Machine Learning: ECML 2001 Book

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