Machine Learning

ECML 2000 : 11th European Conference on Machine Learning Barcelona, Catalonia, Spain May, 31 - June 2, 2000 Proceedings

By: Ramon Lopez de Mantaras (Editor), Enric Plaza (Editor)

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Paperback | 17 May 2000

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The biennial European Conference on Machine Learning (ECML) series is intended to provide an international forum for the discussion of the latest high quality research results in machine learning and is the major European scienti?c event in the ?eld. The eleventh conference (ECML 2000) held in Barcelona, Catalonia, Spain from May 31 to June 2, 2000, has continued this tradition by attracting high quality papers from around the world. Scientists from 21 countries submitted 100 papers to ECML 2000, from which 20 were selected for long oral presentations and 23 for short oral presentations. This selection was based on the recommendations of at least two reviewers for each submitted paper. It is worth noticing that the number of papers reporting applications of machine learning has increased in comparison to past ECML conferences. We believe this fact shows the growing maturity of the ?eld. This volume contains the 43 accepted papers as well as the invited talks by Katharina Morik from the University of Dortmund and Pedro Domingos from the University of Washington at Seattle. In addition, three workshops were jointly organized by ECML 2000 and the European Network of Excellence - net: "Dealing with Structured Data in Machine Learning and Statistics W- stites", "Machine Learning in the New Information Age" , and "Meta-Learning: Building Automatic Advice Strategies for Model Selection and Method Com- nation".

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Non-Fiction Computing & I.T.Computer Science Mathematical Theory of Computation Artificial Intelligence Medicine Medicine in General Databases Data Capture & Analysis Computer Programming & Software Development Algorithms & Data Structures

Invited Papers
Beyond Occam's Razor: Process-Oriented Evaluation	p. 3
The Representation Race - Preprocessing for Handling Time Phenomena	p. 4
Contributed Papers
Short-Term Profiling for a Case-Based Reasoning Recommendation System	p. 23
K-SVCR. A Multi-class Support Vector Machine	p. 31
Learning Trading Rules with Inductive Logic Programming	p. 39
Improving Knowledge Discovery Using Domain Knowledge in Unsupervised Learning	p. 47
Exploiting Classifier Combination for Early Melanoma Diagnosis Support	p. 55
A Comparison of Ranking Methods for Classification Algorithm Selection	p. 63
Hidden Markov Models with Patterns and Their Application to Integrated Circuit Testing	p. 75
Comparing Complete and Partial Classification for Identifying Latently Dissatisfied Customers	p. 88
Wrapper Generation via Grammar Induction	p. 96
Diversity versus Quality in Classification Ensembles Based on Feature Selection	p. 109
Minimax TD-Learning with Neural Nets in a Markov Game	p. 117
Boosting Applied to Word Sense Disambiguation	p. 129
A Multiple Model Cost-Sensitive Approach for Intrusion Detection	p. 142
Value Miner: A Data Mining Environment for the Calculation of the Customer Lifetime Value with Application to the Automotive Industry	p. 154
Investigation and Reduction of Discretization Variance in Decision Tree Induction	p. 162
Asymmetric Co-evolution for Imperfect-Information Zero-Sum Games	p. 171
A Machine Learning Approach to Workflow Management	p. 183
The Utilization of Context Signals in the Analysis of ABR Potentials by Application of Neural Networks	p. 195
Complexity Approximation Principle and Rissanen's Approach to Real-Valued Parameters	p. 203
Handling Continuous-Valued Attributes in Decision Tree with Neural Network Modeling	p. 211
Learning Context-Free Grammars with a Simplicity Bias	p. 220
Partially Supervised Text Classification: Combining Labeled and Unlabeled Documents Using an EM-like Scheme	p. 229
Toward an Explanatory Similarity Measure for Nearest-Neighbor Classification	p. 238
Relative Unsupervised Discretization for Regression Problems	p. 246
Metric-Based Inductive Learning Using Semantic Height Functions	p. 254
Error Analysis of Automatic Speech Recognition Using Principal Direction Divisive Partitioning	p. 263
A Study on the Performance of Large Bayes Classifier	p. 271
Dynamic Discretization of Continuous Values from Time Series	p. 280
Using a Symbolic Machine Learning Tool to Refine Lexico-syntactic Patterns	p. 292
Measuring Performance when Positives Are Rare: Relative Advantage versus Predictive Accuracy - A Biological Case-Study	p. 300
Mining TCP/IP Traffic for Network Intrusion Detection by Using a Distributed Genetic Algorithm	p. 313
Learning Patterns of Behavior by Observing System Events	p. 323
Dimensionality Reduction through Sub-space Mapping for Nearest Neighbour Algorithms	p. 331
Nonparametric Regularization of Decision Trees	p. 344
An Efficient and Effective Procedure for Updating a Competence Model for Case-Based Reasoners	p. 357
Layered Learning	p. 369
Problem Decomposition for Behavioural Cloning	p. 382
Dynamic Feature Selection in Incremental Hierarchical Clustering	p. 392
On the Boosting Pruning Problem	p. 404
An Empirical Study of MetaCost Using Boosting Algorithms	p. 413
Clustered Partial Linear Regression	p. 426
Knowledge Discovery from Very Large Databases Using Frequent Concept Lattices	p. 437
Some Improvements on Event-Sequence Temporal Region Methods	p. 446
Author Index	p. 459
Table of Contents provided by Publisher. All Rights Reserved.

Machine Learning

ECML 2000 : 11th European Conference on Machine Learning Barcelona, Catalonia, Spain May, 31 - June 2, 2000 Proceedings

At a Glance

Paperback

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