Research Commons
      • Browse 
        • Communities & Collections
        • Titles
        • Authors
        • By Issue Date
        • Subjects
        • Types
        • Series
      • Help 
        • About
        • Collection Policy
        • OA Mandate Guidelines
        • Guidelines FAQ
        • Contact Us
      • My Account 
        • Sign In
        • Register
      View Item 
      •   Research Commons
      • University of Waikato Research
      • Computing and Mathematical Sciences
      • Computer Science Working Paper Series
      • 2002 Working Papers
      • View Item
      •   Research Commons
      • University of Waikato Research
      • Computing and Mathematical Sciences
      • Computer Science Working Paper Series
      • 2002 Working Papers
      • View Item
      JavaScript is disabled for your browser. Some features of this site may not work without it.

      A logic boosting approach to inducing multiclass alternating decision trees

      Holmes, Geoffrey; Pfahringer, Bernhard; Kirkby, Richard Brendon; Frank, Eibe; Hall, Mark A.
      Thumbnail
      Files
      uow-cs-wp-2002-01.pdf
      690.8Kb
      Find in your library  
      Citation
      Export citation
      Holmes, G., Pfahringer, B., Kirkby, R., Frank, E. & Hall, M. (2002). A logic boosting approach to inducing multiclass alternating decision trees. (Working paper 01/02). Hamilton, New Zealand: University of Waikato, Department of Computer Science.
      Permanent Research Commons link: https://hdl.handle.net/10289/1012
      Abstract
      The alternating decision tree (ADTree) is a successful classification technique that combine decision trees with the predictive accuracy of boosting into a ser to interpretable classification rules. The original formulation of the tree induction algorithm restricted attention to binary classification problems. This paper empirically evaluates several methods for extending the algorithm to the multiclass case by splitting the problem into several two-class LogitBoost procedure to induce alternating decision trees directly. Experimental results confirm that this procedure is comparable with methods that are based on the original ADTree formulation in accuracy, while inducing much smaller trees.
      Date
      2002-03
      Type
      Working Paper
      Series
      Computer Science Working Papers
      Report No.
      01/02
      Publisher
      University of Waikato, Department of Computer Science
      Collections
      • 2002 Working Papers [12]
      Show full item record  

      Usage

      Downloads, last 12 months
      86
       
       

      Usage Statistics

      For this itemFor all of Research Commons

      The University of Waikato - Te Whare Wānanga o WaikatoFeedback and RequestsCopyright and Legal Statement