ELI5: decision tree classification and regression
// explanation
What is a decision tree?
A decision tree is like a flowchart that helps a computer make decisions, similar to how you might decide what to wear by asking questions like "Is it raining?" or "Is it cold?" [1][4] The computer asks questions about the data over and over until it figures out the answer.
Why does it work?
Decision trees break big, complicated problems into smaller, easier pieces [5]. Each question splits the data into groups, and the computer keeps asking questions until each group is pure (all the same type).
What's the difference between classification and regression?
Classification trees help answer "yes or no" questions, like "Is this email spam?" [3], while regression trees predict numbers, like "How much will this house cost?" [3] Both use the same tree structure but give different types of answers.
How does the computer use it?
Once the tree is built, you can follow the branches by answering each question, and the tree tells you the final answer [1]. It's like following a map where each turn takes you closer to your destination.
// sources
Decision Trees (DTs) are a non-parametric supervised learning method used for classification and regression.
Learn about decision trees, how they work and how they can be used for classification and regression tasks.
Decision tree types · Classification tree analysis is when the predicted outcome is the class (discrete) to which the data belongs. · Regression tree analysis is ...
Sep 26, 2023 ... Decision trees are a type of machine-learning algorithm that can be used for both regression and classification tasks.
Dec 4, 2025 ... To break a dataset into smaller, meaningful groups, CART (Classification and Regression Tree) is used which builds a decision tree that ...
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