• Media type: E-Article
  • Title: CONSTRUCTION AND EVALUATION OF CLASSIFIERS FOR FORENSIC DOCUMENT ANALYSIS
  • Contributor: Saunders, Christopher P.; Davis, Linda J.; Lamas, Andrea C.; Miller, John J.; Gantz, Donald T.
  • imprint: Institute of Mathematical Statistics, 2011
  • Published in: The Annals of Applied Statistics
  • Language: English
  • ISSN: 1932-6157
  • Origination:
  • Footnote:
  • Description: <p>In this study we illustrate a statistical approach to questioned document examination. Specifically, we consider the construction of three classifiers that predict the writer of a sample document based on categorical data. To evaluate these classifiers, we use a data set with a large number of writers and a small number of writing samples per writer. Since the resulting classifiers were found to have near perfect accuracy using leave-one-out crossvalidation, we propose a novel Bayesian-based cross-validation method for evaluating the classifiers.</p>
  • Access State: Open Access