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A Rough Sets Based Ranking Algorithm and Its Application in Medical Data Mining

Baowei ZHANG, Hao JIANG

Abstract


In order to solve the ranking problem in medical data mining, different ranking methods were researched in this paper and a new ranking algorithm based on rough sets theory was presented for sorting the objects in massive medical data. In the new algorithm, a rough sets based binary function is proposed firstly and the medical information table containing ordered information is transformed into a common one using the function, then reduction is done by using rough sets theory in order to eliminate the redundant factors and obtain the core factors. Finally, by determining the weight of reduction sets' factors, objects in the original medical information tables are ranked. In the end the experiment on realistic data illustrates that the algorithm we propose is feasible and effective.

Keywords


Medical Data Mining, Rough Sets, Data Ranking, Attribute Reduction.

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