grouped_counts

Calculates weighted counts grouped by optional columns.

Shed light on black box machine learning models by the help
of model performance, variable importance, global surrogate models,
ICE profiles, partial dependence (Friedman J. H. (2001)
<doi:10.1214/aos/1013203451>), accumulated local effects (Apley D. W.
(2016) <arXiv:1612.08468>), further effects plots, interaction
strength, and variable contribution breakdown (Gosiewska and Biecek
(2019) <arxiv:1903.11420>). All tools are implemented to work with
case weights and allow for stratified analysis. Furthermore, multiple
flashlights can be combined and analyzed together.

Michael Mayer

flashlight

Shed Light on Black Box Machine Learning Models

grouped_counts function

<dl><dt>data</dt>
<dd>A <code>data.frame</code>.</dd>
<dt>by</dt>
<dd>An optional vector of column names in <code>data</code> used to group the results.</dd>
<dt>w</dt>
<dd>Optional name of the column in <code>data</code> with case weights.</dd>
<dt>value_name</dt>
<dd>Name of the resulting column with counts.</dd>
<dt>...</dt>
<dd>Arguments passed to <code><a href="/link/sum()?package=flashlight&version=0.9.0" data-mini-rdoc="flashlight::sum()">sum()</a></code> (only if weights are provided).</dd></dl>

Arguments

Grouped count — grouped_counts

<dl>

<dt>data</dt>
<dd>A <code>data.frame</code>.</dd>


<dt>by</dt>
<dd>An optional vector of column names in <code>data</code> used to group the results.</dd>


<dt>w</dt>
<dd>Optional name of the column in <code>data</code> with case weights.</dd>


<dt>value_name</dt>
<dd>Name of the resulting column with counts.</dd>


<dt>...</dt>
<dd>Arguments passed to <code><a href='https://rdrr.io/r/base/sum.html'>sum()</a></code> (only if weights are provided).</dd>

</dl>

grouped_counts: Grouped count

Description

Usage

Value

Arguments

Examples