Worcester Polytechnic Institute Electronic Theses and Dissertations Collection

Title page for ETD etd-050406-124140

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


    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.

  • Moraski.pdf

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