地球资源数据云——数据资源详情
学生信息数据集
该数据集《Student Information Dataset》主要用于监督学习任务，数据形态以文本为主，应用场景偏向文本内容分析。 题目说明：A Collection of 200 Students' Demographics, Academic Performance, and Expected 任务类型：文本监督学习。 建议流程：先做文本清洗与分词，再比较 TF - IDF+线性模型 与 预训练语言模型。 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：students.csv。 This dataset contains information about 200 students with 7 attributes. It is designed for use in exploratory data analysis, SQL practice, or machine learning experiments related to student performance or demographics. StudentID: Unique identifier for each student. Type: Integer (4 - digit unique number). Example: 1023, 3045. Name: Full name of the student. Type: String (Text). Example: John Doe, Alice Smith. Age: Age of the student. Type: Integer (Range: 18–25). Example: 21, 19. Email: Email address of the student. Type: String (Unique). Example: john.doe@example.com, alice.smith@example.org.
摘要概览
该数据集《Student Information Dataset》主要用于监督学习任务，数据形态以文本为主，应用场景偏向文本内容分析。 题目说明：A Collection of 200 Students' Demographics, Academic Performance, and Expected
任务类型：文本监督学习。
建议流程：先做文本清洗与分词，再比较 TF - IDF+线性模型 与 预训练语言模型。
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：students.csv。
This dataset contains information about 200 students with 7 attributes. It is designed for use in exploratory data analysis, SQL practice, or machine learning experiments related to student performance or demographics.
StudentID: Unique identifier for each student. Type: Integer (4 - digit unique number). Example: 1023, 3045.
Name: Full name of the student. Type: String (Text). Example: John Doe, Alice Smith.
Age: Age of the student. Type: Integer (Range: 18–25). Example: 21, 19.
Email: Email address of the student. Type: String (Unique). Example: john.doe@example.com, alice.smith@example.org.