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4 cards from this section. Quick, good the night before a test.
Define True Positive.
Look for the correct identification of positive cases.
What does accuracy measure?
Think about total correct predictions versus total predictions.
What does a True Positive indicate?
Consider what 'true' means in a prediction context.
Accuracy is calculated as?
Think about the total count of correct outcomes.
You have a model that correctly identifies 120 out of 150 positive cases and mistakenly identifies 30 as positive. Calculate the model's accuracy, precision, and recall.
Think systematically through definitions and formulas.
Discuss a scenario where high recall is necessary but low precision is acceptable. What would it look like?
Think about contexts where missing a positive could have severe consequences.
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