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【书名】 Applied Analytics Using SAS® Enterprise Miner™ 5 Course Notes
【作者】SAS Publishing
【出版社】SAS Institute
【版本】1st
【出版日期】2007
【文件格式】PDF
【文件大小】17.6MB
【页数】597
【ISBN出版号】978-1-59994-515-6
【资料类别】笔记
【市面定价】不清楚
【扫描版还是影印版】清晰，非扫描，也非影印
【是否缺页】无
【关键词】SAS Enterprise Miner ,Data Mining
【内容简介】经典的SAS Course Notes, SAS 内部的资料，压缩后11.1MB。
【目录】
Table of Contents
Course Description....................................................................................................................vii
Prerequisites ..............................................................................................................................viii
Chapter 1 Introduction .......................................................................................... 1-1
1.1 Introduction to SAS Enterprise Miner .............................................................................1-3
Chapter 2 Accessing and Assaying Prepared Data ............................................ 2-1
2.1 Introduction.....................................................................................................................2-3
2.2 Creating a SAS Enterprise Miner Project and Diagram...................................................2-7
2.3 Defining a Data Source..................................................................................................2-13
2.4 Exploring a Data Source ................................................................................................2-21
2.5 Chapter Summary ..........................................................................................................2-49
Chapter 3 Introduction to Pattern Discovery....................................................... 3-1
3.1 Introduction.....................................................................................................................3-3
3.2 Cluster Analysis ...............................................................................................................3-9
3.3 Market Basket Analysis (Self-Study).............................................................................3-56
3.4 Chapter Summary ..........................................................................................................3-80
3.5 Solutions to Exercises....................................................................................................3-82
Chapter 4 Introduction to Predictive Modeling: Decision Trees........................ 4-1
4.1 Introduction.....................................................................................................................4-3
4.2 Cultivating Decision Trees.............................................................................................4-36
4.3 Pruning a Decision Tree.................................................................................................4-60
4.4 Autonomous Tree Growth..............................................................................................4-87
4.5 Autonomous Tree Growth Options (Self-Study) ...........................................................4-92
4.6 Chapter Summary ........................................................................................................4-105
4.7 Solutions to Exercises..................................................................................................4-107
Chapter 5 Introduction to Predictive Modeling: Regressions ........................... 5-1
5.1 Introduction.....................................................................................................................5-3
5.2 Selecting Regression Inputs...........................................................................................5-24
5.3 Optimizing Regression Complexity...............................................................................5-33
5.4 Transforming Inputs.......................................................................................................5-40
5.5 Categorical Inputs ..........................................................................................................5-52
5.6 Polynomial Regressions.................................................................................................5-60
5.7 Chapter Summary ..........................................................................................................5-76
5.8 Solutions to Exercises....................................................................................................5-78
Chapter 6 Introduction to Predictive Modeling: Neural Networks and
Other Modeling Tools........................................................................... 6-1
6.1 Introduction.....................................................................................................................6-3
6.2 Input Selection ...............................................................................................................6-18
6.3 Stopped Training............................................................................................................6-22
6.4 Other Modeling Tools (Self-Study) ...............................................................................6-43
6.5 Chapter Summary ..........................................................................................................6-51
6.6 Solutions to Exercises....................................................................................................6-52
Chapter 7 Model Assessment ............................................................................... 7-1
7.1 Introduction.....................................................................................................................7-3
7.2 Model Fit Statistics ..........................................................................................................7-4
7.3 Statistical Graphics ........................................................................................................7-10
7.4 Adjusting for Separate Sampling ...................................................................................7-27
7.5 Profit Matrices ...............................................................................................................7-40
7.6 Chapter Summary ..........................................................................................................7-53
7.7 Solutions to Exercises....................................................................................................7-55
Chapter 8 Model Implementation.......................................................................... 8-1
8.1 Introduction.....................................................................................................................8-3
8.2 Internally Scored Data Sets..............................................................................................8-4
8.3 Score Code Modules......................................................................................................8-16
8.4 Chapter Summary ..........................................................................................................8-24
Chapter 9 Special Topics....................................................................................... 9-1
9.1 Introduction.....................................................................................................................9-3
9.2 Ensemble Models.............................................................................................................9-4
9.3 Variable Selection ............................................................................................................9-9
9.4 Categorical Input Consolidation ....................................................................................9-16
9.5 Surrogate Models...........................................................................................................9-22
Appendix A Case Studies........................................................................................ A-1
A.1 Banking Segmentation Case Study .................................................................................A-3
A.2 Web Site Usage Associations Case Study .....................................................................A-15
A.3 Credit Risk Case Study .................................................................................................A-20
A.4 Enrollment Management Case Study............................................................................A-36
Appendix B References ........................................................................................... B-1
B.1 References...................................................................................................................... B-3
Appendix C Index ..................................................................................................... C-1
【原创书评】这本书的内容还算比较实用，较好地结合了SAS和数据挖掘，里面图文并茂，是不可多得的好教程。