Random Forest with WebAssembly and WebWorkers

Random forest for classification and regression

A random forest classifier. A random forest is a meta estimator that fits a number of decision tree classifiers on various sub-samples of the dataset and use averaging to improve the predictive accuracy and control over-fitting.

NodeJS implementation of decision tree, random forest, and XGBoost algorithms with comprehensive performance testing (Node.js 20+)

incremental random forest ensemble classifier (native)

Random forest for classification and regression

incremental random forest ensemble classifier (native)

Collection of online classification algorithms. Online random forest.

Random forest for classification and regression

A Random Forest implementation for JavaScript supporting distributed computation

the author don't update the npm , so i forked one;A random forest classifier. A random forest is a meta estimator that fits a number of decision tree classifiers on various sub-samples of the dataset and use averaging to improve the predictive accuracy an

Random Forest from scratch in C11, compiled to WebAssembly -- classification, regression, ExtraTrees, quantile RF, conformal prediction, histogram binning, JARF rotation, sample weights, proximity matrix

Official Express/Sequelize Liana for Forest

Node.js runfiles helpers for Bazel

Official package for all Forest Express Lianas

High-performance (binary) tree and sorted map implementation (AVL, Splay, Radix, Red-Black)

logistic regression/c4.5 decision tree algorithm with random forest

Generate fallback values for content with alt text

This packages is used internally by https://forestadmin.com.

Generate random numbers from various distributions.