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Asian Journal of Information Technology
Year: 2005  |  Volume: 4  |  Issue: 9  |  Page No.: 868 - 872

Labeled Neuro-Fuzzy Classifier

M. Nemissi, H. Seridi and H. Akdag    

Abstract: This study presents a model of Neuro-Fuzzy classification, which its conception is inspired from the labeled classification using Neural Networks. This last aims to improve the classification performances and to accelerate the training of the used classifier. It is based on the addition of a set of labels to all training examples. Tests will be then carried out with each of these labels to classify a new example. The advantage of this approach is the simplicity of its implementation, which does not require modification of the training algorithm. The proposed model is based on the use of this method with the NFC (Neuro Fuzzy Classifier). To appreciate its performances, tests are carried out on the Iris and human tight data basis by the NFC with and withwout labels.

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