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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.

Chapter 1 Preliminaries 1.1 Introduction 1.1.1 What is Machine Learning? Learning, like intelligence, covers such a broad range of processes that it is dif-

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