Select features with p-value (computed from decision tree) < `p_thres` or all features if `show_all_feats == TRUE`.
prediction_df(fit, task, clust_samps, clust_target)
constparty object of the decision tree.
Character string indicating the type of problem, either 'classification' (categorical outcome) or 'regression' (continuous outcome).
Logical. If TRUE, hierarchical clustering would be performed among samples within each leaf node.
Logical. If TRUE, target/label is included in hierarchical clustering of samples within each leaf node and might yield a more interpretable heatmap.
A dataframe of prediction values with scaled columns and clustered samples.