Practice Structure of a Confusion Matrix - 30.2 | 30. Confusion Matrix | CBSE Class 10th AI (Artificial Intelleigence)
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30.2 - Structure of a Confusion Matrix

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Learning

Practice Questions

Test your understanding with targeted questions related to the topic.

Question 1

Easy

What does 'True Positive' mean in a confusion matrix?

💡 Hint: Think about how the model identifies spam.

Question 2

Easy

Which position in the matrix represents False Negatives?

💡 Hint: Look for what the model missed.

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 in a confusion matrix represent?

  • Correct positive prediction
  • Correct negative prediction
  • Incorrect positive prediction

💡 Hint: Remember the definition of True Positive.

Question 2

True or False: A False Negative refers to cases where the model incorrectly predicts the negative class.

  • True
  • False

💡 Hint: Think about what the model misses.

Solve 2 more questions and get performance evaluation

Challenge Problems

Push your limits with challenges.

Question 1

Given the confusion matrix statistics below:

Predicted Positive Predicted Negative
Actual Positive 55 (TP) 15 (FN)
Actual Negative 10 (FP) 60 (TN)
How can you calculate Precision and Recall? Discuss which metric would be more important in a medical diagnosis context.

💡 Hint: Consider the consequences of missing actual positives in a medical setting.

Question 2

If you have a dataset with 1,000 examples where 900 are negative and 100 are positive, how could a model with high accuracy still be inadequate based on the confusion matrix?

💡 Hint: Reflect on class distributions and implications on model performance.

Challenge and get performance evaluation