地球资源数据云——数据资源详情

学生分类数据集

该数据集《Student Classification Dataset》主要用于多分类任务，数据形态以表格为主。 题目说明：Analyzing Academic Success: A Comprehensive Study of Student Performance Factors 任务类型：表格多分类。 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：student.csv。 This dataset encompasses various aspects related to student performance. Each entry is uniquely identified by an 'Id'. The dataset includes demographic information such as 'Student_Age' and 'Sex'. 'High_School_Type' categorizes the type of high school attended, while 'Scholarship' indicates whether the student has a scholarship. Details about 'Additional_Work' and involvement in 'Sports_activity' provide insights into extracurricular commitments. 'Transportation' outlines the mode of commuting for each student. Academic aspects are captured through 'Weekly_Study_Hours', 'Attendance', and evaluations of 'Reading', 'Notes', and 'Listening_in_Class'. The culmination of these factors is reflected in the 'Grade' column, providing a comprehensive overview of student performance. This dataset serves as a valuable resource for exploring the multifaceted dynamics influencing academic outcomes.