Title :
A new validation index for fuzzy clustering and its comparisons with other methods
Author :
Rubio, E. ; Castillo, O. ; Melin, P.
Author_Institution :
Masters Degree in Comput. Sci., Tijuana Inst. of Technol., Tijuana, Mexico
Abstract :
This paper presents a new validation index for the Fuzzy C-Means algorithm, which is composed of two metrics, the modified partition entropy index and the sum of the distances between the means of the fuzzy partitions. The modified partition entropy represents the variation of the data in clusters of the dataset, and the sum of the distances between the means of the fuzzy partition represents the separation between clusters in the data set. The proposed index was tested with synthetic and benchmark datasets with good results.
Keywords :
entropy; fuzzy set theory; pattern clustering; benchmark dataset; fuzzy c-means algorithm; fuzzy clustering; fuzzy partition; modified partition entropy index; validation index; Benchmark testing; Clustering algorithms; Entropy; Equations; Indexes; Mathematical model; Partitioning algorithms; Distance between means; Fuzzy C-Means; Validation index; means of Fuzzy partitions;
Conference_Titel :
Systems, Man, and Cybernetics (SMC), 2011 IEEE International Conference on
Conference_Location :
Anchorage, AK
Print_ISBN :
978-1-4577-0652-3
DOI :
10.1109/ICSMC.2011.6083682
