decision-tree

⚡机器学习实战（Python3）：kNN、决策树、贝叶斯、逻辑回归、SVM、线性回归、树回归

Python package for AutoML on Tabular Data with Feature Engineering, Hyper-Parameters Tuning, Explanations and Automatic Documentation

A collection of research papers on decision, classification and regression trees with implementations.

ID3-based implementation of the ML Decision Tree algorithm

A curated list of gradient boosting research papers with implementations.

M. Beyeler (2017). Machine Learning for OpenCV: Intelligent image processing with Python. Packt Publishing Ltd., ISBN 978-178398028-4.

Examples of techniques for training interpretable ML models, explaining ML models, and debugging ML models for accuracy, discrimination, and security.

Code for IDS-ML: intrusion detection system development using machine learning algorithms (Decision tree, random forest, extra trees, XGBoost, stacking, k-means, Bayesian optimization..)

Connected components on discrete and continuous multilabel 3D & 2D images. Handles 26, 18, and 6 connected variants; periodic boundaries (4, 8, & 6)

Julia implementation of Decision Tree (CART) and Random Forest algorithms

A Generic Low-Code Framework Built on a Config-Driven Tree Walker

Small JavaScript implementation of ID3 Decision tree

I've demonstrated the working of the decision tree-based ID3 algorithm. Use an appropriate data set for building the decision tree and apply this knowledge to classify a new sample. All the steps have been explained in detail with graphics for better understanding.

numpy 实现的 周志华《机器学习》书中的算法及其他一些传统机器学习算法

A fast and easy to use decision tree learner in java

A day to day plan for this challenge. Covers both theoritical and practical aspects

DISCONTINUED (July 2025): the maintenance for this repository has been discontinued. Please refer to: https://github.com/STMicroelectronics/st-mems-machine-learning-core/ for the up-to-date tutorials, examples and tools for the Machine Learning Core (MLC) feature available in STMicroelectronics MEMS sensors.

Boosted trees in Julia

经典机器学习算法的极简实现

A lightweight decision making library for game AI.