How do you interpret and visualize the results of CART?
CART stands for Classification and Regression Trees, a popular machine learning technique for building decision trees. Decision trees are graphical models that split the data into branches based on rules derived from the features. CART can be used for both classification and regression problems, depending on the type of the target variable. In this article, you will learn how to interpret and visualize the results of CART, and how to use the gini index as a measure of node impurity.