KPC: Function to calculate the principal components of a kernel.
In Luisiglm/KBoost: Inference of gene regulatory networks from gene expression data
Description
Usage
Arguments
Value
Examples
Description
Function to calculate the principal components of a kernel.
Usage
1
KPC(K, thr)
Arguments
K
an NxN numeric matrix with the Kernel matrix.
thr
a positive scalar which is a threshold to discard eigen-vectors based on eigen-values.
Value
the kernel principal components
Examples
1
2
3
4
x = rnorm(100,0,1)
k = RBF_K(x,1)
k_ = kernel_normal(k)
kpca = KPC(k,1e-8)
Luisiglm/KBoost documentation built on May 13, 2021, 7:27 p.m.
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Description Usage Arguments Value Examples
Description
Function to calculate the principal components of a kernel.
Usage
1 | KPC(K, thr)
|
Arguments
K |
an NxN numeric matrix with the Kernel matrix. |
thr |
a positive scalar which is a threshold to discard eigen-vectors based on eigen-values. |
Value
the kernel principal components
Examples
1 2 3 4 | x = rnorm(100,0,1)
k = RBF_K(x,1)
k_ = kernel_normal(k)
kpca = KPC(k,1e-8)
|
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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