few-shot learning

This collection includes multiple short text classification datasets designed for various natural language processing tasks. It contains several topic classification datasets, such as AG'News, Snippets, and TMNNews, which cover a wide range of topics and domains to evaluate the effectiveness of classification models. Additionally, the collection includes a binary sentiment classification dataset, such as Twitter, aimed at determining positive or negative sentiment in text.

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 Our dataset has a total of 8 actions, 7 people(P1-P7), and 3 experimental environments(Room-A,Room-B,Room-C). There are a total of 3 directions in each environment, with 5 samples of each action taken for each person in each direction, so the number of samples is 360(samples/person)*7 = 2520.

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