parrt/dtreeviz
A python library for decision tree visualization and model interpretation.
This tool helps data scientists and machine learning engineers understand and interpret decision tree-based models like Random Forests and Gradient Boosting Machines. It takes your trained model and data as input, producing detailed, interactive visualizations of the tree structure, individual prediction paths, and feature space. These visuals help you explain model behavior, debug issues, and learn how these powerful models make decisions.
3,128 stars. Available on PyPI.
Use this if you need to visually explain why your decision tree or ensemble model made a specific prediction or to deeply understand its underlying logic.
Not ideal if your primary goal is to visualize non-tree-based models, or if you prefer purely numerical interpretability metrics without visual components.
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3,128
Forks
340
Language
Jupyter Notebook
License
MIT
Category
Last pushed
Jan 02, 2026
Commits (30d)
0
Dependencies
6
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