A Bee-Inspired Data Clustering Approach to Design RBF Neural Network Classifiers
Advances in intelligent systems and computingPublished 1 January 2014
Dávila Patrícia Ferreira Cruz, Renato Dourado Maia, Leandro A. Silva, Leandro Nunes de Castro
Citations31
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TL;DR
A bee-inspired algorithm to automatically select the number and location of basis functions to be used in such RBF network was designed to solve data clustering problems, where the centroids of clusters are used as centers for theRBF network.
Abstract
Different methods have been used to train radial basis function neural networks. This paper proposes a bee-inspired algorithm to automatically select the number and location of basis functions to be used in such RBF network. The algorithm was designed to solve data clustering problems, where the centroids of clusters are used as centers for the RBF network. The approach presented in this paper is preliminary evaluated in three synthetic datasets, two classification datasets and one function approximation problem, and its results suggest a potential for real-world application.
Keywords
Computer Science
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