[下载][原创]SAS官方培训教程－2005 SAS official Training Course(dataming)

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<P>[UseMoney=8][/UseMoney] </P>
<P>10个PPT，每章一个PPT</P>
<P>Table of Contents<o:p></o:p></P>
<P>Course Description.............................................................................................................. v<o:p></o:p></P>
<P>Prerequisites...................................................................................................................... vi<o:p></o:p></P>
<P>General Conventions.......................................................................................................... vii<o:p></o:p></P>
<P>Chapter 1       Introduction to Data Mining.................................................................. 1-1<o:p></o:p></P>
<P>1.1    Background............................................................................................................. 1-3<o:p></o:p></P>
<P>1.2    SEMMA............................................................................................................... 1-15<o:p></o:p></P>
<P>Chapter 2       Predictive Modeling Using Decision Trees....................................... 2-1<o:p></o:p></P>
<P>2.1    Introduction to Enterprise Miner............................................................................... 2-3<o:p></o:p></P>
<P>2.2    Modeling Issues and Data Difficulties..................................................................... 2-20<o:p></o:p></P>
<P>2.3    Introduction to Decision Trees................................................................................ 2-37<o:p></o:p></P>
<P>2.4    Building and Interpreting Decision Trees.................................................................. 2-46<o:p></o:p></P>
<P>Chapter 3       Predictive Modeling Using Regression............................................. 3-1<o:p></o:p></P>
<P>3.1    Introduction to Regression........................................................................................ 3-3<o:p></o:p></P>
<P>3.2    Regression in Enterprise Miner................................................................................. 3-8<o:p></o:p></P>
<P>Chapter 4       Variable Selection.................................................................................. 4-1<o:p></o:p></P>
<P>4.1    Variable Selection and Enterprise Miner.................................................................... 4-3<o:p></o:p></P>
<P>Chapter 5       Predictive Modeling Using Neural Networks.................................... 5-1<o:p></o:p></P>
<P>5.1    Introduction to Neural Networks............................................................................... 5-3<o:p></o:p></P>
<P>5.2    Visualizing Neural Networks.................................................................................... 5-9<o:p></o:p></P>
<P>Chapter 6       Model Evaluation and Implementation................................................ 6-1<o:p></o:p></P>
<P>6.1    Model Evaluation: Comparing Candidate Models........................................................ 6-3<o:p></o:p></P>
<P>6.2    Ensemble Models................................................................................................... 6-10<o:p></o:p></P>
<P>6.3    Model Implementation: Generating and Using Score Code........................................ 6-16<o:p></o:p></P>
<P>Chapter 7       Cluster Analysis...................................................................................... 7-1<o:p></o:p></P>
<P>7.1    K-Means Cluster Analysis........................................................................................ 7-3<o:p></o:p></P>
<P>7.2    Self-Organizing Maps............................................................................................. 7-24<o:p></o:p></P>
<P>Chapter 8       Association and Sequence Analysis.................................................... 8-1<o:p></o:p></P>
<P>8.1    Introduction to Association Analysis.......................................................................... 8-3<o:p></o:p></P>
<P>8.2    Interpretation of Association and Sequence Analysis.................................................. 8-7<o:p></o:p></P>
<P>8.3    Dissociation Analysis (Self-Study)........................................................................... 8-24<o:p></o:p></P>
<P>Appendix A     References............................................................................................. A-1<o:p></o:p></P>
<P>A.1   References............................................................................................................ A-3<o:p></o:p></P>
<P>Appendix B    Index....................................................................................................... B-1<o:p></o:p></P>
<P><FONT size=3></FONT></P> 117941.rar (2.47 MB, 需要: 8 个论坛币) 本附件包括：

• Introduction to Data Mining.ppt
• Model Evaluation and Implementation.ppt
• Predictive Modeling Using Decision Trees.ppt
• Predictive Modeling Using Neural Networks.ppt
• Predictive Modeling Using Regression.ppt
• References.ppt
• Variable Selection.ppt
• Index.ppt
• Association and Sequence Analysis.ppt
• Cluster Analysis.ppt
• ExerciseHandout.pdf

2007-5-18 11:47:00 上传

[下载][原创]SAS官方培训教程－2005 SAS official Training Course(dataming)
需要: 8 个论坛币  [购买]

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[此贴子已经被作者于2007-5-18 11:49:06编辑过]

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关键词：Training dataming Official taming Course SAS Training Course Official dataming

No download link? <br>plz repair it <br><br>

I can not download file, even though I already paid you.

