Decision Trees for Business Intelligence and Data Mining: Using...

Features

• Cover Type: Paperback with 240 pages
• Published by: SAS Publishing October 30, 2006
• Written in: English
• ISBN 10 Number: 1590475674
• ISBN 13 Number: 978-1590475676
• Book Dimensions: 8.9 x 7.3 x 0.6 inches
• Weighs: 12.8 ounces

Product Review
"Decision Trees for Business Intelligence and Data Mining Using SAS Enterprise Miner provides detailed principles of how decision tree algorithms work from an operational angle and directly links these instructions to the use of SAS Enterprise Miner. In this way, it fills the gap between classical data mining texts and SAS Enterprise Miner training materials." --Zhangxi Lin, Associate Professor of Information Systems

Book Description
Using SAS Enterprise Miner, this book illustrates the application and operation of decision trees in business intelligence, data mining, business analytics, prediction, and knowledge discovery. It explains in detail the use of decision trees as a data mining technique and how this technique complements and supplements data mining approaches such as regression, as well as other business intelligence applications that incorporate tabular reports, OLAP, or multidimensional cubes. Examples show how various aspects of decision trees are constructed, how they operate, how to interpret them, and how to use them in a range of predictive and descriptive applications. The examples are drawn from the areas of purchase behavior, risk assessment, and business-to-business marketing. This book also describes the various disciplines that contributed to the development of decision trees and how, even today, decision trees can be used as a form of machine intelligence. Examples of using and interpreting graphic decision trees as executable rules are provided. The target audience includes analysts who have an introductory understanding of data mining and who want to benefit from a more advanced, in-depth look at the theory and methods of a decision tree approach to business intelligence and data mining.

Reader Reviews
A good book to understand decision trees using SAS e-miner. I wish it could have more literature on the splitting algorithms i.e. Gini, Entropy, Chisquare. The book along with SAS data mining material or Data Mining book by Larose is a good resource to understand Decision Tree. Comment | | (Report this)