| Autor: |
Hutchison, David, Kanade, Takeo, Kittler, Josef, Kleinberg, Jon M., Mattern, Friedemann, Mitchell, John C., Naor, Moni, Nierstrasz, Oscar, Pandu Rangan, C., Steffen, Bernhard, Sudan, Madhu, Terzopoulos, Demetri, Tygar, Doug, Vardi, Moshe Y., Weikum, Gerhard, de Sá, Joaquim Marques, Alexandre, Luís A., Duch, Włodzisław, Mandic, Danilo, Parra, Xavier |
| Zdroj: |
Artificial Neural Networks - ICANN 2007 (978-3-540-74689-8); 2007, p520-528, 9p |
| Abstrakt: |
This paper presents a radial basis function neural network which leads to classifiers of lower complexity by using a qualitative radial function based on distance discretization. The proposed neural network model generates smaller solutions for a similar generalization performance, rising to classifiers with reduced complexity in the sense of fewer radial basis functions. Classification experiments on real world data sets show that the number of radial basis functions can be reduced in some cases significantly without affecting the classification accuracy. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Complementary Index |
| Externí odkaz: |
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