Abstract

This paper analyzed the employees' MMPI Psychological data of a company. Aiming at the problem that traditional K-Means algorithm is sensitive to the initial clustering center, this paper used hierarchical clustering algorithm CURE to mitigate the problem. Finally using CUDA technology clustered several times, so as to improve the execution efficiency of the algorithm. Through experimental verification, the improved K-Means algorithm behaved well in both execution efficiency and clustering results.

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