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* Generalized Disciminant Analysis for MataLab version for Windows 5.2.0.3084 *
* *
* Gaston Baudat & Fatiha Anouar / 21st October 2000 / Exton PA 19341 USA *
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This MatLab (5) version of the GDA uses the method of resolution presented in:
"Generalized Discriminant Analysis Using a Kernel Approach" (Baudat, Anouar 2000)
Neural Computation 12,2385-2404 (2000)
Need the following files (*.m):
KernelFunction.m The kernel current function.
EigenSystem.m Evaluate and sort the eigen values and vectors.
DataSt.m Center and normalize the data.
Iris.m The Fisher's iris data (3 x 50 samples / 4 variables)
BuildGDA.m Build the GDA solution (give a data structure)
SpreadGDA.m Spread test vectors into the GDA discriminant subspace.
PlotGDA.m Plot data into one, or two, discriminant axes.
GDA_Iiris.m An example of the GDA with the Fishier's iris data
The GDA_Iris.m file gives an example of the GDA using the classic Fishier's iris data.
To test the user can compare the results with (Baudat, Anouar 2000).
The orignial kernel was a Gaussian with sigma = 0.7.
Gaston Baudat & Fatiha Anouar
Any questions, or comments can be sent to:
gbaudat@voicenet.com or fanouar@voicenet.com
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