Abstract Summary treeheatr is an R package for creating interpretable decision tree
visualizations with the data represented as a heatmap at the tree's leaf nodes. The …

Balancing accuracy gains with other objectives such as interpretability is a key challenge
when building decision trees. However, this process is difficult to automate because it …

Motivation Dendrogram is a classical diagram for visualizing binary trees. Although efficient
to represent hierarchical relations, it provides limited space for displaying information on the …

Visualization of Machine Learning (ML) models is an important part of the ML process to
enhance the interpretability and prediction accuracy of the ML models. This paper proposes …

As an ensemble model that consists of many independent decision trees, random forests
generate predictions by feeding the input to internal trees and summarizing their outputs …

To increase the interpretability and prediction accuracy of the Machine Learning (ML)
models, visualization of ML models is a key part of the ML process. Decision Trees (DTs) are …

Tree boosting models are widely adopted predictive models and have demonstrated
superior performance than other conventional and even deep learning models, especially …

Visualizations of machine learning models have developed rapidly during these days,
attracting great interests of industry and researchers. However, a pipeline that visualizations …

Decision trees are an intuitive yet powerful tool for performing predictive data analysis in
data mining. In order to generate an adequate predictive model from a data set, a data …

Tree-based regression and classification has become a standard tool in modern data
science. Bayesian Additive Regression Trees (BART) has in particular gained wide …