Practice Confusion Matrix - 4.1 | Classification Algorithms | Data Science Basic
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4.1 - Confusion Matrix

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Learning

Practice Questions

Test your understanding with targeted questions related to the topic.

Question 1

Easy

What are the four components of a confusion matrix?

💡 Hint: Think of the two types of outcomes versus predictions.

Question 2

Easy

How do you calculate accuracy from a confusion matrix?

💡 Hint: You’re looking for the ratio of correct predictions to all 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 a confusion matrix?

  • Correctly predicted positive instances
  • Incorrectly predicted positive instances
  • Correctly predicted negative instances

💡 Hint: Think about the outcomes when predictions are correct.

Question 2

The F1-Score is especially useful when you want to:

  • Assess both precision and recall
  • Only assess accuracy

💡 Hint: Remember, it's about balancing two important measures.

Solve 2 more questions and get performance evaluation

Challenge Problems

Push your limits with challenges.

Question 1

You analyze a model predicting whether customer service tickets are resolved or not. The confusion matrix shows TP=30, TN=40, FP=10, FN=5. Calculate accuracy, precision, recall, and F1-Score.

💡 Hint: Each metric is derived from the confusion matrix components.

Question 2

Imagine you're assessing a model that predicts loan defaults. The confusion matrix shows high false positives. Discuss how this affects the bank's strategy, including potential financial impacts.

💡 Hint: Consider the trade-offs between risk management and customer service.

Challenge and get performance evaluation