Which of the following is a common method for preventing overfitting in Decision

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Question: Which of the following is a common method for preventing overfitting in Decision Trees?

Options:

Correct Answer: Pruning the tree after it has been fully grown.

Solution:

Pruning the tree after it has been fully grown helps to remove branches that have little importance, thus preventing overfitting.

Which of the following is a common method for preventing overfitting in Decision Trees?

Which of the following is a common method for preventing overfitting in Decision Trees?

Step 1: Understand what overfitting means. Overfitting happens when a model learns too much from the training data, including noise and outliers, making it perform poorly on new data.
Step 2: Learn about Decision Trees. A Decision Tree is a model that splits data into branches based on certain conditions to make predictions.
Step 3: Know that a fully grown Decision Tree can become too complex and may overfit the training data.
Step 4: Discover pruning. Pruning is the process of cutting back the branches of the tree after it has been fully grown.
Step 5: Realize that by removing branches that do not add significant value, pruning simplifies the tree and helps it generalize better to new data.
Step 6: Conclude that pruning is a common method used to prevent overfitting in Decision Trees.

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