Which metric is used to evaluate the performance of a classification model that

Practice Questions

Q1
Which metric is used to evaluate the performance of a classification model that outputs probabilities?
  1. Accuracy
  2. Log Loss
  3. F1 Score
  4. Mean Absolute Error

Questions & Step-by-Step Solutions

Which metric is used to evaluate the performance of a classification model that outputs probabilities?
  • Step 1: Understand that a classification model predicts categories (like 'yes' or 'no').
  • Step 2: Some models give probabilities instead of just categories (like 70% chance of 'yes').
  • Step 3: Log Loss is a way to measure how well the model's predicted probabilities match the actual outcomes.
  • Step 4: If the model predicts a high probability for the wrong category, Log Loss gives a bigger penalty.
  • Step 5: A lower Log Loss value means the model is performing better.
No concepts available.
Soulshift Feedback ×

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

Not likely Very likely