地球资源数据云——数据资源详情
该数据集《Career Path Recommendations》主要用于监督学习任务,数据形态以表格为主,应用场景偏向交通/汽车。 题目说明:A synthetic dataset mapping education, skills, and CGPA to career paths. 任务类型:表格监督学习。 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:未检测到标准 CSV,可优先查看目录中的索引或说明文件。 Overview This is a synthetic dataset containing 5,000 rows for career path recommendation based on education level, specialization, skills, certifications, and CGPA. Columns Education Level (Matric, Intermediate, Bachelor's, Master's, PhD) Specialization (e.g., Science, Commerce, Computer Science)

该数据集《Career Path Recommendations》主要用于监督学习任务,数据形态以表格为主,应用场景偏向交通/汽车。 题目说明:A synthetic dataset mapping education, skills, and CGPA to career paths.
任务类型:表格监督学习。
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:未检测到标准 CSV,可优先查看目录中的索引或说明文件。
Overview
This is a synthetic dataset containing 5,000 rows for career path recommendation based on education level, specialization, skills, certifications, and CGPA.
Columns
Education Level (Matric, Intermediate, Bachelor's, Master's, PhD)
Specialization (e.g., Science, Commerce, Computer Science)