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5 cards from this section. Quick, good the night before a test.
What is a confusion matrix?
Think about how predictions relate to truth.
What does True Positive (TP) mean?
It's about right predictions for positives.
What does a confusion matrix primarily visualize?
Consider which option evaluates outcomes.
True Positive means a positive class was correctly predicted.
Recall what it means to be positive in predictions.
A model predicts whether patients have a disease. In a sample of 200 patients, the model identifies 100 positive cases, with 80 true positive, 20 false positive, 80 true negative, and 20 false negative. What is the accuracy, precision, recall, and F1 score?
Break down the calculations for each metric and recalculate meticulously.
If a confusion matrix shows TP = 45, FP = 5, TN = 40, FN = 10, calculate not just metrics, but also explain the importance of the F1 score versus accuracy in this context.
Consider why accuracy may not always be the best metric. Reflect on its limitations.
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