Notice of RetractionAttribute reduction based on rough set and AHP

Notice of Retraction

After careful and considered review of the content of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE´s Publication Principles.

We hereby retract the content of this paper. Reasonable effort should be made to remove all past references to this paper.

The presenting author of this paper has the option to appeal this decision by contacting TPII@ieee.org.

This paper proposed a reasonable evaluation model with the decision-making attribute as the upper factor and the condition attribute as the lower factor, considering both the advantage of reduction in processing massive data and the advantage of AHP in decision-making. AHP has been used in reduction for the rules extracted. The attribute reduction algorithm utilized to improve the reduce of the magnanimous data redundancy. With the aid of the attribute importance in Rough Set theory, it compensates for the AHP evaluation factor subjective factors. The algorithm model omittes the process of extracting nuclear, analyses the rules extracted quantitatively, and accomplishes the reduction of the massive data attributes and rules. Effectiveness of the algorithm has been proved by examples.