On attribute importance measure and its application to supplier selection.

Rough set theory is a powerful mathematical technique of decision making, which can be exploited to feature selection and rule induction from uncertain and ambiguous data. Generally, the attribute significance degree is one of the fundamental metrics used to measure the contained information of each attribute. However, in the most existing rough based methods, some attributes share the identical or zero significance degrees, that cannot reflect the situations in the realistic scenarios. We are then motivated to improve the attribute significance degree of rough set, based on the new attribute significance degree of rough set, a new method of supplier evaluation and selection is presented, it solves the problems existing in current research and verifies the scientific nature and effectiveness of the method with a case. [ABSTRACT FROM AUTHOR]