Hands-On Automated Machine Learning

Encoding

In many practical ML activities, a dataset will contain categorical variables. It is far more appropriate in an enterprise context, where most of the attributes are categorical. These variables have distinct discrete values. For example, the size of an organization can be Small, Medium, or Large, or geographic regions can be such as Americas, Asia Pacific, and Europe. Many ML algorithms, especially tree-based models, can handle this type of data directly.

However, many algorithms do not accept the data directly. Therefore, it is needed to encode these attributes into numerical values for further processing. There are various methods to encode the categorical data. Some extensively used methods are described in the following section: ...