| Labelling {svcR} | R Documentation |
Labelling methods try to identify clusters in a grid.
## S4 method for signature 'findSvcModel':
Labelling.compute(x,
MetLab = 1,
MatriceKernel = MK,
MatriceK = M_K,
pp = vpp,
Nu = 1,
G = 1,
q = 1,
ncol = 1,
nlin = 1,
RadiusC = 2,
r = 2,
KernChoice = 0.01,
NbClassInData = 0.01 )
## S4 method for signature 'findSvcModel':
AdjacencyPP(x, MatriceKernel=matrix(), Vec1=vector(), Vec2=vector())
## S4 method for signature 'findSvcModel':
Adjacency(x, MatriceKernel=matrix())
## S4 method for signature 'findSvcModel':
MST_labelling(x, MatriceKernel=matrix())
## S4 method for signature 'findSvcModel':
KNN_labelling(x, MatriceKernel=matrix())
x |
a findSvcModel object |
MetLab |
option taking value "gridLabeling" (grid labelling) or "mstLabeling" (mst labelling) or "knnLabeling" (knn labelling) |
MatriceKernel |
kernel matrix with vector format |
MatriceK |
kernel matrix with vector format |
pp |
full matrix as a vector |
Nu |
kernel parameter |
G |
kernel parameter |
q |
kernel parameter |
ncol |
number of attributes |
nlin |
size of variables |
RadiusC |
model radius |
r |
residual radius |
KernChoice |
kernel id |
NbClassInData |
number of classes in data |
Vec1 |
vector for computing adjacency |
Vec2 |
vector for computing adjacency |
An S4 object of class labelling
The object is the svc model along with
the slots :
ClassPoints |
class of grid points |
NumPoints |
value fo grid points |
slots can not be accessed.
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 = findSvcModel.Test(); getNumPoints(fmc); # values of the grid