Text Categorization Using Weight Adjusted k -Nearest Neighbor Classification ∗

  • Han E
  • Karypis G
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Author-supplied keywords

  • access to computing facilities
  • and ibm partnership award
  • and no official endorsement
  • and nsf grant
  • army research office contract
  • be inferred
  • by nsf grant asc-9634719
  • classification
  • cray research inc
  • da
  • daah04-95-1-0538
  • data mining
  • does not necessarily reflect
  • fellow-
  • government
  • minnesota supercomputer institute
  • nearest neighbor classification
  • ship
  • should
  • text categorization
  • the content of which
  • the policy of the
  • this work was supported
  • was provided by ahpcrc
  • weight adjustment

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  • Eui-hong Sam Han

  • George Karypis

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