<P>不好意思，现在修复好了，在附件中</P>

<P>楼上的几个消息联系我发到你们信箱中去，不好意思</P>

<P><FONT size=1>内容介绍：</FONT></P>
<P>Course Description：This course provides extensive hands-on experience with Enterprise Miner and covers the basic skills required to assemble analyses using the rich tool set of Enterprise Miner. It also covers concepts fundamental to understanding and successfully applying data mining methods. After completing this course, you should be able to </P>
<P>• identify business problems and determine suitable analytical methods<br>• understand the difficulties presented by massive, opportunistic data<br>• assemble analysis-flow diagrams<br>• prepare data for analysis, including partitioning data and imputing missing values<br>• train, assess, and compare regression models, neural networks, and decision trees<br>• perform cluster analysis<br>• perform association and sequence analysis.</P>
<P><FONT color=#ff3300>Prerequisites<br>Before selecting this course, you should be familiar with Microsoft Windows and Windows-based software. No previous SAS software experience is necessary</FONT></P>
<P>总共10个PPT，每章一个PPT，还有一个习题与解答Exercise Handout（58页pdf文件）</P>
<P>Table of Contents<O:P></O:P></P>
<P>Course Description.............................................................................................................. v<O:P></O:P></P>
<P>Prerequisites...................................................................................................................... vi<O:P></O:P></P>
<P>General Conventions.......................................................................................................... vii<O:P></O:P></P>
<P>Chapter 1       Introduction to Data Mining.................................................................. 1-1<O:P></O:P></P>
<P>1.1    Background............................................................................................................. 1-3<O:P></O:P></P>
<P>1.2    SEMMA............................................................................................................... 1-15<O:P></O:P></P>
<P>Chapter 2       Predictive Modeling Using Decision Trees....................................... 2-1<O:P></O:P></P>
<P>2.1    Introduction to Enterprise Miner............................................................................... 2-3<O:P></O:P></P>
<P>2.2    Modeling Issues and Data Difficulties..................................................................... 2-20<O:P></O:P></P>
<P>2.3    Introduction to Decision Trees................................................................................ 2-37<O:P></O:P></P>
<P>2.4    Building and Interpreting Decision Trees.................................................................. 2-46<O:P></O:P></P>
<P>Chapter 3       Predictive Modeling Using Regression............................................. 3-1<O:P></O:P></P>
<P>3.1    Introduction to Regression........................................................................................ 3-3<O:P></O:P></P>
<P>3.2    Regression in Enterprise Miner................................................................................. 3-8<O:P></O:P></P>
<P>Chapter 4       Variable Selection.................................................................................. 4-1<O:P></O:P></P>
<P>4.1    Variable Selection and Enterprise Miner.................................................................... 4-3<O:P></O:P></P>
<P>Chapter 5       Predictive Modeling Using Neural Networks.................................... 5-1<O:P></O:P></P>
<P>5.1    Introduction to Neural Networks............................................................................... 5-3<O:P></O:P></P>
<P>5.2    Visualizing Neural Networks.................................................................................... 5-9<O:P></O:P></P>
<P>Chapter 6       Model Evaluation and Implementation................................................ 6-1<O:P></O:P></P>
<P>6.1    Model Evaluation: Comparing Candidate Models........................................................ 6-3<O:P></O:P></P>
<P>6.2    Ensemble Models................................................................................................... 6-10<O:P></O:P></P>
<P>6.3    Model Implementation: Generating and Using Score Code........................................ 6-16<O:P></O:P></P>
<P>Chapter 7       Cluster Analysis...................................................................................... 7-1<O:P></O:P></P>
<P>7.1    K-Means Cluster Analysis........................................................................................ 7-3<O:P></O:P></P>
<P>7.2    Self-Organizing Maps............................................................................................. 7-24<O:P></O:P></P>
<P>Chapter 8       Association and Sequence Analysis.................................................... 8-1<O:P></O:P></P>
<P>8.1    Introduction to Association Analysis.......................................................................... 8-3<O:P></O:P></P>
<P>8.2    Interpretation of Association and Sequence Analysis.................................................. 8-7<O:P></O:P></P>
<P>8.3    Dissociation Analysis (Self-Study)........................................................................... 8-24<O:P></O:P></P>
<P>Appendix A     References............................................................................................. A-1<O:P></O:P></P>
<P>A.1   References............................................................................................................ A-3<O:P></O:P></P>
<P>Appendix B    Index....................................................................................................... B-1<O:P></O:P></P>

[此贴子已经被作者于2007-5-18 12:01:36编辑过]

看目录还不错买了

<P>这个资料很不错,给予重奖!</P>

多谢版主：）

是上海sas高级培训的教程