OpenML Curated Classification benchmarking suite 2018 (OpenML-CC18)

OpenML-CC18是由慕尼黑路德维希-马克西米利安大学统计系等机构精心策划的分类基准套件，包含72个中等大小的数据集，旨在为机器学习算法提供实用且具有挑战性的评估平台。该数据集覆盖多种数据类型和复杂度，适用于不同硬件环境下的模型训练。OpenML-CC18的设计遵循一系列严格的标准，确保数据集的质量和适用性，支持跨研究的比较和复现。此套件不仅促进了机器学习方法的深入评估，还为研究者提供了一个共享和重用基准结果的社区平台。

OpenML-CC18 is a carefully curated classification benchmark suite developed by the Department of Statistics, Ludwig Maximilian University of Munich and other institutions. It includes 72 medium-sized datasets, aiming to provide a practical and challenging evaluation platform for machine learning algorithms. The suite covers a wide range of data types and complexity levels, and is applicable to model training across different hardware environments. The design of OpenML-CC18 adheres to a series of strict standards to guarantee the quality and applicability of the datasets, enabling cross-study comparison and reproducibility. This suite not only promotes in-depth evaluation of machine learning methods, but also provides researchers with a community platform for sharing and reusing benchmark results.