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")