Machine Learning: Random Forest with Python from Scratch - Leaf and Decision Node

The video tutorial explains the creation of two classes: a leaf node and a decision node (DCN node). The leaf node is designed to make predictions based on class counts, while the DCN node is structured to have a question, true branch, and false branch. The tutorial outlines the process of writing constructors for these nodes and emphasizes that the build tree method will integrate these components. The build tree method will be concise, leveraging previously written helper functions. The video concludes with a note that the implementation of the build tree method will be covered in the next lecture.

Describe the process of building a tree using the helper functions mentioned.

What will the buildtree method return after its implementation?