Question: Which metric is best suited for imbalanced classification problems?
Options:
Accuracy
Precision
Recall
F1 Score
Correct Answer: F1 Score
Solution:
The F1 Score is preferred in imbalanced classification problems as it considers both precision and recall.
Which metric is best suited for imbalanced classification problems?
Practice Questions
Q1
Which metric is best suited for imbalanced classification problems?
Accuracy
Precision
Recall
F1 Score
Questions & Step-by-Step Solutions
Which metric is best suited for imbalanced classification problems?
Step 1: Understand what imbalanced classification means. This occurs when one class has many more examples than the other class.
Step 2: Learn about precision. Precision measures how many of the predicted positive cases were actually positive.
Step 3: Learn about recall. Recall measures how many of the actual positive cases were correctly predicted.
Step 4: Recognize that in imbalanced datasets, focusing only on accuracy can be misleading because the model might predict the majority class well but fail on the minority class.
Step 5: Understand the F1 Score. The F1 Score is the harmonic mean of precision and recall, balancing both metrics.
Step 6: Conclude that the F1 Score is preferred for imbalanced classification problems because it provides a better measure of a model's performance on both classes.
No concepts available.
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