Target group
Modelers, analysts, and statisticians who need to build predictive models, particularly models from the banking, financial services, direct marketing, insurance, and telecommunications industries
Course structure
Predictive Modeling
- Business applications.
- Analytical challenges.
Fitting the Model
- Parameter estimation.
- Adjustments for oversampling.
Preparing the Input Variables
- Missing values.
- Categorical inputs.
- Variable clustering.
- Variable screening.
- Subset selection.
Classifier Performance
- ROC curves and lift charts.
- Optimal cutoffs.
- K-S statistic.
- c
- Profit.
- Evaluating a series of models.
