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Chefboost ⭐ 428

A Lightweight Decision Tree Framework supporting regular algorithms: ID3, C4,5, CART, CHAID and Regression Trees; some advanced techniques: Gradient Boosting, Random Forest and Adaboost w/categorical features support for Python

Decision Trees For Ml ⭐ 27

Building Decision Trees From Scratch In Python

Random_forests ⭐ 15

This is a very efficient Random Forests implementation for MATLAB based on low level "cart" tree implementation.

Deep learning library based on the gcForest algorithm

Go Mining ⭐ 10

Data mining with Go.

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