关键词: 粗糙模糊K-均值聚类, 糊粗糙K-均值聚类, 支持向量机

Abstract: The shortcomings of the original clustering methods are analyzed. Moreover, the rough theory and fuzzy theory are combined together. The improvement of rough fuzzy K-means clustering algorithm is given. A fuzzy rough K-means clustering algorithm is designed, and the validity of fuzzy rough K-means clustering algorithm is verified. The proposed clustering algorithms are applied to support vector machine. In the above applications, the training samples are pre-processed to reduce the number of samples and improve the training speed and the classification accuracy.

Key words: rough fuzzy K-mean clustering, fuzzy rough K-mean clustering, support vector machine