Which of the following option is / are true for the interpretation of log loss as an evaluation metric? If a classifier is confident about an incorrect classification, then log-loss will penalize it heavily. For a particular observation, the classifier assigns a very small probability for the correct class then the corresponding contribution to the log loss will be very large. The lower the log loss, the better the model.

Crowdly

Add to Chrome

✅ The verified answer to this question is available below. Our community-reviewed solutions help you understand the material better.

Which of the following option is / are true for the interpretation of log loss as an evaluation metric?

If a classifier is confident about an incorrect classification, then log-loss will penalize it heavily.
For a particular observation, the classifier assigns a very small probability for the correct class then the corresponding contribution to the log loss will be very large.
The lower the log loss, the better the model.

1 and 2

1 and 3

1,2 and 3

2 and 3

Get Unlimited Answers To Exam Questions - Install Crowdly Extension Now!

Add to Chrome