qkernels-class: Class "qkernel" "rbfqkernel" "nonlqkernel" "laplqkernel"...

In qkerntool: Q-Kernel-Based and Conditionally Negative Definite Kernel-Based Machine Learning Tools

Description

The built-in kernel classes in qkerntool

Objects from the Class

Objects can be created by calls of the form new("rbfqkernel"), new{"nonlqkernel"}, new{"laplqkernel"}, new{"ratiqkernel"}, new{"multqkernel"}, new{"invqkernel"}, new{"wavqkernel"}, new{"powqkernel"}, new{"logqkernel"}, new{"cauqkernel"}, new{"chiqkernel"}, new{"studqkernel"}

or by calling the rbfbase, nonlbase, laplbase, ratibase, multbase, invbase, wavbase, powbase, logbase, caubase, chibase, studbase functions etc..

Slots

.Data:

Object of class "function" containing the kernel function

qpar:

Object of class "list" containing the kernel parameters

Methods

qkernmatrix

signature(kernel = "rbfqkernel", x = "matrix"): computes the qkernel matrix

Author(s)

Yusen Zhang
[e-mail]

See Also

qkernmatrix,cndkernmatrix

Examples

qkfunc <- rbfbase(sigma=1,q=0.8)
qkfunc

qpar(qkfunc)

## create two vectors
x <- rnorm(10)
y <- rnorm(10)

## calculate dot product
qkfunc(x,y)

qkerntool documentation built on May 2, 2019, 6:11 a.m.