| 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)