Welcome to stable-cart’s documentation!¶

stable-cart provides unified tree estimators with enhanced prediction stability for both regression and classification tasks. All trees follow the familiar scikit-learn API while incorporating advanced stability features.

Key Features¶

🌳 Unified Architecture: Single classes handle both regression and classification via task parameter

🎯 Enhanced Stability: Multiple stability primitives reduce prediction variance across training runs

📊 sklearn Compatible: Works seamlessly with pipelines, cross-validation, and grid search

Quick Start¶

from stable_cart import LessGreedyHybridTree
from sklearn.datasets import make_classification

# Works for both regression and classification
X, y = make_classification(n_samples=1000, n_features=10)

tree = LessGreedyHybridTree(task='classification', max_depth=5)
tree.fit(X, y)
predictions = tree.predict(X)

See the Unified Tree Estimators section for a complete list of available estimators and the Evaluation Functions for assessing model stability.

Documentation¶

API Reference:

API Reference

Links: