Creating new features out of the existing features is an art and it can be done in many different ways.
The objective of feature creation is to provide ML algorithms with such predictors that makes it easy for them to understand the patterns and derive better relationship from the data.
For example, in HR attrition problems, the duration of stay of an employee in an organization is an important attribute. However, sometimes we don't have the duration of stay as a feature in the dataset, but we have the employee start date. In such cases, we can create the data for the duration of stay feature by subtracting the employee start date from the current date.
In the following sections, we will see some of the different ways to generate new features out of the data. However, this is not an extensive list, but a few different methods that can be employed to create...
