Plurality voting-based multiple classifier systems: statistically independent with respect to dependent classifier sets

@article{Demirekler2002PluralityVM,
  title={Plurality voting-based multiple classifier systems: statistically independent with respect to dependent classifier sets},
  author={M{\"u}beccel Demirekler and Hakan Altinçay},
  journal={Pattern Recognition},
  year={2002},
  volume={35},
  pages={2365-2379}
}
Abstract The simultaneous use of multiple classifiers has been shown to provide performance improvement in classification problems. The selection of an optimal set of classifiers is an important part of multiple classifier systems and the independence of classifier outputs is generally considered to be an advantage for obtaining better multiple classifier systems. In this paper, the need for the classifier independence is interrogated from classification performance point of view. The… CONTINUE READING
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