NodeJS implementation of decision tree, random forest, and XGBoost algorithms with comprehensive performance testing (Node.js 20+)
Selectors decision tree - choose matching selectors, fast
selderee plugin - selectors decision tree builder for htmlparser2 DOM.
CART decision tree algorithm
Form decision tree generator
React component to display craft ai decision tree
decision tree diagram
Flo Legal Decision Tree component for the Municipality of Utrecht based on the NL Design System architecture
Visualize decision tree with add and delete actions
Image Description Decision Tree
Flo legal Decision Tree client assets for Utrecht Design System (compatible with flo-client-plugin v1.17.0)
A tool to build data classification rules using visual flowchart-style decision tree
NinjaOne MCP server with decision tree architecture for Claude
HaloPSA MCP server with decision tree architecture for Claude
Module to easily implement decision tree logic in a react app
Decision Tree to predict the value of a continuous target variable
Module to easily implement decision tree logic in a react app
A fieldtrip plugin for making decision tree questions
NodeJS implementation of decision tree using ID3 algorithm
HaloPSA MCP server with decision tree architecture for Claude
Simple decision tree / relationship tree component
NinjaOne MCP server with decision tree architecture for Claude
A Decision Tree executor that uses decision modules to decide pathways. Can accept binary or arbitrary decision modules.
Decision Tree
Tiny decision tree library
Decision tree and ensemble models for the ferrolearn ML framework
Decision tree algorithms for sklears: CART, ID3, C4.5
Pure-Rust AV1 codec — orphan-rebuild scaffold pending clean-room re-implementation.
Simple, fast random forests.
A decision tree implementation in Rust
A crate for implementing various flavors of random forests and decision trees.
Blazingly fast implementation of Random Forest with apache arrow support
Pure-Rust gradient-boosted trees with quantile regression. First GBT crate with pinball loss, early stopping, and JSON-serializable models.
Core types, training engine, and inference for irithyll streaming ML — no_std + alloc, histogram binning, Hoeffding trees, SGBT ensembles, drift detection, f32 + int16 packed formats
Fast Random Forest library.
Decision trees in Rust
A decision tree library which implemented ID3 & C4.5 of algorithms
ID3-based implementation of the M.L. Decision Tree algorithm
A binary decision tree useful for brackets of single elimination tournaments.
Decision trees that request facts as needed
ID3-based implementation of the M.L. Decision Tree algorithm
Rumale::Tree provides classifier and regression based on decision tree algorithms with Rumale interface.
Dwarf is an implementation of decision tree learning algorithms targeted for use in the Rails 3 console environment for classifying ActiveRecord objects.
Decision tree frame work
ID3 decision trees for machine learning in Ruby
A simple decision tree prototype of modular 9 decision making.
Classifiers
ID3-based implementation of the M.L. Decision Tree algorithm
No description provided.
No description provided.
No description provided.
No description provided.
No description provided.
No description provided.
No description provided.
No description provided.
No description provided.
No description provided.
No description provided.
No description provided.