Encoding Techniques for Categorical Features
This chapter is a hands-on guide that provides you with practical experience of using various categorical encoding techniques. You will be implementing several categorical encoding techniques using Python, specifically with the pandas and scikit-learn libraries.
Categorical encoding is the process of converting categorical data (i.e., non-numeric data representing categories or labels) into numerical formats that machine learning (ML) algorithms can use. Most ML models and statistical techniques require numerical input, making it necessary to transform categorical variables into a form that the model can understand and process.
In Chapter 7, you learned how to handle missing values for categorical variables. Additionally, that chapter covered the simple encoding techniques of order mapping and mapping nominal data, including how to handle rare categories. We introduced the two types of categorical data that these encoding techniques...
