Cleanlab/student-grades

该数据集包含用于cleanlab教程的学生成绩数据，用于演示如何通过训练与测试分割来改进机器学习性能。任务是根据学生的考试成绩和笔记预测每个学生的最终字母等级（A、B、C、D、F）。数据集包含约750个示例（训练+测试），特征包括三次考试分数、学生笔记和学生ID，标签为可能包含标签错误的字母等级。数据集故意包含标签噪声、近重复和异常值，用于教育目的，帮助用户学习数据中心的AI技术。

This dataset contains student grade data used in the cleanlab tutorial: Improving ML Performance via Data Curation with Train vs Test Splits. The task is to predict each students final letter grade (A, B, C, D, F) based on their exam scores and notes. The dataset contains ~750 examples (train + test) with features including three exam scores, student notes, and student ID, and the label is the letter grade which may contain label errors. The dataset intentionally includes label noise, near duplicates, and outliers for educational purposes to help users learn data-centric AI techniques.