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      • Computer Science Working Paper Series
      • 2003 Working Papers
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      •   Research Commons
      • University of Waikato Research
      • Computing and Mathematical Sciences
      • Computer Science Working Paper Series
      • 2003 Working Papers
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      Mining data streams using option trees

      Holmes, Geoffrey; Pfahringer, Bernhard; Kirkby, Richard Brendon
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      Holmes, G., Pfahringer, B. & Kirkby, R. (2003). Mining data streams using option trees. (Working paper 08/03). Hamilton, New Zealand: University of Waikato, Department of Computer Science.
      Permanent Research Commons link: https://hdl.handle.net/10289/1004
      Abstract
      The data stream model for data mining places harsh restrictions on a learning algorithm. A model must be induced following the briefest interrogation of the data, must use only available memory and must update itself over time within these constraints. Additionally, the model must be able to be used for data mining at any point in time. This paper describes a data stream classification algorithm using an ensemble of option trees. The ensemble of trees is induced by boosting and iteratively combined into a single interpretable model. The algorithm is evaluated using benchmark datasets for accuracy against state-of-the-art algorithms that make use of the entire dataset.
      Date
      2003-09
      Type
      Working Paper
      Series
      Computer Science Working Papers
      Report No.
      08/03
      Publisher
      University of Waikato, Department of Computer Science
      Collections
      • 2003 Working Papers [8]
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