Clustering-based learning

The clustering-based learning method is identified as an unsupervised learning task wherein the learning starts from no specific target attribute in mind, and the data is explored with a goal of finding intrinsic structures in them.

The following diagram represents the scope of the clustering-based learning method that will be covered in this chapter:

The primary goal of the clustering technique is finding similar or homogenous groups in data that are called clusters. The way this is done is—data instances that are similar or, in short, are near to each other are grouped in one cluster, and the instances that are different are grouped into a different cluster. The following diagram shows a depiction of data points on a graph, and how the clusters are marked (in here, it is by pure intuition) by the three natural clusters:

Thus, a cluster can be defined as a collection of objects that are similar to each other and dissimilar from the objects of another cluster. The...