Data Mining and Data Warehouse MCQs with answers Page - 14

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Q. The ____________ of data could result in the disclosure of information that is deemed to be confidential.

  • (A) authorized use.
  • (B) unauthorized use.
  • (C) authenticated use.
  • (D) unauthenticated use.

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Q. ___________ data are noisy and have many missing attribute values.

  • (A) preprocessed.
  • (B) cleaned.
  • (C) real-world.
  • (D) transformed.

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Q. The rise of DBMS occurred in early ___________.

  • (A) 1950s.
  • (B) 1960s
  • (C) 1970s
  • (D) 1980s.

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Q. SQL stand for _________.

  • (A) standard query language.
  • (B) structured query language.
  • (C) standard quick list.
  • (D) structured query list.

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Q. Which of the following is not a data mining metric?

  • (A) space complexity.
  • (B) time complexity.
  • (C) roi.
  • (D) all of the above.

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Q. Reducing the number of attributes to solve the high dimensionality problem is called as ________.

  • (A) dimensionality curse.
  • (B) dimensionality reduction.
  • (C) cleaning.
  • (D) overfitting.

A

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Q. Data that are not of interest to the data mining task is called as ______.

  • (A) missing data.
  • (B) changing data.
  • (C) irrelevant data.
  • (D) noisy data.

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Q. ______ are effective tools to attack the scalability problem.

  • (A) sampling.
  • (B) parallelization
  • (C) both a & b.
  • (D) none of the above.

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Q. Market-basket problem was formulated by __________.

  • (A) agrawal et al.
  • (B) steve et al.
  • (C) toda et al.
  • (D) simon et al.

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Q. Data mining helps in __________.

  • (A) inventory management.
  • (B) sales promotion strategies.
  • (C) marketing strategies.
  • (D) all of the above.

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