kernelMatrix

[<code>matrix(1)</code>]
Matrix of training data points.

Xtrain

[<code>character(1)</code>]
Type of kernel that is required.

kernel_type

[<code>vector(1)</code>]
Parameters of kernels.

kernel_pars

[<code>matrix(1)</code>]
Matrix of data points to be mapped.

indexes of binary/categorical variables.

bin_cat

computes the kernel matrix for elements taken in an argument.

internal

Performs support vectors analysis for data sets with survival
outcome. Three approaches are available in the package: The regression approach
takes censoring into account when formulating the inequality constraints of
the support vector problem. In the ranking approach, the inequality constraints
set the objective to maximize the concordance index for comparable pairs
of observations. The hybrid approach combines the regression and ranking
constraints in the same model.

Cesaire Fouodo

survivalsvm

Survival Support Vector Analysis

kernelMatrix function

<dl><dt>Xtrain</dt>
<dd>[<code>matrix(1)</code>] 
Matrix of training data points.</dd>
<dt>kernel_type</dt>
<dd>[<code>character(1)</code>] 
Type of kernel that is required.</dd>
<dt>kernel_pars</dt>
<dd>[<code>vector(1)</code>] 
Parameters of kernels.</dd>
<dt>Xt</dt>
<dd>[<code>matrix(1)</code>] 
Matrix of data points to be mapped.</dd>
<dt>bin_cat</dt>
<dd>indexes of binary/categorical variables.</dd></dl>

Arguments

Author

Kernel — kernelMatrix

<dl>

<dt>Xtrain</dt>
<dd>[<code>matrix(1)</code>] 
Matrix of training data points.</dd>


<dt>kernel_type</dt>
<dd>[<code>character(1)</code>] 
Type of kernel that is required.</dd>


<dt>kernel_pars</dt>
<dd>[<code>vector(1)</code>] 
Parameters of kernels.</dd>


<dt>Xt</dt>
<dd>[<code>matrix(1)</code>] 
Matrix of data points to be mapped.</dd>


<dt>bin_cat</dt>
<dd>indexes of binary/categorical variables.</dd>

</dl>

`Type`	type of kernel,
`Mat`	matrix used to compute differences between comparable data points.

kernelMatrix: Kernel

Description

Usage

Value

Arguments

Author

Details