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Most of the existing literatures use Euclidean distance based cluster validity measures in order to identify correct number of clusters for different datasets. It is a very important consideration for clustering. Symmetry can be considered as an important attribute for data clustering. It can be of two types, point symmetry and line symmetry. In this paper we have introduced a newly developed line...
In this paper, a segmentation technique of multi-spectral magnetic resonance image of the brain using a new differential evolution based crisp clustering is proposed. Real-coded encoding of the cluster centres is used for this purpose. Here assignments of points to different clusters are made based on the Euclidean distance. The proposed method is applied on several simulated T1-weighted, T2-weighted...
A genetic algorithm-based clustering technique, called GA-clustering, is proposed in this article. The searching capability of genetic algorithms is exploited in order to search for appropriate cluster centres in the feature space such that a similarity metric of the resulting clusters is optimized. The chromosomes, which are represented as strings of real numbers, encode the centres of a fixed number...
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