Machine Learning: ECML'97: 9th European Conference on Machine Learning, Prague, Czech Republic, April 23 - 25, 1997, Proceedings
Maarten van Someren, Gerhard Widmer
Springer, May 16, 1997 - Machine learning - 361 pages
This book constitutes the refereed proceedings of the Ninth European Conference on Machine Learning, ECML-97, held in Prague, Czech Republic, in April 1997. This volume presents 26 revised full papers selected from a total of 73 submissions. Also included are an abstract and two papers corresponding to the invited talks as well as descriptions from four satellite workshops. The volume covers the whole spectrum of current machine learning issues.
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Uncertain Learning Agents Abstract
Induction of Feature Terms with INDIE
Exploiting Qualitative Knowledge to Enhance Skill Acquisition
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0-subsumption agent application approach Artificial Intelligence attributes classification clauses complexity measure concept drift Conference on Machine convergence cross-validation data combination data mining databases dataset decision list decision tree defined denotes described discrete disjunctive domain dynamics error estimate evaluation experiments feature terms fitness landscape formula function given hidden unit hypothesis Ibots ideal operator Inductive Logic Programming input intervals Kolmogorov complexity language lazy learning learning algorithm linear loyalty Machine Learning method minimum description length model combination Morgan Kaufmann MSDD natural relation negative examples neural network node noise elimination Occam's razor optimal parameter partition performance positive examples predictive accuracy Proceedings prototypical structures pruning Quinlan random reinforcement learning representation robot rule induction rules search space Section sequence step subset symbol Table target concept tasks theory tion training data training examples training set uncovered infinite values variables