地球资源数据云——数据资源详情
2012 年和 2016 年总统选举
该数据集《2012 and 2016 Presidential Elections》主要用于监督学习任务，数据形态以表格为主，应用场景偏向安全检测。 题目说明：Election results with county information on race, income and education 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：county_facts.csv, county_facts_dictionary.csv, US_County_Level_Presidential_Results_12 - 16.csv 等 4 个文件。 These data files contain election results for both the 2012 and 2016 US Presidential Elections, include proportions of votes cast for Romney, Obama (2012) and Trump, Clinton (2016). The election results were obtained from this Git repository: https://github.com/tonmcg/County_Level_Election_Results_12 - 16 The county facts data was obtained from another Kaggle election data set: https://www.kaggle.com/benhamner/2016 - us - election
摘要概览
该数据集《2012 and 2016 Presidential Elections》主要用于监督学习任务，数据形态以表格为主，应用场景偏向安全检测。 题目说明：Election results with county information on race, income and education
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：county_facts.csv, county_facts_dictionary.csv, US_County_Level_Presidential_Results_12 - 16.csv 等 4 个文件。
These data files contain election results for both the 2012 and 2016 US Presidential Elections, include proportions of votes cast for Romney, Obama (2012) and Trump, Clinton (2016).
The election results were obtained from this Git repository: https://github.com/tonmcg/County_Level_Election_Results_12 - 16
The county facts data was obtained from another Kaggle election data set: https://www.kaggle.com/benhamner/2016 - us - election