pdp_plot

The Radiant Model menu includes interfaces for linear and logistic
regression, naive Bayes, neural networks, classification and regression trees,
model evaluation, collaborative filtering, decision analysis, and simulation.
The application extends the functionality in 'radiant.data'.

Vincent Nijs

radiant.model

Model Menu for Radiant: Business Analytics using R and Shiny

pdp_plot function

<dl><dt>x</dt>
<dd>Return value from a model</dd>
<dt>plot_list</dt>
<dd>List used to store plots</dd>
<dt>incl</dt>
<dd>Which variables to include in PDP plots</dd>
<dt>incl_int</dt>
<dd>Which interactions to investigate in PDP plots</dd>
<dt>fix</dt>
<dd>Set the desired limited on yhat or have it calculated automatically.
Set to FALSE to have y-axis limits set by ggplot2 for each plot</dd>
<dt>hline</dt>
<dd>Add a dashed horizontal line at the mean response. Set to FALSE to suppress,
or a numeric value to draw the line at that specific value</dd>
<dt>nr</dt>
<dd>Number of values to use to generate predictions for a numeric explanatory variable</dd>
<dt>pdp_range</dt>
<dd>Numeric vector <code>c(lo, hi)</code> giving the percentile range used to trim the
x-axis for numeric predictors (default <code>c(0.025, 0.975)</code>)</dd>
<dt>minq</dt>
<dd>Deprecated. Use <code>pdp_range[1]</code> instead</dd>
<dt>maxq</dt>
<dd>Deprecated. Use <code>pdp_range[2]</code> instead</dd></dl>

Arguments

Create Partial Dependence Plots — pdp_plot

<dl>

<dt>x</dt>
<dd>Return value from a model</dd>


<dt>plot_list</dt>
<dd>List used to store plots</dd>


<dt>incl</dt>
<dd>Which variables to include in PDP plots</dd>


<dt>incl_int</dt>
<dd>Which interactions to investigate in PDP plots</dd>


<dt>fix</dt>
<dd>Set the desired limited on yhat or have it calculated automatically.
Set to FALSE to have y-axis limits set by ggplot2 for each plot</dd>


<dt>hline</dt>
<dd>Add a dashed horizontal line at the mean response. Set to FALSE to suppress,
or a numeric value to draw the line at that specific value</dd>


<dt>nr</dt>
<dd>Number of values to use to generate predictions for a numeric explanatory variable</dd>


<dt>pdp_range</dt>
<dd>Numeric vector <code>c(lo, hi)</code> giving the percentile range used to trim the
x-axis for numeric predictors (default <code>c(0.025, 0.975)</code>)</dd>


<dt>minq</dt>
<dd>Deprecated. Use <code>pdp_range[1]</code> instead</dd>


<dt>maxq</dt>
<dd>Deprecated. Use <code>pdp_range[2]</code> instead</dd>

</dl>

pdp_plot: Create Partial Dependence Plots

Description

Usage

Arguments