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

Predictive Modeling with SAS Enterprise Miner: Practical Solutions for Business Applications Cover

 

Synopses & Reviews

Publisher Comments:

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.

Book News Annotation:

This book/CD-ROM guide explains the methodology and theory behind tools of SAS Enterprise Miner software, walking readers step by step through comparisons between manual calculations and calculations performed by SAS Enterprise Miner. Examples from the insurance and banking industries are based on simulated, but realistic, data. Data collection, decision trees and regression trees, logistic regression models, and neural networks are some areas covered. The CD-ROM contains data sets, project templates, and SAS code. Readers should be familiar with elements of statistical inference and probability, simple algebra, ordinary least squares, logistic regression, and Base SAS software. The book is for graduate students interested in predictive modeling, experts in data mining who are not familiar with SAS Enterprise Miner, and business analysts who need an introduction to predictive modeling using SAS Enterprise Miner. Sarma is a consultant specializing in predictive modeling and forecasting. Annotation ©2008 Book News, Inc., Portland, OR (booknews.com)

Synopsis:

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.

Product Details

ISBN:
9781590477038
Publisher:
SAS Institute
Subject:
Mathematical & Statistical Software
Author:
Sarma, Kattamuri R., PH.D.
Subject:
General
Subject:
Statistics
Subject:
Business
Subject:
Data mining
Subject:
Business -- Data processing.
Subject:
Mathematics -- Software.
Publication Date:
20071131
Binding:
TRADE PAPER
Language:
English
Illustrations:
Y
Pages:
384
Dimensions:
11.26x8.26x.69 in. 1.95 lbs.

Related Subjects


Science and Mathematics » Mathematics » General
Science and Mathematics » Mathematics » Software

Predictive Modeling with SAS Enterprise Miner: Practical Solutions for Business Applications
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Product details 384 pages SAS Publishing - English 9781590477038 Reviews:
"Synopsis" by , 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.
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