysis of case-based reasoning and control-rule learning systems
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    Chapter 55 A minimization approach to propositional inductive learning
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    Chapter 56 On concept space and hypothesis space in case-based learning algorithms
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    Chapter 57 The power of decision tables
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    Chapter 58 Pruning multivariate decision trees by hyperplane merging
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    Chapter 59 Multiple-Knowledge Representations in concept learning
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    Chapter 60 The effect of numeric features on the scalability of inductive learning programs
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    Chapter 61 Analogical logic program synthesis from examples
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    Chapter 62 A guided tour through hypothesis spaces in ILP
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    Chapter 63 JIGSAW: Puzzling together RUTH and SPECTRE (Extended abstract)
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    Chapter 64 Discovery of constraints and data dependencies in relational databases (Extended abstract)
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    Chapter 65 Learning disjunctive normal forms in a dual classifier system (Extended abstract)
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    Chapter 66 The effects of noise on efficient incremental induction (Extended abstract)
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    Chapter 67 Analysis of Rachmaninoff's piano performances using inductive logic programming (Extended abstract)
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    Chapter 68 Handling real numbers in ILP: A step towards better behavioural clones (Extended abstract)
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    Chapter 69 Simplifying decision trees by pruning and grafting: New results (Extended abstract)
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    Chapter 70 A tight integration of pruning and learning (Extended abstract)
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    Chapter 71 Decision-tree based neural network (Extended abstract)
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    Chapter 72 Learning recursion with iterative bootstrap induction (Extended abstract)
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    Chapter 73 Patching proofs for reuse (Extended abstract)
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    Chapter 74 Adapting to drift in continuous domains (Extended abstract)
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    Chapter 75 Parallel recombinative reinforcement learning (Extended abstract)
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    Chapter 76 Learning to solve complex tasks for reactive systems (Extended abstract)
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    Chapter 77 Co-operative Reinforcement Learning by payoff filters (Extended abstract)
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    Chapter 78 Automatic synthesis of control programs by combination of learning and problem solving methods (Extended abstract)
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    Chapter 79 Analytical learning guided by empirical technology: An approach to integration (Extended abstract)
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    Chapter 80 A new MDL measure for robust rule induction (Extended abstract)
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    Chapter 81 Class-driven statistical discretization of continuous attributes (Extended abstract)
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    Chapter 82 Generating neural networks through the induction of threshold logic unit trees (Extended abstract)
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    Chapter 83 Learning classification rules using lattices (Extended abstract)
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    Chapter 84 Hybrid classification: Using axis-parallel and oblique subdivisions of the attribute space (Extended abstract)
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    Chapter 85 An induction-based control for genetic algorithms (Extended abstract)
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    Chapter 86 Fender: An approach to theory restructuring (extended abstract)
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    Chapter 87 Language series revisited: The complexity of hypothesis spaces in ILP (Extended abstract)
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    Chapter 88 Prototype, nearest neighbor and hybrid algorithms for time series classification (Extended abstract)