Data Preparation for Data Mining Using SAS
eBook - PDF

Data Preparation for Data Mining Using SAS

  1. 424 pages
  2. English
  3. PDF
  4. Available on iOS & Android
eBook - PDF

Data Preparation for Data Mining Using SAS

About this book

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. - 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.

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Yes, you can access Data Preparation for Data Mining Using SAS by Mamdouh Refaat in PDF and/or ePUB format, as well as other popular books in Computer Science & Artificial Intelligence (AI) & Semantics. We have over one million books available in our catalogue for you to explore.

Table of contents

  1. Front Cover
  2. Data Preparation for Data Mining Using SAS
  3. Copyright Page
  4. Contents
  5. List of Figures
  6. List of Tables
  7. Preface
  8. CHAPTER 1. INTRODUCTION
  9. CHAPTER 2. TASKS AND DATA FLOW
  10. CHAPTER 3. REVIEW OF DATA MINING MODELING TECHNIQUES
  11. CHAPTER 4. SAS MACROS: A QUICK START
  12. CHAPTER 5. DATA ACQUISITION AND INTEGRATION
  13. CHAPTER 6. INTEGRITY CHECKS
  14. CHAPTER 7. EXPLORATORY DATA ANALYSIS
  15. CHAPTER 8. SAMPLING AND PARTITIONING
  16. CHAPTER 9. DATA TRANSFORMATIONS
  17. CHAPTER 10. BINNING AND REDUCTION OF CARDINALITY
  18. CHAPTER 11. TREATMENT OF MISSING VALUES
  19. CHAPTER 12. PREDICTIVE POWER AND VARIABLE REDUCTION I
  20. CHAPTER 13. ANALYSIS OF NOMINAL AND ORDINAL VARIABLES
  21. CHAPTER 14. ANALYSIS OF CONTINUOUS VARIABLES
  22. CHAPTER 15. PRINCIPAL COMPONENT ANALYSIS
  23. CHAPTER 16. FACTOR ANALYSIS
  24. CHAPTER 17. PREDICTIVE POWER AND VARIABLE REDUCTION II
  25. CHAPTER 18. PUTTING IT ALL TOGETHER
  26. APPENDIX. LISTING OF SAS MACROS
  27. Bibliography
  28. Index
  29. About the Author