A Genetic Integrated Fuzzy Classifier

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Abstract

This paper introduces a new classifier, that is based on fuzzy-integration schemes controlled by a genetic optimisation procedure. Two different types of integration are proposed here, and are validated by experiments on real data sets of biological cells.The performance of our classifier is tested against a feed-forward neural network and a Support Vector Machine. Results show the good performance and robustness of the integrated classifier strategies.
Lingua originaleEnglish
pagine (da-a)411-420
Numero di pagine10
RivistaPattern Recognition Letters
Volume26
Stato di pubblicazionePublished - 2005

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All Science Journal Classification (ASJC) codes

  • Software
  • Signal Processing
  • Computer Vision and Pattern Recognition
  • Artificial Intelligence

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