A Decision Tree is a flowchart structure in which each internal node represents a test on a feature, each leaf node represents a class label and branches represent conjunctions features that lead to those labels.

The paths from the root to a leaf represent classification rules.

Decision Tree is the predictive modeling approach used in statistics, data mining, and machine learning.

They are constructed via an algorithmic approach that identifies the ways to split a dataset based on different conditions.

They are a non-parametric supervised learning method used for both classification and regression tasks.

Classification Trees are the tree models where the target variable can take a discrete set of values.

Regression Trees are the decision trees where the target variable can take a continuous set of values.