gausskernel: Gaussian RBF kernel
In jpvert/kmr: Kernel multitask regression
Description
Usage
Arguments
Value
Description
Computes the Gaussian RBF kernel k(x,x') = exp(-|x-x'|^2/(2*sigma^2)).
Usage
1
gausskernel(x, sigma = 1, x2)
Arguments
x
Input matrix of covariates with samples in rows.
sigma
Bandwidth of the Gaussian RBF kernel. Default is 1.
x2
(Optional) a second matrix of covariates with samples in rows.
Value
If x2 is provided, returns the kernel matrix crossing samples
in x and samples in x2. If x2 is not provided, returns the kernel
Gram matrix of x versus itself.
jpvert/kmr documentation built on May 20, 2019, 7:56 a.m.
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Description Usage Arguments Value
Description
Computes the Gaussian RBF kernel k(x,x') = exp(-|x-x'|^2/(2*sigma^2)).
Usage
1 | gausskernel(x, sigma = 1, x2)
|
Arguments
x |
Input matrix of covariates with samples in rows. |
sigma |
Bandwidth of the Gaussian RBF kernel. Default is 1. |
x2 |
(Optional) a second matrix of covariates with samples in rows. |
Value
If x2 is provided, returns the kernel matrix crossing samples
in x and samples in x2. If x2 is not provided, returns the kernel
Gram matrix of x versus itself.
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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