Open Source
dtreeviz
A python library for decision tree visualization and model interpretation.
Our verdict
We have not reviewed dtreeviz yet
No one at Enterprise DNA has checked this listing against its sources. The description comes from public listings gathered automatically. Any fact below shows where it came from and when it was last checked.
From the listing
About dtreeviz
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
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
3,148 stars on GitHub. Last updated 2026-01-02. Licensed MIT.
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
Key facts
What we have checked
- Latest version
- 2.3.1 (released 27 Dec 2025)
- GitHub stars
- 3,157
Each value shows when we last confirmed it and where it came from. Values we have not confirmed are left out, never guessed.
Stars and usage
How dtreeviz is growing
3,148 to 3,157
Sources
Where this comes from
- GitHubOfficial
- github api via nightly crawl, recovered from git history 20e874270887c1008f860ee0198e461a23c9e438Registry
A source shows what was published when we checked it. It does not certify security, performance or a working installation. Read our method.
Changelog
What changed
Released 2.3.1
Released 2.3
Released 2.2.2
Released 2.2.1
Released 2.2.0
Released 2.1.4
Released 2.1.3
Released 2.1.2
Released 2.1.1
Released 2.1.0
Pairs with
Other entries in the index that connect to this one. Click through to see the chain.
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Scalable, Portable and Distributed Gradient Boosting (GBDT, GBRT or GBM) Library, for Python, R, Java, Scala, C++ and more. Runs on single machine, Hadoop, Spark, Dask, Flink and D
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