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

【MOOC】交通数据挖掘技术（DataMiningforTransportation）-东南大学中国大学慕课MOOC答案Test11、【单选题】WhichoneisnotthedescriptionofDatamining?本题答案：【Appropriatestatisticalanalysismethodstoanalyzethedatacollected】2、【单选题】Whichonedescribestherightprocessofknowledgediscovery?本题答案：【Selection-Preprocessing-Transformation-Datamining-Interpretation/Evaluation】3、【单选题】WhichoneisnotbelongtotheprocessofKDD?本题答案：【Datadescription】4、【单选题】Whichoneisnottherightalternativenameofdatamining?本题答案：【Dataharvesting】5、【单选题】Whichoneisnotthenominalvariables?本题答案：【Age】6、【单选题】Whichoneiswrongaboutclassificationandregression?本题答案：【Wecanconstructclassificationmodels(functions)withoutsometrainingexamples.】7、【单选题】Whichoneiswrongaboutclusteringandoutliers?本题答案：【Clusteringbelongstosupervisedlearning.】8、【单选题】Aboutdataprocess,whichoneiswrong?本题答案：【Whenmakingdataclassification,wepredictcategoricallabelsexcludingunorderedone.】9、【判断题】Outlierminingsuchasdensitybasedmethodbelongstosupervisedlearning.本题答案：【错误】10、【判断题】Supportvectormachinescanbeusedforclassificationandregression.本题答案：【正确】Test21、【单选题】Whichisnotthereasonweneedtopreprocessthedata?本题答案：【tomakeresultmeetourhypothesis】2、【单选题】Whichisnotthemajortasksindatapreprocessing?本题答案：【Transition】3、【单选题】HowtoconstructnewfeaturespacebyPCA?本题答案：【NewfeaturespacebyPCAisconstructedbyeliminatingtheweakcomponentstoreducethesizeofthedata.】4、【单选题】Whichoneiswrongaboutmethodsfordiscretization?本题答案：【Clusteringanalysisonlybelongstotop-downsplit.】5、【单选题】WhichoneiswrongaboutEqual-width(distance)partitioningandEqual-depth(frequency)partitioning?本题答案：【Theintervaloftheformeroneisnotequal.】6、【单选题】Whichoneiswrongwaytonormalizedata?本题答案：【Simplescaling】7、【多选题】Whicharetherightwaytofillinmissingvalues?本题答案：【Smartmean#Probablevalue#Ignore】8、【多选题】Whicharetherightwaytohandlenoisedata?本题答案：【Regression#Cluster#WT#Manual】9、【多选题】Whichoneisrightaboutwavelettransforms?本题答案：【TheDWTdecomposeseachsegmentoftimeseriesviathesuccessiveuseoflow-passandhigh-passfilteringatappropriatelevels.#Wavelettransformscanbeusedforreducingdataandsmoothingdata.】10、【多选题】Whicharethecommonusedwaystosampling?本题答案：【Simplerandomsamplewithoutreplacement#Simplerandomsamplewithreplacement#Stratifiedsample#Clustersample】11、【判断题】Discretizationmeansdividingtherangeofacontinuousattributeintointervals.本题答案：【正确】Test31、【单选题】What'sthedifferencebetweeneagerlearnerandlazylearner?本题答案：【Eagerlearnerswouldgenerateamodelforclassificationwhilelazylearnerwouldnot.】2、【多选题】HowtochoosetheoptimalvalueforK?本题答案：【Cross-validationcanbeusedtodetermineagoodvaluebyusinganindependentdatasettovalidatetheKvalues.#LowvaluesforK(likek=1ork=2)canbenoisyandsubjecttotheeffectofoutliers.#Historically,theoptimalKformostdatasetshasbeenbetween3-10.】3、【多选题】What’sthemajorcomponentsinKNN?本题答案：【Howtomeasuresimilarity?#Howtochoosek?#Howareclasslabelsassigned?】4、【多选题】WhichoneofthefollowingwayscanbeusedtoobtainattributeweightforAttribute-WeightedKNN?本题答案：【Priorknowledge/experience.#PCA,FA(Factoranalysismethod).#Informationgain.#Gradientdescent,simplexmethodsandgeneticalgorithm.】5、【判断题】AtlearningstageKNNwouldfindtheKclosestneighborsandthendecideclassifyKidentifiednearestlabel.本题答案：【错误】6、【判断题】AtclassificationstageKNNwouldstoreallinstanceorsometypicalofthem.