You create a binary classification model. You need to evaluate the model performance. Which two metrics can you use? Each correct answer presents a complete solution. NOTE: Each correct selection is worth one point.
Suggested Answer:BC🗳️
The evaluation metrics available for binary classification models are: Accuracy, Precision, Recall, F1 Score, and AUC. Note: A very natural question is: 'Out of the individuals whom the model, how many were classified correctly (TP)?' This question can be answered by looking at the Precision of the model, which is the proportion of positives that are classified correctly. Reference: https://docs.microsoft.com/en-us/azure/machine-learning/studio/evaluate-model-performance
This section is not available anymore. Please use the main Exam Page.DP-100 Exam Questions
Log in to ExamTopics
Sign in:
Community vote distribution
A (35%)
C (25%)
B (20%)
Other
Most Voted
A voting comment increases the vote count for the chosen answer by one.
Upvoting a comment with a selected answer will also increase the vote count towards that answer by one.
So if you see a comment that you already agree with, you can upvote it instead of posting a new comment.
kolakone
Highly Voted 1 year, 3 months ago[Removed]
Most Recent 8 months, 1 week ago