kernelMatrix {svcR} | R Documentation |
This function implements three kinds of kernel to build a kernal matrix: Euclidian, Radial-Base and Exponential.
## S4 method for signature 'vector': kernelMatrix.compute(x, SymMat = 1, q = 1, ncol = 2, nlin = 2, KernChoice = 1)
x |
data matrix with a vector format |
SymMat |
indicator to know if matrix is symetrical or not |
q |
q parameter of the model |
ncol |
number of columns of the data matrix |
nlin |
number of lines of the data matrix |
KernChoice |
option taking value 0 (Euclidian) or 1 (RBF) or 2 (Exponential) |
An S4 object of class kernelMatrix
The object is the svc model along with
the slots :
matrixKernel |
kernel matrix with a vector format |
matrixK |
kernel matrix with a matrix format |
slots can be accessed by object@slot
Nicolas Turenne - INRA France nicolas.turenne@jouy.inra.fr
N.Turenne , Some Heuristics to speed-up Support Vector Clustering , technical report 2006, INRA, France http://migale.jouy.inra.fr/~turenne/svc.pdf
## exemple with iris data fmc = findModelCluster.Test(); fmc@MatriceK;