Decision Tree

Overview

A decision tree is a machine learning model that makes decisions by following a series of questions.

Each question helps narrow down possible outcomes until a final prediction or decision is reached.

The structure resembles a tree, with branches representing different choices and outcomes.

Decision trees are often considered one of the easiest machine learning models to understand because the reasoning process can be visualized step by step.

Why It Matters

Decision trees provide a simple and interpretable way to make predictions.

Their transparency makes them useful in situations where understanding how a decision was reached is important.

Real-World Example

A bank may use a decision tree to evaluate loan applications by considering factors such as income, credit score, employment history, and existing debt.

Related Concepts

• Classification
• Regression
• Features
• Machine Learning
• Supervised Learning