Showing 10 of 10 projects
A curated collection of research papers on decision, classification, and regression trees with implementations from top ML conferences.
A Ruby library implementing the ID3 algorithm for decision tree learning with support for continuous and discrete datasets.
A Node.js library implementing Decision Tree (ID3/CART), Random Forest, and XGBoost algorithms with TypeScript support and automatic data type detection.
An Alexa Skill sample that implements a decision tree algorithm to ask yes/no questions and provide career suggestions.
A Go library for scoring machine learning models using PMML, supporting neural networks, decision trees, random forests, and gradient boosted models.
A JavaScript library implementing logistic regression and C4.5 decision tree algorithms for machine learning in the browser and Node.js.
A Go library for building and evaluating dynamic decision trees programmatically or from JSON, with support for pre-processing inputs.
A simple machine learning library for Crystal with a working Bayes classifier and upcoming decision tree.
A functional behavior tree implementation in Lua for game AI and entity behavior modeling.
A simple yet powerful behavior tree implementation for game AI, with built-in tree visualization for LÖVE.
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