prediction_df

Select features with p-value (computed from decision tree) &lt; `p_thres`
or all features if `show_all_feats == TRUE`.

Creates interpretable decision tree visualizations with the
data represented as a heatmap at the tree's leaf nodes.  'treeheatr'
utilizes the customizable 'ggparty' package for drawing decision
trees.

Trang Le

treeheatr

Heatmap-Integrated Decision Tree Visualizations

Jason Moore

University of Pennsylvania 

prediction_df function

<dl><dt>fit</dt>
<dd>constparty object of the decision tree.</dd>
<dt>task</dt>
<dd>Character string indicating the type of problem,
either 'classification' (categorical outcome) or 'regression' (continuous outcome).</dd>
<dt>clust_samps</dt>
<dd>Logical. If TRUE, hierarchical clustering would be performed
among samples within each leaf node.</dd>
<dt>clust_target</dt>
<dd>Logical. If TRUE, target/label is included in hierarchical clustering
of samples within each leaf node and might yield a more interpretable heatmap.</dd></dl>

Arguments

Apply the predicted tree on either new test data or training data. — prediction_df

<dl>

<dt>fit</dt>
<dd>constparty object of the decision tree.</dd>


<dt>task</dt>
<dd>Character string indicating the type of problem,
either 'classification' (categorical outcome) or 'regression' (continuous outcome).</dd>


<dt>clust_samps</dt>
<dd>Logical. If TRUE, hierarchical clustering would be performed
among samples within each leaf node.</dd>


<dt>clust_target</dt>
<dd>Logical. If TRUE, target/label is included in hierarchical clustering
of samples within each leaf node and might yield a more interpretable heatmap.</dd>

</dl>

prediction_df: Apply the predicted tree on either new test data or training data.

Description

Usage

Value

Arguments