Practice Overfitting and Underfitting - 12.6 | 12. Evaluation Methodologies of AI Models | CBSE Class 12th AI (Artificial Intelligence)
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12.6 - Overfitting and Underfitting

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Learning

Practice Questions

Test your understanding with targeted questions related to the topic.

Question 1

Easy

What happens when a model overfits?

💡 Hint: Think about how well a student does on practice tests versus the actual exam.

Question 2

Easy

What is the main issue with underfitting?

💡 Hint: Consider how a student might miss key concepts in their studies.

Practice 4 more questions and get performance evaluation

Interactive Quizzes

Engage in quick quizzes to reinforce what you've learned and check your comprehension.

Question 1

What is overfitting?

  • A model that performs well on seen data only
  • A model that performs equally well on new data
  • A model that is too simple

💡 Hint: Consider how well the model can predict on new data versus training data.

Question 2

True or False: Underfitting refers to a model that has high variance.

  • True
  • False

💡 Hint: Remember the definitions of variance and bias.

Solve 1 more question and get performance evaluation

Challenge Problems

Push your limits with challenges.

Question 1

Consider a dataset where the relationship between variables is quadratic, but you use a linear regression model. What issues arise, and how can this be resolved?

💡 Hint: What additional terms could capture the relationship between your variables?

Question 2

You have data that is very noisy, and a model is trained to fit every point exactly. Explain the likely outcomes and the adjustments you could make to improve generalization.

💡 Hint: What techniques can you think of to penalize complexity?

Challenge and get performance evaluation