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Research Paper | Computer Science & Engineering | India | Volume 4 Issue 6, June 2015 | Rating: 6.1 / 10
Probabilistic Rough Classification in Information Systems with Fuzzy Decision Attributes
B. Venkata Ramana, L. Padma Sree, M. Srinivasa Rao, G. Ganesan
Abstract: In 2004, G. Ganesan et. al introduced the concept of indexing any information system with fuzzy decision attributes using a threshold. These indices are based on the two way approach of Pawlak-s rough sets. However, the approach of Pawlak lacks in quantifying the importance of any basic granule which involve in the approximation. Later, Y. Y. Yao discussed a new Probabilistic Rough Set model which appropriately quantifies the appropriate basic granules. 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 fuzzy decision attributes.
Keywords: information system, rough set, probabilistic rough set, rough index
Edition: Volume 4 Issue 6, June 2015,
Pages: 186 - 190