On Clustering Scheme for Kernel K-Means


Cluster analysis mainly concerned with dividing the number of data elements into clusters observation in the same cluster are homogeneous and are not homogeneous with other clusters, but in the case of nonparametric data it is not possible to deal with classic estimated because of obtaining misleading results This gave rise to adopt efficient estimation methods known as the kernel methods. One of the methods of clustering is Non-Hierarchical clustering aims to divide the dataset into (k) homogeneous cluster groups based on the idea of the central the tendency of the cluster group using (k) averages. There are many methods of non-hierarchical clustering, some depends on the arithmetic mean, and others depend on the mediator or mode.