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CFA Level I · CFA Level I Exam · Introduction to Financial Data Science

An analyst computes term frequency-inverse document frequency (TF-IDF) for the word "covenant" in a loan filing. The word appears 6 times in a filing of 200 tokens, and it appears in 10 of 1,000 filings in the corpus. Using IDF = ln(total documents / documents containing the term), the TF-IDF score is closest to:

The TF-IDF score is about 0.14. Term frequency is 6/200 = 0.03, and inverse document frequency is ln(1,000/10) = 4.605. Multiplying gives 0.138. The value 0.03 ignores the IDF component, which rewards rare words.

  1. A0.03
  2. B0.14Correct
  3. C0.28

Explanation

TF = 6/200 = 0.03. IDF = ln(1,000/10) = ln(100) = 4.605. TF-IDF = 0.03 × 4.605 = 0.138, about 0.14. The 0.03 option uses TF alone, and 0.28 doubles the result.

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