Partially supervised Independent Factor Analysis using soft labels elicited from multiple experts: application to railway track circuit diagnosis

@article{Cherfi2012PartiallySI,
  title={Partially supervised Independent Factor Analysis using soft labels elicited from multiple experts: application to railway track circuit diagnosis},
  author={Zohra Leila Cherfi and Latifa Oukhellou and Etienne C{\^o}me and Thierry Denoeux and Patrice Aknin},
  journal={Soft Comput.},
  year={2012},
  volume={16},
  pages={741-754}
}
Using a statistical model in a diagnosis task generally requires a large amount of labeled data. When ground truth information is not available, too expensive or difficult to collect, one has to rely on expert knowledge. In this paper, it is proposed to use partial information from domain experts expressed as belief functions. Expert opinions are combined in this framework and used with measurement data to estimate the parameters of a statistical model using a variant of the EM algorithm. The… CONTINUE READING
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