plot_varimp_xgboost

recommended parameters to control;

internal

Automatically do statistical exploration. Create formulas using 'tidyselect' syntax, and then determine cross-validated model accuracy and variable contributions using 'glm' and 'xgboost'. Contains additional helper functions to create and modify formulas. Has a flagship function to quickly determine relationships between categorical and continuous variables in the data set.

Harrison Tietze

autostats

Auto Stats

plot_varimp_xgboost function

<dl><dt>xgb</dt>
<dd>xgb.Booster model</dd>
<dt>top_n</dt>
<dd>top n important variables</dd>
<dt>aggregate</dt>
<dd>a character vector. Predictors containing the string will be aggregated, and renamed to that string.</dd>
<dt>as_table</dt>
<dd>logical, default FALSE. If TRUE returns importances in a data frame</dd>
<dt>formula</dt>
<dd>formula for the model. Use to provide original names if xgboost is scrambling the names internally</dd>
<dt>measure</dt>
<dd>choose between Gain, Cover, or Frequency for xgboost importance measure</dd>
<dt>...</dt>
<dd>additional arguments for <code>xgb.ggplot.importance</code></dd></dl>

Arguments

Plot varimp xgboost — plot_varimp_xgboost

<dl>

<dt>xgb</dt>
<dd>xgb.Booster model</dd>


<dt>top_n</dt>
<dd>top n important variables</dd>


<dt>aggregate</dt>
<dd>a character vector. Predictors containing the string will be aggregated, and renamed to that string.</dd>


<dt>as_table</dt>
<dd>logical, default FALSE. If TRUE returns importances in a data frame</dd>


<dt>formula</dt>
<dd>formula for the model. Use to provide original names if xgboost is scrambling the names internally</dd>


<dt>measure</dt>
<dd>choose between Gain, Cover, or Frequency for xgboost importance measure</dd>


<dt>...</dt>
<dd>additional arguments for <code>xgb.ggplot.importance</code></dd>

</dl>

plot_varimp_xgboost: Plot varimp xgboost

Description

Usage

Value

Arguments

Details