| qkspecc-class {qkerntool} | R Documentation |
Class "qkspecc"
Description
The qKernel Spectral Clustering Class
Objects from the Class
Objects can be created by calls of the form new("qkspecc", ...).
or by calling the function qkspecc.
Slots
clust:Object of class
"vector"containing the cluster assignmentseVec:Object of class
"matrix"containing the corresponding eigenvector in each clustereVal:Object of class
"vector"containing the corresponding eigenvalue for each clusterwithinss:Object of class
"vector"containing the within-cluster sum of squares for each cluster
Methods
- clust
signature(object = "qkspecc"): returns the cluster assignments- eVec
signature(object = "qkspecc"): returns the corresponding eigenvector in each cluster- eVal
signature(object = "qkspecc"): returns the corresponding eigenvalue for each cluster- xmatrix
signature(object = "qkspecc"): returns the original data matrix or a kernel Matrix- ymatrix
signature(object = "qkspecc"): returns The eigenvectors corresponding to theksmallest eigenvalues of the graph Laplacian matrix.- cndkernf
signature(object = "qkspecc"): returns the used kernel function- kcall
signature(object = "qkspecc"): returns the performed call
Author(s)
Yusen Zhang
yusenzhang@126.com
See Also
qkspecc, qkernel-class,
cndkernel-class
Examples
## 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)