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Deep Learning Hyper-parameter Tuning for Sentiment Analysis in Twitter based on Evolutionary Algorithms
2019
Proceedings of the 2019 Federated Conference on Computer Science and Information Systems
The state of the art in Sentiment Analysis is defined by deep learning methods, and currently the research efforts are focused on improving the encoding of underlying contextual information in a sequence of text. However, those neural networks with a higher representation capacity are increasingly more complex, which means that they have more hyper-parameters that have to be defined by hand. We argue that the setting of hyper-parameters may be defined as an optimisation task, we thus claim that
doi:10.15439/2019f183
dblp:conf/fedcsis/CamaraBMFRH19
fatcat:vn6jyvoxjzginpaba7hsmlv5za