The same German credit data is being utilized to illustrate the random forest model in order to provide an apple to apple comparison. A very significant difference anyone can observe compared with logistic regression is that effort applied on data preprocessing drastically decreases. The following differences are worth a mention:
- In RF, we have not removed variables one by one from analysis based on significance and VIF values, as significance tests are not applicable for ML models. However five-fold cross validation has been performed on training data to ensure the model's robustness.
- We have removed one extra dummy variable in the logistic regression procedure, whereas in RF we have not ...
