Random Forest Frameworks
Implementations, extensions, and optimizations of Random Forest algorithms and ensemble tree-based methods. Includes deep forest variants, GPU-accelerated versions, and interpretability tools. Does NOT include general decision tree frameworks, gradient boosting methods, or neural network alternatives unless they directly extend random forests.
There are 24 random forest frameworks tracked. 4 score above 50 (established tier). The highest-rated is LAMDA-NJU/Deep-Forest at 61/100 with 962 stars.
Get all 24 projects as JSON
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| # | Framework | Score | Tier |
|---|---|---|---|
| 1 |
LAMDA-NJU/Deep-Forest
An Efficient, Scalable and Optimized Python Framework for Deep Forest (2021.2.1) |
|
Established |
| 2 |
grf-labs/grf
Generalized Random Forests |
|
Established |
| 3 |
cerlymarco/linear-tree
A python library to build Model Trees with Linear Models at the leaves. |
|
Established |
| 4 |
benedekrozemberczki/awesome-decision-tree-papers
A collection of research papers on decision, classification and regression... |
|
Established |
| 5 |
ysraell/random-forest-mc
Random Forest with Dynamic Tree Selection Monte Carlo Based (RF-TSMC). |
|
Emerging |
| 6 |
zhaoxingfeng/RandomForest
随机森林,Random Forest(RF) |
|
Emerging |
| 7 |
kingfengji/gcForest
This is the official implementation for the paper 'Deep forest: Towards an... |
|
Emerging |
| 8 |
neurodata/df-dn-paper
Conceptual & empirical comparisons between decision forests & deep networks |
|
Emerging |
| 9 |
ASEM000/pytreeclass
Visualize, create, and operate on pytrees in the most intuitive way possible. |
|
Emerging |
| 10 |
RyanLucas3/MacroRandomForest
A modification of traditional random forest for time-series forecasting |
|
Emerging |
| 11 |
chriskuchar/RFX-Fuse
Breiman and Cutler's Random Forests as a Forest Unified Learning and... |
|
Emerging |
| 12 |
joshloyal/drforest
Dimension Reduction Forests |
|
Emerging |
| 13 |
gammarayapp/GRB-Web-App
Ensemble Learning Regression Model for GRB Redshift Estimation |
|
Emerging |
| 14 |
KuanHuang/predicting-heavy-metal-adsorption-in-soil
A machine learning model based on gradient boosting decision tree for... |
|
Emerging |
| 15 |
nishiwen1214/PSForest
Paper of ACML 2020: "PSForest: Improving Deep Forest via Feature Pooling and... |
|
Experimental |
| 16 |
chriskuchar/RFX
GPU-accelerated Random Forest library with advanced interpretability,... |
|
Experimental |
| 17 |
csinva/trees-to-networks
Bridging random forests and deep neural networks. Partial implementation of... |
|
Experimental |
| 18 |
stabgan/Random-Forest-Classification
I implemented the Random Forest Classifier in both Python and R |
|
Experimental |
| 19 |
misterekkk/histree
High-performance ensemble learning library optimized with Numba. Features... |
|
Experimental |
| 20 |
kosnil/simplify_rf_dist
Simplify your (probabilistic) random forest predictions |
|
Experimental |
| 21 |
emirhanai/Ozone-Day-AdaBoostClassifier-and-Random-Forest-Tree-Classifier-with-Machine-Learning
Ozone Day AdaBoostClassifier and Random Forest Tree Classifier with Machine Learning |
|
Experimental |
| 22 |
mjuez/rotation-forest-bd
🔄🌳⚡ The Rotation Forest implementation for Big Data on Apache Spark |
|
Experimental |
| 23 |
Singh-Prince-Rinku/Random_Forest
Random Forest algorithm |
|
Experimental |
| 24 |
KevinMoonLab/RF-PHATE
Supervised visualization of high-dimensional data using random forests |
|
Experimental |