http://chineseinput.net/에서 pinyin(병음)방식으로 중국어를 변환할 수 있습니다.
변환된 중국어를 복사하여 사용하시면 됩니다.
Performance Evaluation by Validity Measures of HFC Algorithm
Deepti Gaur,Seema Gaur 한국정보통신학회 2014 2016 INTERNATIONAL CONFERENCE Vol.6 No.1
Hierarchical Fuzzy Clustering Algorithm (HFC) has wide range of applications in various classification areas. The HFC is put forward to overcome the limitations of Fuzzy C-Means (FCM) algorithm. HFC discovers the high concentrated data areas by the agglomerative hierarchical clustering method quickly, analyzes and merges the data areas, and then uses the evaluation function to find the optimum clustering scheme. HFC algorithm is faster than single linkage agglomerative clustering algorithm as it can merge more than two clusters in one iteration when the merging condition is satisfied. In this paper author measured the quality of the clusters obtained by HFC algorithm by calculating various validity measures such as partition coefficient, separation index and Xie and Beni"s index. Experimental results indicate that HFC algorithm gives accurate results comparatively better.