MDFT Academy Quizzes

Which metric should you use?

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.

The forest contains mostly sick trees. Sending a crew out to tend to a sick tree is very expensive, so you want to avoid false negatives as much as possible.

Which metric or combination of metrics should you use to evaluate the model?

Choose all correct answers from the options below.

I'm sorry, your answers are not correct.

Accuracy is incorrect. Accuracy is not a good choice when the dataset is biased.
Precision is incorrect. We should use the precision when we are trying to avoid false positives as much as possible.
Recall is correct
Micro Average is incorrect. The micro average is a metric for multiclass classification models.

We haven't covered the micro average yet, this is a metric for evaluating a multiclass classification model. You will learn about this metric in the next section of the training.

4. Binary Classification

Which metric should you use?