New Learning Paradigms in Soft Computing - Kacprzyk, Janusz

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Résumé :
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Sommaire:
Statistical Learning by Natural Gradient Descent.- Granular Networks and Granular Computing.- Learning and Decision-Making in the Framework of Fuzzy Lattices.- Lazy Learning: A Logical Method for Supervised Learning.- Active Learning in Neural Networks.- Knowledge Extraction from Reinforcement Learning.- Reinforcement Learning for Fuzzy Agents: Application to a Pighouse Environment Control.- Performance Comparisons of Neural Networks and Machine Learning Techniques: A Critical Assessment of the Methodology.- Digital Systems Design Through Learning.- Hybrid Inductive Machine Learning: An Overview of CLIP Algorithms.- An Integer Programming Approach to Inductive Learning Using Genetic and Greedy Algorithms.- Using Unlabeled Data for Learning Classification Problems.- Problems of Rule Induction from Preterm Birth Data.- Reduction of Discriminant Rules Based on Frequent Item Set Calculation.- Deriving a Concise Description of Non-Self Patterns in an Artificial Immune System.