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IEEE-INNS-ENNS International Joint Conference on Neural Networks (IJCNN'00)-Volume 3
The Role of Multiple, Linear-Projection Based Visualization Techniques in RBF-Based Classification of High Dimensional Data
Como, Italy
July 24-July 27
ISBN: 0-7695-0619-4
ASCII Text
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A. Agogino, J. Ghosh, S.J. Perantonis, V. Virvilis, S. Petridis, P.J.G. Lisboa, "The Role of Multiple, Linear-Projection Based Visualization Techniques in RBF-Based Classification of High Dimensional Data," Neural Networks, IEEE - INNS - ENNS International Joint Conference on, vol. 3, pp. 3047, IEEE-INNS-ENNS International Joint Conference on Neural Networks (IJCNN'00)-Volume 3, 2000.
 
 
BibTex
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@article{ 10.1109/IJCNN.2000.861279,
author = {A. Agogino and J. Ghosh and S.J. Perantonis and V. Virvilis and S. Petridis and P.J.G. Lisboa},
title = {The Role of Multiple, Linear-Projection Based Visualization Techniques in RBF-Based Classification of High Dimensional Data},
journal ={Neural Networks, IEEE - INNS - ENNS International Joint Conference on},
volume = {3},
year = {2000},
issn = {1098-7576},
pages = {3047},
doi = {http://doi.ieeecomputersociety.org/10.1109/IJCNN.2000.861279},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
x 
 
TY - CONF
JO - Neural Networks, IEEE - INNS - ENNS International Joint Conference on
TI - The Role of Multiple, Linear-Projection Based Visualization Techniques in RBF-Based Classification of High Dimensional Data
SN - 1098-7576
SP
EP
A1 - A. Agogino,
A1 - J. Ghosh,
A1 - S.J. Perantonis,
A1 - V. Virvilis,
A1 - S. Petridis,
A1 - P.J.G. Lisboa,
PY - 2000
VL - 3
JA - Neural Networks, IEEE - INNS - ENNS International Joint Conference on
ER -
 
A. Agogino, University of Texas at Austin
J. Ghosh, University of Texas at Austin
S.J. Perantonis, National Center for Scientific Research ?Demokritos?
V. Virvilis, National Center for Scientific Research ?Demokritos?
S. Petridis, National Center for Scientific Research ?Demokritos?
P.J.G. Lisboa, Liverpool John Moores University
This paper presents a method for the 3D visualization of the structure of radial basis function networks using traditional and novel methods of dimensionality reduction. This method allows the visualization of basis function characteristics (centers and widths) along with second level weights. To facilitate the interpretation of a wide variety of high dimensional problems, several forms of projections into 2D or 3D spaces can be used interactively. The traditional methods of Principal Component Analysis and Fisher's linear discriminant are used as well as a novel linear projection method.
Citation:
A. Agogino, J. Ghosh, S.J. Perantonis, V. Virvilis, S. Petridis, P.J.G. Lisboa, "The Role of Multiple, Linear-Projection Based Visualization Techniques in RBF-Based Classification of High Dimensional Data," ijcnn, vol. 3, pp.3047, IEEE-INNS-ENNS International Joint Conference on Neural Networks (IJCNN'00)-Volume 3, 2000
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