Recently came across a coursera course on "How to win Kaggle competitions" where they explain how we can engineer a categorical feature from each leaf node of the decision tree.
I cannot understand this concept. Any suggestion or pointers towards understanding this will be great.
For example assume the following random training data:
Gender Age Sample_Ftre M 25 1.5 M 26 1.5 F 28 1.5 F 27 1.5 M 26 1.5
Can anyone explain what will be the value of new
engineered_feature from the decision tree and how to calculate it.