Titlebook: Lazy Learning; David W. Aha Book 1997 Springer Science+Business Media Dordrecht 1997 algorithms.case-based reasoning.classification.cognit

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Book 1997ning and editedk-nearest neighbor classifiers. It is intended for AI researchers andstudents interested in pursuing recent progress in this branch ofmachine learning, but, due to the breadth of its contributions, itshould also interest researchers and practitioners of data mining,case-based reasoning, statistics, and pattern recognition.

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branch ofmachine learning, but, due to the breadth of its contributions, itshould also interest researchers and practitioners of data mining,case-based reasoning, statistics, and pattern recognition.978-90-481-4860-8978-94-017-2053-3

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Discretisation in Lazy Learning Algorithms,hms to hyper-rectangular regions that are orthogonal to the attribute axes. Our generally better results obtained using a more restricted representation language indicate that employing a powerful representation language in a learning algorithm is not always the best choice as it can lead to a loss of accuracy.

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Locally Weighted Learning for Control,plain various forms that control tasks can take, and how this affects the choice of learning paradigm. The discussion section explores the interesting impact that explicitly remembering all previous experiences has on the problem of learning to control.

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Book 1997 inputs, reply to information requests bycombining stored data, and typically discard constructed replies. Itis the first edited volume in AI on this topic, whose many synonymsinclude `instance-based‘, `memory-based‘. `exemplar-based‘, and `locallearning‘, and whose topic intersects case-based reaso