• DocumentCode
    2110492
  • Title

    Demonstration of Principal Component Analysis on TI-86

  • Author

    Stuerke, Cecil

  • Author_Institution
    Member, IEEE
  • fYear
    2008
  • fDate
    17-20 April 2008
  • Firstpage
    1
  • Lastpage
    5
  • Abstract
    We often measure a variety of features when attempting to perform classification. Principal component analysis (PCA) can assist the multivariate investigation by reducing dimensionality and by maximizing feature space variance. For demonstration, this paper shows the techniques for finding the improved feature space and it shows how to project data into this space, using the native commands of the TI-86 calculator.
  • Keywords
    electronic calculators; principal component analysis; TI-86 calculator; multivariate investigation; principal component analysis; Covariance matrix; Data visualization; Discrete transforms; Graphics; Linear discriminant analysis; Performance analysis; Performance evaluation; Principal component analysis; Scattering; Training data;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Region 5 Conference, 2008 IEEE
  • Conference_Location
    Kansas City, MO
  • Print_ISBN
    978-1-4244-2076-6
  • Electronic_ISBN
    978-1-4244-2077-3
  • Type

    conf

  • DOI
    10.1109/TPSD.2008.4562756
  • Filename
    4562756
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=2110492