You have built a binary classification model to predict if a tree in a forest is sick or healthy. A prediction with an output value of 1.0 means that the model is 100% confident that a tree is healthy.
You calculate the AUC value of your tree prediction model and get a value of 0.9.
Is this good or bad?
Choose the correct answer from the options below.
Please select at least one answer!
Congratulations, you are correct!
I'm sorry, your answer is not correct.
This is good, it means that 90% of all predictions are correct is incorrect. The AUC does not specify how many predictions are correct.
This is bad, it means that 10% of all predictions are correct is incorrect. The AUC does not specify how many predictions are correct.
This is good, it means the model has excellent prediction quality is correct
This is bad, it means the model has terrible prediction quality is incorrect. An AUC value of 0.9 or higher indicates that the model has excellent predictive quality.
Remember, the AUC metric has no unit. An AUC value of 0.9 is great, but the number itself doesn't mean anything.