机器学习十大算法

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1、Chapter1C4.5NarenRamakrishnanContents1.1Introduction..............................................................11.2AlgorithmDescription....................................................31.3C4.5Features.............................................................71.3.1Tr

2、eePruning......................................................71.3.2ImprovedUseofContinuousAttributes............................81.3.3HandlingMissingValues..........................................91.3.4InducingRulesets................................................101.4D

3、iscussiononAvailableSoftwareImplementations......................101.5TwoIllustrativeExamples...............................................111.5.1GolfDataset.....................................................111.5.2SoybeanDataset...........................................

4、......121.6AdvancedTopics........................................................131.6.1MiningfromSecondaryStorage..................................131.6.2ObliqueDecisionTrees..........................................131.6.3FeatureSelection...................................

5、.............131.6.4EnsembleMethods..............................................141.6.5ClassificationRules..............................................141.6.6Redescriptions...................................................151.7Exercises.....................................

6、..........................15References...................................................................171.1IntroductionC4.5[30]isasuiteofalgorithmsforclassificationproblemsinmachinelearninganddatamining.Itistargetedatsupervisedlearning:Givenanattribute-valueddatasetwherein

7、stancesaredescribedbycollectionsofattributesandbelongtooneofasetofmutuallyexclusiveclasses,C4.5learnsamappingfromattributevaluestoclassesthatcanbeappliedtoclassifynew,unseeninstances.Forinstance,seeFigure1.1whererowsdenotespecificdays,attributesdenoteweatherconditionsonthegiv

8、enday,andtheclassdenoteswhethertheconditionsareconducivetoplayinggolf.Thus,