https://www.selleckchem.com/products/OSI-906.html
High accuracy of text classification can be achieved through simultaneous learning of multiple information, such as sequence information and word importance. In this article, a kind of flat neural networks called the broad learning system (BLS) is employed to derive two novel learning methods for text classification, including recurrent BLS (R-BLS) and long short-term memory (LSTM)-like architecture gated BLS (G-BLS). The proposed two methods possess three advantages 1) higher accuracy due to the simultaneous learning of multiple inform
Like
Comment
Share