本题答案：【错误】7、【判断题】Normalizingthedatacansolvetheproblemthatdifferentattributeshavedifferentvalueranges.本题答案：【正确】8、【判断题】ByEuclideandistanceorManhattandistance,wecancalculatethedistancebetweentwoinstances.本题答案：【正确】9、【判断题】DatanormalizationbeforeMeasureDistancecanavoiderrorscausedbydifferentdimensions,self-variations,orlargenumericaldifferences.本题答案：【正确】10、【判断题】Thewaytoobtaintheregressionforanewinstancefromtheknearestneighborsistocalculatetheaveragevalueofkneighbors.本题答案：【正确】11、【判断题】Thewaytoobtaintheclassificationforanewinstancefromtheknearestneighborsistocalculatethemajorityclassofkneighbors.本题答案：【正确】12、【判断题】ThewaytoobtaininstanceweightforDistance-WeightedKNNistocalculatethereciprocalofthedistancesquaredbetweenobjectandneighbors.本题答案：【正确】Test41、【多选题】Whichdescriptionisrightaboutnodesindecisiontree?本题答案：【Internalnodestestthevalueofparticularfeatures#Leafnodesspecifytheclass】2、【多选题】ComputinginformationgainforcontinuousvalueattributewhenusingID3consistsofthefollowingprocedure:本题答案：【SortthevalueAinincreasingorder.#Considerthemidpointbetweeneachpairofadjacentvaluesasapossiblesplitpoint.#Selecttheminimumexpectedinformationrequirementasthesplit-point.#Split.】3、【多选题】Whichisthetypicalalgorithmstogeneratetrees?本题答案：【ID3#C4.5#CART】4、【多选题】Whichoneisrightaboutunderfittingandoverfitting?本题答案：【Underfittingmeanspooraccuracybothfortrainingdataandunseensamples.#Overfittingmeanshighaccuracyfortrainingdatabutpooraccuracyforunseensamples.#Underfittingimpliesthemodelistoosimplethatweneedtoincreasethemodelcomplexity.#Overfittingoccurstoomanybranchesthatweneedtodecreasethemodelcomplexity.】5、【多选题】Whichoneisrightaboutpre-pruningandpost-pruning?本题答案：【Bothofthemaremethodstodealwithoverfittingproblem.#Pre-pruningdoesnotsplitanodeifthiswouldresultinthegoodnessmeasurefallingbelowathreshold.#Post-pruningremovesbranchesfroma“fullygrown”tree.】6、【多选题】Post-pruninginCARTconsistsofthefollowingprocedure:本题答案：【First,considerthecostcomplexityofatree.#Then,foreachinternalnode,N,computethecostcomplexityofthesubtreeatN.#AndalsocomputethecostcomplexityofthesubtreeatNifitweretobepruned.#Atlast,comparethetwovalues.IfpruningthesubtreeatnodeNwouldresultinasmallercostcomplexity,thesubtreeispruned.Otherwise,thesubtreeiskept.】7、【判断题】ThecostcomplexitypruningalgorithmusedinCARTevaluatecostcomplexitybythenumberofleavesinthetree,andtheerrorrate.本题答案：【正确】8、【判断题】GainratioisusedasattributeselectionmeasureinC4.5andtheformulaisGainRatio(A)=Gain(A)/SplitInfo(A).本题答案：【正确】9、【判断题】Ruleiscreatedforeachpartfromitsroottoitsleafnotes.本题答案：【正确】10、【判断题】ID3useinformationgainasitsattributeselectionmeasure.AndtheattributewiththelowestinformationgainischosenasthesplittingattributefornoteN.本题答案：【错误】Test51、【多选题】WhatthefeatureofSVM?本题答案：【Extremelyslow,butarehighlyaccurate.#Muchlesspronetooverfittingthanothermethods.#Provideacompactdescriptionofthelearnedmodel.】2、【多选题】Whichisthetypicalcommonkernel?本题答案：【Linear#Polynomial#Radialbasisfunction(Gaussiankernel)#Sigmoidkernel】3、【多选题】WhatadaptationscanbemadetoallowSVMtodealwithMulticlassClassificationproblem?本题答案：【Oneversusrest(OVR).#Oneversusone(OVO).#Errorcorrectingoutputcodes(ECOC).】4、【多选题】What'stheproblemofOVR?本题答案：【Sensitivetotheaccuracyoftheconfidencefiguresproducedbytheclassifiers.#Thescaleoftheconfidencevaluesmaydifferbetweenthebinaryclassifiers.