A New Spatial Fuzzy C-Means for Spatial Clustering

Provided by: WSEAS
Topic: Data Management
Format: PDF
Fuzzy c-means is a widely used clustering algorithm in data mining. Since traditional fuzzy c-means algorithms do not take spatial information into consideration, they often can't effectively explore geographical data information. So in this paper, the authors design a Spatial Distance Weighted Fuzzy C-Means algorithm, named as SDWFCM, to deal with this problem. This algorithm can fully use spatial features to assign samples to different clusters, and it only needs to calculate the memberships one time, which reduces the running time greatly compared with other spatial fuzzy c-means algorithms.

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