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DOI: 10.14569/IJACSA.2017.080235
PDF

Logarithmic Spiral-based Construction of RBF Classifiers

Author 1: Mohamed Wajih Guerfala
Author 2: Amel Sifaoui
Author 3: Afef Abdelkrim

International Journal of Advanced Computer Science and Applications(IJACSA), Volume 8 Issue 2, 2017.

  • Abstract and Keywords
  • How to Cite this Article
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Abstract: Clustering process is defined as grouping similar objects together into homogeneous groups or clusters. Objects that belong to one cluster should be very similar to each other, but objects in different clusters will be dissimilar. It aims to simplify the representation of the initial data. The automatic classification recovers all the methods allowing the automatic construction of such groups. This paper describes the design of radial basis function (RBF) neural classifiers using a new algorithm for characterizing the hidden layer structure. This algorithm, called k-means Mahalanobis distance, groups the training data class by class in order to calculate the optimal number of clusters of the hidden layer, using two validity indexes. To initialize the initial clusters of k-means algorithm, the method of logarithmic spiral golden angle has been used. Two real data sets (Iris and Wine) are considered to improve the efficiency of the proposed approach and the obtained results are compared with basic literature classifier

Keywords: Radial Basis Function neural network; classification; k -means; validity index of Davis Bouldin; Mean Squared Error; Mahalanobis distance; Logarithmic spiral; golden angle; golden ratio

Mohamed Wajih Guerfala, Amel Sifaoui and Afef Abdelkrim, “Logarithmic Spiral-based Construction of RBF Classifiers” International Journal of Advanced Computer Science and Applications(IJACSA), 8(2), 2017. http://dx.doi.org/10.14569/IJACSA.2017.080235

@article{Guerfala2017,
title = {Logarithmic Spiral-based Construction of RBF Classifiers},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2017.080235},
url = {http://dx.doi.org/10.14569/IJACSA.2017.080235},
year = {2017},
publisher = {The Science and Information Organization},
volume = {8},
number = {2},
author = {Mohamed Wajih Guerfala and Amel Sifaoui and Afef Abdelkrim}
}



Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

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