Transcription of INTRODUCTION MACHINE LEARNING
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INTRODUCTION MACHINE LEARNING
INTRODUCTIONTOMACHINE LEARNINGAN EARLY DRAFT OF A PROPOSEDTEXTBOOKNils J. NilssonRobotics LaboratoryDepartment of Computer ScienceStanford UniversityStanford, CA 94305e-mail: 3, 1998 Copyrightc 2005 Nils J. NilssonThis material may not be copied, reproduced, or distributed without thewritten permission of the copyright INTRODUCTION .. is MACHINE LEARNING ? .. of MACHINE LEARNING .. of MACHINE LEARNING .. LEARNING Input-Output Functions .. of LEARNING .. Vectors .. Regimes .. Evaluation .. LEARNING Requires Bias .. Sample Applications .. Sources .. Bibliographical and Historical Remarks .. 132 Boolean Representation .. Algebra .. Representations .. Classes of Boolean Functions .. and Clauses .. Functions .. Functions .. Lists .. and Voting Functions .. Separable Functions .. Summary .. Bibliographical and Historical Remarks.
the book is not a handbook of machine learning practice. Instead, my goal is ... whenever it changes its structure, program, or data (based on its inputs or in response to external information) in such a manner that its expected future performance improves. Some of these changes, such as the addition of a record
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