The video tutorial discusses techniques for handling categorical inputs, focusing on dimension reduction. It covers methods to reduce variables, such as removing those with high missing rates or redundant levels. Crosstab analysis is introduced for feature selection, highlighting its use in identifying impactful predictor variables. The tutorial also explains collapsing categorical variables to improve algorithm efficiency and demonstrates creating dummy variables in SAS for logistic regression.

Describe how collapsing categorical variables can improve model performance.

What is the process of turning character variables into dummy variables?

How can business experience aid in the process of dimension reduction?