MOOC 交通数据挖掘技术（Data Mining for Transportation）-东南大学 中国大学慕课答案

MOOC交通数据挖掘技术（DataMiningforTransportation）-东南大学中国大学慕课答案Test11、问题：WhichoneisnotthedescriptionofDatamining?选项：A、ExtractionofinterestingpatternsorknowledgeB、Explorationsandanalysisbyautomaticorsemi-automaticmeansC、DiscovermeaningfulpatternsfromlargequantitiesofdataD、Appropriatestatisticalanalysismethodstoanalyzethedatacollected正确答案:【Appropriatestatisticalanalysismethodstoanalyzethedatacollected】2、问题：Whichonedescribestherightprocessofknowledgediscovery?选项：A、Selection-Preprocessing-Transformation-Datamining-Interpretation/EvaluationB、Preprocessing-Transformation-Datamining-Selection-Interpretation/EvaluationC、Datamining-Selection-Interpretation/Evaluation-Preprocessing-TransformationD、Transformation-Datamining-election-Preprocessing-Interpretation/Evaluation正确答案:【Selection-Preprocessing-Transformation-Datamining-Interpretation/Evaluation】3、问题：WhichoneisnotbelongtotheprocessofKDD?选项：A、DataminingB、DatadescriptionC、DatacleaningD、Dataselection正确答案:【Datadescription】4、问题：Whichoneisnottherightalternativenameofdatamining?选项：A、KnowledgeextractionB、DataarcheologyC、DatadredgingD、Dataharvesting正确答案:【Dataharvesting】5、问题：Whichoneisnotthenominalvariables?选项：A、OccupationB、EducationC、AgeD、Color正确答案:【Age】6、问题：Whichoneiswrongaboutclassificationandregression?选项：A、Regressionanalysisisastatisticalmethodologythatismostoftenusedfornumericprediction.B、Wecanconstructclassificationmodels(functions)withoutsometrainingexamples.C、Classificationpredictscategorical(discrete,unordered)labels.D、Regressionmodelspredictcontinuous-valuedfunctions.正确答案:【Wecanconstructclassificationmodels(functions)withoutsometrainingexamples.】7、问题：Whichoneiswrongaboutclusteringandoutliers?选项：A、Clusteringbelongstosupervisedlearning.B、Principlesofclusteringincludemaximizingintra-classsimilarityandminimizinginterclasssimilarity.C、Outlieranalysiscanbeusefulinfrauddetectionandrareeventsanalysis.D、Outliermeansadataobjectthatdoesnotcomplywiththegeneralbehaviorofthedata.正确答案:【Clusteringbelongstosupervisedlearning.】8、问题：Aboutdataprocess,whichoneiswrong?选项：A、Whenmakingdatadiscrimination,wecomparethetargetclasswithoneorasetofcomparativeclasses(thecontrastingclasses).B、Whenmakingdataclassification,wepredictcategoricallabelsexcludingunorderedone.C、Whenmakingdatacharacterization,wesummarizethedataoftheclassunderstudy(thetargetclass)ingeneralterms.D、Whenmakingdataclustering,wewouldgroupdatatoformnewcategories.正确答案:【Whenmakingdataclassification,wepredictcategoricallabelsexcludingunorderedone.】9、问题：Outlierminingsuchasdensitybasedmethodbelongstosupervisedlearning.选项：A、正确B、错误正确答案:【错误】10、问题：Supportvectormachinescanbeusedforclassificationandregression.选项：A、正确B、错误正确答案:【正确】Test21、问题：Whichisnotthereasonweneedtopreprocessthedata?选项：A、tosavetimeB、tomakeresultmeetourhypothesisC、toavoidunreliableoutputD、toeliminatenoise正确答案:【tomakeresultmeetourhypothesis】2、问题：Whichisnotthemajortasksindatapreprocessing?选项：A、CleanB、IntegrationC、TransitionD、Reduction正确答案:【Transition】3、问题：HowtoconstructnewfeaturespacebyPCA?选项：A、NewfeaturespacebyPCAisconstructedbychoosingthemostimportantfeaturesyouthink.B、NewfeaturespacebyPCAisconstructedbynormalizinginputdata.C、NewfeaturespacebyPCAisconstructedbyselectingfeaturesrandomly.D、NewfeaturespacebyPCAisconstructedbyeliminatingtheweakcomponentstoreducethesizeofthedata.正确答案:【NewfeaturespacebyPCAisconstructedbyeliminatingtheweakcomponentstoreducethesizeofthedata.】4、问题：Whichoneiswrongaboutmethodsfordiscretization?