Data Mining: Concepts and Techniques
3.2.7 A Starnet Query Model for Querying Multidimensional Databases 126 3.3 Data Warehouse Architecture 127 3.3.1 Steps for the Design and Construction of Data Warehouses 128 3.3.2 A Three-Tier Data Warehouse Architecture 130 3.3.3 Data Warehouse Back-End Tools and Utilities 134 3.3.4 Metadata Repository 134 3.3.5 Types of OLAP Servers: ROLAP ...
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Data Mining: Concepts and Techniques
hanj.cs.illinois.edu2.4 Data Integration and Transformation 67 2.4.1 Data Integration 67 2.4.2 Data Transformation 70 2.5 Data Reduction 72 2.5.1 Data Cube Aggregation 73 2.5.2 Attribute Subset Selection 75 2.5.3 Dimensionality Reduction 77 2.5.4 Numerosity Reduction 80 2.6 Data Discretization and Concept Hierarchy Generation 86
2.4.8 Kullback-Leibler Divergence
hanj.cs.illinois.edufrom an observed frequency distribution, as illustrate in the following example. Example 2.24. Computing the KL Divergence by Smoothing. Sup-pose there are two sample distributions P and Q as follows: P: (a: 3/5,b:
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