地球资源数据云——数据资源详情
该数据集《Anime Recommendation Dataset》主要用于监督学习任务,数据形态以文本为主。 题目说明:Anime with descriptions, genres, and character information for building recommen 任务类型:文本监督学习。 建议流程:先做文本清洗与分词,再比较 TF - IDF+线性模型 与 预训练语言模型。 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:anime_recommendation_dataset.csv。 This dataset contains over 50,000 anime entries with key information useful for building recommendation systems. Data was collected via the AniList GraphQL API, cleaned, and formatted into a CSV file. This dataset is suitable for NLP tasks, recommendation engines, and data visualization projects. Inspired by the growing interest in anime recommendation models and the lack of comprehensive, high - quality datasets.

该数据集《Anime Recommendation Dataset》主要用于监督学习任务,数据形态以文本为主。 题目说明:Anime with descriptions, genres, and character information for building recommen
任务类型:文本监督学习。
建议流程:先做文本清洗与分词,再比较 TF - IDF+线性模型 与 预训练语言模型。
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:anime_recommendation_dataset.csv。
This dataset contains over 50,000 anime entries with key information useful for building recommendation systems.
Data was collected via the AniList GraphQL API, cleaned, and formatted into a CSV file. This dataset is suitable for NLP tasks, recommendation engines, and data visualization projects.
Inspired by the growing interest in anime recommendation models and the lack of comprehensive, high - quality datasets.
该数据集《Anime Recommendation Dataset》主要用于监督学习任务,数据形态以文本为主。
数据格式为 CSV。
Data was collected via the AniList GraphQL API, cleaned, and formatted into a CSV file.
在本页登录后即可下载。建议引用格式:地球资源数据云. 动漫推荐数据集. https://www.gis5g.com/dataset/2031263803264897025