An Extended FCM Clustering Algorithm Based-on Interval Numbers
Weixiang Li · Huagong zidonghua ji yibiao · 2010
In the interval-valued data clustering algorithm,the distance between interval numbers mostly consider the upper and lower bounds value,the biggest defect is that the defined distance does not meet the visual rationality.Therefore,it is difficult to use traditional fuzzy C-means(FCM) to the interval-valued data clustering.In order to solve the problem,a new distance measure for interval numbers was introduced,and FCM clustering algorithm was extended to deal directly with the clustering problem of feature space denoted by interval numbers.By comparing with the traditional method,this method is more effective,more accurate,and more accordant to practice.