Data Preparation for Data Mining Using SAS (Google eBook)

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Morgan Kaufmann, Jul 27, 2010 - Computers - 424 pages
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Are you a data mining analyst, who spends up to 80% of your time assuring data quality, then preparing that data for developing and deploying predictive models? And do you find lots of literature on data mining theory and concepts, but when it comes to practical advice on developing good mining views find little “how to information? And are you, like most analysts, preparing the data in SAS?

This book is intended to fill this gap as your source of practical recipes. It introduces a framework for the process of data preparation for data mining, and presents the detailed implementation of each step in SAS. In addition, business applications of data mining modeling require you to deal with a large number of variables, typically hundreds if not thousands. Therefore, the book devotes several chapters to the methods of data transformation and variable selection.

FEATURES
* A complete framework for the data preparation process, including implementation details for each step.
* The complete SAS implementation code, which is readily usable by professional analysts and data miners.
* A unique and comprehensive approach for the treatment of missing values, optimal binning, and cardinality reduction.
* Assumes minimal proficiency in SAS and includes a quick-start chapter on writing SAS macros.
* CD includes dozens of SAS macros plus the sample data and the program for the book's case study.
  

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Contents

CHAPTER 1 INTRODUCTION
1
CHAPTER 2 TASKS AND DATA FLOW
7
CHAPTER 3 REVIEW OF DATA MINING MODELING TECHNIQUES
15
A QUICK START
29
CHAPTER 5 DATA ACQUISITION AND INTEGRATION
43
CHAPTER 6 INTEGRITY CHECKS
63
CHAPTER 7 EXPLORATORY DATA ANALYSIS
83
CHAPTER 8 SAMPLING AND PARTITIONING
99
CHAPTER 13 ANALYSIS OF NOMINAL AND ORDINAL VARIABLES
211
CHAPTER 14 ANALYSIS OF CONTINUOUS VARIABLES
233
CHAPTER 15 PRINCIPAL COMPONENT ANALYSIS
247
CHAPTER 16 FACTOR ANALYSIS
257
CHAPTER 17 PREDICTIVE POWER AND VARIABLE REDUCTION II
267
CHAPTER 18 PUTTING IT ALL TOGETHER
279
APPENDIX LISTING OF SAS MACROS
297
Bibliography
373

CHAPTER 9 DATA TRANSFORMATIONS
115
CHAPTER 10 BINNING AND REDUCTION OF CARDINALITY
141
CHAPTER 11 TREATMENT OF MISSING VALUES
171
CHAPTER 12 PREDICTIVE POWER AND VARIABLE REDUCTION I
207
Index
375
About the Author
393
Copyright

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