Welcome to the third installment of AI for Jurists! 🌳🤖⚖️
Today we will learn what a decision tree is 🌴📊
A Decision Tree is a simple way to make decisions or predictions by breaking them down step-by-step, like a flowchart.
💭 Imagine you’re trying to decide whether to go to the beach. The decision tree would start with a question, like “Isn’t it a lovely day?” ☀️ If the answer is “yes,” then you move to the next step: “Is the beach close by?” 🏖️ If that answer is also “yes,” then the final decision (the “leaf” of the tree) would be “Let’s go!” 🎉 If any of the answers were “no,” you might decide not to go… ❌
In this example, each question is a “node” in the tree 🌲, and each answer leads to another branch with a new question or a final decision. Decision Trees work the same way in predicting things, like whether a person will attend an event based on certain conditions, by asking a series of questions about the data. The goal is to reach a conclusion step by step, just like deciding whether to go to the beach. 🏝️
If you enjoyed this post, stay tuned for the next one! Until then, keep your curiosity growing and branching out! 🌱✨
