Machine Learning: ECML 2001

Regular Papers.- An Axiomatic Approach to Feature Term Generalization.- Lazy Induction of Descriptions for Relational Case-Based Learning.- Estimating the Predictive Accuracy of a Classifier.- Improving the Robustness and Encoding Complexity of Behavioural Clones.- A Framework for Learning Rules from Multiple Instance Data.- Wrapping Web Information Providers by Transducer Induction.- Learning While Exploring: Bridging the Gaps in the Eligibility Traces.- A Reinforcement Learning Algorithm Applied to Simplified Two-Player Texas Hold'em Poker.- Speeding Up Relational Reinforcement Learning through the Use of an Incremental First Order Decision Tree Learner.- Analysis of the Performance of AdaBoost.M2 for the Simulated Digit-Recognition-Example.- Iterative Double Clustering for Unsupervised and Semi-supervised Learning.- On the Practice of Branching Program Boosting.- A Simple Approach to Ordinal Classification.- Fitness Distance Correlation of Neural Network Error Surfaces: A Scalable, Continuous Optimization Problem.- Extraction of Recurrent Patterns from Stratified Ordered Trees.- Understanding Probabilistic Classifiers.- Efficiently Determining the Starting Sample Size for Progressive Sampling.- Using Subclasses to Improve Classification Learning.- Learning What People (Don't) Want.- Towards a Universal Theory of Artificial Intelligence Based on Algorithmic Probability and Sequential Decisions.- Convergence and Error Bounds for Universal Prediction of Nonbinary Sequences.- Consensus Decision Trees: Using Consensus Hierarchical Clustering for Data Relabelling and Reduction.- Learning of Variability for Invariant Statistical Pattern Recognition.- The Evaluation of Predictive Learners: Some Theoretical and Empirical Results.- An Evolutionary Algorithm for Cost-Sensitive Decision Rule Learning.- A Mixture Approach to Novelty Detection Using Training Data with Outliers.- Applying the Bayesian Evidence Framework to ?-Support Vector Regression.- DQL: A New Updating