CompTIA
DY0-001 · Question #64
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…
The correct answer is D. Type II error. Classifying an actual cat (positive instance) as a dog (negative prediction) is a false negative, which corresponds to a Type II error.
Modeling, Analysis, and Outcomes
Question
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?
Options
- AError due to reality
- BFalse positive error
- CSampling error
- DType II error
How the community answered
(67 responses)- A3% (2)
- B4% (3)
- C7% (5)
- D85% (57)
Explanation
Classifying an actual cat (positive instance) as a dog (negative prediction) is a false negative, which corresponds to a Type II error.
Topics
#Type II error#false negative#classification error#model evaluation
Community Discussion
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