Practice Common Evaluation Metrics - 12.2 | 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

What is the formula for accuracy?

πŸ’‘ Hint: Consider the components of true positives and negatives.

Question 2

Easy

Define precision in your own words.

πŸ’‘ Hint: Think about false positives.

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 accuracy measure in classification tasks?

  • True positive rate
  • Overall correctness
  • False positive rate

πŸ’‘ Hint: Think about all correct and incorrect predictions.

Question 2

Is Precision always more informative than Accuracy in imbalanced datasets?

  • True
  • False

πŸ’‘ Hint: Consider the impact of negative cases.

Solve 2 more questions and get performance evaluation

Challenge Problems

Push your limits with challenges.

Question 1

You have a class imbalance where you predicted 100 positives and 70 of them are true positives, while 30 are false positives. Calculate precision. Discuss the significance.

πŸ’‘ Hint: Think about what happens when false positives are high.

Question 2

Given MSE = 16 and N=4 for your predictions, how would you interpret this in terms of model performance? Compare this with RMSE.

πŸ’‘ Hint: Consider how errors impact decisions.

Challenge and get performance evaluation