PROCEEDINGS IPMU '08
A preliminary study of the effect of feature selection in evolutionary RBFN design
M.D. Pérez-Godoy, J.J. Aguilera, F.J. Berlanga, V. Rivas, A.J. Rivera.
In this paper, the effect of the
inclusion of a feature selection stage
previous to the RBFNs design is
analyzed.
Two different RBFNs design
algorithms have been used: a
cooperative-competitive scheme,
where each individual is a single
neuron, and a Pittsburgh evolutionary
scheme, where each individual
is a complete network. On the other
hand, six different feature selection
algorithms (three filter and three
wrapper) have been considered.
The experimentation shows the generalization
ability of the obtained
RBFNs (with and without applying
feature selection). Furthermore the
inclusion of an FS stage leads to
less complicated network structure
and thus increases the simplicity
of the system and the efficiency in
processing data.
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