Title :
Application of self-organizing network and MLP for fuzzy rule extraction
Author :
Gaweda, Adam E. ; Zurada, Jacek M.
Author_Institution :
Dept. of Electr. Eng., Louisville Univ., KY, USA
Abstract :
A multi-stage algorithm for classification and fuzzy rule extraction from data based on a self-organizing network and a two-layer perceptron network is proposed. Self-organizing techniques are applied to find data prototypes, which are subsequently used to initialize the perceptron network and to produce membership functions from the learned mapping. Fuzzy rules created by the algorithm provide linguistic description of the relationship encoded in data
Keywords :
fuzzy neural nets; fuzzy set theory; inference mechanisms; knowledge acquisition; multilayer perceptrons; pattern classification; self-organising feature maps; unsupervised learning; fuzzy inference; fuzzy rule extraction; fuzzy set theory; knowledge acquisition; membership functions; multilayer perceptron; pattern classification; self-organizing network; unsupervised learning; Clustering algorithms; Data mining; Electronic mail; Fuzzy neural networks; Fuzzy sets; Fuzzy systems; Inference algorithms; Neural networks; Prototypes; Self-organizing networks;
Conference_Titel :
Neural Networks, 1999. IJCNN '99. International Joint Conference on
Conference_Location :
Washington, DC
Print_ISBN :
0-7803-5529-6
DOI :
10.1109/IJCNN.1999.830856
