July 2017
Beginner to intermediate
442 pages
10h 8m
English
Content preview from Statistics for Machine Learning
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Applying steps in logistic regression modeling
The following steps are applied in linear regression modeling in industry:
- Exclusion criteria and good-bad definition finalization
- Initial data preparation and univariate analysis
- Derived/dummy variable creation
- Fine classing and coarse classing
- Fitting the logistic model on the training data
- Evaluating the model on test data
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