首页|An Outlier Detection Method based on Fuzzy C-Means Clustering
An Outlier Detection Method based on Fuzzy C-Means Clustering
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NETL
NSTL
Both fuzzy c-means (FCM) clustering and outlier detection are useful data mining techniques in real applications. In this paper, we show that the task of outlier detection could he achieved as by-product of fuzzy c-mcans clustering. The proposed strategy consists of two stages. The first stage consists of purely fuzzy c-means process, while the second stage identifies exceptional objects according to a novel metric based on the entropy of membership values. We provide experimental results to demonstrate the effectiveness of our technique.
NETL
NSTL
