Probabilistic Rough indices in Information Systems under Intuitionistic Fuzziness

The concept of classifying the records of the information system has been due to Two Way Approach [ ie, lower and upper approximations ] of Pawlak’s rough sets model. But the approximation does to take into consideration the degree of contribution of the basic categories. This deficiency was eliminated in early nineties by Ziarko who has proposed VPRS model and later on various efforts were made in defining a new Probabilistic Rough Set Model. In 2004, G.Ganesan et.al., have introduced the concept of classifying the records of the information system with fuzzy decision attributes using a threshold. Later, G. Ganesan extended this algorithm for any information system with intuitionistic fuzzy decision attributes. In this paper, we extended the work of G.Ganesan et.al., for the Probabilistic Rough Set Model to improve the efficiency of rough indices in the information system with intuitionistic fuzzy decision attributes.