NICHE：Python中工程机器学习项目的精选数据集
NICHE: A Curated Dataset of Engineered Machine Learning Projects in Python
摘要：
机器学习（ML）已经得到了广泛的关注，并已融入我们的日常生活。虽然在GitHub等开源平台上有许多公开可用的ML项目，但在过滤这些项目以策划高质量ML项目方面的尝试有限。这种高质量数据集的有限可用性对理解ML项目构成了障碍。为了帮助清除这个障碍，我们提出了NICHE，一个由572个ML项目组成的手动标记数据集。基于良好的软件工程实践的证据，我们将这些项目中的441个标记为工程项目，131个标记为非工程项目。该数据集可以帮助研究人员了解高质量ML项目所遵循的实践。它还可以用作分类器的基准，用于识别工程ML项目。
英文摘要：
Machine learning (ML) has gained much attention and been incorporated into our daily lives. While there are numerous publicly available ML projects on open source platforms such as GitHub, there have been limited attempts in filtering those projects to curate ML projects of high quality. The limited availability of such a high-quality dataset poses an obstacle in understanding ML projects. To help clear this obstacle, we present NICHE, a manually labelled dataset consisting of 572 ML projects. Based on evidences of good software engineering practices, we label 441 of these projects as engineered and 131 as non-engineered. This dataset can help researchers understand the practices that are followed in high-quality ML projects. It can also be used as a benchmark for classifiers designed to identify engineered ML projects.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
