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What is a limitation of Decision Trees in real-world applications?

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Question: What is a limitation of Decision Trees in real-world applications?

Options:

  1. They are not interpretable
  2. They can easily overfit the training data
  3. They require extensive feature engineering
  4. They cannot handle categorical data

Correct Answer: They can easily overfit the training data

Solution: 

Decision Trees are prone to overfitting, especially with complex datasets, which can limit their effectiveness.

What is a limitation of Decision Trees in real-world applications?

Practice Questions

Q1
What is a limitation of Decision Trees in real-world applications?
  1. They are not interpretable
  2. They can easily overfit the training data
  3. They require extensive feature engineering
  4. They cannot handle categorical data

Questions & Step-by-Step Solutions

What is a limitation of Decision Trees in real-world applications?
  • Overfitting – Overfitting occurs when a model learns the noise in the training data instead of the underlying pattern, leading to poor generalization on unseen data.
  • Complex Datasets – Complex datasets may contain many features or intricate relationships, making it easier for decision trees to fit the noise rather than the signal.
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