On some symmetry based validity indices

—Identification of the correct number of clusters and the corresponding partitioning are two important considerations in clustering. In this paper, a newly developed point symmetry based distance is used to propose symmetry based versions of six cluster validity indices namely, DB-index, Dunn-index, Generalized Dunn-index, PS-index, I-index and XB-index. These indices provide measures of “symmetricity” of the different partitionings of a data set. A Kd-tree-based data structure is used to reduce the complexity of computing the symmetry distance. A newly developed genetic point symmetry based clustering technique, GAPS-clustering is used as the underlying partitioning algorithm. The number of clusters are varied from 2 to √ n where n is the total number of data points present in the data set and the values of all the validity indices are noted down. The optimum value of a validity index over these √ n − 1 partitions corresponds to the appropriate partitioning and the number...

• Type: Conference
• Year: 2007
• Where: CEC
• Authors: Sriparna Saha, Sanghamitra Bandyopadhyay
• Keywords: Artificial Intelligence, CEC 2007, Point Symmetry, Symmetry, Validity Indices