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

orange3

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

dtreeviz

A python library for decision tree visualization and model interpretation.

quantile-forest

Quantile Regression Forests compatible with scikit-learn.

smac

SMAC3: A Versatile Bayesian Optimization Package for Hyperparameter Optimization

tpot

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

fasttreeshap

Fast SHAP value computation for interpreting tree-based models

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, ...).

arboreto

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

forestfire-ml

Machine learning from the ground up in Rust

mljar-supervised

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

emlearn

Machine Learning inference engine for Microcontrollers and Embedded devices

pyabcranger

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

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.

previsionio

python wrapper for prevision api

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

Visualize decision trees in Python

crforest

Python toolkit for competing risks: forest (RSF) today; Fine-Gray + Aalen-Johansen + Gray's test + cause-specific Cox in v0.4. Scales to n=10⁶ in ~1 min, 10–22× faster than randomForestSRC on real EHR data, sklearn-compatible.