一、Introduction
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1、Major Issues in Data Mining
User Interaction
Presentation and visualization of data mining results : Efficiency and Scalability
Diversity of data types: complex types of data; Mining dynamic, networked, and global data repositories
Data mining and society: Privacy-preserving; Social impacts of data mining; Invisible data mining
二、Getting to Know Your Data
1、Type of Data Sets
Record：Relational records; Data matrix; Text documents; Transaction data
2、 Important Characteristics of Structured Data
Dimensionality: Curse of dimensionality;
Sparsity: Only presnce counts;
Resolution: Patterns depend on the scale;
Distribution: Centrality and dispersion
3、Attribute (dimensions features varibles)
types: Nominal; Ordinal; Binary: Symmetric, Asymmetric; Quantity: Interval, Ratio
Discrete Attribute
Continuous Attribute
4、Basic Statistical Descriptions of Data
Data dispersion characterstics: median, max, min, quantiles, outliers, variance
mean：Weighted arithmetic mean; Trimmed mean
5、Measuring the Dispersion of Data
Quartiles：Q1(25th percentile)、Q3（75th percentile）
Inter-quartile range（IQR）：最当中的50%
Five number summary ：min、Q1，median、Q3、max
6、Graphic Displays of Basic Statistcal Description
7、五种数据分析图
boxplot analysis：
Histogram Analysis
Quantile Plot
Quantile-Quantile Plot（Q-Q Plot）
Scatter Plot
8、 Categorization of visualization methods
Pixel-orirnted:
① The m dimension values of a record are mapped to m pixels at the corresponding positions in the windows
② The color of pixel reflect corresponding values
③ For a dataset of m dimensions, create m windows on the screen, one for each dimension
Parallel Coordinates：用于画k维属性的图。
Geometric projection
Icon-based
Chenoff Faces：
Stick Figures：A 5-piece stick figure
Hierarchical:
Dimensional Stacking
Worlds-within-Worlds
Tree-Map
Infocube
8、Similarity and Dissimilarity
① Data matrix
② Dissimilarity matrix
Proximity Measure of Nominal Attributes
a. Simple matching
b. Use a large number of binary attributes: create a new binary attribute for each
Standardizing Numeric Data: z-score
