地球资源数据云——数据资源详情
世界空气质量和水污染数据集
该数据集《World's Air Quality and Water Pollution Dataset》主要用于监督学习任务，数据形态以表格为主。 题目说明：Python: Exploratory Data Analysis 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：cities_air_quality_water_pollution.18 - 10 - 2021 (1).csv。 The Dataset "World's Air Quality and Water Pollution" was obtained from Jack Jae Hwan Kim Kaggle page. This Dataset is comprized of 5 columns; "City", "Region", "Country", "Air Quality" and "Water Pollution". The last two columns consist of values varying from 0 to 100; Air Quality Column: Air quality varies from 0 (bad quality) to 100 (top good quality) Water Pollution Column: Water pollution varies from 0 (no pollution) to 100 (extreme pollution).
摘要概览
该数据集《World's Air Quality and Water Pollution Dataset》主要用于监督学习任务，数据形态以表格为主。 题目说明：Python: Exploratory Data Analysis
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：cities_air_quality_water_pollution.18 - 10 - 2021 (1).csv。
The Dataset "World's Air Quality and Water Pollution" was obtained from Jack Jae Hwan Kim Kaggle page. This Dataset is comprized of 5 columns; "City", "Region", "Country", "Air Quality" and "Water Pollution".
The last two columns consist of values varying from 0 to 100; Air Quality Column: Air quality varies from 0 (bad quality) to 100 (top good quality) Water Pollution Column: Water pollution varies from 0 (no pollution) to 100 (extreme pollution).