Decision Trees Python Packages

lightgbm

A fast, distributed, high performance gradient boosting (GBT, GBDT, GBRT, GBM or MART) framework based on decision tree algorithms, used for ranking, classification and many other machine learning tasks.

catboost

A fast, scalable, high performance Gradient Boosting on Decision Trees library, used for ranking, classification, regression and other machine learning tasks for Python, R, Java, C++. Supports computation on CPU and GPU.

tensorflow-decision-forests

A collection of state-of-the-art algorithms for the training, serving and interpretation of Decision Forest models in Keras.

ydf

A library to train, evaluate, interpret, and productionize decision forest models such as Random Forest and Gradient Boosted Decision Trees.

dtreeviz

A python library for decision tree visualization and model interpretation.

catboost-dev

A fast, scalable, high performance Gradient Boosting on Decision Trees library, used for ranking, classification, regression and other machine learning tasks for Python, R, Java, C++. Supports computation on CPU and GPU.

orange3

🍊 :bar_chart: :bulb: Orange: Interactive data analysis

lleaves

Compiler for LightGBM gradient-boosted trees, based on LLVM. Speeds up prediction by ≥10x.

stochtree

Stochastic tree ensembles (BART / XBART) for supervised learning and causal inference

linear-tree

A python library to build Model Trees with Linear Models at the leaves.

gosdt

Generalized Optimal Sparse Decision Trees

dectree

A tool to explore and visualize decision trees

adaxt

adaXT: tree-based machine learning in Python

rfgboost

RFGBoost: Gradient Boosting with Asynchronous Random Forests

rgf-python

Home repository for the Regularized Greedy Forest (RGF) library. It includes original implementation from the paper and multithreaded one written in C++, along with various language-specific wrappers.

supertree

Impress your boss with interactive Decision Tree visualization

ydf-tf

A library to train, evaluate, interpret, and productionize decision forest models such as Random Forest and Gradient Boosted Decision Trees.

certcc-ssvc

Stakeholder-Specific Vulnerability Categorization

chefboost

A Lightweight Decision Tree Framework supporting regular algorithms: ID3, C4.5, CART, CHAID and Regression Trees; some advanced techniques: Gradient Boosting, Random Forest and Adaboost w/categorical features support for Python

fukuml

Simple machine learning library / 簡單易用的機器學習套件

trust-free

An interpretable regression model in Python with Random-Forest-level accuracy

pynets

A Reproducible Workflow for Structural and Functional Connectome Ensemble Learning

spkit

Signal Processing Toolkit, including ML models with visualization

pyscipopt-ml

Python interface to automatically formulate Machine Learning models into Mixed-Integer Programs