Practice Core Classification Metrics - 5.3 | Module 3: Supervised Learning - Classification Fundamentals (Weeks 5) | Machine Learning
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Practice Questions

Test your understanding with targeted questions related to the topic.

Question 1

Easy

What is a confusion matrix?

πŸ’‘ Hint: What does the matrix display?

Question 2

Easy

Define precision.

πŸ’‘ Hint: Think about the accuracy of positive predictions.

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 a True Positive (TP) represent in a confusion matrix?

  • Model predicted positive and it is positive
  • Model predicted negative and it is positive
  • Model predicted positive and it is negative

πŸ’‘ Hint: Think about accurate positive predictions.

Question 2

True or False: Precision is the same as recall.

  • True
  • False

πŸ’‘ Hint: Consider what each metric emphasizes.

Solve 1 more question and get performance evaluation

Challenge Problems

Push your limits with challenges.

Question 1

Given a confusion matrix where TP = 50, TN = 40, FP = 10, FN = 5, calculate the accuracy, precision, recall, and F1-score.

πŸ’‘ Hint: Calculate each metric step by step using the formulas.

Question 2

In a fraud detection system, if the precision is too low but the recall is high, what adjustments would you consider making to your model to improve precision without sacrificing recall?

πŸ’‘ Hint: Think about how the criteria for classifying a positive case can be altered.

Challenge and get performance evaluation