#Thebinaryclassificationlearnersseeunbalanceddistributions.】5、【多选题】WhichoneisrightabouttheadvantagesofSVM?本题答案：【Theyareaccurateinhigh-dimensionalspaces.#Theyarememoryefficient.#Thealgorithmisnotproneforover-fittingcomparedtootherclassificationmethod.#Thesupportvectorsaretheessentialorcriticaltrainingtuples.】6、【判断题】Kerneltrickwasusedtoavoidcostlycomputationanddealwithmappingproblems.本题答案：【正确】7、【判断题】ThereisnostructuredwayandnogoldenrulesforsettingtheparametersinSVM.本题答案：【正确】8、【判断题】Errorcorrectingoutputcodes(ECOC)isakindofproblemtransformationtechniques.本题答案：【错误】9、【判断题】Regressionformulasincludingthreetypes:linear,nonlinearandgeneralform.本题答案：【正确】10、【判断题】Ifyouhaveabigdataset,SVMissuitableforefficientcomputation.本题答案：【错误】Test61、【多选题】Whichdescriptionisrighttodescribeoutliers?本题答案：【Outlierscausedbymeasurementerror#Outliersreflectinggroundtruth#Outlierscausedbyequipmentfailure】2、【多选题】Whatisapplicationcaseofoutliermining?本题答案：【Trafficincidentdetection#Creditcardfrauddetection#Networkintrusiondetection#Medicalanalysis】3、【多选题】Whichoneisthemethodtodetectoutliers?本题答案：【Statistics-basedapproach#Distance-basedapproach#Density-basedapproach】4、【多选题】Howtopicktherightkbyaheuristicmethodfordensity-basedoutlierminingmethod?本题答案：【Kshouldbeatleast10toremoveunwantedstatisticalfluctuations.#Pick10to20appearstoworkwellingeneral.#Picktheupperboundvalueforkasthemaximumof“closeby”objectsthatcanpotentiallybelocaloutliers.】5、【多选题】Whichoneisrightaboutthreemethodsofoutliermining?本题答案：【Statistics-basedapproachissimpleandfastbutdifficulttodealwithperiodicitydataandcategoricaldata.#Theefficiencyofdistance-basedapproachislowforthegreatdatasetinhighdimensionalspace.】6、【判断题】Distance-basedoutlierMiningisnotsuitabletodatasetthatdoesnotfitanystandarddistributionmodel.本题答案：【错误】7、【判断题】Statistic-basedmethodneedstorequireknowingthedistributionofthedataandthedistributionparametersinadvance.本题答案：【正确】8、【判断题】Whenidentifyingoutlierswithadiscordancytest,thedatapointisconsideredasanoutlierifitfallswithintheconfidenceinterval.本题答案：【错误】9、【判断题】MahalanobisDistanceaccountsfortherelativedispersionsandinherentcorrelationsamongvectorelements,whichisdifferentfromEuclideanDistance.本题答案：【正确】10、【判断题】Anoutlierisadataobjectthatdeviatessignificantlyfromtherestoftheobjects,asifitweregeneratedbyadifferentmechanism.本题答案：【正确】Test71、【多选题】Howtodealwithimbalanceddatain2-classclassification?本题答案：【Oversampling#Undersampling#Threshold-moving#Ensembletechniques】2、【多选题】Whichoneisrightwhendealingwiththeclass-imbalanceproblem？本题答案：【Smotealgorithmaddssynthetictuplesthatareclosetotheminoritytuplesintuplespace.#Threshold-movingandensemblemethodswereempiricallyobservedtooutperformoversamplingandundersampling.】3、【多选题】Whichstepisnecessarywhenconstructinganensemblemodel?本题答案：【Creatingmultipledataset#Constructingasetofclassifiersfromthetrainingdata#Combiningpredictionsmadebymultipleclassifierstoobtainfinalclasslabel】4、【判断题】Ensemblestendtoyieldbetterresultswhenthereisasignificantdiversityamongthebasemodels.本题答案：【正确】5、【判断题】EnsemblemethodcannotparallelizablebecausenoteverybaseclassifiercanbeallocatedtoadifferentCPU.本题答案：【错误】6、【判断题】Togeneratethesingleclassifier,differentmodelmaybeusedtodealwithdifferentdatasubset.本题答案：【正确】7、【判断题】Inrandomforest,usingar