Approximating the combination of belief functions using the fast Mo"bius transform in a coarsened frame

@article{Denoeux2002ApproximatingTC,
  title={Approximating the combination of belief functions using the fast Mo"bius transform in a coarsened frame},
  author={Thierry Denoeux and Amel Ben Yaghlane},
  journal={Int. J. Approx. Reasoning},
  year={2002},
  volume={31},
  pages={77-101}
}
A method is proposed for reducing the size of a frame of discernment, in such a way that the loss of information content in a set of belief functions is minimized. This method may be seen as a hierarchical clustering procedure applied to the columns of a binary data matrix, using a particular dissimilarity measure. It allows to compute approximations of the mass functions, which can be combined efficiently in the coarsened frame using the fast M€ obius transform algorithm, yielding inner and… CONTINUE READING
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