Comparison between Bayesian network classifiers and SVMs for semantic localization

@article{Rubio2016ComparisonBB,
  title={Comparison between Bayesian network classifiers and SVMs for semantic localization},
  author={Fernando Rubio and Jesus Mart{\'i}nez-G{\'o}mez and M. Julia Flores and Jose Miguel Puerta},
  journal={Expert Syst. Appl.},
  year={2016},
  volume={64},
  pages={434-443}
}
We propose a method for the use of image descriptors as input in graphical model.We compare the results obtained in two datasets when using SVMs and BNCs.A large number of inputs decreases the results of BNCs with structural learning.Graphical models provide capabilities of an easier interpretation than SVMs.BNCs allow incremental modelling, so new information can be added to enrich them. This work presents a methodology to apply Bayesian networks classifiers (BNCs) to the problem of semantic… CONTINUE READING

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