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Chapter 1 - Introduction
Pages 1-5 - Book chapterAbstract only
Chapter 2 - Tasks and Data Flow
Pages 7-13 - Book chapterAbstract only
Chapter 3 - Review of Data Mining Modeling Techniques
Pages 15-27 - Book chapterAbstract only
Chapter 4 - SAS Macros: A Quick Start
Pages 29-41 - Book chapterAbstract only
Chapter 5 - Data Acquisition and Integration
Pages 43-61 - Book chapterAbstract only
Chapter 6 - Integrity Checks
Pages 63-82 - Book chapterAbstract only
Chapter 7 - Exploratory Data Analysis
Pages 83-97 - Book chapterAbstract only
Chapter 8 - Sampling and Partitioning
Pages 99-114 - Book chapterAbstract only
Chapter 9 - Data Transformations
Pages 115-140 - Book chapterAbstract only
Chapter 10 - Binning and Reduction of Cardinality
Pages 141-170 - Book chapterAbstract only
Chapter 11 - Treatment of Missing Values
Pages 171-206 - Book chapterAbstract only
Chapter 12 - Predictive Power and Variable Reduction I
Pages 207-210 - Book chapterAbstract only
Chapter 13 - Analysis of Nominal and Ordinal Variables
Pages 211-231 - Book chapterAbstract only
Chapter 14 - Analysis of Continuous Variables
Pages 233-245 - Book chapterAbstract only
Chapter 15 - Principal Component Analysis
Pages 247-256 - Book chapterAbstract only
Chapter 16 - Factor Analysis
Pages 257-266 - Book chapterAbstract only
Chapter 17 - Predictive Power and Variable Reduction II
Pages 267-278 - Book chapterAbstract only
Chapter 18 - Putting it All Together
Pages 279-295 - Book chapterNo access
Appendix - Listing of SAS Macros
Pages 297-372 - Book chapterNo access
Bibliography
Pages 373-374 - Book chapterNo access
Index
Pages 375-392 - Book chapterNo access
About the author
Page 393
About the book
Description
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.
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.
Key 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.
- 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.
Details
ISBN
978-0-12-373577-5
Language
English
Published
2007
Copyright
Copyright © 2007 Elsevier Inc. All rights reserved
Imprint
Morgan Kaufmann