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        1.
        2012.12 KCI 등재 구독 인증기관 무료, 개인회원 유료
        F-Measure is one of the external measures for evaluating the validity of clustering results. Though it has clear advantages over other widely used external measures such as Purity and Entropy, F-Measure has inherently been less sensitive than other validity measures. This insensitivity owes to the definition of F-Measure that counts only most influential portions. In this research, we present Fn-Measure, an external cluster evaluation measure based on F-Measure. Fn-Measure is so sensitive that it can detect their difference in the cases that F-Measure cannot detect the difference in clustering results. We compare Fn-Measure to F-Measure for a few clustering results and show which measure draws better result based upon homogeneity and completeness
        4,000원