kernCompute {tigre} | R Documentation

## Compute the kernel given the parameters and X.

### Description

Compute the kernel given the parameters and X.

### Usage

      kernCompute(kern, x, x2)
      kernDiagCompute(kern, x)

### Arguments

`kern` | kernel structure to be computed.
`x` | first or only input data matrix (rows are data points) to the kernel computation.
`x2` | (optional) second input matrix to the kernel computation (forms the columns of the kernel).

### Details

`K <- kernCompute(kern, X)` computes a kernel matrix for the given kernel type given an input data matrix.

`K <- kernCompute(kern, X1, X2)` computes a kernel matrix for the given kernel type given two input data matrices, one for the rows and one for the columns.

`K <- kernDiagCompute(kern, X)` computes the diagonal of a kernel matrix for the given kernel.

`K <- *X*kernCompute(kern1, kern2, X)` `K <- *X*kernCompute(kern1, kern2, X1, X2)` same as above, but for cross combinations of two kernels, `kern1` and `kern2`.

### Value

`K` | computed elements of the kernel structure.
`Kd` | vector containing computed diagonal elements of the kernel structure.

### See Also

`kernCreate`

### Examples

    kern <- kernCreate(1, 'rbf')
    K <- kernCompute(kern, as.matrix(3:8))

[Package tigre version 1.38.0 Index]