My Learning Cart
?
Categories
Account

Which metric is best used for imbalanced datasets?

₹0.0
Login to Download
  • 📥 Instant PDF Download
  • ♾ Lifetime Access
  • 🛡 Secure & Original Content

What’s inside this PDF?

Question: Which metric is best used for imbalanced datasets?

Options:

  1. Accuracy
  2. F1 Score
  3. Mean Squared Error
  4. R-squared

Correct Answer: F1 Score

Solution: 

F1 Score is the harmonic mean of precision and recall, making it more suitable for imbalanced datasets where one class is more prevalent.

Which metric is best used for imbalanced datasets?

Practice Questions

Q1
Which metric is best used for imbalanced datasets?
  1. Accuracy
  2. F1 Score
  3. Mean Squared Error
  4. R-squared

Questions & Step-by-Step Solutions

Which metric is best used for imbalanced datasets?
  • Step 1: Understand what an imbalanced dataset is. This is 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: Understand the F1 Score. The F1 Score combines precision and recall into one number, balancing both metrics.
  • Step 5: Recognize that the F1 Score is useful for imbalanced datasets because it focuses on the minority class, which is often more important.
No concepts available.
Soulshift Feedback ×

On a scale of 0–10, how likely are you to recommend The Soulshift Academy?

Not likely Very likely
Home Practice Performance eBooks