选项：A、HistogramanalysisandBingingarebothunsupervisedmethods.B、Clusteringanalysisonlybelongstotop-downsplit.C、Intervalmergingbyc2Analysiscanbeappliedrecursively.D、Decision-treeanalysisisEntropy-baseddiscretization.正确答案:【Clusteringanalysisonlybelongstotop-downsplit.】5、问题：WhichoneiswrongaboutEqual-width(distance)partitioningandEqual-depth(frequency)partitioning?选项：A、Equal-widthpartitioningisthemoststraightforward,butoutliersmaydominatepresentation.B、Equal-depthpartitioningdividestherangeintoNintervals,eachcontainingapproximatelysamenumberofsamples.C、Theintervaloftheformeroneisnotequal.D、Thenumberoftuplesisthesamewhenusingthelatterone.正确答案:【Theintervaloftheformeroneisnotequal.】6、问题：Whichoneiswrongwaytonormalizedata?选项：A、Min-maxnormalizationB、SimplescalingC、Z-scorenormalizationD、Normalizationbydecimalscaling正确答案:【Simplescaling】7、问题：Whicharetherightwaytofillinmissingvalues?选项：A、SmartmeanB、ProbablevalueC、IgnoreD、Falsify正确答案:【Smartmean#Probablevalue#Ignore】8、问题：Whicharetherightwaytohandlenoisedata?选项：A、RegressionB、ClusterC、WTD、Manual正确答案:【Regression#Cluster#WT#Manual】9、问题：Whichoneisrightaboutwavelettransforms?选项：A、Wavelettransformsstorelargefractionsofthestrongestofthewaveletcoefficients.B、TheDWTdecomposeseachsegmentoftimeseriesviathesuccessiveuseoflow-passandhigh-passfilteringatappropriatelevels.C、Wavelettransformscanbeusedforreducingdataandsmoothingdata.D、Wavelettransformsmeansapplyingtopairsofdata,resultingintwosetofdataofthesamelength.正确答案:【TheDWTdecomposeseachsegmentoftimeseriesviathesuccessiveuseoflow-passandhigh-passfilteringatappropriatelevels.#Wavelettransformscanbeusedforreducingdataandsmoothingdata.】10、问题：Whicharethecommonusedwaystosampling?选项：A、SimplerandomsamplewithoutreplacementB、SimplerandomsamplewithreplacementC、StratifiedsampleD、Clustersample正确答案:【Simplerandomsamplewithoutreplacement#Simplerandomsamplewithreplacement#Stratifiedsample#Clustersample】11、问题：Discretizationmeansdividingtherangeofacontinuousattributeintointervals.选项：A、正确B、错误正确答案:【正确】Test31、问题：What'sthedifferencebetweeneagerlearnerandlazylearner?选项：A、Eagerlearnerswouldgenerateamodelforclassificationwhilelazylearnerwouldnot.B、Eagerlearnersclassifytheturplebasedonitssimilaritytothestoredtrainingturplewhilelazylearnernot.C、Eagerlearnerssimplystoredata(ordoesonlyalittleminorprocessing)whilelazylearnernot.D、Lazylearnerwouldgenerateamodelforclassificationwhileeagerlearnerwouldnot.正确答案:【Eagerlearnerswouldgenerateamodelforclassificationwhilelazylearnerwouldnot.】2、问题：HowtochoosetheoptimalvalueforK?选项：A、Cross-validationcanbeusedtodetermineagoodvaluebyusinganindependentdatasettovalidatetheKvalues.B、LowvaluesforK(likek=1ork=2)canbenoisyandsubjecttotheeffectofoutliers.C、Alargekvaluecanreducetheoverallnoisesothevaluefor'k'canbeasbigaspossible.D、Historically,theoptimalKformostdatasetshasbeenbetween3-10.正确答案:【Cross-validationcanbeusedtodetermineagoodvaluebyusinganindependentdatasettovalidatetheKvalues.#LowvaluesforK(likek=1ork=2)canbenoisyandsubjecttotheeffectofoutliers.#Historically,theoptimalKformostdatasetshasbeenbetween3-10.】3、问题：What’sthemajorcomponentsinKNN?选项：A、Howtomeasuresimilarity?B、Howtochoosek?C、Howareclasslabelsassigned?D、Howtodecidethedistance?正确答案:【Howtomeasuresimilarity?#Howtochoosek?#Howareclasslabelsassigned?】4、问题：WhichoneofthefollowingwayscanbeusedtoobtainattributeweightforAttribute-WeightedKNN?