[下载][原创]SAS官方培训教程－2005 SAS official Training Course(dataming)-经管之家官网！

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10个PPT，每章一个PPT

Table of Contents

Course Description.............................................................................................................. v

Prerequisites...................................................................................................................... vi

General Conventions.......................................................................................................... vii

Chapter 1 Introduction to Data Mining.................................................................. 1-1

1.1 Background............................................................................................................. 1-3

1.2 SEMMA............................................................................................................... 1-15

Chapter 2 Predictive Modeling Using Decision Trees....................................... 2-1

2.1 Introduction to Enterprise Miner............................................................................... 2-3

2.2 Modeling Issues and Data Difficulties..................................................................... 2-20

2.3 Introduction to Decision Trees................................................................................ 2-37

2.4 Building and Interpreting Decision Trees.................................................................. 2-46

Chapter 3 Predictive Modeling Using Regression............................................. 3-1

3.1 Introduction to Regression........................................................................................ 3-3

3.2 Regression in Enterprise Miner................................................................................. 3-8

Chapter 4 Variable Selection.................................................................................. 4-1

4.1 Variable Selection and Enterprise Miner.................................................................... 4-3

Chapter 5 Predictive Modeling Using Neural Networks.................................... 5-1

5.1 Introduction to Neural Networks............................................................................... 5-3

5.2 Visualizing Neural Networks.................................................................................... 5-9

Chapter 6 Model Evaluation and Implementation................................................ 6-1

6.1 Model Evaluation: Comparing Candidate Models........................................................ 6-3

6.2 Ensemble Models................................................................................................... 6-10

6.3 Model Implementation: Generating and Using Score Code........................................ 6-16

Chapter 7 Cluster Analysis...................................................................................... 7-1

7.1 K-Means Cluster Analysis........................................................................................ 7-3

7.2 Self-Organizing Maps............................................................................................. 7-24

Chapter 8 Association and Sequence Analysis.................................................... 8-1

8.1 Introduction to Association Analysis.......................................................................... 8-3

8.2 Interpretation of Association and Sequence Analysis.................................................. 8-7

8.3 Dissociation Analysis (Self-Study)........................................................................... 8-24

Appendix A References............................................................................................. A-1

A.1 References............................................................................................................ A-3

Appendix B Index....................................................................................................... B-1

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