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" Machine Learning An Artificial Intelligence Approach "
R S Michalski
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BL
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| Record Number
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728985
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b548739
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| Main Entry
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R S Michalski
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| Title & Author
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Machine Learning An Artificial Intelligence Approach\ R S Michalski
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| Publication Statement
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Berlin Springer Berlin, 2013
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| Series Statement
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Symbolic Computation
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| Page. NO
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XI, 572 Seiten in 1 Teil XI, 572 Seiten, 25 schw.-w. Illustrationen 244 x 170 mm
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| ISBN
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3662124076
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: 9783662124079
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| Contents
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One General Issues in Machine Learning.- 1 An Overview of Machine Learning.- 2 Why Should Machines Learn?.- Two Learning from Examples.- 3 A Comparative Review of Selected Methods for Learning from Examples.- 4 A Theory and Methodology of Inductive Learning.- Three Learning in Problem-Solving and Planning.- 5 Learning by Analogy: Formulating and Generalizing Plans from Past Experience.- 6 Learning by Experimentation: Acquiring and Refining Problem-Solving Heuristics.- 7 Acquisition of Proof Skills in Geometry.- 8 Using Proofs and Refutations to Learn from Experience.- Four Learning from Observation and Discovery.- 9 The Role of Heuristics in Learning by Discovery: Three Case Studies.- 10 Rediscovering Chemistry With the BACON System.- 11 Learning From Observation: Conceptual Clustering.- Five Learning from Instruction.- 12 Machine Transformation of Advice into a Heuristic Search Procedure.- 13 Learning by Being Told: Acquiring Knowledge for Information Management.- 14 The Instructible Production System: A Retrospective Analysis.- Six Applied Learning Systems.- 15 Learning Efficient Classification Procedures and their Application to Chess End Games.- 16 Inferring Student Models for Intelligent Computer-Aided Instruction.- Comprehensive Bibliography of Machine Learning.- Glossary of Selected Terms In Machine Learning.- About the Authors.- Author Index.
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| LC Classification
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Q325.R765 2013
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| Added Entry
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J G Carbonell
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R S Michalski
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T M Mitchell
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