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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, at first a new line symmetry (LS) based distance is proposed which calculates the amount of symmetry of a point with respect to the first principal axis of a data set. The proposed distance uses a recently developed point symmetry (PS) based distance in its computation. Kd-tree based nearest neighbor search is used to reduce the complexity of computing the closest symmetric point. Thereafter...
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