SEARCH

SEARCH BY CITATION

Keywords:

  • classification;
  • data reduction;
  • neural networks;
  • pattern recognition

Abstract

The Bayesian data reduction algorithm (BDRA) is compared to traditional classification methods as well as feed forward artificial neural networks through a rigorous experiment. The BDRA performs comparably to alternative techniques and approaches theoretical optimal classification rates. Furthermore, it has a fundamentally different method for determining class membership. This study is novel in that it explores how the BDRA relates to established techniques, how it might be used in an explanatory manner, and how best to use it. © 2009 Wiley Periodicals, Inc. Complexity, 2010