kernelMatrix {kernlab} | R Documentation |
kernelMatrix
calculates the kernel matrix K_{ij} = k(x_i,x_j) or K_{ij} =
k(x_i,y_j).
kernelPol
computes the quadratic kernel expression H = z_i z_j
k(x_i,x_j), H = z_i k_j k(x_i,y_j).
kernelMult
calculates the kernel expansion f(x_i) =
sum_{i=1}^m z k(x_i,x_j)
## S4 method for signature 'kernel': kernelMatrix(kernel, x, y = NULL) ## S4 method for signature 'kernel': kernelPol(kernel, x, y = NULL, z, k = NULL) ## S4 method for signature 'kernel': kernelMult(kernel, x, y = NULL, z, blocksize = 256)
kernel |
the kernel function to be used to calculate the kernel
matrix.
This has to be a function of class kernel |
x |
a data matrix to be used to calculate the kernel matrix |
y |
second data matrix to calculate the kernel matrix |
z |
a suitable vector or matrix |
k |
a suitable vector or matrix |
blocksize |
the kernel expansion computations are done block wise
to avoid storing the kernel matrix into memory. blocksize
defines the size of the computational blocks. |
Common functions used during kernel based computations.
This kernel
parameter can be set to any function, of class
kernel, which computes a dot product between two
vector arguments. kernlab provides the most popular kernel functions
which can be initialized by using the following
functions:
rbfdot
Radial Basis kernel function
polydot
Polynomial kernel function
vanilladot
Linear kernel function
tanhdot
Hyperbolic tangent kernel function
laplacedot
Laplacian kernel function
besseldot
Bessel kernel function
anovadot
ANOVA RBF kernel function
kernelMatrix
returns a symmetric diagonal semi-definite matrix.
kernelPol
returns a matrix.
kernelMult
{usually returns a one-column matrix}
Alexandros Karatzoglou
alexandros.karatzoglou@ci.tuwien.ac.at
rbfdot
, polydot
,
tanhdot
, vanilladot
## use the spam data data(spam) dt <- as.matrix(spam[c(10:20,3000:3010),-58]) ## initialize kernel function rbf <- rbfdot(sigma = 0.05) rbf ## calculate kernel matrix kernelMatrix(rbf, dt) yt <- as.matrix(as.integer(spam[c(10:20,3000:3010),58])) yt[yt==2] <- -1 ## calculate the quadratic kernel expression kernelPol(rbf, dt, ,yt) ## calculate the kernel expansion kernelMult(rbf, dt, ,yt)