Visualizing complex decision trees with static plots can make it hard to analyze and explain model decisions.

supertree is a Python package that addresses this by providing interactive and user-friendly decision tree visualizations within notebooks.

Key features include:

• Zooming and panning through large trees
• Collapsing and expanding selected nodes

Example usage:

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()

Link to supertree.