Data Preparation for Data Mining Using SAS

Mamdouh Refaat

392 pages, parution le 09/11/2006

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Résumé

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.

Sommaire

List of Figures
List of Tables
Preface
Introduction
Tasks and Data Flow
Review of Data Mining Modeling Techniques
SAS Macros: A Quick Start
Data Acquisition and Integration
Integrity Checks
Exploratory Data Analysis
Sampling and Partitioning
Data Transformations
Binning and Reduction of Cardinality
Treatment of Missing Values
Predictive Power and Variable Reduction I
Analysis of Nominal and Ordinal Variables
Analysis of Continuous Variables
Principal Component Analysis
Factor Analysis
Predictive Power and Variable Reduction II
Putting It All Together
Listing of SAS Macros
Bibliography
Index
About the Author

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Caractéristiques techniques

	PAPIER
Éditeur(s)	Morgan Kaufmann
Auteur(s)	Mamdouh Refaat
Parution	09/11/2006
Nb. de pages	392
Format	19 x 23,5
Couverture	Broché
Poids	893g
Intérieur	Noir et Blanc
EAN13	9780123735775
ISBN13	978-0-12-373577-5