probabilistic reasoning with nave bayes and bayesian networks overview

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1、ProbabilisticReasoningwithNaïveBayesandBayesianNetworks1ZdravkoMarkov,IngridRussellJuly,2007OverviewBayesian(alsocalledBelief)Networks(BN)areapowerfulknowledgerepresentationandreasoningmechanism.BNrepresenteventsandcausalrelationshipsbetweenthemasconditionalprobabilitiesinvolvingrandomvariables.Give

2、nthevaluesofasubsetofthesevariables(evidencevariables)BNcancomputetheprobabilitiesofanothersubsetofvariables(queryvariables).BNcanbecreatedautomatically(learnt)byusingstatisticaldata(examples).Thewell-knownMachineLearningalgorithm,NaïveBayesisactuallyaspecialcaseofaBayesianNetwork.Theprojectallowsst

3、udentstoexperimentwithandusetheNaïveBayesalgorithmandBayesianNetworkstosolvepracticalproblems.Thisincludescollectingdatafromrealdomains(e.g.webpages),convertingthesedataintoproperformatsothatconditionalprobabilitiescanbecomputed,andusingBayesianNetworksandtheNaïveBayesalgorithmforcomputingprobabilit

4、iesandsolvingclassificationtasks.ObjectivesTheaimofthisprojectistoexposestudentstotwoimportantreasoningandlearningalgorithms–NaïveBayesandBayesianNetworks,andtoexploretheirrelationshipinthecontextofsolvingpracticalclassificationproblems.Inparticular,theobjectivesoftheprojectare:•LearningthebasicsofB

5、ayesianapproachtoMachineLearningandtheBayesianNetworksapproachtoProbabilisticReasoninginAI.•Gainingexperienceinusingrecentsoftwareapplicationsintheseareasforsolvingpracticalproblems.•BetterunderstandingoffundamentalconceptsofBayesianLearningandProbabilisticReasoningandtheirrelationshipinthemoregener

6、alcontextofknowledgerepresentationandreasoningmechanismsinAI.ProjectDescription1Correspondingauthor:markovz@ccsu.edu,DepartmentofComputerScience,CentralConnecticutStateUniversity,1615StanleyStreet,NewBritain,CT06050.SimilarlytotheWebdocumentclassificationproject(http://uhaweb.hartford.edu/compsci/cc

7、li/wdc.htm)thisprojectalsohasthreemainsteps:Datacollection,Datapreparation,andMachineLearning.Thefirsttwostepsofthetwoprojectsarebasicallythesame.Infact,documentsanddatasetsinWeka’sARFFformatpreparedf