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Data Preparation for Data Mining Using SAS.
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 view...
| Clasificación: | Libro Electrónico |
|---|---|
| Autor principal: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Burlington :
Elsevier,
2006.
|
| Temas: | |
| Acceso en línea: | Texto completo |
MARC
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| 100 | 1 | |a Refaat, Mamdouh. | |
| 245 | 1 | 0 | |a Data Preparation for Data Mining Using SAS. |
| 260 | |a Burlington : |b Elsevier, |c 2006. | ||
| 300 | |a 1 online resource (425 pages) | ||
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| 337 | |a computer |b c |2 rdamedia | ||
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| 505 | 0 | |a Front Cover; Data Preparation for Data Mining Using SAS; Copyright Page; Contents; List of Figures; List of Tables; Preface; CHAPTER 1. INTRODUCTION; CHAPTER 2. TASKS AND DATA FLOW; CHAPTER 3. REVIEW OF DATA MINING MODELING TECHNIQUES; CHAPTER 4. SAS MACROS: A QUICK START; CHAPTER 5. DATA ACQUISITION AND INTEGRATION; CHAPTER 6. INTEGRITY CHECKS; CHAPTER 7. EXPLORATORY DATA ANALYSIS; CHAPTER 8. SAMPLING AND PARTITIONING; CHAPTER 9. DATA TRANSFORMATIONS; CHAPTER 10. BINNING AND REDUCTION OF CARDINALITY; CHAPTER 11. TREATMENT OF MISSING VALUES. | |
| 505 | 8 | |a CHAPTER 12. PREDICTIVE POWER AND VARIABLE REDUCTION ICHAPTER 13. ANALYSIS OF NOMINAL AND ORDINAL VARIABLES; CHAPTER 14. ANALYSIS OF CONTINUOUS VARIABLES; CHAPTER 15. PRINCIPAL COMPONENT ANALYSIS; CHAPTER 16. FACTOR ANALYSIS; CHAPTER 17. PREDICTIVE POWER AND VARIABLE REDUCTION II; CHAPTER 18. PUTTING IT ALL TOGETHER; APPENDIX. LISTING OF SAS MACROS; Bibliography; Index; About the Author. | |
| 520 | |a 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. | ||
| 588 | 0 | |a Print version record. | |
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| 630 | 0 | 0 | |a SAS (Computer file) |
| 630 | 0 | 7 | |a SAS (Computer file) |2 fast |
| 650 | 0 | |a Data mining. | |
| 650 | 6 | |a Exploration de données (Informatique) | |
| 650 | 7 | |a Data mining |2 fast | |
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