haojun sun,shengruiwang*,qingshan jiang received 16 december 2002; received in revised form 29 march...
TRANSCRIPT
FCM-Based Model Selection Algorithms for Determining the
Number of Clusters
Haojun Sun,ShengruiWang*,Qingshan Jiang
Received 16 December 2002; received in revised form 29 March 2004; accepted 29 March 2004
Presenter Chia-Cheng Chen 1
Introduction
Basic algorithm
A new validity index
Experimental results
Conclusion and perspectives
Outline
2
Clustering is a process for grouping a set of objects into classes or clusters so that the objects within a cluster have high similarity.
Because of its concept of fuzzy membership, FCM is able to deal more effectively with outliers and to perform membership grading, which is very important in practice.
Introduction
3
DataSet1◦ IRIS data◦ This is a biometric data set consisting of 150 measurements
belonging to three flower varieties DataSet2◦Mixture of Gaussian distributions◦ 50 data vectors in each of the 5ve clusters
DataSet3 ◦Mixture of Gaussian distributions◦ 500 data vectors
Experimental results
11