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1、.JI';iPANG-NINGTANMichiganStateUniversityMICHAELSTEINBACHUniversityofMinnesotaVIPINKUMARUniversityofMinnesotaandArmyHighPerformanceComputingResearchCenter~TT?.BostonSanFr.mciscoNewYorkLondonTorontoSydneyTokyoSingaporeMadridMexicoCicyMunichParisC?pcTownHongKongMo
2、ntrealxivContents2.4.5ExamplesofProximityMeasures.............732.4.6IssuesinProximityCalculation..............802.4.7SelectingtheRightProximityMeasure..........832.5BibliographicNotes.........................842.6Exercises..............................88Contents3
3、ExploringData973.1TheIrisDataSet..........................983.2SummaryStatistics.........................98Prefacevii3.2.1FrequenciesandtheMode.................993.2.2Percentiles.........................1001Introduction13.2.3MeasuresofLocation:MeanandMedian.......
4、.1011.1WhatIsDataMining?.......................23.2.4MeasuresofSpread:RangeandVariance........1021.2MotivatingChallenges.......................43.2.5MultivariateSummaryStatistics.............1041.3TheOriginsofDataMining....................63.2.6OtherWaystoSummariz
5、etheData...........1051.4DataMiningTasks.........................73.3Visualization............................1051.5ScopeandOrganizationoftheBook...............113.3.1MotivationsforVisualization...............1051.6BibliographicNotes.........................133.3.
6、2GeneralConcepts......................1061.7Exercises..............................163.3.3Techniques.........................1103.3.4VisualizingHigher-DimensionalData...........1242Data193.3.5Do’sandDon’ts......................1302.1TypesofData....................
7、........223.4OLAPandMultidimensionalDataAnalysis...........1312.1.1AttributesandMeasurement...............233.4.1RepresentingIrisDataasaMultidimensionalArray..1312.1.2TypesofDataSets.....................293.4.2MultidimensionalData:TheGeneralCase........1332.2DataQ
8、uality............................363.4.3AnalyzingMultidimensionalData............1352.2.1MeasurementandDataCollectionIssues.........373.4.4FinalComment
