地球资源数据云——数据资源详情

学生表现

该数据集《Student Performance》主要用于二分类任务，数据形态以表格为主，应用场景偏向医疗健康。 题目说明：Predict student performance in secondary education (high school) 任务类型：表格二分类。 建议流程：先做缺失值/异常值处理与特征编码，再比较逻辑回归、随机森林、XGBoost。 评估建议：使用分层切分或交叉验证，优先关注 F1、Recall、AUC 等分类指标。 可用文件：Maths.csv, Portuguese.csv。 This data approach student achievement in secondary education of two Portuguese schools. The data attributes include student grades, demographic, social and school related features) and it was collected by using school reports and questionnaires. Two datasets are provided regarding the performance in two distinct subjects: Mathematics (mat) and Portuguese language (por). In [Cortez and Silva, 2008], the two datasets were modeled under binary/five - level classification and regression tasks. Important note: the target attribute G3 has a strong correlation with attributes G2 and G1. This occurs because G3 is the final year grade (issued at the 3rd period), while G1 and G2 correspond to the 1st and 2nd period grades. It is more difficult to predict G3 without G2 and G1, but such prediction is much more useful (see paper source for more details). Attributes for both Maths.csv (Math course) and Portuguese.csv (Portuguese language course) datasets: | Columns | Description |