| qkLLE-class {qkerntool} | R Documentation |
Class "qkLLE"
Description
The qKernel Locally Linear Embedding class
Objects of class "qkLLE"
Objects can be created by calls of the form new("qkLLE", ...).
or by calling the qkLLE function.
Slots
prj:Object of class
"matrix"containing the reduced input datadims:Object of class
"numeric"containing the dimension of the target space (default 2)eVal:Object of class
"vector"containing the corresponding eigenvalueseVec:Object of class
"matrix"containing the corresponding eigenvectors
Methods
- prj
signature(object = "qkLLE"): returns the reduced input data- dims
signature(object = "qkLLE"): returns the dimension- eVal
signature(object = "qkLLE"): returns the eigenvalues- eVec
signature(object = "qkLLE"): returns the eigenvectors- xmatrix
signature(object = "qkLLE"): returns the used data matrix- kcall
signature(object = "qkLLE"): returns the performed call- cndkernf
signature(object = "qkLLE"): returns the used kernel function
Author(s)
Yusen Zhang
yusenzhang@126.com
See Also
qkernel-class,
cndkernel-class
Examples
## S4 method for signature 'matrix'
data(iris)
testset <- sample(1:150,20)
train <- as.matrix(iris[-testset,-5])
labeltrain<- as.integer(iris[-testset,5])
test <- as.matrix(iris[testset,-5])
plot(train ,col=labeltrain, xlab="1st Principal Component",ylab="2nd Principal Component")
# ratibase(c=1,q=0.8)
d_low <- qkLLE(train, kernel = "ratibase", qpar = list(c=1,q=0.8), dims=2, k=5)
#plot the data projection on the components
plot(prj(d_low),col=labeltrain,xlab="1st Principal Component",ylab="2nd Principal Component")
## S4 method for signature 'qkernmatrix'
# ratibase(c=0.1,q=0.8)
qkfunc <- ratibase(c=0.1,q=0.8)
ktrain1 <- qkernmatrix(qkfunc,train)
d_low <- qkLLE(ktrain1, dims = 2, k=5)
#plot the data projection on the components
plot(prj(d_low),col=labeltrain,xlab="1st Principal Component",ylab="2nd Principal Component")