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Machine Learning: Ecml 2001 : 12th European Conference on Machine Learning, Freiburg, Germany, September 5-7, 2001. Proceedings - Luc de Raedt

Machine Learning: Ecml 2001

12th European Conference on Machine Learning, Freiburg, Germany, September 5-7, 2001. Proceedings

By: Luc de Raedt (Editor), Peter Flach (Editor)


Published: 23rd August 2001
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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.

An Axiomatic Approach to Feature Term Generalizationp. 1
Lazy Induction of Descriptions for Relational Case-Based Learningp. 13
Estimating the Predictive Accuracy of a Classifierp. 25
Improving the Robustness and Encoding Complexity of Behavioural Clonesp. 37
A Framework for Learning Rules from Multiple Instance Datap. 49
Wrapping Web Information Providers by Transducer Inductionp. 61
Learning While Exploring: Bridging the Gaps in the Eligibility Tracesp. 73
A Reinforcement Learning Algorithm Applied to Simplified Two-Player Texas Hold'em Pokerp. 85
Speeding Up Relational Reinforcement Learning through the Use of an Incremental First Order Decision Tree Learnerp. 97
Analysis of the Performance of AdaBoost.M2 for the Simulated Digit-Recognition-Examplep. 109
Iterative Double Clustering for Unsupervised and Semi-supervised Learningp. 121
On the Practice of Branching Program Boostingp. 133
A Simple Approach to Ordinal Classificationp. 145
Fitness Distance Correlation of Neural Network Error Surfaces: A Scalable, Continuous Optimization Problemp. 157
Extraction of Recurrent Patterns from Stratified Ordered Treesp. 167
Understanding Probabilistic Classifiersp. 179
Efficiently Determining the Starting Sample Size for Progressive Samplingp. 192
Using Subclasses to Improve Classification Learningp. 203
Learning What People (Don't) Wantp. 214
Towards a Universal Theory of Artificial Intelligence Based on Algorithmic Probability and Sequential Decisionsp. 226
Convergence and Error Bounds for Universal Prediction of Nonbinary Sequencesp. 239
Consensus Decision Trees: Using Consensus Hierarchical Clustering for Data Relabelling and Reductionp. 251
Learning of Variability for Invariant Statistical Pattern Recognitionp. 263
The Evaluation of Predictive Learners: Some Theoretical and Empirical Resultsp. 276
An Evolutionary Algorithm for Cost-Sensitive Decision Rule Learningp. 288
A Mixture Approach to Novelty Detection Using Training Data with Outliersp. 300
Applying the Bayesian Evidence Framework to v-Support Vector Regressionp. 312
DQL: A New Updating Strategy for Reinforcement Learning Based on Q-Learningp. 324
A Language-Based Similarity Measurep. 336
Backpropagation in Decision Trees for Regressionp. 348
Comparing the Bayes and Typicalness Frameworksp. 360
Symbolic Discriminant Analysis for Mining Gene Expression Patternsp. 372
Social Agents Playing a Periodical Policyp. 382
Learning When to Collaborate among Learning Agentsp. 394
Building Committees by Clustering Models Based on Pairwise Similarity Valuesp. 406
Second Order Features for Maximising Text Classification Performancep. 419
Importance Sampling Techniques in Neural Detector Trainingp. 431
Induction of Qualitative Treesp. 442
Text Categorization Using Transductive Boostingp. 454
Using Multiple Clause Constructors in Inductive Logic Programming for Semantic Parsingp. 466
Using Domain Knowledge on Population Dynamics Modeling for Equation Discoveryp. 478
Mining the Web for Synonyms: PMI-IR versus LSA on TOEFLp. 491
A Unified Framework for Evaluation Metrics in Classification Using Decision Treesp. 503
Improving Term Extraction by System Combination Using Boostingp. 515
Classification on Data with Biased Class Distributionp. 527
Discovering Admissible Simultaneous Equation Models from Observed Datap. 539
Discovering Strong Principles of Expressive Music Performance with the PLCG Rule Learning Strategyp. 552
Proportional k-Interval Discretization for Naive-Bayes Classifiersp. 564
Using Diversity in Preparing Ensembles of Classifiers Based on Different Feature Subsets to Minimize Generalization Errorp. 576
Geometric Properties of Naive Bayes in Nominal Domainsp. 588
Support Vectors for Reinforcement Learningp. 600
Combining Discrete Algorithmic and Probabilistic Approaches in Data Miningp. 601
Statistification or Mystification? The Need for Statistical Thought in Visual Data Miningp. 602
The Musical Expression Project: A Challenge for Machine Learning and Knowledge Discoveryp. 603
Scalability, Search, and Sampling: From Smart Algorithms to Active Discoveryp. 615
Author Indexp. 617
Table of Contents provided by Blackwell. All Rights Reserved.

ISBN: 9783540425366
ISBN-10: 3540425365
Series: Lecture Notes in Computer Science
Audience: General
Format: Paperback
Language: English
Number Of Pages: 620
Published: 23rd August 2001
Publisher: Springer-Verlag Berlin and Heidelberg Gmbh & Co. Kg
Country of Publication: DE
Dimensions (cm): 23.39 x 15.6  x 3.3
Weight (kg): 0.89