Practice Common Mistakes to Avoid - 30.7 | 30. Confusion Matrix | CBSE Class 10th AI (Artificial Intelleigence)
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30.7 - Common Mistakes to Avoid

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Learning

Practice Questions

Test your understanding with targeted questions related to the topic.

Question 1

Easy

Why should we not rely solely on accuracy for model evaluation?

💡 Hint: Think about what happens if the majority class dominates the predictions.

Question 2

Easy

Explain how precision and recall differ in evaluating a classification model.

💡 Hint: Consider scenarios like spam detection or disease diagnosis.

Practice 1 more question and get performance evaluation

Interactive Quizzes

Engage in quick quizzes to reinforce what you've learned and check your comprehension.

Question 1

What is a major risk of relying on accuracy alone?

  • It can underestimate performance
  • It may miss critical errors
  • It is always accurate

💡 Hint: Consider what accuracy measures and what contexts it fails.

Question 2

True or False: Precision is not important in medical diagnosis.

  • True
  • False

💡 Hint: Think about how critical negative outcomes are in this field.

Solve and get performance evaluation

Challenge Problems

Push your limits with challenges.

Question 1

You have a classification model that predicts customer churn. The confusion matrix shows 80 true positives, 10 false positives, 15 false negatives, and 45 true negatives. Evaluate the model using accuracy, precision, recall, and F1 score. Discuss the implications.

💡 Hint: Check how variations in TP, FP, and FN affect these metrics.

Question 2

Analyze a scenario where a fraud detection model has low recall but high precision. What could be the business implications of these metrics?

💡 Hint: Think about costs associated with false negatives.

Challenge and get performance evaluation