Summary
In this chapter, you explored various encoding techniques for transforming categorical variables into a format suitable for predictive modeling. From mean encoding, which establishes a direct relationship between the encoded variable and the target, to more specialized techniques such as probability ratio encoding and WoE encoding, each method offers unique advantages depending on the specific characteristics of the data and the requirements of the model. Additionally, you learned strategies for handling rare categories, ensuring that these infrequent occurrences do not negatively impact model performance. By carefully selecting and applying these encoding techniques, you can significantly enhance the predictive power and robustness of your models.
In the next chapter, Chapter 9, you will apply the data cleaning methods and techniques from Chapter 6, the feature selection techniques you learned in Chapter 7, and the encoding methods in this chapter while building models...
