Auto feature engineering workflow

There are two workflows: One for data which is not large. Full (or 80% of data) can be used for training and rest for testing, feature generation and subsequent ML model building.
IInd workflow is for large data where a fraction of it is used for 'autofeat' modeling and then this model is used to create features in the full training dataset.
Two components have been used: auto feature generator I and auto feature generator II.

External resources

• The autofeat Python Library for Automated Feature Engineering and Selection
• Automatic Feature Engineering and Selection