Generalized Random Forests

Random Planted Forest

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

GammaRay: a graphical interface to GSLib and other geomodeling algorithms. *NEW* in May, 6th: Drift analysis.

An update to imbs-hl/ranger for use with multiple imputation via chained equations

A library to train, evaluate and make inference using random forests.

This is the implementation of Sparse Projection Oblique Randomer Forest

C++ implementation of random forests classification, regression, proximity and variable importance.

Efficient Online Transfer Learning for 3D Object Detection in Autonomous Driving

ThunderGBM: Fast GBDTs and Random Forests on GPUs

Classification of Data Using Decision Tree and Random Forest

implementation of some classification algorithms in c and c++

K-nearest neighbors (KNN) is a supervised machine learning algorithm that is used for classification and regression tasks. It works by finding the K nearest data points to a given input and using their labels to predict the label for the input.

BLOCKSET: Efficient out of core tree ensemble inference

Multivariate Outcome Treatment Effect Random Forest

R package CORElearn

Implementation of ML on IoT based data.

Random Forest library university project

A Machine Learning binary classifier for extremely imbalanced datasets