Past work on missing information

  • Quantitatively focused
  • Treat missing information as “random variables” (Orchard)
  • Try to find reasonable/plausible maximums and minimums to constrain guessing
  • Data mining
  • Ignore all records with missing values
  • Replace missing values with mode or mean
  • Infer missing values from other records
  • All approaches assume a large corpus of available information, and that missing values can be computed based on other available information
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