predictHybrid

[<code><a rd-options="" href="/link/survivalsvm?package=survivalsvm&version=0.0.5" data-mini-rdoc="survivalsvm::survivalsvm">survivalsvm</a>(1)</code>]
survivalsvm object, fitted with <a rd-options="" href="/link/survivalsvm?package=survivalsvm&version=0.0.5" data-mini-rdoc="survivalsvm::survivalsvm">survivalsvm</a>.

object

[<code>matrix</code>]
matrix of data points of interest.

X_pred

Maker of predictions based on model fitted using the hybrid approach of survival support vector machines.

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

predictHybrid function

<dl><dt>object</dt>
<dd>[<code>survivalsvm(1)</code>] 
survivalsvm object, fitted with survivalsvm.</dd>
<dt>X_pred</dt>
<dd>[<code>matrix</code>] 
matrix of data points of interest.</dd></dl>

Arguments

Author

Survivalsvm predictions — predictHybrid

<dl>

<dt>object</dt>
<dd>[<code>survivalsvm(1)</code>] 
survivalsvm object, fitted with survivalsvm.</dd>


<dt>X_pred</dt>
<dd>[<code>matrix</code>] 
matrix of data points of interest.</dd>

</dl>

`typeofsurvivalsvm`	type of the survivalsvm object that is fitted in model,
`typeofkernel`	type of kernel used to fit the model,
`parameterofkernel`	parameters of kernel used to fit the model,
`opt.meth`	program used to fit the model,
`predicted`	values predicted.

predictHybrid: Survivalsvm predictions

Description

Usage

Value

Arguments

Author