Explore live open-source projects and AI models.

包含线性回归、逻辑回归、决策树、随机森林、支持向量机与神经网络识别手写数字等机器学习基本模型的python实现，数据，以及详细的中文注释 "Python implementations of introductory machine learning models, including linear regression, logistic regression, decision tree, random forest, support vector machine, along with datasets and detailed comments in Chinese

# Cervical_cancer_detection_using_ML # Introduction According to World Health Organisation (WHO), when detected at an early stage, cervical cancer is one of the most curable cancers. Hence, the main motive behind this project is to detect the cancer in its early stages so that it can be treated a... Read more

Understanding gender differences in professional European football through Machine Learning interpretability and match actions data. This repository contains the full data pipeline implemented for the study *Understanding gender differences in professional European football through Machine Learni... Read more

C4.5 Decision Tree Implementation

Implementations of decision tree construction algorithms.

The code implements a novel method for converting random forest into a single decision tree

The implementation for paper Machine Unlearning in Gradient Boosting Decision Trees (Accepted on KDD 2023), supporting training and unlearning.