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Which of the following is a disadvantage of Decision Trees?

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Question: Which of the following is a disadvantage of Decision Trees?

Options:

  1. They can handle both numerical and categorical data
  2. They are prone to overfitting
  3. They are easy to interpret
  4. They require less data

Correct Answer: They are prone to overfitting

Solution: 

Decision Trees are prone to overfitting, especially when they are deep and complex.

Which of the following is a disadvantage of Decision Trees?

Practice Questions

Q1
Which of the following is a disadvantage of Decision Trees?
  1. They can handle both numerical and categorical data
  2. They are prone to overfitting
  3. They are easy to interpret
  4. They require less data

Questions & Step-by-Step Solutions

Which of the following is a disadvantage of Decision Trees?
  • Step 1: Understand what a Decision Tree is. It is a model used for making decisions based on data.
  • Step 2: Learn about overfitting. This happens when a model learns too much from the training data, including noise and outliers.
  • Step 3: Recognize that Decision Trees can become very complex if they have many branches (deep trees).
  • Step 4: Realize that when a Decision Tree is too complex, it may not perform well on new, unseen data.
  • Step 5: Conclude that the disadvantage of Decision Trees is that they can overfit, making them less reliable for predictions.
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