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Selecting Objects for ALVOT

  • Miguel Angel Medina-Pérez
  • Milton García-Borroto
  • Yenny Villuendas-Rey
  • José Ruiz-Shulcloper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4225)

Abstract

ALVOT is a model of supervised classification based on partial precedences. In this paper a new object selection method based on a voting procedure for ALVOT is proposed. The method was developed for dealing with databases having objects described by features that are not exclusively numeric or categorical. A comparative numerical experiment was performed with different algorithms of object selection. The experimental results show a good performance of the proposed method with respect to the other algorithms.

Keywords

Radial Base Function Network Supervise Classification Partial Evaluation Vote Power Partial Precedence 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Miguel Angel Medina-Pérez
    • 1
  • Milton García-Borroto
    • 2
  • Yenny Villuendas-Rey
    • 1
  • José Ruiz-Shulcloper
    • 3
  1. 1.University of Ciego de ÁvilaCuba
  2. 2.Bioplants CenterUNICA, C. de ÁvilaCuba
  3. 3.Advanced Technologies Applications CenterMINBASCuba

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