地球资源数据云——数据资源详情
Netflix 用户数据库
该数据集《Netflix Users Database》主要用于监督学习任务，数据形态以表格为主。 题目说明：Synthetic Netflix user data with demographics, subscriptions, and watch history. 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：netflix_users.csv。 Overview This dataset contains 25,000 fictional Netflix user records generated for analysis, visualization, and machine learning practice. It includes demographic details, subscription type, watch time, and login history for each user. Columns User_ID – Unique identifier for each user Name – Randomly generated name Age – Age of the user (13 to 80) Country – User’s country (randomly chosen from 10 options) Subscription_Type – Type of Netflix plan (Basic, Standard, Premium) Watch_Time_Hours – Total hours watched in the last month Favorite_Genre – User’s preferred genre Last_Login – Last recorded login date within the past year Use Cases Data visualization and analytics Customer segmentation and trend analysis Machine learning model testing (e.g., churn prediction, recommendation systems) This dataset is synthetic and does not contain real user data. Feel free to use it for experiments and projects!
摘要概览
该数据集《Netflix Users Database》主要用于监督学习任务，数据形态以表格为主。 题目说明：Synthetic Netflix user data with demographics, subscriptions, and watch history.
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：netflix_users.csv。
Overview
This dataset contains 25,000 fictional Netflix user records generated for analysis, visualization, and machine learning practice. It includes demographic details, subscription type, watch time, and login history for each user.
Columns
User_ID – Unique identifier for each user Name – Randomly generated name Age – Age of the user (13 to 80) Country – User’s country (randomly chosen from 10 options) Subscription_Type – Type of Netflix plan (Basic, Standard, Premium) Watch_Time_Hours – Total hours watched in the last month Favorite_Genre – User’s preferred genre Last_Login – Last recorded login date within the past year
Use Cases Data visualization and analytics Customer segmentation and trend analysis Machine learning model testing (e.g., churn prediction, recommendation systems) This dataset is synthetic and does not contain real user data. Feel free to use it for experiments and projects!