• DocumentCode
    1120999
  • Title

    Nonparametric Data Reduction

  • Author

    Fukunaga, K. ; Mantock, J.M.

  • Author_Institution
    Department of Electrical Engineering, Purdue University, West Lafayette, IN 47907.
  • Issue
    1
  • fYear
    1984
  • Firstpage
    115
  • Lastpage
    118
  • Abstract
    A nonparametric data reduction technique is proposed. Its goal is to select samples that are ``representative´´ of the entire data set. The technique is iterative and is based on the use of a criterion function and nearest neighbor density estimates. Experiments are presented to demonstrate the algorithm.
  • Keywords
    Application software; Clustering algorithms; Databases; Indium tin oxide; Iterative algorithms; Nearest neighbor searches; Neural networks; Pattern analysis; Pattern classification; Sorting; Condensing algorithms; data reduction; nearest neighbor techniques;
  • fLanguage
    English
  • Journal_Title
    Pattern Analysis and Machine Intelligence, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0162-8828
  • Type

    jour

  • DOI
    10.1109/TPAMI.1984.4767485
  • Filename
    4767485
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=1120999