Stochastic nature of earthquake has raised a challenge for engineers to choose which record for their analyses. Clustering is offered as a solution for such a data mining problem to automatically distinguish between ground motion records based on similarities in the corresponding seismic attributes. The present work formulates an optimization problem to seek for the best clustering measures. In...

This paper proposes two algorithms for clustering data, which are variable-sized sets of elementary items. An example such data occurs in the analysis a medical diagnosis, where goal is to detect human subjects who share common diseases possibly predict future illnesses from previous history. The first proposed algorithm based on K-medoids and second extends random swap algorithm, has proven be...

This paper presents a comprehensive review of existing techniques k-means clustering algorithms made at various times. The algorithm is aimed partitioning objects or points to be analyzed into well separated clusters. There are different for such as traditional algorithm, standard basic and the conventional this perhaps most widely used versions algorithms. These uses Euclidean distance its met...