Chapter 3. Feature Engineering
This chapter discusses arguably the most important step in solving a machine learning problem. Feature engineering involves the preparation and representation of data on which the models can be trained. A good feature set is compulsory for the success of a modeling project. In this chapter, we are going to cover the following topics:
- Feature construction
- Feature extraction
- Feature selection
- Dimensionality reduction
Feature engineering
Let's start by understanding what is meant by feature engineering. Feature engineering is performed after data cleansing and preparation, before or even during model training. It aims to provide better representation of the data to the machine learning algorithm. Feature engineering as a ...
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