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Which of the following is the correct Python syntax to compute cosine similarity using sklearn for two vectors A and B?

easy📝 Syntax Q3 of 15
NLP - Text Similarity and Search
Which of the following is the correct Python syntax to compute cosine similarity using sklearn for two vectors A and B?
Acosine_similarity([A], [B])
Bcosine_similarity(A, B).sum()
Ccosine_similarity(A, B, axis=1)
Dcosine_similarity(A, B)
Step-by-Step Solution
Solution:

  1. Step 1: Recall sklearn cosine_similarity input format

    sklearn's cosine_similarity expects 2D arrays, so vectors must be wrapped in lists.

  2. Step 2: Identify correct syntax

    Passing [A] and [B] creates 2D arrays; direct A, B (1D) causes error.

  3. Final Answer:

    cosine_similarity([A], [B]) -> Option A

  4. Quick Check:

    Correct sklearn syntax = wrap vectors in lists [OK]
Quick Trick: Wrap vectors in lists for sklearn cosine_similarity [OK]
Common Mistakes:
MISTAKES
  • Passing 1D arrays directly causes errors
  • Using extra parameters like axis incorrectly
  • Summing similarity output unnecessarily

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