选项：A、Priorknowledge/experience.B、PCA,FA(Factoranalysismethod).C、Informationgain.D、Gradientdescent,simplexmethodsandgeneticalgorithm.正确答案:【Priorknowledge/experience.#PCA,FA(Factoranalysismethod).#Informationgain.#Gradientdescent,simplexmethodsandgeneticalgorithm.】5、问题：AtlearningstageKNNwouldfindtheKclosestneighborsandthendecideclassifyKidentifiednearestlabel.选项：A、正确B、错误正确答案:【错误】6、问题：AtclassificationstageKNNwouldstoreallinstanceorsometypicalofthem.选项：A、正确B、错误正确答案:【错误】7、问题：Normalizingthedatacansolvetheproblemthatdifferentattributeshavedifferentvalueranges.选项：A、正确B、错误正确答案:【正确】8、问题：ByEuclideandistanceorManhattandistance,wecancalculatethedistancebetweentwoinstances.选项：A、正确B、错误正确答案:【正确】9、问题：DatanormalizationbeforeMeasureDistancecanavoiderrorscausedbydifferentdimensions,self-variations,orlargenumericaldifferences.选项：A、正确B、错误正确答案:【正确】10、问题：Thewaytoobtaintheregressionforanewinstancefromtheknearestneighborsistocalculatetheaveragevalueofkneighbors.选项：A、正确B、错误正确答案:【正确】11、问题：Thewaytoobtaintheclassificationforanewinstancefromtheknearestneighborsistocalculatethemajorityclassofkneighbors.选项：A、正确B、错误正确答案:【正确】12、问题：ThewaytoobtaininstanceweightforDistance-WeightedKNNistocalculatethereciprocalofthedistancesquaredbetweenobjectandneighbors.选项：A、正确B、错误正确答案:【正确】Test41、问题：Whichdescriptionisrightaboutnodesindecisiontree?选项：A、InternalnodestestthevalueofparticularfeaturesB、LeafnodesspecifytheclassC、BranchnodesdecidetheresultD、Rootnodesdecidethestartpoint正确答案:【Internalnodestestthevalueofparticularfeatures#Leafnodesspecifytheclass】2、问题：ComputinginformationgainforcontinuousvalueattributewhenusingID3consistsofthefollowingprocedure:选项：A、SortthevalueAinincreasingorder.B、Considerthemidpointbetweeneachpairofadjacentvaluesasapossiblesplitpoint.C、Selecttheminimumexpectedinformationrequirementasthesplit-point.D、Split.正确答案:【SortthevalueAinincreasingorder.#Considerthemidpointbetweeneachpairofadjacentvaluesasapossiblesplitpoint.#Selecttheminimumexpectedinformationrequirementasthesplit-point.#Split.】3、问题：Whichisthetypicalalgorithmstogeneratetrees?选项：A、ID3B、C4.5C、CARTD、PCA正确答案:【ID3#C4.5#CART】4、问题：Whichoneisrightaboutunderfittingandoverfitting?选项：A、Underfittingmeanspooraccuracybothfortrainingdataandunseensamples.B、Overfittingmeanshighaccuracyfortrainingdatabutpooraccuracyforunseensamples.C、Underfittingimpliesthemodelistoosimplethatweneedtoincreasethemodelcomplexity.D、Overfittingoccurstoomanybranchesthatweneedtodecreasethemodelcomplexity.正确答案:【Underfittingmeanspooraccuracybothfortrainingdataandunseensamples.#Overfittingmeanshighaccuracyfortrainingdatabutpooraccuracyforunseensamples.#Underfittingimpliesthemodelistoosimplethatweneedtoincreasethemodelcomplexity.#Overfittingoccurstoomanybranchesthatweneedtodecreasethemodelcomplexity.】5、问题：Whichoneisrightaboutpre-pruningandpost-pruning?选项：A、Bothofthemaremethodstodealwithoverfittingproblem.B、Pre-pruningdoesnotsplitanodeifthiswouldresultinthegoodnessmeasurefallingbelowathreshold.C、Post-pruningremovesbranchesfroma“fullygrown”tree.D、Thereisnoneedtochooseanappropriatethresholdwhenmakingpre-pruning.正确答案:【Bothofthemaremethodstodealwithoverfittingproblem.#Pre-pruningdoesnotsplitanodeifthiswouldresultinthegoodnessmeasurefallingbelowathreshold.#Post-pruningremovesbranchesfroma“fullygrown”tree.】6、问题：Post-pruninginCARTconsistsofthefollowingprocedure:选项：A、First,considerthecostcomplexityofatree.B、Then,foreachinternalnode,N,computethecostcomplexityofthesubtreeatN.C、AndalsocomputethecostcomplexityofthesubtreeatNifitweretobepruned.D、Atlast,comparethetwovalues.IfpruningthesubtreeatnodeNwouldresultinasmallercostcomplexity,thesubtreeispruned.Otherwise,thesubtreeiskept.