Completeness:
This separation is based on the characteristic that requires all data objects to be grouped. A complete clustering assigns every object to a cluster. All of the previous clustering figures are examples of complete clustering because in each one of them each data point is assigned to a cluster. Partial clustering (shown in Figure 5 below) on the other hand allows some data objects to left alone.