Practice Overfitting and Underfitting - 28.5 | 28. Introduction to Model Evaluation | CBSE 10 AI (Artificial Intelleigence)
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Overfitting and Underfitting

28.5 - Overfitting and Underfitting

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Learning

Practice Questions

Test your understanding with targeted questions

Question 1 Easy

What does overfitting mean in machine learning?

💡 Hint: Think about the model's memory versus understanding.

Question 2 Easy

What is underfitting?

💡 Hint: Consider how a model's complexity relates to its understanding of data.

4 more questions available

Interactive Quizzes

Quick quizzes to reinforce your learning

Question 1

What is overfitting in machine learning?

High accuracy on training data
low on test data
Low accuracy on both
Good performance on training and test

💡 Hint: Focus on where the model excels and where it struggles.

Question 2

True or False: Underfitting can occur when a model is too complex.

True
False

💡 Hint: Revisit definitions of complexity in models.

2 more questions available

Challenge Problems

Push your limits with advanced challenges

Challenge 1 Hard

Given a dataset with a linear trend, design a simplistic model for prediction. Indicate potential pitfalls of underfitting in your approach.

💡 Hint: What happens if too few features are included?

Challenge 2 Hard

Explain how you would diagnose a model that is suspected of overfitting. What metrics and techniques would you use?

💡 Hint: Look at evaluation strategies for any discrepancies in model performance.

Get performance evaluation

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