Algorithms for Different Approximations in Incomplete Information Systems with Maximal Compatible Classes as Primitive Granules
Chen Wu, Xiaohua Tony Hu, Zhoujun Li, Xiaohua Zhou, Palakorn Achananuparp · 2007 IEEE International Conference on Granular Computing (GRC 2007) · 2007
This paper proposes some expanded rough set models with maximal compatible classes as primitive granules, introduces two new granules for extending rough set model, and designs algorithms to solve maximal compatible classes, to find the lower and upper approximations according to the newly granules, to compute reducts and minimal reducts with attribute significance. It also verifies the validity of algorithms by examples. These provide an important and implemental theoretical base for rough set theory to deal with problems in incomplete information systems . Key words: incomplete information system; rough set model; maximal compatible class; algorithm