正确答案:【First,considerthecostcomplexityofatree.#Then,foreachinternalnode,N,computethecostcomplexityofthesubtreeatN.#AndalsocomputethecostcomplexityofthesubtreeatNifitweretobepruned.#Atlast,comparethetwovalues.IfpruningthesubtreeatnodeNwouldresultinasmallercostcomplexity,thesubtreeispruned.Otherwise,thesubtreeiskept.】7、问题：ThecostcomplexitypruningalgorithmusedinCARTevaluatecostcomplexitybythenumberofleavesinthetree,andtheerrorrate.选项：A、正确B、错误正确答案:【正确】8、问题：GainratioisusedasattributeselectionmeasureinC4.5andtheformulaisGainRatio(A)=Gain(A)/SplitInfo(A).选项：A、正确B、错误正确答案:【正确】9、问题：Ruleiscreatedforeachpartfromitsroottoitsleafnotes.选项：A、正确B、错误正确答案:【正确】10、问题：ID3useinformationgainasitsattributeselectionmeasure.AndtheattributewiththelowestinformationgainischosenasthesplittingattributefornoteN.选项：A、正确B、错误正确答案:【错误】Test51、问题：WhatthefeatureofSVM?选项：A、Extremelyslow,butarehighlyaccurate.B、Muchlesspronetooverfittingthanothermethods.C、Blackboxmodel.D、Provideacompactdescriptionofthelearnedmodel.正确答案:【Extremelyslow,butarehighlyaccurate.#Muchlesspronetooverfittingthanothermethods.#Provideacompactdescriptionofthelearnedmodel.】2、问题：Whichisthetypicalcommonkernel?选项：A、LinearB、PolynomialC、Radialbasisfunction(Gaussiankernel)D、Sigmoidkernel正确答案:【Linear#Polynomial#Radialbasisfunction(Gaussiankernel)#Sigmoidkernel】3、问题：WhatadaptationscanbemadetoallowSVMtodealwithMulticlassClassificationproblem?选项：A、Oneversusrest(OVR).B、Oneversusone(OVO).C、Errorcorrectinginputcodes(ECIC).D、Errorcorrectingoutputcodes(ECOC).正确答案:【Oneversusrest(OVR).#Oneversusone(OVO).#Errorcorrectingoutputcodes(ECOC).】4、问题：What'stheproblemofOVR?选项：A、Sensitivetotheaccuracyoftheconfidencefiguresproducedbytheclassifiers.B、Thescaleoftheconfidencevaluesmaydifferbetweenthebinaryclassifiers.C、Thebinaryclassificationlearnersseeunbalanceddistributions.D、Onlywhentheclassdistributionisbalancedcanbalanceddistributionsattain.正确答案:【Sensitivetotheaccuracyoftheconfidencefiguresproducedbytheclassifiers.#Thescaleoftheconfidencevaluesmaydifferbetweenthebinaryclassifiers.#Thebinaryclassificationlearnersseeunbalanceddistributions.】5、问题：WhichoneisrightabouttheadvantagesofSVM?选项：A、Theyareaccurateinhigh-dimensionalspaces.B、Theyarememoryefficient.C、Thealgorithmisnotproneforover-fittingcomparedtootherclassificationmethod.D、Thesupportvectorsaretheessentialorcriticaltrainingtuples.正确答案:【Theyareaccurateinhigh-dimensionalspaces.#Theyarememoryefficient.#Thealgorithmisnotproneforover-fittingcomparedtootherclassificationmethod.#Thesupportvectorsaretheessentialorcriticaltrainingtuples.】6、问题：Kerneltrickwasusedtoavoidcostlycomputationanddealwithmappingproblems.选项：A、正确B、错误正确答案:【正确】7、问题：ThereisnostructuredwayandnogoldenrulesforsettingtheparametersinSVM.选项：A、正确B、错误正确答案:【正确】8、问题：Errorcorrectingoutputcodes(ECOC)isakindofproblemtransformationtechniques.选项：A、正确B、错误正确答案:【错误】9、问题：Regressionformulasincludingthreetypes:linear,nonlinearandgeneralform.选项：A、正确B、错误正确答案:【正确】10、问题：Ifyouhaveabigdataset,SVMissuitableforefficientcomputation.选项：A、正确B、错误正确答案:【错误】Test61、问题：Whichdescriptionisrighttodescribeoutliers?选项：A、OutlierscausedbymeasurementerrorB、OutliersreflectinggroundtruthC、OutlierscausedbyequipmentfailureD、Outliersneededtobedroppedoutalways正确答案:【Outlierscausedbymeasurementerror#Outliersreflectinggroundtruth#Outlierscausedbyequipmentfailure】2、问题：Whatisapplicationcaseofoutliermining?