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Machine Learning: ECML-97

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Cover of 'Machine Learning: ECML-97'

Table of Contents

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    Book Overview
  2. Altmetric Badge
    Chapter 67 Uncertain learning agents
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    Chapter 68 Constructing and sharing perceptual distinctions
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    Chapter 69 On prediction by data compression
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    Chapter 70 Induction of feature terms with INDIE
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    Chapter 71 Exploiting qualitative knowledge to enhance skill acquisition
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    Chapter 72 Integrated learning and planning based on truncating temporal differences
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    Chapter 73 θ-subsumption for structural matching
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    Chapter 74 Classification by Voting Feature Intervals
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    Chapter 75 Constructing intermediate concepts by decomposition of real functions
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    Chapter 76 Conditions for Occam's razor applicability and noise elimination
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    Chapter 77 Learning different types of new attributes by combining the neural network and iterative attribute construction
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    Chapter 78 Metrics on terms and clauses
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    Chapter 79 Learning when negative examples abound
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    Chapter 80 A model for generalization based on confirmatory induction
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    Chapter 81 Learning Linear Constraints in Inductive Logic Programming
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    Chapter 82 Finite-Element methods with local triangulation refinement for continuous reinforcement learning problems
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    Chapter 83 Inductive Genetic Programming with Decision Trees
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    Chapter 84 Parallel and distributed search for structure in multivariate time series
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    Chapter 85 Compression-based pruning of decision lists
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    Chapter 86 Probabilistic Incremental Program Evolution: Stochastic search through program space
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    Chapter 87 NeuroLinear: A system for extracting oblique decision rules from neural networks
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    Chapter 88 Inducing and using decision rules in the GRG knowledge discovery system
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    Chapter 89 Learning and exploitation do not conflict under minimax optimality
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    Chapter 90 Model combination in the multiple-data-batches scenario
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    Chapter 91 Search-based class discretization
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    Chapter 92 Natural ideal operators in Inductive Logic Programming
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    Chapter 93 A case study in loyalty and satisfaction research
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    Chapter 94 Ibots learn genuine team solutions
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    Chapter 95 Global data analysis and the fragmentation problem in decision tree induction
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    Chapter 96 Case-based learning: Beyond classification of feature vectors
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    Chapter 97 Empirical learning of Natural Language Processing tasks
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    Chapter 98 Human-Agent Interaction and Machine Learning
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    Chapter 99 Learning in dynamically changing domains: Theory revision and context dependence issues
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Title
Machine Learning: ECML-97
Published by
Springer, Berlin, Heidelberg, January 1997
DOI 10.1007/3-540-62858-4
ISBNs
978-3-54-062858-3, 978-3-54-068708-5
Editors

Maarten van Someren, Gerhard Widmer

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X Demographics

The data shown below were collected from the profiles of 5 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 12 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 12 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 2 17%
Professor 1 8%
Student > Doctoral Student 1 8%
Unknown 8 67%
Readers by discipline Count As %
Psychology 2 17%
Computer Science 1 8%
Engineering 1 8%
Unknown 8 67%