Discover the power of tree-structured data mining during this popular introductory seminar, geared toward statisticians and IT audiences who are interested in understanding the conceptual basis of decision tree technology -- what it is, why it works, how it has been used, and how it can help you make better business decisions.

• Decision tree fundamentals
• Decision tree applications
• How to build and interpret CART models

Explore SPM's unique modeling automation capabilities while running multiple data sets on both GUI and Non-GUI interfaces, and the advantages and disadvantages to both. We'll introduce the CART component of SPM, and explain:

• Parts of the display
• Variable importance
• Summary reporting
• Surrogates and competitors
• How the utility handles missing values

CART Splitting Rules and Tree Building Mechanisms

• Gini
• Entropy
• Twoing
• Costs and Priors

Model Evaluation and Hybrid Models

• Model evaluation using relative costs, ROC and cross-validation
• CART and LOGIT
• CART and linear regression

Introduction to the Powerful Use of Batteries in SPM

Major Battery Functions:

• Battery target and handling missing values
• Importance of the prior probabilities control in CART
• Battery priors
• Uses for hotspot detection

Loose Ends and Application

Q&A with the experts for further discussion and apply SPM to your own data sets.