Practice Confusion Matrix (28.4.5) - Introduction to Model Evaluation - CBSE 10 AI (Artificial Intelleigence)
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Confusion Matrix

Practice - Confusion Matrix

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Learning

Practice Questions

Test your understanding with targeted questions

Question 1 Easy

What does a True Positive (TP) signify in a confusion matrix?

💡 Hint: Think of it as right answers for positive cases.

Question 2 Easy

Explain what a False Positive (FP) is.

💡 Hint: Consider it as a wrong answer for a positive case.

4 more questions available

Interactive Quizzes

Quick quizzes to reinforce your learning

Question 1

What is the purpose of a confusion matrix?

To visualize data
To evaluate model performance
To train models

💡 Hint: Consider what tools are used after training a machine learning model.

Question 2

True or False: True Negatives represent the number of negative classes that were incorrectly predicted as positive.

True
False

💡 Hint: Remember what 'true' means in this context.

1 more question available

Challenge Problems

Push your limits with advanced challenges

Challenge 1 Hard

Consider a model's confusion matrix: TP = 25, TN = 50, FP = 5, FN = 20. What is the accuracy, precision, and recall?

💡 Hint: Calculate each metric using their respective formulas.

Challenge 2 Hard

Discuss how you would improve a classification model if the confusion matrix shows a high number of False Negatives.

💡 Hint: Think about adjustments that could help the model learn better.

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