Error in naIVE BIAS ASSIGNMENT

Course Q&A Natural Language Processing NLP with Classification and Vector Spaces
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{moderator edit - solution code removed}

THIS CODE OUTPUT MATCHES RESULTS BUT FAILES TEST cases says dictionary wrong values.
while all other test cases which includes this function passes.
can anyone explain

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You are making the most common mistake on this function. When you see a word, you are adding 1 to the positive or negative count. The point is to use the frequency of that word appearing in a positive or negative tweet. That’s what they mean by the comments that they gave you in the template code.

1 Like
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It sounds like your dictionary’s structure or values don’t match the test case’s expectations. Double-check:

  1. Key Names: Ensure they match exactly (case-sensitive).
  2. Value Types: Verify types (e.g., int, float, list).
  3. Formatting: Round floats, sort lists, or trim strings if needed.
  4. Extra/Missing Keys: Remove unnecessary keys or add missing ones.

Print your output and compare it with the expected result to spot differences. Let me know if you need help debugging! :blush:

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thanks a lot it worked