Computes a linear kernel from inner products between observations.
Usage
kernel_linear(x, y = NULL, variance = 1)
Arguments
- x
Numeric vector or matrix. Matrix rows are observations and columns
are input dimensions.
- y
Optional numeric vector or matrix with the same number of input
dimensions as x. If NULL, computes the covariance of x with
itself.
- variance
Positive marginal variance.
Value
A numeric covariance matrix.
Stability
Stable: from version 1.0.0 this interface changes incompatibly only in a
major release, after a deprecation period. Results and options that
concern an experimental model class, kernel, or argument follow that
interface's tier. See gaussianprocesses-package for the
policy.
See also
linear_kernel() creates the same kernel as a reusable
specification, which can be combined, optimized, and used in models.
Examples
x <- cbind(c(1, 2, 3), c(0, 1, 0))
kernel_linear(x, variance = 0.5)
#> [,1] [,2] [,3]
#> [1,] 0.5 1.0 1.5
#> [2,] 1.0 2.5 3.0
#> [3,] 1.5 3.0 4.5