地球资源数据云——数据资源详情

亚马逊创业教育

发布时间:2026-03-17 14:31:33资源ID:2031977397568835585资源类型:免费

该数据集《Entrepreneurial Education for Amazon》主要用于监督学习任务,数据形态以表格为主。 题目说明:Detailed Insights into Local Engagement, Geolocation, and Participation Metrics 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:genese_ee_for_amazon.csv, genese_ee_for_amazon_complementar.csv。 This dataset provides a comprehensive overview of the Genese Data Set, which focuses on entrepreneurial education for Amazon’s sustainable development program from 2022 to 2023. The data is sourced from the Harvard Dataverse and offers detailed insights into local engagement, geolocation, and participation metrics. The dataset is structured to include key metrics such as local area, latitude, longitude, front type, cycle, number of participants, and total number of participants, providing a robust foundation for analyzing program engagement and impact. Key Features Local Engagement: The dataset includes a unique identifier for each local area, facilitating easy identification and tracking of engagement metrics. Geolocation: Information is presented by latitude and longitude, allowing for spatial analysis and mapping of program locations.

亚马逊创业教育

摘要概览

该数据集《Entrepreneurial Education for Amazon》主要用于监督学习任务,数据形态以表格为主。 题目说明:Detailed Insights into Local Engagement, Geolocation, and Participation Metrics

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:genese_ee_for_amazon.csv, genese_ee_for_amazon_complementar.csv。

This dataset provides a comprehensive overview of the Genese Data Set, which focuses on entrepreneurial education for Amazon’s sustainable development program from 2022 to 2023. The data is sourced from the Harvard Dataverse and offers detailed insights into local engagement, geolocation, and participation metrics.

The dataset is structured to include key metrics such as local area, latitude, longitude, front type, cycle, number of participants, and total number of participants, providing a robust foundation for analyzing program engagement and impact.

Key Features

Local Engagement: The dataset includes a unique identifier for each local area, facilitating easy identification and tracking of engagement metrics.

Geolocation: Information is presented by latitude and longitude, allowing for spatial analysis and mapping of program locations.