Decision Tree

Decision trees are versatile tools that can be employed for both Regression and Classification tasks.

When developing a decision tree, it’s crucial to ask a series of targeted questions in order to zero in on the most accurate label. The objective is to construct an efficient tree that minimizes the number of splits necessary to divide the data. This process continues until no further splits can be made.

It’s important to find the right balance, as shallow trees tend to under-fit the data, while deep trees can lead to overfitting, with each example ending up as its own leaf node.