地球资源数据云——数据资源详情
学生辍学和成功预测数据集
该数据集《Student Dropout & Success Prediction Dataset》主要用于多分类任务，数据形态以表格为主，应用场景偏向文本内容分析。 题目说明：Classify dropout, enrolled, or graduate status using 36 student features 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。 注意事项：疑似存在类别不均衡，建议使用分层抽样、类别权重与 F1/Recall 指标。 可用文件：students_dropout_academic_success.csv。 This dataset originates from a Portuguese higher education institution and was developed as part of a national project aiming to combat student dropout and academic failure in universities. It brings together rich information from 4,424 undergraduate students across 8 degree programs, such as Agronomy, Design, Education, Nursing, Journalism, Management, Social Service, and Technologies. Objective The core objective is to support early intervention by using machine learning models to predict a student’s academic outcome—whether they will: Drop out
摘要概览
该数据集《Student Dropout & Success Prediction Dataset》主要用于多分类任务，数据形态以表格为主，应用场景偏向文本内容分析。 题目说明：Classify dropout, enrolled, or graduate status using 36 student features
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。
注意事项：疑似存在类别不均衡，建议使用分层抽样、类别权重与 F1/Recall 指标。
可用文件：students_dropout_academic_success.csv。
This dataset originates from a Portuguese higher education institution and was developed as part of a national project aiming to combat student dropout and academic failure in universities.
It brings together rich information from 4,424 undergraduate students across 8 degree programs, such as Agronomy, Design, Education, Nursing, Journalism, Management, Social Service, and Technologies.
Objective
The core objective is to support early intervention by using machine learning models to predict a student’s academic outcome—whether they will:
Drop out