As mentioned in the previous section, in this iteration, we will focus on feature transformation as well as implementing a voting classifier that will use the AdaBoost and GradientBoosting classifiers. Hopefully, by using this approach, we will get the best ROC-AUC score on the validation dataset as well as the real testing dataset. This is the best possible approach in order to generate the best result. If you have any creative solutions, you can also try them as well. Now we will jump to the implementation part.
Here, we will implement the following techniques:
Let's implement feature transformation first.
We will ...