Algorithm in clustering location data for uncertain data mining
一种不精确数据的聚类挖掘方法*

To consider data uncertainty in the clustering process, this paper proposed a FK-means clustering algorithm that enhanced the K-means algorithm to the goal of minimizing the expected sum of squared errors E(SSE). Specially noted that a data object xi was specified by an uncertainty region with an uncertainty pdf f(xi). This paper applied FK-means to the particular pattern of moving-object uncertainty. Experimental results show that by considering uncertainty, the clustering algorithm can produce more accurate results.