Learn Before
Short Answer

How can a search method return the wrong result even when its score order is correct?

Question: In one to three sentences, explain how a system can still produce an inferior output even if its scoring rule ranks the truly best candidate above that output.

Sample answer: The search procedure may be approximate, so it does not guarantee that it will explore enough possibilities to find the globally best candidate. Even with a correct scoring rule, the search can stop on a lower-scoring option and return that one instead.

Key points:

  • The search method is approximate
  • It may miss the globally best candidate
  • The scoring rule itself can still be correct

Rubric: Full credit: mentions that the search procedure is approximate and can fail to find the true best candidate even when the scoring rule ranks it higher. Partial credit: refers to search failure without clearly stating that the search is approximate. No credit: blames the scoring rule rather than the search process.

0

1

Updated 2026-08-12

Contributors are:

Who are from:

Tags

Machine Learning

Deep Learning

Supervised Learning

Dive into Deep Learning @ D2L

Data Science

Machine Learning Strategy

Machine Learning Yearning @ DeepLearning.AI