Predictive Modeling Using SAS Enterprise Miner 5.2 Credential

Duration  : 42  hours

Audience

A SAS Enterprise Miner predictive modeler should have current SAS Enterprise Miner experience including the ability to prepare data, build predictive models, assess models, score new data sets, and implement models. Candidates should also be familiar with the enhancements and new functionalities for predictive modeling that are available in SAS Enterprise Miner 5.2.

Test Content

Please note: You will be performing all the tasks listed below using SAS Enterprise Miner 5.2.

Data Preparation

• Missing values
• Initial data exploration including data visualization/measurement levels or scales/variable reduction
• Transformation/recoding/binning

Predictive Models

• Data splitting/balancing/overfitting/oversampling
• Logistic/linear regression
• Artificial neural networks (MLP)
• Decision trees
• Variable importance/odds ratio
• Profit/loss/prior probabilities

Model Assessment

• Comparison between models/lift chart/ROC/profit & loss
• Assessment of a single model

Scoring and Implementation

• Score a data set