Decision Trees

Decision trees are a supervised machine learning algorithm used for classification and regression tasks. They work by splitting the data into subsets based on the value of input features, creating a tree-like model of decisions. Each internal node represents a feature, each branch represents a decision rule, and each leaf node represents an outcome. Decision trees are popular due to their simplicity, interpretability, and ability to handle both numerical and categorical data. They are commonly used in various fields, including finance for credit scoring, healthcare for diagnosis, and marketing for customer segmentation.