Synopses & Reviews
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
decision trees and regression trees
logistic regression models
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.
Providing an in-depth explanation of the methodology and the theory behind each tool in SAS Enterprise Miner software, Dr. Sarma covers such topics as data collection, data cleaning, data exploration, logistic regression models, and more.