dtreeviz

Overview

dtreeviz is a Python library for visualizing decision tree models. It generates detailed, interpretable tree diagrams that show split conditions, feature distributions, and prediction paths. The library integrates with scikit-learn, XGBoost, and other popular ML frameworks.

Best for

Best for
Data scientists and ML engineers who need clear, interpretable visualizations of decision tree models

Use cases

• Debugging and interpreting decision tree models during development
• Explaining model predictions to non-technical stakeholders
• Comparing tree structures across different training runs or hyperparameters

Notes

dtreeviz is a Python library for visualizing decision tree models. It generates detailed, interpretable tree diagrams that show split conditions, feature distributions, and prediction paths. The library integrates with scikit-learn, XGBoost, and other popular ML frameworks.

3,148 stars on GitHub. Last updated 2026-01-02. Licensed MIT.

Use cases

• Debugging and interpreting decision tree models during development
• Explaining model predictions to non-technical stakeholders
• Comparing tree structures across different training runs or hyperparameters

Pros

• Produces publication-quality, color-coded tree visualizations
• Supports multiple tree-based frameworks including scikit-learn and XGBoost
• Provides per-node feature distribution histograms for deeper insight

Cons

• Limited to decision tree models, not applicable to other model types
• Visualizations can become cluttered for very deep or large trees
• Requires Jupyter Notebook environment for optimal rendering

Indexed from awesome-llmops and enriched against its public facts.