7 datasets found

The dataset is used for multilabel learning tasks. It contains 7395 documents, each labeled with 159 relevant tickers.

Multi-label classification deals with the problem where each instance is associated with multiple class labels.

The dataset used in this paper is a multi-label learning dataset, which is used to test the proposed algorithm for multi-label learning.

The dataset used in the paper is a synthetic dataset for infinite-label learning. It consists of 500 training data points and 1000 testing data points from a five-component...

The Yahoo dataset used for training and testing the proposed model, containing leaked passwords.

OpenImagesv5: A large-scale dataset for multi-label image classification.

Large-scale vision-and-language models trained on curated and web-scrapped data have led to significant improvements over task-specific models when transferred to downstream...