Chapter 10: Statistics for Tree-Based Methods
In the previous chapter, we covered some important concepts in classification models. We also built a naïve Bayes classifier from scratch, which is very important because it requires you to understand every aspect of the details.
In this chapter, we are going to dive into another family of statistical models that are also widely used in statistical analysis as well as machine learning: tree-based models. Tree-based models can be used for both classification tasks and regression tasks.
By the end of this chapter, you will have achieved the following:
- Gained an overview of tree-based classification
- Understood the details of classification tree building
- Understood the mechanisms of regression trees
- Know how to use the
scikit-learnlibrary to build and regularize a tree-based method
Let's get started! All the code snippets used in this chapter can be found in the official GitHub repository here: https...
