tskrrTuneHomogeneous-class

tskrrTuneHomogeneous

<p>The class tskrrTuneHomogeneous represents a tuned homogeneous
<code><a rd-options="xnet:tskrr-class" href="/link/tskrr?package=xnet&version=0.1.11&to=xnet%3Atskrr-class" data-mini-rdoc="xnet:tskrr-class::tskrr">tskrr</a></code> model. It inherits from
the classes <code><a rd-options="xnet:tskrrHomogeneous-class" href="/link/tskrrHomogeneous?package=xnet&version=0.1.11&to=xnet%3AtskrrHomogeneous-class" data-mini-rdoc="xnet:tskrrHomogeneous-class::tskrrHomogeneous">tskrrHomogeneous</a></code>
and <code><a rd-options="xnet:tskrrTune-class" href="/link/tskrrTune?package=xnet&version=0.1.11&to=xnet%3AtskrrTune-class" data-mini-rdoc="xnet:tskrrTune-class::tskrrTune">tskrrTune</a></code>.</p>

Fit a two-step kernel ridge regression model for
predicting edges in networks, and carry out cross-validation
using shortcuts for swift and accurate performance assessment
(Stock et al, 2018 <doi:10.1093/bib/bby095> ).

Joris Meys

xnet

Two-Step Kernel Ridge Regression for Network Predictions

Michiel Stock

tskrrTuneHomogeneous-class function

<p>The class tskrrTuneHomogeneous represents a tuned homogeneous
<code><a rd-options='xnet:tskrr-class' href='tskrr'>tskrr</a></code> model. It inherits from
the classes <code><a rd-options='xnet:tskrrHomogeneous-class' href='tskrrHomogeneous'>tskrrHomogeneous</a></code>
and <code><a rd-options='xnet:tskrrTune-class' href='tskrrTune'>tskrrTune</a></code>.</p>

tskrrTuneHomogeneous-class: Class tskrrTuneHomogeneous

Description

Arguments