CompTIA DataX (DY0-001) — Question 27

A computer vision model is trained to identify cats on a training set that is composed of both cat and dog images. The model predicts a picture of a cat is a dog. Which of the following describes this error?

Answer options

• A. Error due to reality
• B. False positive error
• C. Sampling error
• D. Type II error

Correct answer: D

Explanation

The correct answer is D, Type II error, which occurs when a model fails to identify a positive instance, in this case, misclassifying a cat as a dog. Options A and C do not accurately represent the situation, while B refers to a false positive, which is not applicable here since the model predicted a negative outcome (dog) instead of a positive one (cat).