Practice Model Evaluation and Validation Techniques - 12 | 12. Model Evaluation and Validation | Data Science Advance
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Practice Questions

Test your understanding with targeted questions related to the topic.

Question 1

Easy

Define accuracy in your own words.

💡 Hint: Think about how you measure performance overall.

Question 2

Easy

What is the purpose of using cross-validation?

💡 Hint: Consider how we can split data effectively.

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 does precision measure in a classification task?

  • True positives only
  • True positives and false negatives
  • True positives divided by the sum of true positives and false positives

💡 Hint: Remember how precision relates to the positive predictions made.

Question 2

True or False: Overfitting is when a model performs well on unseen data.

  • True
  • False

💡 Hint: Think about the training vs. testing scenarios.

Solve 2 more questions and get performance evaluation

Challenge Problems

Push your limits with challenges.

Question 1

Given an imbalanced dataset with a class ratio of 95:5, outline a plan to assess the model’s performance effectively.

💡 Hint: Consider impacts of accuracy versus other metrics.

Question 2

Design an experiment using nested cross-validation to both tune hyperparameters and evaluate a model. Describe your process.

💡 Hint: How do inner and outer loops interact?

Challenge and get performance evaluation