A new definition for similarity between possibility distributions is
and discussed as a basis for detecting dependence between variables by
measuring the similarity degree of their respective distributions.
This new definition is used to detect conditional independence
relations in possibility
distributions derived from data. This is the basis for a new hybrid
algorithm for recovering possibilistic causal networks. The algorithm
POSSCAUSE is presented and its applications discussed and compared
with analogous developments in possibilistic and probabilistic causal
CitationSangüesa, R., Cabós, J., Cortes, C. "Probabilistic conditional independence: a similarity-based measure and its application to causal network learning". 1996.
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