Predictive Modeling With SAS Enterprise Miner: Practical Solutions for Business Applications

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9781590477038: Predictive Modeling With SAS Enterprise Miner: Practical Solutions for Business Applications
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Predictive Modeling with SAS Enterprise Miner: Practical Solutions for Business Applications demonstrates how to make the fullest use of SAS Enterprise Miner software. Kattamuri Sarma provides an in-depth explanation of the methodology and the theory behind each tool that he covers, and then shows you how the software performs the tasks. Step by step, you'll be able to compare manual calculations with the calculations that are performed by SAS Enterprise Miner. Examples from the insurance and banking industries are based on simulated, but realistic, data. The approaches discussed in this book are relevant to any industry.

Here are a few of the topics discussed in detail:

  • data collection and data cleaning
  • data exploration
  • decision trees and regression trees
  • logistic regression models
  • neural networks
  • variable selection and variable transformation

You need this book if you are a graduate student interested in predictive modeling, an expert in data mining who is not familiar with SAS Enterprise Miner, or a business analyst who needs an introduction to predictive modeling using SAS Enterprise Miner. To get the most from this book, you should be familiar with elements of statistical inference and probability, simple algebra, ordinary least squares, logistic regression, and Base SAS software.

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About the Author:

Kattamuri S. Sarma, Ph.D., is an economist and statistician with 30 years of experience in American business, including stints with IBM and AT&T. He is the founder and president of Ecostat Research Corp., a consulting firm specializing in predictive modeling and forecasting. Over the years, Dr. Sarma has developed predictive models for the banking, insurance, telecommunication, and technology industries. He has been a SAS user since 1992, and he has extensive experience with multivariate statistical methods, econometrics, decision trees, and data mining with neural networks. The author of numerous professional papers and publications, Dr. Sarma is a SAS Certified Professional and a SAS Alliance Partner. Dr. Sarma received his bachelor's degree in mathematics and his master's degree in economic statistics from universities in India, and his Ph.D. in economics from the University of Pennsylvania, where he worked under the supervision of Nobel Laureate Lawrence R. Klein.

Review:

"The author is congratulated and appreciated for writing such a practical and useful book for both entry-level and seasoned practitioners. It provides very clear step-by-step instruction using various case examples. In addition, it also provides the explanation of essential theoretical background in each modeling technique. As an instructor, I think this is an excellent textbook for introducing predictive modeling using SAS Enterprise Miner, and I plan to use it for my class. " --Carl Lee, Ph.D., Professor of Statistics, Central Michigan University

"Kattamuri Sarma has written a practical guide that will be of use to modeling professionals of all backgrounds and levels of experience. In it he shows us the power of SAS Enterprise Miner to enhance the modeling process in a way that is straightforward, easy to follow, and thorough. From data scrubbing to model fitting, each step in the model building process is described in a clear manner. The book draws on the author's extensive real-world experience to illustrate the ways in which Enterprise Miner can help to facilitate the modeling process. Predictive Modeling with SAS Enterprise Miner: Practical Solutions for Business Applications is destined to become the definitive guide to the use of SAS Enterprise Miner, and should be considered an indispensable resource for modelers who want a better understanding of the software's capabilities. " --Lee Medoff, SAS User

"I'm very impressed. The text is clear, and follows a logical flow. Step-by-step directions with screen shots help those new to SAS Enterprise Miner. The details give good support, without being too overwhelming." --Andrea Wainwright-Zimmerman, Senior statistical analysis manager

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