DIANA
DIANA is also known as Divisive Analysis clustering algorithm. It is the top-down approach form of hierarchical clustering where all data points are initially assigned a single cluster. Further, the clusters are split into two least similar clusters. This is done recursively until clusters groups are formed which are distinct to each other.
In step 1 that is the blue outline circle can be thought of as all the points are assigned a single cluster. Moving forward it is divided into 2 red-colored clusters based on the distances/density of points. Now, we have two red-colored clusters in step 2. Lastly, in step 3 the two red clusters are further divided into 2 blacks dotted each, again based on density and distances to give us final four clusters. Since the points in the respective 4 clusters are very similar to each other and very different when compared to the other cluster groups they are not further divided. Thus, this is how user gets DIANA clusters or top-down approached Hierarchical clusters.
In the partitioning method when database that contains multiple objects then the partitioning method constructs user-specified partitions of the data in which each partition represents a cluster and a particular region. There are many algorithms that come under partitioning method some of the popular ones are K-means clustering, K-Mode Clustering etc.