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What does the F1 score represent in model evaluation?
What does the F1 score represent in model evaluation?
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What does the F1 score represent in model evaluation?
The harmonic mean of precision and recall
The average of precision and recall
The ratio of true positives to total predicted positives
The ratio of true positives to total actual positives
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The F1 score is the harmonic mean of precision and recall, providing a balance between the two metrics.
Questions & Step-by-step Solutions
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Q
Q: What does the F1 score represent in model evaluation?
Solution:
The F1 score is the harmonic mean of precision and recall, providing a balance between the two metrics.
Steps: 7
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Step 1: Understand that the F1 score is a way to measure how well a model performs.
Step 2: Know that two important metrics for evaluating models are precision and recall.
Step 3: Precision tells us how many of the predicted positive cases were actually positive.
Step 4: Recall tells us how many of the actual positive cases were correctly predicted by the model.
Step 5: The F1 score combines precision and recall into one number to give a balanced view.
Step 6: The F1 score is calculated using the formula: F1 = 2 * (Precision * Recall) / (Precision + Recall).
Step 7: A higher F1 score means a better balance between precision and recall.
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