Data Preparation for Data Mining Using SAS
Published on 27. October 2006
Book
Paperback/Softback
424 pages
978-0-12-373577-5 (ISBN)
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.
Reviews / Votes
"It is easy to write books that address broad topics and ideas leaving the reader with the question "Yes, but how?? By combining a comprehensive guide to data preparation for data mining along with specific examples in SAS, Mamdouh's book is a rare find-a blend of theory and the practical at the same time. As anyone who has mined data will confess, 80% of the problem is in data preparation; Mamdouh addresses this difficult subject with strong practical techniques and methods.If you are working on an SAS data mining project, this book is a must! If you are working on any data mining project, the techniques and methods will be a guiding light!" --Frank Byrum, Cormine Intelligent Data, LLC
More details
Series
Language
English
Place of publication
San Francisco
United States
Publishing group
Elsevier Science & Technology
Target group
Professional and scholarly
Data Mining professionals, business analysts, SAS programmers, and data management and statistics students who plan to work in data mining. Essentially the same audience as all of our data mining books.
Illustrations
Illustrated
Dimensions
Height: 235 mm
Width: 191 mm
Weight
870 gr
ISBN-13
978-0-12-373577-5 (9780123735775)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Other editions
Additional editions
Mamdouh Refaat
Data Preparation for Data Mining Using SAS
E-Book
07/2010
Morgan Kaufmann
€65.95
Available for download
Person
Mamdouh Refaat is a data mining and business analytics consultant advising major organizations in North America and Europe. He has held several positions in consulting organizations and software vendors, including the director of consulting services at ANGOSS Software Corporation, a global data mining software and service provider. During his career, Mamdouh has managed numerous data mining consulting projects in marketing, CRM, and credit risk for Fortune 500 organizations in North America and Europe. In addition, he has delivered over 50 professional training courses in data mining and business analytics. Mamdouh holds a Ph.D. in Engineering from the University of Toronto, and an MBA from the University of Leeds.During his career, Mamdouh has managed numerous data mining consulting projects in marketing, CRM, and credit risk for Fortune 500 organizations in North America and Europe. In addition, he has delivered over 50 professional training courses in data mining and business analytics.Mamdouh holds a PhD in Engineering from the University of Toronto, and an MBA from the University of Leeds.
Content
Contents 1 Introduction 2 Tasks and Data Flow 3 Review of Data Mining Modeling Techniques 4 SAS Macros: A Quick Start 5 Data Acquisition and Integration 6 Integrity Checks 8 Sampling and Partitioning 9 Data Transformations 10 Binning and Reduction of Cardinality11 Treatment of Missing Values 12 Predictive Power and Variable Reduction I 13 Analysis of Nominal and Ordinal Variables 14 Analysis of Continuous Variables 15 Principal Component Analysis (PCA) 2 16 Factor Analysis 17 Predictive Power and Variable Reduction II 18 Putting it All Together A Listing of SAS Macros