We have two types of features:
- Generic features, or datatype-specific features: These are features based on the datatype of the field.
- Domain-specific features: These are features that are dependent upon the domain of the data. Here, we derive some features from the data based on our business knowledge or the domain.
Features can be extracted from the existing features. For instance, when we consider a date variable, we can extract the year from the entire date. From these datatypes, it is essential to extract the feature.
Imagine that you have a dataset containing information such as dates, months, and years in a non-numerical format; for example, 31/05/2019. We cannot feed this information to a machine learning algorithm, as such algorithms will not understand date-type values. Thus, converting date and time into machine-readable data format is an important skill for a machine learning engineer.
We can extract...