What is the primary advantage of using Random Forests over a single Decision Tre

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Question: What is the primary advantage of using Random Forests over a single Decision Tree?

Options:

Correct Answer: Random Forests reduce overfitting by averaging multiple trees.

Solution:

Random Forests reduce overfitting by averaging the predictions of multiple decision trees, leading to better generalization on unseen data.

What is the primary advantage of using Random Forests over a single Decision Tree?

What is the primary advantage of using Random Forests over a single Decision Tree?

Step 1: Understand what a Decision Tree is. A Decision Tree is a model that makes decisions based on asking a series of questions about the data.
Step 2: Recognize that a single Decision Tree can sometimes make mistakes, especially if it learns too much from the training data. This is called overfitting.
Step 3: Learn that Random Forests use many Decision Trees instead of just one. This means they can make better predictions by combining the results of all the trees.
Step 4: Realize that by averaging the predictions from multiple trees, Random Forests can reduce the chances of making mistakes that a single tree might make.
Step 5: Conclude that the primary advantage of Random Forests is that they provide better accuracy and generalization on new, unseen data compared to a single Decision Tree.

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