地球资源数据云——数据资源详情
该数据集《Layoffs NLP 2022》主要用于监督学习任务,数据形态以文本为主。 题目说明:Recent linkedIn posts regarding the layoffs trend ongoing in 2022. 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:linkedin_temp.csv。 This dataset consists of several scraped LinkedIn posts by professionals and users about the ongoing layoff trends. This data could be used to have a look at the present reaction of several professionals about the layoffs. This data was collected by scraping recent LinkedIn posts.

该数据集《Layoffs NLP 2022》主要用于监督学习任务,数据形态以文本为主。 题目说明:Recent linkedIn posts regarding the layoffs trend ongoing in 2022.
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:linkedin_temp.csv。
This dataset consists of several scraped LinkedIn posts by professionals and users about the ongoing layoff trends. This data could be used to have a look at the present reaction of several professionals about the layoffs.
This data was collected by scraping recent LinkedIn posts.
该数据集《Layoffs NLP 2022》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。
This dataset consists of several scraped LinkedIn posts by professionals and users about the ongoing layoff trends.
在本页登录后即可下载。建议引用格式:地球资源数据云. 2022 年 NLP 裁员. https://www.gis5g.com/dataset/2032004349314895873