Bounded Support and Confidence over Evidential Databases

In this work, we propose a new definition of support and confidence measures based on interval representation. Moreover, a new algorithm, named EBS-Apriori, based on these bounded measures and several pruning strategies is developed. A new associative classifier, named WEvAC, based on fusion and weighting technique is implemented and tested. Experiments are conducted using several database benchmarks. Performance analysis showed a better prediction outcome for our proposed approach in comparison with several literature-based methods.