What is decision trees?

Decision trees are a non-parametric supervised learning method used for classification and regression. They learn simple decision rules inferred from the data features. A decision tree is a flowchart-like structure in which each internal node represents a "test" on an attribute (e.g., whether a coin flip comes up heads or tails), each branch represents the outcome of the test, and each leaf node represents a class label (decision taken after computing all attributes) or regression value. They are commonly used in data mining, machine learning, and predictive modeling to make decisions or predictions based on input data.