From the Data Mining and Warehousing subject I found a process called clustering. Briefly describe me what is clustering and what the advantages of clustering. And also I need some details about these two different approaches to clustering:
·        Partitioning methods
·        Hierarchical methods
A cluster can be defined as a group or collect of data objects that share some similarity in one way or the other in a manner that they can be put together or collectively. This simple definition helps us to define the process of clustering. Clustering is a method used in data mining to put together sets of data into useful groups referred to as clusters. This is usually done, in most cases, without prior knowledge of group definition. It is also referred in some instances as unsupervised classification.
The hierarchical technique of clustering refers to a method that creates different clusters of data- ranging from small to big. These clusters may done in either large numbers or small. On the other hand, partitioning method of clustering involves division of the set of data which results in the creation of several sets of M clusters in which each object will belong to a cluster. The clusters in this situation are represented by a centroid or what is known as a cluster representative.
