Measures of uncertainty for a four-hybrid information system and their applications

A four-hybrid information system (4HIS) is an where the dataset of object descriptions consists categorical, boolean, real-valued and missing data or attributes. This paper studies measures uncertainty for a 4HIS its application in attribute reduction. The distance function each type first provided. Then, this used to produce tolerance relation induced by given subsystem 4HIS. Next, structure proposed terms set vector dependence between structures introduced. Moreover, granulation entropy are investigated on basis structures. In order verify feasibility measures, effectiveness analysis performed from statistical perspective. Finally, reduction given.