With regard to chapter 7 of the course notes:
1. What is the difference between "SAS Code" and "Optimized SAS Code" (see page 7-8)?
My Answer:
SAS code: Base SAS code associated with the process flow diagram used in building the predictive model.
Optimized SAS code: After excluding all redundant SAS codes associated with the variables not included in the final model, the optimized SAS code only includes BASE SAS code needed to score the new scoring data.
My Answer:
2. Is it correct to say that when scoring a Score table, Enterprise Miner assumes the table is a true representation of the population in terms of proportions of events/non-events?
My Answer:
Yes this is a correct assumption
As such, no adjustments based on prior probabilities are applied; however, Decisions, in terms of Expected Profit and Decision classification, are based on the Decision Weights and Prior Probabilities specified for the data source used for training
My Answer:
This is incorrect. Because if over or separate sampling was practiced during the model development, the SAS code for future scoring contains code for proper posterior probability adjustments, and computing expected and average profits.
3. With regard to Decisions, is it possible to use property Decision of the Input Data node related to the Score table (see page 7.7) to amend the decision weights to be applied during scoring? If so, would that require a target variable present on the Score dataset?
My Answer:
Yes, this step is automatically performed and this adjustment is included in the optimized Base SAS code.