kernelMatrix {svcR}R Documentation

Computation of clustering model by support vector machine

Description

This function implements three kinds of kernel to build a kernal matrix: Euclidian, Radial-Base and Exponential.

Usage

## S4 method for signature 'vector':
kernelMatrix.compute(x, 
          SymMat        = 1,
          q             = 1,
          ncol          = 2,
          nlin          = 2,
          KernChoice    = 1)

Arguments

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)

Value

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

Author(s)

Nicolas Turenne - INRA France nicolas.turenne@jouy.inra.fr

References

N.Turenne , Some Heuristics to speed-up Support Vector Clustering , technical report 2006, INRA, France http://migale.jouy.inra.fr/~turenne/svc.pdf

Examples


## exemple with iris data

fmc = findModelCluster.Test(); 

fmc@MatriceK;


[Package svcR version 1.4.2 Index]