出版社:Springer
出版日期:2002-09-17
ISBN:9783540440369
作者:Tapio Elomaa
页数:528页
作者简介
This book constitutes the refereed preceedings of the 13th European Conference on Machine Learning, ECML 2002, held in Helsinki, Finland in August 2002.The 41 revised full papers presented together with 4 invited contributions were carefully reviewed and selected from numerous submissions. Among the topics covered are computational discovery, search strategies, Classification, support vector machines, kernel methods, rule induction, linear learning, decision tree learning, boosting, collaborative learning, statistical learning, clustering, instance-based learning, reinforcement learning, multiagent learning, multirelational learning, Markov decision processes, active learning, etc.
书籍目录
Contributed Papers Convergent Gradient Ascent in General-Sum Games Revising Engineering Models: Combining Computational Discovery Variational Extensions to EM and Multinomial PCA Learning and Inference for Clause Identification An Empirical Study of Encoding Schemes and Search Strategies in Discovering Causal Networks Variance Optimized Bagging How to Make AdaBoost.M1 Work for Weak Base Classifiers Sparse Online Greedy Support Vector Regression Pairwise Classification as an Ensemble Technique RIONA: A Classifier Combining Rule Induction and k-NN Method with Automated Selection of Optimal Neighbourhood Using Hard Classifiers to Estimate Conditional Class Probabilities Evidence that Incremental Delta-Bar-Delta Is an Attribute-Efficient Linear Learner Scaling Boosting by Margin-Based Inclusion of Features and Relations Multiclass Alternating Decision Trees Possibilistic Induction in Decision-Tree Learning Improved Smoothing for Probabilistic Suffix Trees Seen as Variable Order Markov Chains Collaborative Learning of Term-Based Concepts for Automatic Query Expansion Learning to Play a Highly Complex Game from Human Expert Games Reliable Classifications with Machine Learning Matja2 Kukar and Igor Kononenko Robustness Analyses of Instance-Based Collaborative Recommendation iBoost: Boosting Using an instance-Based Exponential Weighting Scheme Towards a Simple Clustering Criterion Based on Minimum Length Encoding Class Probability Estimation and Cost-Sensitive Classification Decisions On-Line Support Vector Machine Regression Q-Cut - Dynamic Discovery of Sub-goals in Reinforcement Learning A Multistrategy Approach to the Classification of Phases in Business Cycles A Robust Boosting Algorithm Case Exchange Strategies in Multiagent Learning Inductive Confidence Machines for Regression Macro-Operators in Multirelational Learning A Search-Space Reduction Technique……Invited PapersAuthor Index
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