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时间:2019-07-03
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1、INTRODUCTIONTOMACHINELEARNINGANEARLYDRAFTOFAPROPOSEDTEXTBOOKNilsJ.NilssonRoboticsLaboratoryDepartmentofComputerScienceStanfordUniversityStanford,CA94305e-mail:nilsson@cs.stanford.eduNovember3,1998Copyrightc2005NilsJ.NilssonThismaterialmaynotbecopied,reproduced,ordistributedwi
2、thoutthewrittenpermissionofthecopyrightholder.iiContents1Preliminaries11.1Introduction..............................11.1.1WhatisMachineLearning?.................11.1.2WellspringsofMachineLearning..............31.1.3VarietiesofMachineLearning................41.2LearningInput-O
3、utputFunctions..................51.2.1TypesofLearning......................51.2.2InputVectors.........................71.2.3Outputs............................81.2.4TrainingRegimes.......................81.2.5Noise.............................91.2.6PerformanceEvaluation......
4、.............91.3LearningRequiresBias........................91.4SampleApplications.........................111.5Sources................................131.6BibliographicalandHistoricalRemarks..............132BooleanFunctions152.1Representation............................152.
5、1.1BooleanAlgebra.......................152.1.2DiagrammaticRepresentations...............162.2ClassesofBooleanFunctions....................172.2.1TermsandClauses......................172.2.2DNFFunctions........................182.2.3CNFFunctions........................212.2.4
6、DecisionLists.........................222.2.5SymmetricandVotingFunctions..............232.2.6LinearlySeparableFunctions................232.3Summary...............................242.4BibliographicalandHistoricalRemarks..............25iii3UsingVersionSpacesforLearning273.1Vers
7、ionSpacesandMistakeBounds................273.2VersionGraphs............................293.3LearningasSearchofaVersionSpace...............323.4TheCandidateEliminationMethod................323.5BibliographicalandHistoricalRemarks..............344NeuralNetworks354.1ThresholdLog
8、icUnits........................354.1.1DenitionsandGeometry.........
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