Title :
Comparing different clustering techniques-RBF networks training
Author :
Brizzotti, M.M. ; de Carvalho, A.C.P.L.F.
Author_Institution :
Dept. de Ciencias de Comput. e Estatistica, Sao Paulo Univ., Brazil
Abstract :
Clustering techniques have a strong influence on the performance achieved by RBF neural networks. The article compares the performance achieved by RBF networks using seven different clustering techniques. For such, different sizes of RBF networks are trained and tested using an automatic target recognition data set. The performances of these RBF networks using each clustering technique are compared and analyzed
Keywords :
iterative methods; optimisation; pattern clustering; radial basis function networks; self-organising feature maps; tree searching; unsupervised learning; RBF networks training; automatic target recognition data set; clustering techniques; Automatic testing; Computer networks; Image analysis; Information science; Interpolation; Neural networks; Performance analysis; Radial basis function networks; Target recognition; Unsupervised learning;
Conference_Titel :
Neural Networks, 2000. Proceedings. Sixth Brazilian Symposium on
Conference_Location :
Rio de Janeiro, RJ
Print_ISBN :
0-7695-0856-1
DOI :
10.1109/SBRN.2000.889743
