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In this paper, we present an agglomerative fuzzy K-Means clustering algorithm for numerical data, an extension to the standard fuzzy K-Means algorithm by introducing a penalty term...
Mark Junjie Li, Michael K. Ng, Yiu-ming Cheung, Jo...
In this paper two agglomerative learning algorithms based on new similarity measures defined for hyperbox fuzzy sets are proposed. They are presented in a context of clustering and...
The crucial issue in many classification applications is how to achieve the best possible classifier with a limited number of labeled data for training. Training data selection is ...
: The fuzzy c-means clustering algorithm has been widely used to obtain the fuzzy k-partitions. This algorithm requires that the user gives the number of clusters k. To find automa...
A proposed KFCM-based fuzzy classifier was introduced. As for the process of constructing such classifier, firstly, the original sample space is mapped into a high dimensional fea...