地球资源数据云——数据资源详情
该数据集《COVID - 19 Data Visualization Using Python》主要用于监督学习任务,数据形态以表格为主。 题目说明:+Data From 01/20 - 04/22 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:countries - aggregated.csv。 Data visualization using Python (Pandas, Plotly). Data was used to visualization of the infection rate and the death rate from 01/20 to 04/22. The data was made available on Github: https://raw.githubusercontent.com/datasets/covid - 19/master/data/countries - aggregated.csv

该数据集《COVID - 19 Data Visualization Using Python》主要用于监督学习任务,数据形态以表格为主。 题目说明:+Data From 01/20 - 04/22
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:countries - aggregated.csv。
Data visualization using Python (Pandas, Plotly).
Data was used to visualization of the infection rate and the death rate from 01/20 to 04/22.
The data was made available on Github: https://raw.githubusercontent.com/datasets/covid - 19/master/data/countries - aggregated.csv