GitHub - mljar/supertree: Visualize decision trees in Python (original) (raw)

supertree - Interactive Decision Tree Visualization

supertree is a Python package designed to visualize decision trees in an interactive and user-friendly way within Jupyter Notebooks, Jupyter Lab, Google Colab, and any other notebooks that support HTML rendering. With this tool, you can not only display decision trees, but also interact with them directly within your notebook environment. Key features include:

• ability to zoom and pan through large trees,
• collapse and expand selected nodes,
• explore the structure of the tree in an intuitive and visually appealing manner.

Examples

Decision Tree classifier on iris data

from sklearn.tree import DecisionTreeClassifier from sklearn.datasets import load_iris from supertree import SuperTree # <- import supertree :)

Load the iris dataset

iris = load_iris() X, y = iris.data, iris.target

Train model

model = DecisionTreeClassifier() model.fit(X, y)

Initialize supertree

super_tree = SuperTree(model, X, y, iris.feature_names, iris.target_names)

show tree in your notebook

super_tree.show_tree()

Random Forest Regressor Example

from sklearn.ensemble import RandomForestRegressor from sklearn.datasets import load_diabetes from supertree import SuperTree # <- import supertree :)

Load the diabetes dataset

diabetes = load_diabetes() X = diabetes.data y = diabetes.target

Train model

model = RandomForestRegressor(n_estimators=100, max_depth=3, random_state=42) model.fit(X, y)

Initialize supertree

super_tree = SuperTree(model,X, y)

show tree with index 2 in your notebook

super_tree.show_tree(2)

There are more code snippets in the examples directory.

Instalation

You can install SuperTree package using pip:

Conda support coming soon.

Supported Libraries

• scikit-learn (sklearn)
• LightGBM
• XGBoost
• ONNX:

Supported Algorithms

The package is compatible with a wide range of classifiers and regressors from these libraries, specifically:

Scikit-learn

• DecisionTreeClassifier
• ExtraTreeClassifier
• ExtraTreesClassifier
• RandomForestClassifier
• GradientBoostingClassifier
• HistGradientBoostingClassifier
• DecisionTreeRegressor
• ExtraTreeRegressor
• ExtraTreesRegressor
• RandomForestRegressor
• GradientBoostingRegressor
• HistGradientBoostingRegressor

LightGBM

• LGBMClassifier
• LGBMRegressor
• Booster

XGBoost

• XGBClassifier
• XGBRFClassifier
• XGBRegressor
• XGBRFRegressor
• Booster

If we do not support the model you want to use, please let us know.

Features

Check this features in example directory :)

Articles

• Visualize decision tree from scikit-learn package
• 4 ways to vizualize decision tree from LightGBM
• How to visualize decision tree from Xgboost

Support

If you encounter any issues, find a bug, or have a feature request, we would love to hear from you! Please don't hesitate to reach out to us at supertree/issues. We are committed to improving this package and appreciate any feedback or suggestions you may have.

License

supertree is a commercial software with two licenses available:

• AGPL-3.0 license
• Commercial license with support and maintenance included. Pricing website https://mljar.com/supertree/ License supertree-commercial-license.pdf.