Applying steps in logistic regression modeling

The following steps are applied in linear regression modeling in industry:

1. Exclusion criteria and good-bad definition finalization
2. Initial data preparation and univariate analysis
3. Derived/dummy variable creation
4. Fine classing and coarse classing
5. Fitting the logistic model on the training data
6. Evaluating the model on test data