地球资源数据云——数据资源详情
该数据集《World Happiness Data》主要用于监督学习任务,数据形态以表格为主,应用场景偏向医疗健康。 题目说明:Happy Data Visualization 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。 - - The Top 10 from 2017 - 2019 SELECT Country, Happiness_Rank, Happiness_Score, Economy_GDP_per_Capita, Family, Health_Life_Expectancy, Freedom, Generosity, Trust_Government_Corruption, Dystopia_Residual, DateYear FROM WorldHappiness2017 WHERE Happiness_Rank <= 10 ORDER BY Happiness_Rank SELECT FROM WorldHappiness2018 WHERE Overall_rank <= 10 ORDER BY Overall_rank SELECT FROM WorldHappiness2019 WHERE Overall_rank <= 10 ORDER BY Overall_rank - - Ranks by Region - - Top 10's Happiness Score Distributions 2017

该数据集《World Happiness Data》主要用于监督学习任务,数据形态以表格为主,应用场景偏向医疗健康。 题目说明:Happy Data Visualization
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。
- - The Top 10 from 2017 - 2019
SELECT Country, Happiness_Rank, Happiness_Score, Economy_GDP_per_Capita, Family, Health_Life_Expectancy, Freedom, Generosity, Trust_Government_Corruption, Dystopia_Residual, DateYear FROM WorldHappiness2017 WHERE Happiness_Rank <= 10 ORDER BY Happiness_Rank
SELECT FROM WorldHappiness2018 WHERE Overall_rank <= 10 ORDER BY Overall_rank
SELECT FROM WorldHappiness2019 WHERE Overall_rank <= 10 ORDER BY Overall_rank
- - Ranks by Region - - Top 10's Happiness Score Distributions 2017