[OSS101] Task 5:Research and Implementation of Multi-Label Classification Methods for GitHub Repositories

[PureNatural]

Description

The aim of this task is to research and implement multi-label classification methods for GitHub repositories. By analyzing the code content, commit history, README files, and associated tag information of GitHub repositories, a multi-label classification model will be established to automatically assign repositories to one or more categories. Multi-label classification of GitHub repositories can improve repository organization and management, enhance retrieval efficiency, and provide a better user experience for developers and users. This task seeks to explore various machine learning and deep learning techniques to achieve automatic classification and labeling of GitHub repositories.

The relevant code and dataset for this task need to be provided in the repository.

[yangxinyu7427]

任务已完成，在openperf/benchmarks/data_science/multi-label_classification _for_repositories目录下
PR：#78
仓库地址：https://github.com/yangxinyu7427/open-perf