We’ve just published Decision Trees for Analytics Using SAS Enterprise Miner by Barry de Ville and Padraic Neville. Filled with many figures and examples, this comprehensive book has garnered strong early user reviews.

We invited the authors to share a few words about their new book. Neville had this to say about what a tree is and who should care:

“Decision trees reveal subgroups that have interesting responses.  For instance, decision tree algorithms would automatically discover that women and young children had the best survival chances in an analysis of the classic Titanic survival data (google “Titanic data” to learn more).  And an expert in marketing can use recommendations from decision trees and search algorithms in order to improve and customize their segmentation of the market.” 

Neville went on share his thoughts about the value of Decision Trees for Analytics Using SAS Enterprise Miner:

“The book provides an accessible discussion of how to use decision trees.  We felt a need because other authors focus on explaining algorithms and other technical features.  We focus on practical usage.”

In addition, the book illustrates the application and operation of decision trees in business intelligence, data mining, business analytics, prediction, and knowledge discovery. It details using decision trees as a data mining technique and how this technique complements and supplements data mining approaches such as regression and other business intelligence applications that incorporate tabular reports, OLAP, or multidimensional cubes.
Analysts who have an introductory understanding of data mining and who are looking for a more advanced, in-depth look at the theory and methods of a decision tree approach to business intelligence and data mining will benefit from this book.

Learn more about the book and order your copy here.