yelp_data.txt

yelp数据集最新数据资料，适合NLP分类任务，情感分类等。In 2015, Yelp held a contest in which it asked participants to predict the rating of
a restaurant given its review. Zhang, Zhao, and Lecun (2015) simplified the dataset by converting the 1- and 2-star ratings into a “negative” sentiment class and the 3- and 4-star ratings into a “positive” sentiment class, and split it into 560,000 training samples and 38,000 testing samples.