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Lecture Notes for Chapter 3 Introduction to Data Mining

Techniques Used In Data ExplorationSummary StatisticsMeasures of Location: Mean and MedianMeasures of Spread: Range and VarianceVisualizationRepresentationArrangementSelectionTwo-Dimensional HistogramsVisualization Techniques: Scatter PlotsVisualization Techniques: Matrix PlotsVisualization Techniques: Parallel CoordinatesOther Visualization TechniquesOLAPCreating a Multidimensional ArrayExample: Iris dataOLAP Operations: Data CubeOLAP Operations: Slicing and DicingOLAP Operations: Roll-up and Drill-downIn EDA, as originally defined by Tukey The focus was on visualization Clustering and anomaly detection were viewed as exploratory techniques In data mining, clustering and anomaly detection are major areas of interest, and not thought of as just exploratory In our discussion of data exploration, we focus on Summary statistics Visualization Online A...标记:Introduction To Data MiningPDF Data MiningData Mining Lecture Notes标记:Introduction To Data MiningSteinbach, Wartburgkreis标记:Introduction To Data MiningPDF Data Mining