A New Method Based on Genetic Algorithm for Reduction of Attribution under Incomplete Decision-Making Table

Under incomplete information system, the reduction of attribution based on rough set theory is an important but difficult task, and researches have already proved that finding minimal relative reduction is the NP complete question. Regarding to the complete decision-making table, there have been many methods to find the minimal relative reduction, but for incomplete decision-making tables, researches on this aspect are quite few. By defining approximate classified precision and the approximate classified quality of the consistent relation class, combining global optimization and connotative parallel characteristic of the genetic algorithm, adopting the most super preserved strategy, we proposed an attribute reduction method to focus on incomplete decision-making table. The result of the experiment showed that this algorithm has good solution ability, no matter whether the decision-making table is consistent or not, it can find the minimal relative reduction.