Random Forest Python Packages

flaml

A fast library for AutoML and tuning. Join our Discord: https://discord.gg/Cppx2vSPVP.

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.

h2o

H2O is an Open Source, Distributed, Fast & Scalable Machine Learning Platform: Deep Learning, Gradient Boosting (GBM) & XGBoost, Random Forest, Generalized Linear Modeling (GLM with Elastic Net), K-Means, PCA, Generalized Additive Models (GAM), RuleFit, Support Vector Machine (SVM), Stacked Ensembles, Automatic Machine Learning (AutoML), etc.

miceforest

Multiple Imputation with LightGBM in Python

dtreeviz

A python library for decision tree visualization and model interpretation.

quantile-forest

Quantile Regression Forests compatible with scikit-learn.

orange3

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

smac

SMAC3: A Versatile Bayesian Optimization Package for Hyperparameter Optimization

fasttreeshap

Fast SHAP value computation for interpreting tree-based models

tpot

A Python Automated Machine Learning tool that optimizes machine learning pipelines using genetic programming.

linear-tree

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

pyxai

PyXAI (Python eXplainable AI) is a Python library (version 3.6 or later) allowing to bring formal explanations suited to (regression or classification) tree-based ML models (Decision Trees, Random Forests, Boosted Trees, ...).

mljar-supervised

Python package for AutoML on Tabular Data with Feature Engineering, Hyper-Parameters Tuning, Explanations and Automatic Documentation

arboreto

A scalable python-based framework for gene regulatory network inference using tree-based ensemble regressors.

macrorandomforest

A modification of traditional random forest for time-series forecasting

emlearn

Machine Learning inference engine for Microcontrollers and Embedded devices

rfgboost

RFGBoost: Gradient Boosting with Asynchronous Random Forests

pyabcranger

ABC random forests for model choice and parameter estimation, pure C++ implementation

h2o-client

H2O is an Open Source, Distributed, Fast & Scalable Machine Learning Platform: Deep Learning, Gradient Boosting (GBM) & XGBoost, Random Forest, Generalized Linear Modeling (GLM with Elastic Net), K-Means, PCA, Generalized Additive Models (GAM), RuleFit, Support Vector Machine (SVM), Stacked Ensembles, Automatic Machine Learning (AutoML), etc.

supertree

Impress your boss with interactive Decision Tree visualization

drforest

Fast distributional random forests with CART, MMD, and sliced-Wasserstein splitting

skranger

scikit-learn compatible Python bindings for ranger C++ random forest library

ydf-tf

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