Cover for Data Preparation for Data Mining Using SAS

Data Preparation for Data Mining Using SAS

A volume in The Morgan Kaufmann Series in Data Management Systems

Book2007

Author:

Mamdouh Refaat

Data Preparation for Data Mining Using SAS

A volume in The Morgan Kaufmann Series in Data Management Systems

Book2007

 

Cover for Data Preparation for Data Mining Using SAS

Author:

Mamdouh Refaat

About the book

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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 lot ... read full description

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  2. Book chapterAbstract only

    Chapter 1 - Introduction

    Pages 1-5

  3. Book chapterAbstract only

    Chapter 2 - Tasks and Data Flow

    Pages 7-13

  4. Book chapterAbstract only

    Chapter 3 - Review of Data Mining Modeling Techniques

    Pages 15-27

  5. Book chapterAbstract only

    Chapter 4 - SAS Macros: A Quick Start

    Pages 29-41

  6. Book chapterAbstract only

    Chapter 5 - Data Acquisition and Integration

    Pages 43-61

  7. Book chapterAbstract only

    Chapter 6 - Integrity Checks

    Pages 63-82

  8. Book chapterAbstract only

    Chapter 7 - Exploratory Data Analysis

    Pages 83-97

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    Chapter 8 - Sampling and Partitioning

    Pages 99-114

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    Chapter 9 - Data Transformations

    Pages 115-140

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    Chapter 10 - Binning and Reduction of Cardinality

    Pages 141-170

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    Chapter 11 - Treatment of Missing Values

    Pages 171-206

  13. Book chapterAbstract only

    Chapter 12 - Predictive Power and Variable Reduction I

    Pages 207-210

  14. Book chapterAbstract only

    Chapter 13 - Analysis of Nominal and Ordinal Variables

    Pages 211-231

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    Chapter 14 - Analysis of Continuous Variables

    Pages 233-245

  16. Book chapterAbstract only

    Chapter 15 - Principal Component Analysis

    Pages 247-256

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    Chapter 16 - Factor Analysis

    Pages 257-266

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    Chapter 17 - Predictive Power and Variable Reduction II

    Pages 267-278

  19. Book chapterAbstract only

    Chapter 18 - Putting it All Together

    Pages 279-295

  20. Book chapterNo access

    Appendix - Listing of SAS Macros

    Pages 297-372

  21. Book chapterNo access

    Bibliography

    Pages 373-374

  22. Book chapterNo access

    Index

    Pages 375-392

  23. 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

Authors

Mamdouh Refaat