LO
Explain how a decision tree works for categorical and continuous outcome variables
Build a decision tree using SAS Visual Analytics (SAS VA)
Explain how a splitting algorithm works
Discuss how the performance of a decision tree is evaluated
Construct a confusion matrix
Discuss the use of decision trees versus logistic and multiple regression
Explain how decision tree parameters can be adjusted to improve performance.

Classification and regression trees (CART) can be used in place of:
Multiple regression with a continuous outcome
Logistic regression with a binary outcome
Multinomial regression with an outcome that has multiple unordered responses
Ordinal regression with an outcome that has multiple ordered responses.

Simple decision trees in SAS Visual Analytics (SAS VA)

How classification and regression trees (CART) work

Information entropy

Information gain

Building the full Titanic decision tree

Model performance

Growth strategies

Interactive modelling

Decision trees and continuous targets