qkspecc-class {qkerntool} | R Documentation |
The qKernel Spectral Clustering Class
Objects can be created by calls of the form new("qkspecc", ...)
.
or by calling the function qkspecc
.
clust
:Object of class "vector"
containing the cluster assignments
eVec
:Object of class "matrix"
containing
the corresponding eigenvector in each cluster
eVal
:Object of class "vector"
containing
the corresponding eigenvalue for each cluster
withinss
:Object of class "vector"
containing
the within-cluster sum of squares for each cluster
signature(object = "qkspecc")
: returns the cluster assignments
signature(object = "qkspecc")
: returns the corresponding eigenvector in each cluster
signature(object = "qkspecc")
: returns the corresponding eigenvalue for each cluster
signature(object = "qkspecc")
: returns the original data matrix or a kernel Matrix
signature(object = "qkspecc")
: returns The eigenvectors corresponding to the k
smallest eigenvalues of the graph Laplacian matrix.
signature(object = "qkspecc")
: returns the used kernel function
signature(object = "qkspecc")
: returns the performed call
Yusen Zhang
yusenzhang@126.com
qkspecc
, qkernel-class
,
cndkernel-class
## Cluster the iris data set.
data("iris")
x=as.matrix(iris[,-5])
qspe <- qkspecc(x,kernel = "rbfbase", qpar = list(sigma = 10, q = 0.9),
Nocent=3, normalize="symmetric", maxk=15, iterations=1200)
clust(qspe)
eVec(qspe)
eVal(qspe)
xmatrix(qspe)
ymatrix(qspe)
cndkernf(qspe)