Practice The Confusion Matrix (The Performance Breakdown) - 5.3.1 | Module 3: Supervised Learning - Classification Fundamentals (Weeks 5) | Machine Learning
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5.3.1 - The Confusion Matrix (The Performance Breakdown)

Learning

Practice Questions

Test your understanding with targeted questions related to the topic.

Question 1

Easy

What do True Positives represent in a confusion matrix?

πŸ’‘ Hint: Think about what a successful prediction would look like.

Question 2

Easy

What is the main purpose of the Confusion Matrix?

πŸ’‘ Hint: Consider what information we need to evaluate 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 represent in the Confusion Matrix?

  • Correctly predicted positive cases
  • Incorrect positive cases
  • Correctly predicted negative cases

πŸ’‘ Hint: Think about what it means to accurately predict a class.

Question 2

True or False: Precision is concerned with the correctness of negative predictions.

  • True
  • False

πŸ’‘ Hint: Refocus on the definitions of Precision and Recall.

Solve 1 more question and get performance evaluation

Challenge Problems

Push your limits with challenges.

Question 1

You have a Confusion Matrix with TP=70, TN=50, FP=10, FN=15. Calculate the accuracy, precision, recall, and F1-Score. Discuss the implications if this were a model for a serious disease.

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

Question 2

Design an experiment to collect data to evaluate a classification model in a case where the Confusion Matrix shows high False Positives. What metrics would you prioritize and why?

πŸ’‘ Hint: Consider scenarios where high costs associated with positive misclassifications would dictate the prioritization of metrics.

Challenge and get performance evaluation