What type of learning does a Decision Tree primarily use?

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Question: What type of learning does a Decision Tree primarily use?

Options:

Correct Answer: Supervised Learning

Solution:

Decision Trees primarily use Supervised Learning, where the model is trained on labeled data.

What type of learning does a Decision Tree primarily use?

What type of learning does a Decision Tree primarily use?

Step 1: Understand what a Decision Tree is. It is a model used to make decisions based on data.
Step 2: Learn about the types of learning in machine learning. There are mainly two types: Supervised Learning and Unsupervised Learning.
Step 3: Know that Supervised Learning means the model is trained on data that has labels (answers).
Step 4: Realize that Decision Trees are trained using labeled data, which helps them learn how to make decisions.
Step 5: Conclude that since Decision Trees use labeled data for training, they primarily use Supervised Learning.

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