地球资源数据云——数据资源详情
该数据集《IMDb Top 5000 TV Shows》主要用于监督学习任务,数据形态以表格为主。 题目说明:Top 5000 IMDb TV Show with Writers and Directors 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:imdb_top_5000_tv_shows.csv。 This dataset brings together the Top 5000 highest - rated TV shows according to IMDb users. It was curated to enable analysis of rating patterns, popularity trends, genres, and other relevant attributes in the TV show landscape. Data Source: https://developer.imdb.com/non - commercial - datasets/ Processing and Code Repository: https://github.com/TiagoAdriaNunes/imdb_top_5000_tv_shows/blob/main/imdb_tv_shows_analysis.R Purpose: Inspired by the structure of the "IMDB Top 5000 Movies" dataset, this version focuses exclusively on TV series, offering a solid base for data analysis and visualization projects in the entertainment domain. Pipeline: https://github.com/TiagoAdriaNunes/imdb_top_5000_tv_shows/blob/main/.github/workflows/imdb - tv - shows - pipeline.yml

该数据集《IMDb Top 5000 TV Shows》主要用于监督学习任务,数据形态以表格为主。 题目说明:Top 5000 IMDb TV Show with Writers and Directors
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:imdb_top_5000_tv_shows.csv。
This dataset brings together the Top 5000 highest - rated TV shows according to IMDb users. It was curated to enable analysis of rating patterns, popularity trends, genres, and other relevant attributes in the TV show landscape.
Data Source: https://developer.imdb.com/non - commercial - datasets/
Processing and Code Repository: https://github.com/TiagoAdriaNunes/imdb_top_5000_tv_shows/blob/main/imdb_tv_shows_analysis.R
Purpose: Inspired by the structure of the "IMDB Top 5000 Movies" dataset, this version focuses exclusively on TV series, offering a solid base for data analysis and visualization projects in the entertainment domain.
Pipeline: https://github.com/TiagoAdriaNunes/imdb_top_5000_tv_shows/blob/main/.github/workflows/imdb - tv - shows - pipeline.yml