Essay

Explain error attribution when the cat detector outputs an appropriate bounding box but the final breed label is incorrect.

Question: In a pipeline consisting of a cat detector and a cat breed classifier, explain why a misclassification of a Siamese cat is attributed to the breed classifier if the cat detector outputs an appropriate bounding box.

Sample answer: When the cat detector outputs an appropriate bounding box, it means it has successfully identified and located the cat in the image, thereby completing its designated task. Consequently, if the system subsequently fails to label the Siamese cat correctly, the error cannot be attributed to the detector. Instead, the failure must lie in the cat breed classifier, which failed to correctly identify the breed from the properly bounded image region.

Key points:

  • An appropriate bounding box confirms the cat detector completed its task successfully.
  • Errors in the final breed label are isolated from the detector if the detector's output is correct.
  • The misclassification of the Siamese cat must be attributed to the cat breed classifier.

Rubric: Answers must explain that an appropriate bounding box indicates the cat detector successfully performed its role, shifting the source of the final breed misclassification error entirely to the subsequent component, which is the cat breed classifier.

0

1

Updated 2026-05-26

Contributors are:

Who are from:

Tags

Machine Learning

Deep Learning

Supervised Learning

Dive into Deep Learning @ D2L

Data Science

Machine Learning Strategy

Related