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Random Forest Python Packages

Python packages with the GitHub topic random-forest. Sorted by monthly downloads, with stars and forks.
microsoft
flaml

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

328K 4K 569
h2oai
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.

157K 8K 2K
tensorflow
tensorflow-decision-forests

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

136K 693 114
google
ydf

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

123K 678 86
zillow
quantile-forest

Quantile Regression Forests compatible with scikit-learn.

76K 255 33
parrt
dtreeviz

A python library for decision tree visualization and model interpretation.

48K 3K 337
biolab
orange3

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

43K 6K 1K
AnotherSamWilson
miceforest

Multiple Imputation with LightGBM in Python

36K 412 33
automl
smac

SMAC3: A Versatile Bayesian Optimization Package for Hyperparameter Optimization

23K 1K 244
linkedin
fasttreeshap

Fast SHAP value computation for interpreting tree-based models

23K 566 38
EpistasisLab
tpot

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

16K 10K 2K
emlearn
emlearn

Machine Learning inference engine for Microcontrollers and Embedded devices

9K 765 81
google
ydf-tf

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

9K 678 86
mljar
mljar-supervised

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

8K 3K 448
crillab
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, ...).

7K 42 4
cerlymarco
linear-tree

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

6K 387 63
aertslab
arboreto

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

6K 71 37
diyabc
pyabcranger

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

3K 10 4
crflynn
skranger

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

3K 55 10
rezayw
cve-riskengine-rf

Leakage-free evaluation of a Recursive Feature Elimination Random Forest for CVE exploitability prioritization: code, data, results and a calibrated scoring package.

2K 0 1
sunnyadn
comprisk

Scalable, scikit-learn-compatible competing-risks survival analysis in pure Python — CR random survival forest, Fine-Gray, cause-specific Cox, Aalen-Johansen CIF, Gray's test, and exact TreeSHAP. 10–22× faster than randomForestSRC on real EHR and 16.6–544× vs scikit-survival (n=5k→50k); scales to n=10⁶ in ~1 min.

2K 10 0
h2oai
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.

2K 8K 2K
mljar
supertree

Impress your boss with interactive Decision Tree visualization

2K 692 37
LAMDA-NJU
deep-forest

An Efficient, Scalable and Optimized Python Framework for Deep Forest (2021.2.1)

1K 960 168
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