Data volume reduction in covering approximation spaces with respect to twenty-two types of covering based rough sets

摘要

In this paper, we investigate whether consistent mappings can be used as homomorphism mappings between a covering based approximation space and its image with respect to twenty-two pairs of covering upper and lower approximation operators. We also consider the problem of constructing such mappings and minimizing them. In addition, we investigate the problem of reducing the data volume using consistent mappings as well as the maximum amount of their compressibility. We also apply our algorithms against several datasets. (C) 2016 Elsevier Inc. All rights reserved.