4.2 - Metrics
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Practice Questions
Test your understanding with targeted questions
What does TP stand for in the context of a confusion matrix?
💡 Hint: Think about how many times we correctly predicted the positive class.
How would you calculate accuracy from a confusion matrix?
💡 Hint: Remember to add true positives and true negatives.
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Interactive Quizzes
Quick quizzes to reinforce your learning
What does a True Positive indicate?
💡 Hint: Think about what the 'True' refers to in this context.
Is a low F1-score an indication of poor model performance?
💡 Hint: Consider the relationship between precision and recall.
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Challenge Problems
Push your limits with advanced challenges
You have a dataset where 100 instances were tested. The confusion matrix shows TP=70, FP=10, TN=15, FN=5. What are the accuracy, precision, recall, and F1-score?
💡 Hint: Break down each metric using the confusion matrix values.
Propose a strategy to increase the precision of a model that has low precision currently while ensuring not to severely sacrifice recall.
💡 Hint: Think about what kind of adjustments help in precision without completely missing too many actual positive cases.
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