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1、MachineLearning,MachineLearning(extended)4–SupervisedLearning:BayesianClassificationKashifRajpootk.m.rajpoot@cs.bham.ac.ukSchoolofComputerScienceUniversityofBirminghamOutline•Supervisedlearning•Classification•Probabilisticvsnon-probabilistic•Generativevsd
2、iscriminative•Refresher:probability•Bayesianclassification•NaïveBayesclassification2•GaussianclassificationSupervisedlearning•Regression•Minimisedloss(e.g.leastsquares)•Maximumlikelihood•Classification•Generative(e.g.Bayesian)•Instance-based(e.g.k-NN)•Dis
3、criminative(e.g.SVM)3Classification•AsetofNobjectswithattributes(usuallyvector)??•Eachobjecthasanassociatedtargetlabel??•Binaryclassification??∈0,1or??∈−1,1•Multi-classclassification??∈1,2,…,?•Classifierlearnsfrom?1,?2,…,??and?1,?2,…,??sothatitcanlatercla
4、ssify????4Probabilisticvsnon-probabilisticclassification•Probabilisticclassifiersproduceaprobabilityofclassmembership•Non-probabilisticclassifiersproduceahardassignment5Probabilisticvsnon-probabilisticclassification•Probabilitiesprovideuswithmoreinformati
5、on•?????=1=0.6ismoreusefulthan????=1•Confidencelevel•Particularlyimportantwherecostofmisclassificationishighandimbalanced•Diagnosis:tellingadiseasedpersontheyarehealthyismuchworsethantellingahealthypersontheyarediseased6Generativevsdiscriminativeclassific
6、ation•Generativeclassifiersgenerateamodelforeachclass,basedontrainingsamplesavailable•Dataineachclasscanbeseenasgeneratedbysomemodel•Fornewtestsamples,theyassignthesesamplestotheclassthatsuitsbest(e.g.byprobabilitymeasure)•Incontrast,discriminativeclassif
7、iersattempttoexplicitlydefinethedecisionboundarythatseparatestheclasses•Intuitively,thesemethodsareforbinaryclassproblemsbutcanbeextendedtomulti-classproblems7Bayesianclassifier•AclassifierbuiltonBayesrule•Buildsaprobabilisticmodelofthedata,embeddingprior
8、knowledge•Allowsustoextractpriorknowledgefromobserveddata•Generativeapproach•Buildsamodelfromtrainingobjects•Anynewobjectscanbeclassifiedbasedontheprobabilisticmodelspecification8Refresher:probability•Conditionalpro
