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Quiz

Module 3 - Data and Data Exploration

DENISE PEASLEE 23 perguntas

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Perguntas do quiz (23)

  1. 1Which of the following is not a strategy for dealing with missing data?
    1. AEliminate data objects containing missing values
    2. BEstimate attributes with missing values
    3. CEliminate duplicate data objects
    4. DIgnore the missing values during analysis
  2. 2Which one of the following is not a data quality issue?
    1. ADuplicate data
    2. BMissing values
    3. CThe dimensionality of a data set
    4. DNoise
    5. EOutliers
  3. 3Is noise ever interesting or desirable?
    1. Ayes
    2. Bno
  4. 4Can noise objects be outliers?
    1. Ayes
    2. Bno
  5. 5Are noise objects always outliers?
    1. Ayes
    2. Bno
  6. 6Can noise make a typical value into an unusual one or vice versa?
    1. Ayes
    2. Bno
  7. 7Compute the Hamming distance between the following two binary vectors:
    x=0101010001
    y=0100011000
    [blank_start]Answer =[blank_end]
    1. A3
  8. 8Which approach, Jaccard or Hamming distance is more similar to the Simple Matching Coefficient and which approach is more similar to the cosine measure?
    1. AHamming is similar to Simple Matching Coefficient
      Jaccard is similar to Cosine
    2. BJaccard is similar to Simple Matching Coefficient
      Hamming is similar to Cosine
  9. 9Suppose that you are comparing how similar two organisms of different species are in terms of the number of genes they share. Which measure would you choose for comparing the genetic makeup of two organisms. Assume each organism is represented as a binary vector where each attribute is 1 if a particular gene is present and 0 if it is not present.
    1. AJaccard
    2. BHamming
  10. 10If you need to compare the genetic makeup of two organisms of the same species (i.e., two human beings), which proximity measure would you use? Note that human beings share 99.9% of the same genes.
    1. AJaccard
    2. BHamming
    3. COther

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Quiz sobre Module 3 - Data and Data Exploration, criado por DENISE PEASLEE em 12-03-2017.
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