Deep Learning Hyper-parameter Tuning for Sentiment Analysis in Twitter based on Evolutionary Algorithms

@article{MartnezCmara2019DeepLH,
  title={Deep Learning Hyper-parameter Tuning for Sentiment Analysis in Twitter based on Evolutionary Algorithms},
  author={Eugenio Mart{\'i}nez-C{\'a}mara and Nuria Rodr{\'i}guez Barroso and Antonio R. Moya and Jos{\'e} Alberto Fern{\'a}ndez and Elena Romero and Francisco Herrera},
  journal={2019 Federated Conference on Computer Science and Information Systems (FedCSIS)},
  year={2019},
  pages={255-264}
}
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… 

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