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

₹0.0

Question: Which metric is used to evaluate the performance of a classification model that outputs probabilities?

Options:

Correct Answer: Log Loss

Solution:

Log Loss evaluates the performance of a classification model that outputs probabilities, penalizing incorrect classifications more heavily.

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

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.