Practice Accuracy - 30.3.1 | 30. Confusion Matrix | CBSE Class 10th AI (Artificial Intelleigence)
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30.3.1 - Accuracy

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Learning

Practice Questions

Test your understanding with targeted questions related to the topic.

Question 1

Easy

What is the formula for calculating accuracy?

💡 Hint: Think about how many correct predictions you need compared to all predictions.

Question 2

Easy

Why might accuracy be a misleading metric?

💡 Hint: Think about scenarios with many more negative cases.

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 is the main formula used to calculate accuracy?

  • TP / (TP + FN)
  • TP + TN / (TP + TN + FP + FN)
  • TP / (TP + TN)

💡 Hint: Remember both positive and negative predictions are included.

Question 2

True or False: Accuracy can be a reliable metric for all types of data sets.

  • True
  • False

💡 Hint: Think about how many predictions each class has.

Solve 1 more question and get performance evaluation

Challenge Problems

Push your limits with challenges.

Question 1

In a scenario with 300 instances: 200 actual negatives and 100 positives, a model predicts 80 positives but incorrectly identifies 30 as negatives. Calculate TP, TN, FP, FN, and accuracy.

💡 Hint: Break down the predictions using the definitions given earlier.

Question 2

You have a dataset with an extreme imbalance, say 90% negatives and only 10% positives. If your model predicts 95% correctly but misses most positives, discuss the implications of this accuracy.

💡 Hint: Consider what accuracy alone fails to explain in performance.

Challenge and get performance evaluation