setWeights

Set the prior weights in a UBaymodel object.

The framework proposed in Jenul et al., (2022) <doi:10.1007/s10994-022-06221-9>, together with an interactive Shiny dashboard. 'UBayFS' is an ensemble feature selection technique embedded in a Bayesian statistical framework. The method combines data and user knowledge, where the first is extracted via data-driven ensemble feature selection. The user can control the feature selection by assigning prior weights to features and penalizing specific feature combinations. 'UBayFS' can be used for common feature selection as well as block feature selection.

Anna Jenul

UBayFS

A User-Guided Bayesian Framework for Ensemble Feature Selection

Stefan Schrunner

Kristian Hovde Liland

Oliver Tomic

Jürgen Pilz

setWeights function

<dl><dt>model</dt>
<dd>a UBaymodel object created using build.UBaymodel</dd>
<dt>weights</dt>
<dd>the vector of user-defined prior weights for each feature</dd>
<dt>block_list</dt>
<dd>the list of feature indices for each block; only required, if block-wise weights are specified and block_matrix is NULL</dd>
<dt>block_matrix</dt>
<dd>the matrix containing affiliations of features to each block; only required, if block-wise weights are specified and block_list is NULL</dd></dl>

Arguments

Set weights in UBaymodel object — setWeights

<dl>

<dt>model</dt>
<dd>a UBaymodel object created using build.UBaymodel</dd>


<dt>weights</dt>
<dd>the vector of user-defined prior weights for each feature</dd>


<dt>block_list</dt>
<dd>the list of feature indices for each block; only required, if block-wise weights are specified and block_matrix is NULL</dd>


<dt>block_matrix</dt>
<dd>the matrix containing affiliations of features to each block; only required, if block-wise weights are specified and block_list is NULL</dd>

</dl>

setWeights: Set weights in UBaymodel object

Description

Usage

Value

Arguments

See Also