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

by De Raedt, Luc; Flach, Peter

• ISBN13: 9783540425366
• ISBN10: 3540425365
• Format: Paperback
• Copyright: 2001-10-01
• Publisher: Springer Verlag

Summary

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.

Table of Contents

Regular Papers
An Axiomatic Approach to Feature Term Generalization	1	(12)
Hassan Ait-Kaci
Yutaka Sasaki
Lazy Induction of Descriptions for Relational Case-Based Learning	13	(12)
Eva Armengol
Enric Plaza
Estimating the Predictive Accuracy of a Classifier	25	(12)
Hilan Bensusan
Alexandros Kalousis
Improving the Robustness and Encoding Complexity of Behavioural Clones	37	(12)
Rui Camacho
Pavel Brazdil
A Framework for Learning Rules from Multiple Instance Data	49	(12)
Yann Chevaleyre
Jean-Daniel Zucker
Wrapping Web Information Providers by Transducer Induction	61	(12)
Boris Chidlovskii
Learning While Exploring: Bridging the Gaps in the Eligibility Traces	73	(12)
Fredrik A. Dahl
Ole Martin Halck
A Reinforcement Learning Algorithm Applied to Simplified Two-Player Texas Hold'em Poker	85	(12)
Fredrik A. Dahl
Speeding Up Relational Reinforcement Learning through the Use of an Incremental First Order Decision Tree Learner	97	(12)
Kurt Driessens
Jan Ramon
Hendrik Blockeel
Analysis of the Performance of AdaBoost.M2 for the Simulated Digit-Recognition-Example	109	(12)
Gunther Eibl
Karl Peter Pfeiffer
Iterative Double Clustering for Unsupervised and Semi-supervised Learning	121	(12)
Ran El-Yaniv
Oren Souroujon
On the Practice of Branching Program Boosting	133	(12)
Tapio Elomaa
Matti Kaariainen
A Simple Approach to Ordinal Classification	145	(12)
Eibe Frank
Mark Hall
Fitness Distance Correlation of Neural Network Error Surfaces: A Scalable, Continuous Optimization Problem	157	(10)
Marcus Gallagher
Extraction of Recurrent Patterns from Stratified Ordered Trees	167	(12)
Jean-Gabriel Ganascia
Understanding Probabilistic Classifiers	179	(13)
Ashutosh Garg
Dan Roth
Efficiently Determining the Starting Sample Size for Progressive Sampling	192	(11)
Baohua Gu
Bing Liu
Feifang Hu
Huan Liu
Using Subclasses to Improve Classification Learning	203	(11)
Achim Hoffmann
Rex Kwok
Paul Compton
Learning What People (Don't) Want	214	(12)
Thomas Hofmann
Towards a Universal Theory of Artificial Intelligence Based on Algorithmic Probability and Sequential Decisions	226	(13)
Marcus Hutter
Convergence and Error Bounds for Universal Prediction of Nonbinary Sequences	239	(12)
Marcus Hutter
Consensus Decision Trees: Using Consensus Hierarchical Clustering for Data Relabelling and Reduction	251	(12)
Branko Kavsek
Nada Lavrac
Anuska Ferligoj
Learning of Variability for Invariant Statistical Pattern Recognition	263	(13)
Daniel Keysers
Wolfgang Macherey
Jorg Dahmen
Hermann Ney
The Evaluation of Predictive Learners: Some Theoretical and Empirical Results	276	(12)
Kevin B. Korb
Lucas R. Hope
Michelle J. Hughes
An Evolutionary Algorithm for Cost-Sensitive Decision Rule Learning	288	(12)
Wojciech Kwedlo
Marek Kretowski
A Mixture Approach to Novelty Detection Using Training Data with Outliers	300	(12)
Martin Lauer
Applying the Bayesian Evidence Framework to v-Support Vector Regression	312	(12)
Martin H. Law
James T. Kwok
DQL: A New Updating Strategy for Reinforcement Learning Based on Q-Learning	324	(12)
Carlos E. Mariano
Eduardo F. Morales
A Language-Based Similarity Measure	336	(12)
Lionel Martin
Frederic Moal
Backpropagation in Decision Trees for Regression	348	(12)
Victor Medina-Chico
Alberto Suarez
James F. Lutsko
Comparing the Bayes and Typicalness Frameworks	360	(12)
Thomas Melluish
Craig Saunders
Ilia Nouretdinov
Volodya Vovk
Symbolic Discriminant Analysis for Mining Gene Expression Patterns	372	(10)
Jason H. Moore
Joel S. Parker
Lance W. Hahn
Social Agents Playing a Periodical Policy	382	(12)
Ann Nowe
Johan Parent
Katja Verbeeck
Learning When to Collaborate among Learning Agents	394	(12)
Santiago Ontanon
Enric Plaza
Building Committees by Clustering Models Based on Pairwise Similarity Values	406	(13)
Thomas Ragg
Second Order Features for Maximising Text Classification Performance	419	(12)
Bhavani Raskutti
Herman Ferra
Adam Kowalczyk
Importance Sampling Techniques in Neural Detector Training	431	(11)
Jose L. Sanz-Gonzalez
Diego Andina
Induction of Qualitative Trees	442	(12)
Dorian Suc
Ivan Bratko
Text Categorization Using Transductive Boosting	454	(12)
Hirotoshi Taira
Masahiko Haruno
Using Multiple Clause Constructors in Inductive Logic Programming for Semantic Parsing	466	(12)
Lappoon R. Tang
Raymond J. Mooney
Using Domain Knowledge on Population Dynamics Modeling for Equation Discovery	478	(13)
Ljupco Todorovski
Saso Dzeroski
Mining the Web for Synonyms: PMI-IR versus LSA on TOEFL	491	(12)
Peter D. Turney
A Unified Framework for Evaluation Metrics in Classification Using Decision Trees	503	(12)
Ricardo Vilalta
Mark Brodie
Daniel Oblinger
Irina Rish
Improving Term Extraction by System Combination Using Boosting	515	(12)
Jordi Vivaldi
Lluis Marquez
Horacio Rodriguez
Classification on Data with Biased Class Distribution	527	(12)
Slobodan Vucetic
Zoran Obradovic
Discovering Admissible Simultaneous Equation Models from Observed Data	539	(13)
Takashi Washio
Hiroshi Motoda
Yuji Niwa
Discovering Strong Principles of Expressive Music Performance with the PLCG Rule Learning Strategy	552	(12)
Gerhard Widmer
Proportional k-Interval Discretization for Naive-Bayes Classifiers	564	(12)
Ying Yang
Geoffrey I. Webb
Using Diversity in Preparing Ensembles of Classifiers Based on Different Feature Subsets to Minimize Generalization Error	576	(12)
Gabriele Zenobi
Padraig Cunningham
Geometric Properties of Naive Bayes in Nominal Domains	588	(12)
Huajie Zhang
Charles X. Ling
Invited Papers
Support Vectors for Reinforcement Learning	600	(1)
Thomas G. Dietterich
Xin Wang
Combining Discrete Algorithmic and Probabilistic Approaches in Data Mining	601	(1)
Heikki Mannila
Statistification or Mystification? The Need for Statistical Thought in Visual Data Mining	602	(1)
Antony Unwin
The Musical Expression Project: A Challenge for Machine Learning and Knowledge Discovery	603	(12)
Gerhard Widmer
Scalability, Search, and Sampling: From Smart Algorithms to Active Discovery	615	(2)
Stefan Wrobel
Author Index	617