Abstract: In the traditional rough K-modes algorithm, three important parameters, w} , wk and。，are set fixedly,making the clustering result unstable and interfered easily by noise. We proposed a rough K-modes algorithm based on MapRe- duce adaptive parameters,which adjusts parameters depending on the characteristics of different clustering stages,opti- mining the clustering result In addition, we designed the rough K-modes algorithm with adaptive parameters that can be used in MapReduce to improve the efficiency of the algorithm and performance of clustering largcscale data. Finally, this algorithm's validity is proved by experiments.

Key words: Rough K-modes,Adaptivc paramctcrs,MapReduce validity