Practice Overfitting - 12.4.A | 12. Model Evaluation and Validation | Data Science Advance
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Overfitting

12.4.A - Overfitting

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Learning

Practice Questions

Test your understanding with targeted questions

Question 1 Easy

What is overfitting?

💡 Hint: Think about the training accuracy versus test accuracy.

Question 2 Easy

Name one technique to prevent overfitting.

💡 Hint: It adds a penalty to complexity.

4 more questions available

Interactive Quizzes

Quick quizzes to reinforce your learning

Question 1

What is a sign of overfitting?

High validation accuracy
Low training accuracy
High training accuracy and low validation accuracy

💡 Hint: Think about the difference between training and validation datasets.

Question 2

Is early stopping a method to prevent overfitting?

True
False

💡 Hint: Consider training dynamics.

1 more question available

Challenge Problems

Push your limits with advanced challenges

Challenge 1 Hard

Consider a dataset with numerous features. Describe a systematic approach to ensure your model does not overfit while tuning for the best performance.

💡 Hint: Think about balancing feature sets and evaluating performance.

Challenge 2 Hard

After implementing a model with an accuracy drop on test data, what steps would you take to analyze and rectify the issue?

💡 Hint: Consider the possible reasons for discrepancies in performance.

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