What is tree-based models?

Tree-based models are a type of supervised machine learning algorithm that use a tree-like structure to make predictions. They work by recursively partitioning the input space into smaller and smaller regions, based on the values of the input features. Common examples include decision trees, random forests, and gradient boosting machines. They are widely used for classification and regression tasks due to their interpretability and ability to handle non-linear relationships.