Show HN: SuperTree – interactive decision tree plot for sklearn,xgboost,lightgbm (github.com)

A new tool, SuperTree, has been announced that allows users to visualize decision trees interactively in Jupyter, JupyterLab, and Google Colab. This tool supports popular machine learning frameworks such as scikit-learn, XGBoost, LightGBM, and ONNX, making it easier for data scientists and machine learning practitioners to understand their models. With features like zooming, panning, collapsing nodes, and tracing sample paths, SuperTree enhances the interpretability of complex models, which is a crucial aspect in AI/ML workflows. The significance of SuperTree lies in its ability to streamline the visualization process for various decision tree-based algorithms, including classifiers and regressors like DecisionTreeClassifier, RandomForestRegressor, and LGBMClassifier, among others. By providing an interactive experience, it allows users to delve deeper into their model's decision-making processes while directly within their coding environment. The tool is open source under the Apache License 2.0, inviting contributions and feedback from the community, which could further improve its capabilities and expand its use cases.