Worcester Polytechnic Institute Electronic Theses and Dissertations Collection

Title page for ETD etd-050406-124140


Document Typethesis
Author NameMoraski, Ashley M.
URNetd-050406-124140
TitleClassification via distance profile nearest neighbors
DegreeMS
DepartmentMathematical Sciences
Advisors
  • Jayson Wilbur, Advisor
  • Keywords
  • classification
  • distance profile nearest neighbor
  • Date of Presentation/Defense2006-05-04
    Availability unrestricted

    Abstract

    Most classification rules can be expressed in terms of a distance (or dissimilarity) from the point to be classified to each of the candidate classes. For example, linear discriminant analysis classifies points into the class for which the (sample) Mahalanobis distance is smallest. However, dependence among these point-to-group distance measures is generally ignored. The primary goal of this project is to investigate the properties of a general non-parametric classification rule which takes this dependence structure into account. A review of classification procedures and applications is presented. The distance profile nearest-neighbor classification rule is defined. Properties of the rule are then explored via application to both real and simulated data and comparisons to other classification rules are discussed.

    Files
  • Moraski.pdf

  • Browse by Author | Browse by Department | Search all available ETDs

    [WPI] [Library] [Home] [Top]

    Questions? Email etd-questions@wpi.edu
    Maintained by webmaster@wpi.edu