predict_grid

For each point we have the predicted class / regression value in column
response. If the learner predicts probabilities, a column ".prob.response" is
added that contains the probability of the predicted class

Visualization package of the 'mlr3' ecosystem. It features plots
for mlr3 objects such as tasks, learners, predictions, benchmark results,
tuning instances and filters via the 'autoplot()' generic of 'ggplot2'.
The package draws plots with the 'viridis' color palette and applies the
minimal theme. Visualizations include barplots, boxplots, histograms, ROC
curves, and Precision-Recall curves.

Michel Lang

mlr3viz

Visualizations for 'mlr3'

Patrick Schratz

Raphael Sonabend

Marc Becker

Jakob Richter

Damir Pulatov

predict_grid function

<dl><dt>learners</dt>
<dd>list of trained learners, each learner belongs to one
resampling iteration</dd>
<dt>task</dt>
<dd>the task all learners are trained on</dd>
<dt>grid_points</dt>
<dd>(int): see sequenize</dd>
<dt>expand_range</dt>
<dd>see sequenize</dd></dl>

Arguments

Generates a data.table of evenly distributed points. — predict_grid

<dl>

<dt>learners</dt>
<dd>list of trained learners, each learner belongs to one
resampling iteration</dd>


<dt>task</dt>
<dd>the task all learners are trained on</dd>


<dt>grid_points</dt>
<dd>(int): see sequenize</dd>


<dt>expand_range</dt>
<dd>see sequenize</dd>

</dl>

predict_grid: Generates a data.table of evenly distributed points.

Description

Usage

Arguments