mljar-supervised provides tabular data AutoML with feature engineering, hyperparameter tuning, explanations, and documentation.
Open source
24 alternativesdtreeviz
Python library for decision tree visualization and model interpretation.
About dtreeviz
dtreeviz is an open-source Python library for decision tree visualization and model interpretation. It renders tree visualizations, prediction path explanations, leaf information, feature space exploration, and regression or classification views. It supports scikit-learn, XGBoost, Spark MLlib, LightGBM, and TensorFlow through an adaptor obtained from dtreeviz.model(), which keeps the programmer interface consistent across those libraries. Its decision_boundaries() utility illustrates one- and two-dimensional feature space for classifiers, including probabilities, decision boundaries, and misclassified entities; it works with models that implement predict_proba(), including scikit-learn models and Keras models that define predict(), not only tree models.
Key features
- Tree visualizations for supported decision tree and ensemble models
- Prediction path explanations for individual samples
- Leaf information and feature space exploration views
- Classification boundary plots for one- and two-dimensional feature space
- Supports scikit-learn, XGBoost, Spark MLlib, LightGBM, and TensorFlow
- AI-powered sklearn notebook for interactive chat and LLM explanations
Best for: Python users who need to visualize, learn from, or interpret decision tree models and supported tree-based ensembles.
Good for
- Open source and available on GitHub.
- Supports several popular machine learning libraries with a consistent adaptor interface.
- Decision boundary utility works with any model that implements predict_proba().
Watch out for
- The dtreeviz.decision_boundaries() utility does not use tree-specific adaptors from dtreeviz.model().
- Interactive chat and LLM explanations are described for sklearn in the source.
- Supported ML libraries are limited to scikit-learn, XGBoost, Spark MLlib, LightGBM, and TensorFlow.
dtreeviz at a glance
- Website
- github.com/parrt/dtreeviz
- Category
- AI & Machine Learning › AI Data & Analytics
- Type
- Open-source project
- Pricing
- Not confirmed. Check the site
- Open source
- Yes · Source code
- Language
- English
- Last checked
- Oct 5, 2026 · Online when checked
- Listed
- Oct 5, 2026
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dtreeviz FAQ
Which machine learning libraries does dtreeviz support?
It supports scikit-learn, XGBoost, Spark MLlib, LightGBM, and TensorFlow.
Can dtreeviz show decision boundaries for models other than trees?
Yes. dtreeviz.decision_boundaries() works with any model that answers predict_proba(), including scikit-learn models and Keras models that define predict().
How do I use dtreeviz with a trained model?
Obtain a dtreeviz adaptor with dtreeviz.model(your_trained_model, ...), then call functions such as viz_model.view() or viz_model.explain_prediction_path(sample_x).
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