A New Symmetry-Based Genetic Clustering Algorithm
نویسندگان
چکیده
In this paper, a new type of point symmetry based distance is proposed. Thereafter a genetic algorithm based clustering technique which uses this point symmetry based distance (GASDCA) is developed. GASDCA is therefore able to detect both convex and non-convex clusters. Kd-tree based nearest neighbor search is used to reduce the complexity of finding the closest symmetric point. The proposed GASDCA is compared with existing symmetry based clustering technique, SBKM, its modified version, Mod-SBKM and the well-known K-means algorithm. Results on several data sets show the effectiveness of GASDCA.
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