ID3

ID3 (Iterative Dichotomiser 3) is a method used in machine learning to build decision trees for classification tasks. It works by analyzing data with different features and selecting the most informative ones to split the data into groups. This splitting is based on measuring the "information gain," which indicates how well a feature separates the data into different categories. The process continues recursively, creating a tree structure where each branch represents a decision based on a feature, helping to predict outcomes efficiently. Essentially, ID3 organizes data to make accurate classification decisions automatically.