Sentiment analysis with genetically evolved gaussian kernels

@article{Roman2019SentimentAW,
  title={Sentiment analysis with genetically evolved gaussian kernels},
  author={Ibai Roman and Alexander Mendiburu and Roberto Santana and Jos{\'e} Antonio Lozano},
  journal={Proceedings of the Genetic and Evolutionary Computation Conference},
  year={2019}
}
Sentiment analysis consists of evaluating opinions or statements based on text analysis. Among the methods used to estimate the degree to which a text expresses a certain sentiment are those based on Gaussian Processes. However, traditional Gaussian Processes methods use a predefined kernels with hyperparameters that can be tuned but whose structure can not be adapted. In this paper, we propose the application of Genetic Programming for the evolution of Gaussian Process kernels that are more… 

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