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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
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