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

Sarma, Kattamuri S., Ph.D.

Brossura

ISBN 10: 1590477030 ISBN 13: 9781590477038

Casa editrice: Sas Inst, 2007

Riassunto

Predictive Modeling with SAS Enterprise Miner: Practical Solutions for Business Applications demonstrates how to make the fullest use of SAS Enterprise Miner software. Dr. 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. Your bonus CD-ROM includes the following: data sets, Enterprise Miner project templates, and SAS code.

Su questo libro

Informazioni sull?autore

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.

Dalla quarta di copertina

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.

Dettagli dell'edizione

• Editore: Sas Inst
• Data di pubblicazione: 2007
• Lingua: Inglese
• ISBN 10: 1590477030
• ISBN 13: 9781590477038
• Rilegatura: Copertina flessibile
• Numero di pagine: 360
• Contatto del produttore: non disponibile
• Persona responsabile: non disponibile