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.
state, but I do give plausibility arguments and citations to formal proofs. And, I do not treat many matters that would be of practical importance in applications; the book is not a handbook of machine learning practice. Instead, my goal is to give the reader su cient preparation to make the extensive literature on machine learning accessible.
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