地球资源数据云——数据资源详情
薪资预测分类
该数据集《Salary Prediction Classification》主要用于多分类任务，数据形态以表格为主，应用场景偏向交通/汽车。 题目说明：Classification on Salary whether less than 50K or greater than 50K 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：salary.csv。 Extraction was done by Barry Becker from the 1994 Census database. Prediction task is to determine whether a person makes over 50K a year. Columns are: age: continuous. workclass: Private, Self - emp - not - inc, Self - emp - inc, Federal - gov, Local - gov, State - gov, Without - pay, Never - worked. fnlwgt: continuous.
摘要概览
该数据集《Salary Prediction Classification》主要用于多分类任务，数据形态以表格为主，应用场景偏向交通/汽车。 题目说明：Classification on Salary whether less than 50K or greater than 50K
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：salary.csv。
Extraction was done by Barry Becker from the 1994 Census database. Prediction task is to determine whether a person makes over 50K a year.
Columns are:
age: continuous.
workclass: Private, Self - emp - not - inc, Self - emp - inc, Federal - gov, Local - gov, State - gov, Without - pay, Never - worked.
fnlwgt: continuous.