选项：A、TrafficincidentdetectionB、CreditcardfrauddetectionC、NetworkintrusiondetectionD、Medicalanalysis正确答案:【Trafficincidentdetection#Creditcardfrauddetection#Networkintrusiondetection#Medicalanalysis】3、问题：Whichoneisthemethodtodetectoutliers?选项：A、Statistics-basedapproachB、Distance-basedapproachC、Bulk-basedapproachD、Density-basedapproach正确答案:【Statistics-basedapproach#Distance-basedapproach#Density-basedapproach】4、问题：Howtopicktherightkbyaheuristicmethodfordensity-basedoutlierminingmethod?选项：A、Kshouldbeatleast10toremoveunwantedstatisticalfluctuations.B、Pick10to20appearstoworkwellingeneral.C、Picktheupperboundvalueforkasthemaximumof“closeby”objectsthatcanpotentiallybeglobaloutliers.D、Picktheupperboundvalueforkasthemaximumof“closeby”objectsthatcanpotentiallybelocaloutliers.正确答案:【Kshouldbeatleast10toremoveunwantedstatisticalfluctuations.#Pick10to20appearstoworkwellingeneral.#Picktheupperboundvalueforkasthemaximumof“closeby”objectsthatcanpotentiallybelocaloutliers.】5、问题：Whichoneisrightaboutthreemethodsofoutliermining?选项：A、Statistics-basedapproachissimpleandfastbutdifficulttodealwithperiodicitydataandcategoricaldata.B、Theefficiencyofdistance-basedapproachislowforthegreatdatasetinhighdimensionalspace.C、Distance-basedapproachcannotbeusedinmultidimensionaldataset.D、Density-basedapproachspendslowcostonsearchingneighborhood.正确答案:【Statistics-basedapproachissimpleandfastbutdifficulttodealwithperiodicitydataandcategoricaldata.#Theefficiencyofdistance-basedapproachislowforthegreatdatasetinhighdimensionalspace.】6、问题：Distance-basedoutlierMiningisnotsuitabletodatasetthatdoesnotfitanystandarddistributionmodel.选项：A、正确B、错误正确答案:【错误】7、问题：Statistic-basedmethodneedstorequireknowingthedistributionofthedataandthedistributionparametersinadvance.选项：A、正确B、错误正确答案:【正确】8、问题：Whenidentifyingoutlierswithadiscordancytest,thedatapointisconsideredasanoutlierifitfallswithintheconfidenceinterval.选项：A、正确B、错误正确答案:【错误】9、问题：MahalanobisDistanceaccountsfortherelativedispersionsandinherentcorrelationsamongvectorelements,whichisdifferentfromEuclideanDistance.选项：A、正确B、错误正确答案:【正确】10、问题：Anoutlierisadataobjectthatdeviatessignificantlyfromtherestoftheobjects,asifitweregeneratedbyadifferentmechanism.选项：A、正确B、错误正确答案:【正确】Test71、问题：Howtodealwithimbalanceddatain2-classclassification?选项：A、OversamplingB、UndersamplingC、Threshold-movingD、Ensembletechniques正确答案:【Oversampling#Undersampling#Threshold-moving#Ensembletechniques】2、问题：Whichoneisrightwhendealingwiththeclass-imbalanceproblem？选项：A、Oversamplingworksbydecreasingthenumberofminoritypositivetuples.B、Undersamplingworksbyincreasingthenumberofmajoritynegativetuples.C、Smotealgorithmaddssynthetictuplesthatareclosetotheminoritytuplesintuplespace.D、Threshold-movingandensemblemethodswereempiricallyobservedtooutperformoversamplingandundersampling.正确答案:【Smotealgorithmaddssynthetictuplesthatareclosetotheminoritytuplesintuplespace.#Threshold-movingandensemblemethodswereempiricallyobservedtooutperformoversamplingandundersampling.】3、问题：Whichstepisnecessarywhenconstructinganensemblemodel?选项：A、CreatingmultipledatasetB、ConstructingasetofclassifiersfromthetrainingdataC、CombiningpredictionsmadebymultipleclassifierstoobtainfinalclasslabelD、Findthebestperformingpredictionstoobtainfinalclasslabel正确答案:【Creatingmultipledataset#Constructingasetofclassifiersfromthetrainingdata#Combiningpredictionsmadebymultipleclassifierstoobtainfinalclass