Supervised Generalized Association Plots Based on Decision Trees

Documentation for package ‘dtGAP’ version 0.0.2

add_data_type	Assigns a train/test indicator to a combined dataset
compare_dtGAP	Compare Multiple Decision Tree Models Side-by-Side
compute_tree	Compute Decision Tree Data for Plotting and Analysis
diabetes	Diabetes patient records.
draw_all	Draw Full Visualization: Decision Tree with Heatmap and Evaluation
dtGAP	Decision Tree Generalized Association Plots (dtGAP)
eval_tree	Evaluate Tree Model Predictions and Metrics
galaxy	Galaxy dataset for regression.
penguins	Data of three different species of penguins.
prepare_features	Prepare Features for Modeling
prepare_tree	Prepare Tree Plot Data for Visualization
Psychosis_Disorder	Psychosis Disorder Data
rf_dtGAP	Visualize a Single Tree from a Conditional Random Forest
rf_summary	Random Forest Ensemble Summary
save_dtGAP	Save dtGAP Visualization to File
scale_norm	Performs transformation on continuous variables.
sorted_mat	Sort Feature Matrix by Tree and Correlation Structure
test_covid	External test dataset. Medical information of Wuhan patients collected between 2020-01-10 and 2020-02-18.
train_covid	Training dataset. Medical information of Wuhan patients collected between 2020-01-10 and 2020-02-18. Containing NAs.
train_rf	Fit a Conditional Random Forest
train_tree	Fit a Decision Tree Model
wine	Results of a chemical analysis of wines grown in a specific area of Italy.
wine_quality_red	Red variant of the Portuguese "Vinho Verde" wine.