normalize_kernel: Normalize a kernel
In pfocal: Fast Convolution of Matrices
normalize_kernel R Documentation
Normalize a kernel
Description
A normalized kernel is one that, if given a data matrix that is all 1s, will
result in 1. This function applies a scalier multiple to the kernel to make
it normalized, if possible. Otherwise, it optionally warns and returns the
input kernel.
Usage
normalize_kernel(k, warning_enabled = TRUE)
Arguments
k
[matrix] The kernel.
warning_enabled
[logical] Whether to unable warnings, default
to TRUE.
Value
The normalized kernel, a matrix.
Examples
kernel <- distance_kernel(vertical_radius = 2, horizontal_radius = 2)
kernel_norm <- normalize_kernel(kernel)
sum(kernel_norm)
pfocal documentation built on June 17, 2022, 5:07 p.m.
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| normalize_kernel | R Documentation |
Normalize a kernel
Description
A normalized kernel is one that, if given a data matrix that is all 1s, will result in 1. This function applies a scalier multiple to the kernel to make it normalized, if possible. Otherwise, it optionally warns and returns the input kernel.
Usage
normalize_kernel(k, warning_enabled = TRUE)
Arguments
k |
[matrix] The kernel. |
warning_enabled |
[logical] Whether to unable warnings, default
to |
Value
The normalized kernel, a matrix.
Examples
kernel <- distance_kernel(vertical_radius = 2, horizontal_radius = 2) kernel_norm <- normalize_kernel(kernel) sum(kernel_norm)
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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