区间值数据模糊c-均值聚类新算法

A novel algorithm of FCM clustering for interval valued data

针对范九伦等提出的两种模糊ｃ－均值聚类算法进行了改进，提出了更一般的区间值数据模糊ｃ－均值聚类算法．证明了当加权系数λ为１时，新算法等效于老算法Ⅰ；当λ趋于０ 时，新算法趋近于老算法Ⅱ．新算法以老算法Ⅰ和Ⅱ为其特例，并可用现有的模糊ｃ－均值工具箱直接实现．

A new algorithm of FCM clustering is proposed for interval valued data. it is proved that our algorithm is identical to Algorithm Ⅰ developed by Fan Jiu lun in the case of λ=1, while it is identical to Algorithm Ⅱ of the same reference in the case of λ→0, where λ is a weighting factor. Therefore, the proposed algorithm is a general form. Moreover, the new algorithm is of more definite physical significance, and can be implemented by the existing tools for the FCM algorithm.